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Sample records for adaptive color segmentation

  1. Real-Time Adaptive Color Segmentation by Neural Networks

    NASA Technical Reports Server (NTRS)

    Duong, Tuan A.

    2004-01-01

    Artificial neural networks that would utilize the cascade error projection (CEP) algorithm have been proposed as means of autonomous, real-time, adaptive color segmentation of images that change with time. In the original intended application, such a neural network would be used to analyze digitized color video images of terrain on a remote planet as viewed from an uninhabited spacecraft approaching the planet. During descent toward the surface of the planet, information on the segmentation of the images into differently colored areas would be updated adaptively in real time to capture changes in contrast, brightness, and resolution, all in an effort to identify a safe and scientifically productive landing site and provide control feedback to steer the spacecraft toward that site. Potential terrestrial applications include monitoring images of crops to detect insect invasions and monitoring of buildings and other facilities to detect intruders. The CEP algorithm is reliable and is well suited to implementation in very-large-scale integrated (VLSI) circuitry. It was chosen over other neural-network learning algorithms because it is better suited to realtime learning: It provides a self-evolving neural-network structure, requires fewer iterations to converge and is more tolerant to low resolution (that is, fewer bits) in the quantization of neural-network synaptic weights. Consequently, a CEP neural network learns relatively quickly, and the circuitry needed to implement it is relatively simple. Like other neural networks, a CEP neural network includes an input layer, hidden units, and output units (see figure). As in other neural networks, a CEP network is presented with a succession of input training patterns, giving rise to a set of outputs that are compared with the desired outputs. Also as in other neural networks, the synaptic weights are updated iteratively in an effort to bring the outputs closer to target values. A distinctive feature of the CEP neural

  2. A hybrid and adaptive segmentation method using color and texture information

    NASA Astrophysics Data System (ADS)

    Meurie, C.; Ruichek, Y.; Cohen, A.; Marais, J.

    2010-01-01

    This paper presents a new image segmentation method based on the combination of texture and color informations. The method first computes the morphological color and texture gradients. The color gradient is analyzed taking into account the different color spaces. The texture gradient is computed using the luminance component of the HSL color space. The texture gradient procedure is achieved using a morphological filter and a granulometric and local energy analysis. To overcome the limitations of a linear/barycentric combination, the two morphological gradients are then mixed using a gradient component fusion strategy (to fuse the three components of the color gradient and the unique component of the texture gradient) and an adaptive technique to choose the weighting coefficients. The segmentation process is finally performed by applying the watershed technique using different type of germ images. The segmentation method is evaluated in different object classification applications using the k-means algorithm. The obtained results are compared with other known segmentation methods. The evaluation analysis shows that the proposed method gives better results, especially with hard image acquisition conditions.

  3. Efficient text segmentation and adaptive color error diffusion for text enhancement

    NASA Astrophysics Data System (ADS)

    Kwon, Jae-Hyun; Park, Tae-Yong; Kim, Yun-Tae; Cho, Yang-Ho; Ha, Yeong-Ho

    2005-01-01

    This paper proposes an adaptive error diffusion algorithm for text enhancement followed by an efficient text segmentation that uses the maximum gradient difference (MGD). The gradients are calculated along with scan lines, then the MGD values are filled within a local window to merge text segments. If the value is above a threshold, the pixel is considered as potential text. Isolated segments are then eliminated in a non-text region filtering process. After the text segmentation, a conventional error diffusion method is applied to the background, while edge enhancement error diffusion is used for the text. Since it is inevitable that visually objectionable artifacts are generated when using two different halftoning algorithms, gradual dilation is proposed to minimize the boundary artifacts in the segmented text blocks before halftoning. Sharpening based on the gradually dilated text region (GDTR) then prevents the printing of successive dots around the text region boundaries. The method is extended to halftone color images to sharpen the text regions. The proposed adaptive error diffusion algorithm involves color halftoning that controls the amount of edge enhancement using a general error filter. However, edge enhancement unfortunately produces color distortion, as edge enhancement and color difference are trade-offs. The multiplicative edge enhancement parameters are selected based on the amount of edge sharpening and color difference. Plus, an additional error factor is introduced to reduce the dot elimination artifact generated by the edge enhancement error diffusion. In experiments, the text of a scanned image was sharper when using the proposed algorithm than with conventional error diffusion without changing the background.

  4. Efficient text segmentation and adaptive color error diffusion for text enhancement

    NASA Astrophysics Data System (ADS)

    Kwon, Jae-Hyun; Park, Tae-Yong; Kim, Yun-Tae; Cho, Yang-Ho; Ha, Yeong-Ho

    2004-12-01

    This paper proposes an adaptive error diffusion algorithm for text enhancement followed by an efficient text segmentation that uses the maximum gradient difference (MGD). The gradients are calculated along with scan lines, then the MGD values are filled within a local window to merge text segments. If the value is above a threshold, the pixel is considered as potential text. Isolated segments are then eliminated in a non-text region filtering process. After the text segmentation, a conventional error diffusion method is applied to the background, while edge enhancement error diffusion is used for the text. Since it is inevitable that visually objectionable artifacts are generated when using two different halftoning algorithms, gradual dilation is proposed to minimize the boundary artifacts in the segmented text blocks before halftoning. Sharpening based on the gradually dilated text region (GDTR) then prevents the printing of successive dots around the text region boundaries. The method is extended to halftone color images to sharpen the text regions. The proposed adaptive error diffusion algorithm involves color halftoning that controls the amount of edge enhancement using a general error filter. However, edge enhancement unfortunately produces color distortion, as edge enhancement and color difference are trade-offs. The multiplicative edge enhancement parameters are selected based on the amount of edge sharpening and color difference. Plus, an additional error factor is introduced to reduce the dot elimination artifact generated by the edge enhancement error diffusion. In experiments, the text of a scanned image was sharper when using the proposed algorithm than with conventional error diffusion without changing the background.

  5. Color segmentation using MDL clustering

    NASA Astrophysics Data System (ADS)

    Wallace, Richard S.; Suenaga, Yasuhito

    1991-02-01

    This paper describes a procedure for segmentation of color face images. A cluster analysis algorithm uses a subsample of the input image color pixels to detect clusters in color space. The clustering program consists of two parts. The first part searches for a hierarchical clustering using the NIHC algorithm. The second part searches the resultant cluster tree for a level clustering having minimum description length (MDL). One of the primary advantages of the MDL paradigm is that it enables writing robust vision algorithms that do not depend on user-specified threshold parameters or other " magic numbers. " This technical note describes an application of minimal length encoding in the analysis of digitized human face images at the NTT Human Interface Laboratories. We use MDL clustering to segment color images of human faces. For color segmentation we search for clusters in color space. Using only a subsample of points from the original face image our clustering program detects color clusters corresponding to the hair skin and background regions in the image. Then a maximum likelyhood classifier assigns the remaining pixels to each class. The clustering program tends to group small facial features such as the nostrils mouth and eyes together but they can be separated from the larger classes through connected components analysis.

  6. Feature encoding for color image segmentation

    NASA Astrophysics Data System (ADS)

    Li, Ning; Li, Youfu

    2001-09-01

    An approach for color image segmentation is proposed based on the contributions of color features to segmentation rather than the choice of a particular color space. It is different from the pervious methods where SOFM is used for construct the feature encoding so that the feature-encoding can self-organize the effective features for different color images. Fuzzy clustering is applied for the final segmentation when the well-suited color features and the initial parameter are available. The proposed method has been applied in segmenting different types of color images and the experimental results show that it outperforms the classical clustering method. Our study shows that the feature encoding approach offers great promise in automating and optimizing color image segmentation.

  7. Bayesian Fusion of Color and Texture Segmentations

    NASA Technical Reports Server (NTRS)

    Manduchi, Roberto

    2000-01-01

    In many applications one would like to use information from both color and texture features in order to segment an image. We propose a novel technique to combine "soft" segmentations computed for two or more features independently. Our algorithm merges models according to a mean entropy criterion, and allows to choose the appropriate number of classes for the final grouping. This technique also allows to improve the quality of supervised classification based on one feature (e.g. color) by merging information from unsupervised segmentation based on another feature (e.g., texture.)

  8. Outstanding-objects-oriented color image segmentation using fuzzy logic

    NASA Astrophysics Data System (ADS)

    Hayasaka, Rina; Zhao, Jiying; Matsushita, Yutaka

    1997-10-01

    This paper presents a novel fuzzy-logic-based color image segmentation scheme focusing on outstanding objects to human eyes. The scheme first segments the image into rough fuzzy regions, chooses visually significant regions, and conducts fine segmentation on the chosen regions. It can not only reduce the computational load, but also make contour detection easy because the brief object externals has been previously determined. The scheme reflects human sense, and it can be sued efficiently in automatic extraction of image retrieval key, robot vision and region-adaptive image compression.

  9. Color Image Segmentation in a Quaternion Framework

    PubMed Central

    Subakan, Özlem N.; Vemuri, Baba C.

    2010-01-01

    In this paper, we present a feature/detail preserving color image segmentation framework using Hamiltonian quaternions. First, we introduce a novel Quaternionic Gabor Filter (QGF) which can combine the color channels and the orientations in the image plane. Using the QGFs, we extract the local orientation information in the color images. Second, in order to model this derived orientation information, we propose a continuous mixture of appropriate hypercomplex exponential basis functions. We derive a closed form solution for this continuous mixture model. This analytic solution is in the form of a spatially varying kernel which, when convolved with the signed distance function of an evolving contour (placed in the color image), yields a detail preserving segmentation. PMID:21243101

  10. Color, complex document segmentation and compression

    NASA Astrophysics Data System (ADS)

    Fung, Hei Tao; Parker, Kevin J.

    1997-04-01

    We propose a novel segmentation algorithm called SMART for color, complex documents. It decomposes a document image into 'binarizable' and 'non-binarizable' components. The segmentation procedure includes color transformation, halftone texture suppression, subdivision of the image into 8 by 8 blocks, classification of the 8 by 8 blocks as 'active' or 'inactive', formation of macroblocks from the active blocks, and classification of the macroblocks as binarizable or non-binarizable. The classification processes involve the DCT coefficients and a histogram analysis. SMART is compared to three well-known segmentation algorithms: CRLA, RXYC, and SPACE. SMART can handle image components of various shapes, multiple backgrounds of different gray levels, different relative grayness of text to this background, tilted image components, and text of different gray levels. To compress the segmented image, we apply JPEG4 to the non-binarizable macroblocks and the Group 4 coding scheme to the binary image representing the binarizable macroblocks and to the bitmap storing the configuration of all macroblocks. Data about the representative gray values, the color information, and other descriptors of the binarizable macroblocks and the background regions are also sent to allow image reconstruction. The gain is using our compression algorithm over using JPEG for the whole image is significant. This gain increases as the proportion of the size of the subjects prefer the reconstructed images from our compression algorithm to those form the bitrate-matching JPEG images. In a series of test images, this document segmentation and compression system enables compression ratios two times to six times improved over standard methods.

  11. Adaptive image segmentation by quantization

    NASA Astrophysics Data System (ADS)

    Liu, Hui; Yun, David Y.

    1992-12-01

    Segmentation of images into textural homogeneous regions is a fundamental problem in an image understanding system. Most region-oriented segmentation approaches suffer from the problem of different thresholds selecting for different images. In this paper an adaptive image segmentation based on vector quantization is presented. It automatically segments images without preset thresholds. The approach contains a feature extraction module and a two-layer hierarchical clustering module, a vector quantizer (VQ) implemented by a competitive learning neural network in the first layer. A near-optimal competitive learning algorithm (NOLA) is employed to train the vector quantizer. NOLA combines the advantages of both Kohonen self- organizing feature map (KSFM) and K-means clustering algorithm. After the VQ is trained, the weights of the network and the number of input vectors clustered by each neuron form a 3- D topological feature map with separable hills aggregated by similar vectors. This overcomes the inability to visualize the geometric properties of data in a high-dimensional space for most other clustering algorithms. The second clustering algorithm operates in the feature map instead of the input set itself. Since the number of units in the feature map is much less than the number of feature vectors in the feature set, it is easy to check all peaks and find the `correct' number of clusters, also a key problem in current clustering techniques. In the experiments, we compare our algorithm with K-means clustering method on a variety of images. The results show that our algorithm achieves better performance.

  12. Color segmentation in the HSI color space using the K-means algorithm

    NASA Astrophysics Data System (ADS)

    Weeks, Arthur R.; Hague, G. Eric

    1997-04-01

    Segmentation of images is an important aspect of image recognition. While grayscale image segmentation has become quite a mature field, much less work has been done with regard to color image segmentation. Until recently, this was predominantly due to the lack of available computing power and color display hardware that is required to manipulate true color images (24-bit). TOday, it is not uncommon to find a standard desktop computer system with a true-color 24-bit display, at least 8 million bytes of memory, and 2 gigabytes of hard disk storage. Segmentation of color images is not as simple as segmenting each of the three RGB color components separately. The difficulty of using the RGB color space is that it doesn't closely model the psychological understanding of color. A better color model, which closely follows that of human visual perception is the hue, saturation, intensity model. This color model separates the color components in terms of chromatic and achromatic information. Strickland et al. was able to show the importance of color in the extraction of edge features form an image. His method enhances the edges that are detectable in the luminance image with information from the saturation image. Segmentation of both the saturation and intensity components is easily accomplished with any gray scale segmentation algorithm, since these spaces are linear. The modulus 2(pi) nature of the hue color component makes its segmentation difficult. For example, a hue of 0 and 2(pi) yields the same color tint. Instead of applying separate image segmentation to each of the hue, saturation, and intensity components, a better method is to segment the chromatic component separately from the intensity component because of the importance that the chromatic information plays in the segmentation of color images. This paper presents a method of using the gray scale K-means algorithm to segment 24-bit color images. Additionally, this paper will show the importance the hue

  13. Adaptive color correction based on object color classification

    NASA Astrophysics Data System (ADS)

    Kotera, Hiroaki; Morimoto, Tetsuro; Yasue, Nobuyuki; Saito, Ryoichi

    1998-09-01

    An adaptive color management strategy depending on the image contents is proposed. Pictorial color image is classified into different object areas with clustered color distribution. Euclidian or Mahalanobis color distance measures, and maximum likelihood method based on Bayesian decision rule, are introduced to the classification. After the classification process, each clustered pixels are projected onto principal component space by Hotelling transform and the color corrections are performed for the principal components to be matched each other in between the individual clustered color areas of original and printed images.

  14. Self-adaptive algorithm for segmenting skin regions

    NASA Astrophysics Data System (ADS)

    Kawulok, Michal; Kawulok, Jolanta; Nalepa, Jakub; Smolka, Bogdan

    2014-12-01

    In this paper, we introduce a new self-adaptive algorithm for segmenting human skin regions in color images. Skin detection and segmentation is an active research topic, and many solutions have been proposed so far, especially concerning skin tone modeling in various color spaces. Such models are used for pixel-based classification, but its accuracy is limited due to high variance and low specificity of human skin color. In many works, skin model adaptation and spatial analysis were reported to improve the final segmentation outcome; however, little attention has been paid so far to the possibilities of combining these two improvement directions. Our contribution lies in learning a local skin color model on the fly, which is subsequently applied to the image to determine the seeds for the spatial analysis. Furthermore, we also take advantage of textural features for computing local propagation costs that are used in the distance transform. The results of an extensive experimental study confirmed that the new method is highly competitive, especially for extracting the hand regions in color images.

  15. Efficient color representation for image segmentation under nonwhite illumination

    NASA Astrophysics Data System (ADS)

    Park, Jae Byung

    2003-10-01

    Color image segmentation algorithms often consider object color to be a constant property of an object. If the light source dominantly exhibits a particular color, however, it becomes necessary to consider the color variation induced by the colored illuminant. This paper presents a new approach to segmenting color images that are photographed under non-white illumination conditions. It also addresses how to estimate the color of illuminant in terms of the standard RGB color values rather than the spectrum of the illuminant. With respect to the illumination axis that goes through the origin and the centroid of illuminant color clusters (prior given by the estimation process), the RGB color space is transformed into our new color coordinate system. Our new color scheme shares the intuitiveness of the HSI (HSL or HSV) space that comes from the conical (double-conical or cylindrical) structure of hue and saturation aligned with the intensity variation at its center. It has been developed by locating the ordinary RGB cube in such a way that the illumination axis aligns with the vertical axis (Z-axis) of a larger Cartesian (XYZ) space. The work in this paper uses the dichromatic reflection model [1] to interpret the physics about light and optical effects in color images. The linearity proposed in the dichromatic reflection model is essential and is well preserved in the RGB color space. By proposing a straightforward color model transduction, we suggest dimensionality reduction and provide an efficient way to analyze color images of dielectric objects under non-white illumination conditions. The feasibility of the proposed color representation has been demonstrated by our experiment that is twofold: 1) Segmentation result from a multi-modal histogram-based thresholding technique and 2) Color constancy result from discounting illumination effect further by color balancing.

  16. Automatic watershed segmentation of randomly textured color images.

    PubMed

    Shafarenko, L; Petrou, M; Kittler, J

    1997-01-01

    A new method is proposed for processing randomly textured color images. The method is based on a bottom-up segmentation algorithm that takes into consideration both color and texture properties of the image. An LUV gradient is introduced, which provides both a color similarity measure and a basis for applying the watershed transform. The patches of watershed mosaic are merged according to their color contrast until a termination criterion is met. This criterion is based on the topology of the typical processed image. The resulting algorithm does not require any additional information, be it various thresholds, marker extraction rules, and suchlike, thus being suitable for automatic processing of color images. The algorithm is demonstrated within the framework of the problem of automatic granite inspection. The segmentation procedure has been found to be very robust, producing good results not only on granite images, but on the wide range of other noisy color images as well, subject to the termination criterion.

  17. An adaptive algorithm for motion compensated color image coding

    NASA Technical Reports Server (NTRS)

    Kwatra, Subhash C.; Whyte, Wayne A.; Lin, Chow-Ming

    1987-01-01

    This paper presents an adaptive algorithm for motion compensated color image coding. The algorithm can be used for video teleconferencing or broadcast signals. Activity segmentation is used to reduce the bit rate and a variable stage search is conducted to save computations. The adaptive algorithm is compared with the nonadaptive algorithm and it is shown that with approximately 60 percent savings in computing the motion vector and 33 percent additional compression, the performance of the adaptive algorithm is similar to the nonadaptive algorithm. The adaptive algorithm results also show improvement of up to 1 bit/pel over interframe DPCM coding with nonuniform quantization. The test pictures used for this study were recorded directly from broadcast video in color.

  18. Pixel classification based color image segmentation using quaternion exponent moments.

    PubMed

    Wang, Xiang-Yang; Wu, Zhi-Fang; Chen, Liang; Zheng, Hong-Liang; Yang, Hong-Ying

    2016-02-01

    Image segmentation remains an important, but hard-to-solve, problem since it appears to be application dependent with usually no a priori information available regarding the image structure. In recent years, many image segmentation algorithms have been developed, but they are often very complex and some undesired results occur frequently. In this paper, we propose a pixel classification based color image segmentation using quaternion exponent moments. Firstly, the pixel-level image feature is extracted based on quaternion exponent moments (QEMs), which can capture effectively the image pixel content by considering the correlation between different color channels. Then, the pixel-level image feature is used as input of twin support vector machines (TSVM) classifier, and the TSVM model is trained by selecting the training samples with Arimoto entropy thresholding. Finally, the color image is segmented with the trained TSVM model. The proposed scheme has the following advantages: (1) the effective QEMs is introduced to describe color image pixel content, which considers the correlation between different color channels, (2) the excellent TSVM classifier is utilized, which has lower computation time and higher classification accuracy. Experimental results show that our proposed method has very promising segmentation performance compared with the state-of-the-art segmentation approaches recently proposed in the literature.

  19. Pixel classification based color image segmentation using quaternion exponent moments.

    PubMed

    Wang, Xiang-Yang; Wu, Zhi-Fang; Chen, Liang; Zheng, Hong-Liang; Yang, Hong-Ying

    2016-02-01

    Image segmentation remains an important, but hard-to-solve, problem since it appears to be application dependent with usually no a priori information available regarding the image structure. In recent years, many image segmentation algorithms have been developed, but they are often very complex and some undesired results occur frequently. In this paper, we propose a pixel classification based color image segmentation using quaternion exponent moments. Firstly, the pixel-level image feature is extracted based on quaternion exponent moments (QEMs), which can capture effectively the image pixel content by considering the correlation between different color channels. Then, the pixel-level image feature is used as input of twin support vector machines (TSVM) classifier, and the TSVM model is trained by selecting the training samples with Arimoto entropy thresholding. Finally, the color image is segmented with the trained TSVM model. The proposed scheme has the following advantages: (1) the effective QEMs is introduced to describe color image pixel content, which considers the correlation between different color channels, (2) the excellent TSVM classifier is utilized, which has lower computation time and higher classification accuracy. Experimental results show that our proposed method has very promising segmentation performance compared with the state-of-the-art segmentation approaches recently proposed in the literature. PMID:26618250

  20. Video rate color region segmentation for mobile robotic applications

    NASA Astrophysics Data System (ADS)

    de Cabrol, Aymeric; Bonnin, Patrick J.; Hugel, Vincent; Blazevic, Pierre; Chetto, Maryline

    2005-08-01

    Color Region may be an interesting image feature to extract for visual tasks in robotics, such as navigation and obstacle avoidance. But, whereas numerous methods are used for vision systems embedded on robots, only a few use this segmentation mainly because of the processing duration. In this paper, we propose a new real-time (ie. video rate) color region segmentation followed by a robust color classification and a merging of regions, dedicated to various applications such as RoboCup four-legged league or an industrial conveyor wheeled robot. Performances of this algorithm and confrontation with other methods, in terms of result quality and temporal performances are provided. For better quality results, the obtained speed up is between 2 and 4. For same quality results, the it is up to 10. We present also the outlines of the Dynamic Vision System of the CLEOPATRE Project - for which this segmentation has been developed - and the Clear Box Methodology which allowed us to create the new color region segmentation from the evaluation and the knowledge of other well known segmentations.

  1. Region Adaptive Color Demosaicing Algorithm Using Color Constancy

    NASA Astrophysics Data System (ADS)

    Kim, Chang Won; Oh, Hyun Mook; Yoo, Du Sic; Kang, Moon Gi

    2010-12-01

    This paper proposes a novel way of combining color demosaicing and the auto white balance (AWB) method, which are important parts of image processing. Performance of the AWB is generally affected by demosaicing results because most AWB algorithms are performed posterior to color demosaicing. In this paper, in order to increase the performance and efficiency of the AWB algorithm, the color constancy problem is examined during the color demosaicing step. Initial estimates of the directional luminance and chrominance values are defined for estimating edge direction and calculating the AWB gain. In order to prevent color failure in conventional edge-based AWB methods, we propose a modified edge-based AWB method that used a predefined achromatic region. The estimation of edge direction is performed region adaptively by using the local statistics of the initial estimates of the luminance and chrominance information. Simulated and real Bayer color filter array (CFA) data are used to evaluate the performance of the proposed method. When compared to conventional methods, the proposed method shows significant improvements in terms of visual and numerical criteria.

  2. Color Image Segmentation Based on Different Color Space Models Using Automatic GrabCut

    PubMed Central

    Ebied, Hala Mousher; Hussein, Ashraf Saad; Tolba, Mohamed Fahmy

    2014-01-01

    This paper presents a comparative study using different color spaces to evaluate the performance of color image segmentation using the automatic GrabCut technique. GrabCut is considered as one of the semiautomatic image segmentation techniques, since it requires user interaction for the initialization of the segmentation process. The automation of the GrabCut technique is proposed as a modification of the original semiautomatic one in order to eliminate the user interaction. The automatic GrabCut utilizes the unsupervised Orchard and Bouman clustering technique for the initialization phase. Comparisons with the original GrabCut show the efficiency of the proposed automatic technique in terms of segmentation, quality, and accuracy. As no explicit color space is recommended for every segmentation problem, automatic GrabCut is applied with RGB, HSV, CMY, XYZ, and YUV color spaces. The comparative study and experimental results using different color images show that RGB color space is the best color space representation for the set of the images used. PMID:25254226

  3. Incorporating Adaptive Local Information Into Fuzzy Clustering for Image Segmentation.

    PubMed

    Liu, Guoying; Zhang, Yun; Wang, Aimin

    2015-11-01

    Fuzzy c-means (FCM) clustering with spatial constraints has attracted great attention in the field of image segmentation. However, most of the popular techniques fail to resolve misclassification problems due to the inaccuracy of their spatial models. This paper presents a new unsupervised FCM-based image segmentation method by paying closer attention to the selection of local information. In this method, region-level local information is incorporated into the fuzzy clustering procedure to adaptively control the range and strength of interactive pixels. First, a novel dissimilarity function is established by combining region-based and pixel-based distance functions together, in order to enhance the relationship between pixels which have similar local characteristics. Second, a novel prior probability function is developed by integrating the differences between neighboring regions into the mean template of the fuzzy membership function, which adaptively selects local spatial constraints by a tradeoff weight depending upon whether a pixel belongs to a homogeneous region or not. Through incorporating region-based information into the spatial constraints, the proposed method strengthens the interactions between pixels within the same region and prevents over smoothing across region boundaries. Experimental results over synthetic noise images, natural color images, and synthetic aperture radar images show that the proposed method achieves more accurate segmentation results, compared with five state-of-the-art image segmentation methods.

  4. Segmentation and tracking of facial regions in color image sequences

    NASA Astrophysics Data System (ADS)

    Menser, Bernd; Wien, Mathias

    2000-05-01

    In this paper a new algorithm for joint detection and segmentation of human faces in color images sequence is presented. A skin probability image is generated using a model for skin color. Instead of a binary segmentation to detect skin regions, connected operators are used to analyze the skin probability image at different threshold levels. A hierarchical scheme of operators using shape and texture simplifies the skin probability image. For the remaining connected components, the likelihood of being a face is estimated using principal components analysis. To track a detected face region through the sequence, the connected component that represent the face in the previous frame is projected into the current frame. Using the projected segment as a marker, connected operators extract the actual face region from the skin probability image.

  5. Adaptation and perceptual norms in color vision.

    PubMed

    Webster, Michael A; Leonard, Deanne

    2008-11-01

    Many perceptual dimensions are thought to be represented relative to an average value or norm. Models of norm-based coding assume that the norm appears psychologically neutral because it reflects a neutral response in the underlying neural code. We tested this assumption in human color vision by asking how judgments of "white" are affected as neural responses are altered by adaptation. The adapting color was varied to determine the stimulus level that did not bias the observer's subjective white point. This level represents a response norm at the stages at which sensitivity is regulated by the adaptation, and we show that these response norms correspond to the perceptually neutral stimulus and that they can account for how the perception of white varies both across different observers and within the same observer at different locations in the visual field. We also show that individual differences in perceived white are reduced when observers are exposed to a common white adapting stimulus, suggesting that the perceptual differences are due in part to differences in how neural responses are normalized. These results suggest a close link between the norms for appearance and coding in color vision and illustrate a general paradigm for exploring this link in other perceptual domains.

  6. Unsupervised motion-based object segmentation refined by color

    NASA Astrophysics Data System (ADS)

    Piek, Matthijs C.; Braspenning, Ralph; Varekamp, Chris

    2003-06-01

    for its ability to estimate motion vectors which closely resemble the true motion. BLOCK-BASED MOTION SEGMENTATION As mentioned above we start with a block-resolution segmentation based on motion vectors. The presented method is inspired by the well-known K-means segmentation method te{K-means}. Several other methods (e.g. te{kmeansc}) adapt K-means for connectedness by adding a weighted shape-error. This adds the additional difficulty of finding the correct weights for the shape-parameters. Also, these methods often bias one particular pre-defined shape. The presented method, which we call K-regions, encourages connectedness because only blocks at the edges of segments may be assigned to another segment. This constrains the segmentation method to such a degree that it allows the method to use least squares for the robust fitting of affine motion models for each segment. Contrary to te{parmkm}, the segmentation step still operates on vectors instead of model parameters. To make sure the segmentation is temporally consistent, the segmentation of the previous frame will be used as initialisation for every new frame. We also present a scheme which makes the algorithm independent of the initially chosen amount of segments. COLOUR-BASED INTRA-BLOCK SEGMENTATION The block resolution motion-based segmentation forms the starting point for the pixel resolution segmentation. The pixel resolution segmentation is obtained from the block resolution segmentation by reclassifying pixels only at the edges of clusters. We assume that an edge between two objects can be found in either one of two neighbouring blocks that belong to different clusters. This assumption allows us to do the pixel resolution segmentation on each pair of such neighbouring blocks separately. Because of the local nature of the segmentation, it largely avoids problems with heterogeneously coloured areas. Because no new segments are introduced in this step, it also does not suffer from oversegmentation problems

  7. Automatic sputum color image segmentation for tuberculosis diagnosis

    NASA Astrophysics Data System (ADS)

    Forero-Vargas, Manuel G.; Sierra-Ballen, Eduard L.; Alvarez-Borrego, Josue; Pech-Pacheco, Jose L.; Cristobal-Perez, Gabriel; Alcala, Luis; Desco, Manuel

    2001-11-01

    Tuberculosis (TB) and other mycobacteriosis are serious illnesses which control is mainly based on presumptive diagnosis. Besides of clinical suspicion, the diagnosis of mycobacteriosis must be done through genus specific smears of clinical specimens. However, these techniques lack of sensitivity and consequently clinicians must wait culture results as much as two months. Computer analysis of digital images from these smears could improve sensitivity of the test and, moreover, decrease workload of the micobacteriologist. Bacteria segmentation of particular species entails a complex process. Bacteria shape is not enough as a discriminant feature, because there are many species that share the same shape. Therefore the segmentation procedure requires to be improved using the color image information. In this paper we present two segmentation procedures based on fuzzy rules and phase-only correlation techniques respectively that will provide the basis of a future automatic particle' screening.

  8. Improved nonlocal fuzzy color segmentation-based color reconstruction hybrid approach for white-RGB imaging systems

    NASA Astrophysics Data System (ADS)

    Wang, Chang-shuai; Chong, Jong-wha

    2014-11-01

    Conventional local-based color reconstruction for a white-RGB (WRGB) imaging system relies excessively on reference pixels. Therefore, it is sensitive to noisy interference. To address this issue, we propose an improved nonlocal fuzzy color segmentation-based color reconstruction hybrid approach for a WRGB imaging system. Unlike local-based approaches, we attempt to reproduce color information based on the statistical color distribution of the raw sensor data. According to the distribution analysis, the color distribution (histogram and cumulative distribution function) is close to that of the full-resolution image. However, brief histogram matching gives rise to zipper artifacts, which result from the multicombination of the red, green, and blue corresponding to one white. Therefore, a hybrid color segmentation is proposed to address this issue. The first step is a brief sorting-based color segmentation in the hue channel. Fuzzy-based color segmentation is then utilized to acquire more subregions in the proposed saturation space. Finally, fast histogram matching is carried out to obtain the full-color information for the white pixel for each region. Compared with state-of-the-art approaches, the proposed nonlocal hybrid approach is capable of significantly reducing the influence of noise with higher peak signal-to-noise ratios. Furthermore, according to the hybrid color segmentation, zipper artifacts are successfully avoided.

  9. Research on adaptive segmentation and activity classification method of filamentous fungi image in microbe fermentation

    NASA Astrophysics Data System (ADS)

    Cai, Xiaochun; Hu, Yihua; Wang, Peng; Sun, Dujuan; Hu, Guilan

    2009-10-01

    The paper presents an adaptive segmentation and activity classification method for filamentous fungi image. Firstly, an adaptive structuring element (SE) construction algorithm is proposed for image background suppression. Based on watershed transform method, the color labeled segmentation of fungi image is taken. Secondly, the fungi elements feature space is described and the feature set for fungi hyphae activity classification is extracted. The growth rate evaluation of fungi hyphae is achieved by using SVM classifier. Some experimental results demonstrate that the proposed method is effective for filamentous fungi image processing.

  10. Consistent depth video segmentation using adaptive surface models.

    PubMed

    Husain, Farzad; Dellen, Babette; Torras, Carme

    2015-02-01

    We propose a new approach for the segmentation of 3-D point clouds into geometric surfaces using adaptive surface models. Starting from an initial configuration, the algorithm converges to a stable segmentation through a new iterative split-and-merge procedure, which includes an adaptive mechanism for the creation and removal of segments. This allows the segmentation to adjust to changing input data along the movie, leading to stable, temporally coherent, and traceable segments. We tested the method on a large variety of data acquired with different range imaging devices, including a structured-light sensor and a time-of-flight camera, and successfully segmented the videos into surface segments. We further demonstrated the feasibility of the approach using quantitative evaluations based on ground-truth data.

  11. Edge detection, color quantization, segmentation, texture removal, and noise reduction of color image using quaternion iterative filtering

    NASA Astrophysics Data System (ADS)

    Hsiao, Yu-Zhe; Pei, Soo-Chang

    2014-07-01

    Empirical mode decomposition (EMD) is a simple, local, adaptive, and efficient method for nonlinear and nonstationary signal analysis. However, for dealing with multidimensional signals, EMD and its variants such as bidimensional EMD (BEMD) and multidimensional EMD (MEMD) are very slow due to the needs of a large amount of envelope interpolations. Recently, a method called iterative filtering has been proposed. This filtering-based method is not as precise as EMD but its processing speed is very fast and can achieve comparable results as EMD does in many image and signal processing applications. We combine quaternion algebra and iterative filtering to achieve the edge detection, color quantization, segmentation, texture removal, and noise reduction task of color images. We can obtain similar results by using quaternion combined with EMD; however, as mentioned before, EMD is slow and cumbersome. Therefore, we propose to use quaternion iterative filtering as an alternative method for quaternion EMD (QEMD). The edge of color images can be detected by using intrinsic mode functions (IMFs) and the color quantization results can be obtained from residual image. The noise reduction algorithm of our method can be used to deal with Gaussian, salt-and-pepper, speckle noise, etc. The peak signal-to-noise ratio results are satisfactory and the processing speed is also very fast. Since textures in a color image are high-frequency components, we also can use quaternion iterative filtering to decompose a color image into many high- and low-frequency IMFs and remove textures by eliminating high-frequency IMFs.

  12. Epistatic adaptive evolution of human color vision.

    PubMed

    Yokoyama, Shozo; Xing, Jinyi; Liu, Yang; Faggionato, Davide; Altun, Ahmet; Starmer, William T

    2014-12-01

    Establishing genotype-phenotype relationship is the key to understand the molecular mechanism of phenotypic adaptation. This initial step may be untangled by analyzing appropriate ancestral molecules, but it is a daunting task to recapitulate the evolution of non-additive (epistatic) interactions of amino acids and function of a protein separately. To adapt to the ultraviolet (UV)-free retinal environment, the short wavelength-sensitive (SWS1) visual pigment in human (human S1) switched from detecting UV to absorbing blue light during the last 90 million years. Mutagenesis experiments of the UV-sensitive pigment in the Boreoeutherian ancestor show that the blue-sensitivity was achieved by seven mutations. The experimental and quantum chemical analyses show that 4,008 of all 5,040 possible evolutionary trajectories are terminated prematurely by containing a dehydrated nonfunctional pigment. Phylogenetic analysis further suggests that human ancestors achieved the blue-sensitivity gradually and almost exclusively by epistasis. When the final stage of spectral tuning of human S1 was underway 45-30 million years ago, the middle and long wavelength-sensitive (MWS/LWS) pigments appeared and so-called trichromatic color vision was established by interprotein epistasis. The adaptive evolution of human S1 differs dramatically from orthologous pigments with a major mutational effect used in achieving blue-sensitivity in a fish and several mammalian species and in regaining UV vision in birds. These observations imply that the mechanisms of epistatic interactions must be understood by studying various orthologues in different species that have adapted to various ecological and physiological environments. PMID:25522367

  13. Epistatic Adaptive Evolution of Human Color Vision

    PubMed Central

    Yokoyama, Shozo; Xing, Jinyi; Liu, Yang; Faggionato, Davide; Altun, Ahmet; Starmer, William T.

    2014-01-01

    Establishing genotype-phenotype relationship is the key to understand the molecular mechanism of phenotypic adaptation. This initial step may be untangled by analyzing appropriate ancestral molecules, but it is a daunting task to recapitulate the evolution of non-additive (epistatic) interactions of amino acids and function of a protein separately. To adapt to the ultraviolet (UV)-free retinal environment, the short wavelength-sensitive (SWS1) visual pigment in human (human S1) switched from detecting UV to absorbing blue light during the last 90 million years. Mutagenesis experiments of the UV-sensitive pigment in the Boreoeutherian ancestor show that the blue-sensitivity was achieved by seven mutations. The experimental and quantum chemical analyses show that 4,008 of all 5,040 possible evolutionary trajectories are terminated prematurely by containing a dehydrated nonfunctional pigment. Phylogenetic analysis further suggests that human ancestors achieved the blue-sensitivity gradually and almost exclusively by epistasis. When the final stage of spectral tuning of human S1 was underway 45–30 million years ago, the middle and long wavelength-sensitive (MWS/LWS) pigments appeared and so-called trichromatic color vision was established by interprotein epistasis. The adaptive evolution of human S1 differs dramatically from orthologous pigments with a major mutational effect used in achieving blue-sensitivity in a fish and several mammalian species and in regaining UV vision in birds. These observations imply that the mechanisms of epistatic interactions must be understood by studying various orthologues in different species that have adapted to various ecological and physiological environments. PMID:25522367

  14. Epistatic adaptive evolution of human color vision.

    PubMed

    Yokoyama, Shozo; Xing, Jinyi; Liu, Yang; Faggionato, Davide; Altun, Ahmet; Starmer, William T

    2014-12-01

    Establishing genotype-phenotype relationship is the key to understand the molecular mechanism of phenotypic adaptation. This initial step may be untangled by analyzing appropriate ancestral molecules, but it is a daunting task to recapitulate the evolution of non-additive (epistatic) interactions of amino acids and function of a protein separately. To adapt to the ultraviolet (UV)-free retinal environment, the short wavelength-sensitive (SWS1) visual pigment in human (human S1) switched from detecting UV to absorbing blue light during the last 90 million years. Mutagenesis experiments of the UV-sensitive pigment in the Boreoeutherian ancestor show that the blue-sensitivity was achieved by seven mutations. The experimental and quantum chemical analyses show that 4,008 of all 5,040 possible evolutionary trajectories are terminated prematurely by containing a dehydrated nonfunctional pigment. Phylogenetic analysis further suggests that human ancestors achieved the blue-sensitivity gradually and almost exclusively by epistasis. When the final stage of spectral tuning of human S1 was underway 45-30 million years ago, the middle and long wavelength-sensitive (MWS/LWS) pigments appeared and so-called trichromatic color vision was established by interprotein epistasis. The adaptive evolution of human S1 differs dramatically from orthologous pigments with a major mutational effect used in achieving blue-sensitivity in a fish and several mammalian species and in regaining UV vision in birds. These observations imply that the mechanisms of epistatic interactions must be understood by studying various orthologues in different species that have adapted to various ecological and physiological environments.

  15. Survey of contemporary trends in color image segmentation

    NASA Astrophysics Data System (ADS)

    Vantaram, Sreenath Rao; Saber, Eli

    2012-10-01

    In recent years, the acquisition of image and video information for processing, analysis, understanding, and exploitation of the underlying content in various applications, ranging from remote sensing to biomedical imaging, has grown at an unprecedented rate. Analysis by human observers is quite laborious, tiresome, and time consuming, if not infeasible, given the large and continuously rising volume of data. Hence the need for systems capable of automatically and effectively analyzing the aforementioned imagery for a variety of uses that span the spectrum from homeland security to elderly care. In order to achieve the above, tools such as image segmentation provide the appropriate foundation for expediting and improving the effectiveness of subsequent high-level tasks by providing a condensed and pertinent representation of image information. We provide a comprehensive survey of color image segmentation strategies adopted over the last decade, though notable contributions in the gray scale domain will also be discussed. Our taxonomy of segmentation techniques is sampled from a wide spectrum of spatially blind (or feature-based) approaches such as clustering and histogram thresholding as well as spatially guided (or spatial domain-based) methods such as region growing/splitting/merging, energy-driven parametric/geometric active contours, supervised/unsupervised graph cuts, and watersheds, to name a few. In addition, qualitative and quantitative results of prominent algorithms on several images from the Berkeley segmentation dataset are shown in order to furnish a fair indication of the current quality of the state of the art. Finally, we provide a brief discussion on our current perspective of the field as well as its associated future trends.

  16. [An adaptive threshloding segmentation method for urinary sediment image].

    PubMed

    Li, Yongming; Zeng, Xiaoping; Qin, Jian; Han, Liang

    2009-02-01

    In this paper is proposed a new method to solve the segmentation of the complicated defocusing urinary sediment image. The main points of the method are: (1) using wavelet transforms and morphology to erase the effect of defocusing and realize the first segmentation, (2) using adaptive threshold processing in accordance to the subimages after wavelet processing, and (3) using 'peel off' algorithm to deal with the overlapped cells' segmentations. The experimental results showed that this method was not affected by the defocusing, and it made good use of many kinds of characteristics of the images. So this new mehtod can get very precise segmentation; it is effective for defocusing urinary sediment image segmentation.

  17. Color image segmentation by the vector-valued Allen-Cahn phase-field model: a multigrid solution.

    PubMed

    Kay, David A; Tomasi, Alessandro

    2009-10-01

    We present an efficient numerical solution of a PDE-driven model for color image segmentation and give numerical examples of the results. The method combines the vector-valued Allen-Cahn phase field equation with initial data fitting terms with prescribed interface width and fidelity constants. Efficient numerical solution is achieved using a multigrid splitting of a finite element space, thereby producing an efficient and robust method for the segmentation of large images. We also present the use of adaptive mesh refinement to further speed up the segmentation process.

  18. A model of incomplete chromatic adaptation for calculating corresponding colors

    SciTech Connect

    Fairchild, M.D.

    1990-01-01

    A new mathematical model of chromatic adaptation for calculating corresponding colors across changes in illumination is formulated and tested. This model consists of a modified von Kries transform that accounts for incomplete levels of adaptation. The model predicts that adaptation will be less complete as the saturation of the adapting stimulus increases and more complete as the luminance of the adapting stimulus increases. The model is tested with experimental results from two different studies and found to be significantly better at predicting corresponding colors than other proposed models. This model represents a first step toward the specification of color appearance across varying conditions. 30 refs., 3 figs., 1 tab.

  19. Do common mechanisms of adaptation mediate color discrimination and appearance? Contrast adaptation

    NASA Astrophysics Data System (ADS)

    Hillis, James M.; Brainard, David H.

    2007-08-01

    Are effects of background contrast on color appearance and sensitivity controlled by the same mechanism of adaptation? We examined the effects of background color contrast on color appearance and on color-difference sensitivity under well-matched conditions. We linked the data using Fechner's hypothesis that the rate of apparent stimulus change is proportional to sensitivity and examined a family of parametric models of adaptation. Our results show that both appearance and discrimination are consistent with the same mechanism of adaptation.

  20. Do common mechanisms of adaptation mediate color discrimination and appearance? Contrast adaptation.

    PubMed

    Hillis, James M; Brainard, David H

    2007-08-01

    Are effects of background contrast on color appearance and sensitivity controlled by the same mechanism of adaptation? We examined the effects of background color contrast on color appearance and on color-difference sensitivity under well-matched conditions. We linked the data using Fechner's hypothesis that the rate of apparent stimulus change is proportional to sensitivity and examined a family of parametric models of adaptation. Our results show that both appearance and discrimination are consistent with the same mechanism of adaptation.

  1. Comparison of color image segmentations for lane following

    NASA Astrophysics Data System (ADS)

    Sandt, Frederic; Aubert, Didier

    1993-05-01

    For ten years, unstructured road following has been the subject of many studies. Road following must support the automatic navigation, at reasonable speed, of mobile robots on irregular paths and roads, with unhomogeneous surfaces and under variable lighting conditions. Civil and military applications of this technology include transportation, logistics, security and engineering. The definition of our lane following system requires an evaluation of the existing technologies. Although the various operational systems converge on a color perception and a region segmentation optimizing discrimination and stability respectively, the treatments and performances vary. In this paper, the robustness of four operational systems and two connected techniques are compared according to common evaluation criteria. We identify typical situations which constitute a basis for the realization of an image database. We describe the process of experimentation conceived for the comparative analysis of performances. The analytical results are useful in order to infer a few optimal combinations of techniques driven by the situations, and to define the present limits of the color perception's validity.

  2. Recognition of sport players' numbers using fast-color segmentation

    NASA Astrophysics Data System (ADS)

    Verleysen, Cédric; De Vleeschouwer, Christophe

    2012-01-01

    This paper builds on a prior work for player detection, and proposes an efficient and effective method to distinguish among players based on the numbers printed on their jerseys. To extract the numbers, the dominant colors of the jersey are learnt during an initial phase and used to speed up the segmentation of the candidate digit regions. An additional set of criteria, considering the relative position and size (compared to the player bounding box) and the density (compared to the digit rectangular support) of the digit, are used to filter out the regions that obviously do not correspond to a digit. Once the plausible digit regions have been extracted, their recognition is based on feature-based classification. A number of original features are proposed to increase the robustness against digit appearance changes, resulting from the font thickness variability and from the deformations of the jersey during the game. Finally, the efficiency and the effectiveness of the proposed method are demonstrated on a real-life basketball dataset. It shows that the proposed segmentation runs about ten times faster than the mean-shift algorithm, but also outlines that the proposed additional features significantly increase the digit recognition accuracy. Despite significant deformations, 40% of the samples, that can be visually recognized as digits, are well classified as numbers. Out of these classified samples, more than 80% of them are correctly recognized. Besides, more than 95% of the samples, that are not numbers, are correctly identified as non-numbers.

  3. Microscopic cell nuclei segmentation based on adaptive attention window.

    PubMed

    Ko, ByoungChul; Seo, MiSuk; Nam, Jae-Yeal

    2009-06-01

    This paper presents an adaptive attention window (AAW)-based microscopic cell nuclei segmentation method. For semantic AAW detection, a luminance map is used to create an initial attention window, which is then reduced close to the size of the real region of interest (ROI) using a quad-tree. The purpose of the AAW is to facilitate background removal and reduce the ROI segmentation processing time. Region segmentation is performed within the AAW, followed by region clustering and removal to produce segmentation of only ROIs. Experimental results demonstrate that the proposed method can efficiently segment one or more ROIs and produce similar segmentation results to human perception. In future work, the proposed method will be used for supporting a region-based medical image retrieval system that can generate a combined feature vector of segmented ROIs based on extraction and patient data.

  4. Space Adaptation of Active Mirror Segment Concepts

    NASA Technical Reports Server (NTRS)

    Ames, Gregory H.

    1999-01-01

    This report summarizes the results of a three year effort by Blue Line Engineering Co. to advance the state of segmented mirror systems in several separate but related areas. The initial set of tasks were designed to address the issues of system level architecture, digital processing system, cluster level support structures, and advanced mirror fabrication concepts. Later in the project new tasks were added to provide support to the existing segmented mirror testbed at Marshall Space Flight Center (MSFC) in the form of upgrades to the 36 subaperture wavefront sensor. Still later, tasks were added to build and install a new system processor based on the results of the new system architecture. The project was successful in achieving a number of important results. These include the following most notable accomplishments: 1) The creation of a new modular digital processing system that is extremely capable and may be applied to a wide range of segmented mirror systems as well as many classes of Multiple Input Multiple Output (MIMO) control systems such as active structures or industrial automation. 2) A new graphical user interface was created for operation of segmented mirror systems. 3) The development of a high bit rate serial data loop that permits bi-directional flow of data to and from as many as 39 segments daisy-chained to form a single cluster of segments. 4) Upgrade of the 36 subaperture Hartmann type Wave Front Sensor (WFS) of the Phased Array Mirror, Extendible Large Aperture (PAMELA) testbed at MSFC resulting in a 40 to 5OX improvement in SNR which in turn enabled NASA personnel to achieve many significant strides in improved closed-loop system operation in 1998. 5) A new system level processor was built and delivered to MSFC for use with the PAMELA testbed. This new system featured a new graphical user interface to replace the obsolete and non-supported menu system originally delivered with the PAMELA system. The hardware featured Blue Line's new stackable

  5. Adaptive automatic segmentation of Leishmaniasis parasite in Indirect Immunofluorescence images.

    PubMed

    Ouertani, F; Amiri, H; Bettaib, J; Yazidi, R; Ben Salah, A

    2014-01-01

    This paper describes the first steps for the automation of the serum titration process. In fact, this process requires an Indirect Immunofluorescence (IIF) diagnosis automation. We deal with the initial phase that represents the fluorescence images segmentation. Our approach consists of three principle stages: (1) a color based segmentation which aims at extracting the fluorescent foreground based on k-means clustering, (2) the segmentation of the fluorescent clustered image, and (3) a region-based feature segmentation, intended to remove the fluorescent noisy regions and to locate fluorescent parasites. We evaluated the proposed method on 40 IIF images. Experimental results show that such a method provides reliable and robust automatic segmentation of fluorescent Promastigote parasite. PMID:25571049

  6. Adaptive color contrast enhancement for digital images

    NASA Astrophysics Data System (ADS)

    Wang, Yanfang; Luo, Yupin

    2011-11-01

    Noncanonical illumination that is too dim or with color cast induces degenerated images. To cope with this, we propose a method for color-contrast enhancement. First, intensity, chrominance, and contrast characteristics are explored and integrated in the Naka-Rushton equation to remove underexposure and color cast simultaneously. Motivated by the comparison mechanism in Retinex, the ratio of each pixel to its surroundings is utilized to improve image contrast. Finally, inspired by the two color-opponent dimensions in CIELAB space, a color-enhancement strategy is devised based on the transformation from CIEXYZ to CIELAB color space. For images that suffer from underexposure, color cast, or both problems, our algorithm produces promising results without halo artifacts and corruption of uniform areas.

  7. Unsupervised color image segmentation using graph cuts with multi-components

    NASA Astrophysics Data System (ADS)

    Li, Lei; Jin, Lianghai; Song, Enmin; Dong, Zhuoli

    2013-10-01

    A novel unsupervised color image segmentation method based on graph cuts with multi-components is proposed, which finds an optimal segmentation of an image by regarding it as an energy minimization problem. First, L*a*b* color space is chosen as color feature, and the multi-scale quaternion Gabor filter is employed to extract texture feature of the given image. Then, the segmentation is formulated in terms of energy minimization with an iterative process based on graph cuts, and the connected regions in each segment are considered as the components of the segment in each iteration. In addition, canny edge detector combined with color gradient is used to remove weak edges in segmentation results with the proposed algorithm. In contrast to previous algorithms, our method could greatly reduce computational complexity during inference procedure by graph cuts. Experimental results demonstrate the promising performance of the proposed method.

  8. Adaptive color rendering of maps for users with color vision deficiencies

    NASA Astrophysics Data System (ADS)

    Kvitle, Anne Kristin; Green, Phil; Nussbaum, Peter

    2015-01-01

    A map is an information design object for which canonical colors for the most common elements are well established. For a CVD observer, it may be difficult to discriminate between such elements - for example, it may be hard to distinguish a red road from a green landscape on the basis of color alone. We address this problem through an adaptive color schema in which the conspicuity of elements in a map to the individual user is maximized. This paper outlines a method to perform adaptive color rendering of map information for users with color vision deficiencies. The palette selection method is based on a pseudo-color palette generation technique which constrains colors to those which lie on the boundary of a reference object color gamut. A user performs a color vision discrimination task, and based on the results of the test, a palette of colors is selected using the pseudo-color palette generation method. This ensures that the perceived difference between palette elements is high but which retains the canonical color of well-known elements as far as possible. We show examples of color palettes computed for a selection of normal and CVD observers, together with maps rendered using these palettes.

  9. Adaptive geodesic transform for segmentation of vertebrae on CT images

    NASA Astrophysics Data System (ADS)

    Gaonkar, Bilwaj; Shu, Liao; Hermosillo, Gerardo; Zhan, Yiqiang

    2014-03-01

    Vertebral segmentation is a critical first step in any quantitative evaluation of vertebral pathology using CT images. This is especially challenging because bone marrow tissue has the same intensity profile as the muscle surrounding the bone. Thus simple methods such as thresholding or adaptive k-means fail to accurately segment vertebrae. While several other algorithms such as level sets may be used for segmentation any algorithm that is clinically deployable has to work in under a few seconds. To address these dual challenges we present here, a new algorithm based on the geodesic distance transform that is capable of segmenting the spinal vertebrae in under one second. To achieve this we extend the theory of the geodesic distance transforms proposed in1 to incorporate high level anatomical knowledge through adaptive weighting of image gradients. Such knowledge may be provided by the user directly or may be automatically generated by another algorithm. We incorporate information 'learnt' using a previously published machine learning algorithm2 to segment the L1 to L5 vertebrae. While we present a particular application here, the adaptive geodesic transform is a generic concept which can be applied to segmentation of other organs as well.

  10. White blood cell segmentation by color-space-based k-means clustering.

    PubMed

    Zhang, Congcong; Xiao, Xiaoyan; Li, Xiaomei; Chen, Ying-Jie; Zhen, Wu; Chang, Jun; Zheng, Chengyun; Liu, Zhi

    2014-09-01

    White blood cell (WBC) segmentation, which is important for cytometry, is a challenging issue because of the morphological diversity of WBCs and the complex and uncertain background of blood smear images. This paper proposes a novel method for the nucleus and cytoplasm segmentation of WBCs for cytometry. A color adjustment step was also introduced before segmentation. Color space decomposition and k-means clustering were combined for segmentation. A database including 300 microscopic blood smear images were used to evaluate the performance of our method. The proposed segmentation method achieves 95.7% and 91.3% overall accuracy for nucleus segmentation and cytoplasm segmentation, respectively. Experimental results demonstrate that the proposed method can segment WBCs effectively with high accuracy.

  11. Enhancement dark channel algorithm of color fog image based on the local segmentation

    NASA Astrophysics Data System (ADS)

    Yun, Lijun; Gao, Yin; Shi, Jun-sheng; Xu, Ling-zhang

    2015-04-01

    The classical dark channel theory algorithm has yielded good results in the processing of single fog image, but in some larger contrast regions, it appears image hue, brightness and saturation distortion problems to a certain degree, and also produces halo phenomenon. In the view of the above situation, through a lot of experiments, this paper has found some factors causing the halo phenomenon. The enhancement dark channel algorithm of color fog image based on the local segmentation is proposed. On the basis of the dark channel theory, first of all, the classic dark channel theory of mathematical model is modified, which is mainly to correct the brightness and saturation of image. Then, according to the local adaptive segmentation theory, it process the block of image, and overlap the local image. On the basis of the statistical rules, it obtains each pixel value from the segmentation processing, so as to obtain the local image. At last, using the dark channel theory, it achieves the enhanced fog image. Through the subjective observation and objective evaluation, the algorithm is better than the classic dark channel algorithm in the overall and details.

  12. Habitual wearers of colored lenses adapt more rapidly to the color changes the lenses produce.

    PubMed

    Engel, Stephen A; Wilkins, Arnold J; Mand, Shivraj; Helwig, Nathaniel E; Allen, Peter M

    2016-08-01

    The visual system continuously adapts to the environment, allowing it to perform optimally in a changing visual world. One large change occurs every time one takes off or puts on a pair of spectacles. It would be advantageous for the visual system to learn to adapt particularly rapidly to such large, commonly occurring events, but whether it can do so remains unknown. Here, we tested whether people who routinely wear spectacles with colored lenses increase how rapidly they adapt to the color shifts their lenses produce. Adaptation to a global color shift causes the appearance of a test color to change. We measured changes in the color that appeared "unique yellow", that is neither reddish nor greenish, as subjects donned and removed their spectacles. Nine habitual wearers and nine age-matched control subjects judged the color of a small monochromatic test light presented with a large, uniform, whitish surround every 5s. Red lenses shifted unique yellow to more reddish colors (longer wavelengths), and greenish lenses shifted it to more greenish colors (shorter wavelengths), consistent with adaptation "normalizing" the appearance of the world. In controls, the time course of this adaptation contained a large, rapid component and a smaller gradual one, in agreement with prior results. Critically, in habitual wearers the rapid component was significantly larger, and the gradual component significantly smaller than in controls. The total amount of adaptation was also larger in habitual wearers than in controls. These data suggest strongly that the visual system adapts with increasing rapidity and strength as environments are encountered repeatedly over time. An additional unexpected finding was that baseline unique yellow shifted in a direction opposite to that produced by the habitually worn lenses. Overall, our results represent one of the first formal reports that adjusting to putting on or taking off spectacles becomes easier over time, and may have important

  13. Colorization and Automated Segmentation of Human T2 MR Brain Images for Characterization of Soft Tissues

    PubMed Central

    Attique, Muhammad; Gilanie, Ghulam; Hafeez-Ullah; Mehmood, Malik S.; Naweed, Muhammad S.; Ikram, Masroor; Kamran, Javed A.; Vitkin, Alex

    2012-01-01

    Characterization of tissues like brain by using magnetic resonance (MR) images and colorization of the gray scale image has been reported in the literature, along with the advantages and drawbacks. Here, we present two independent methods; (i) a novel colorization method to underscore the variability in brain MR images, indicative of the underlying physical density of bio tissue, (ii) a segmentation method (both hard and soft segmentation) to characterize gray brain MR images. The segmented images are then transformed into color using the above-mentioned colorization method, yielding promising results for manual tracing. Our color transformation incorporates the voxel classification by matching the luminance of voxels of the source MR image and provided color image by measuring the distance between them. The segmentation method is based on single-phase clustering for 2D and 3D image segmentation with a new auto centroid selection method, which divides the image into three distinct regions (gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using prior anatomical knowledge). Results have been successfully validated on human T2-weighted (T2) brain MR images. The proposed method can be potentially applied to gray-scale images from other imaging modalities, in bringing out additional diagnostic tissue information contained in the colorized image processing approach as described. PMID:22479421

  14. Patterns of Transfer of Adaptation Among Body Segments

    NASA Technical Reports Server (NTRS)

    Seidler, R. D.; Bloomberg, J. J.; Stelmach, George E.

    2000-01-01

    Two experiments were conducted in order to determine the patterns of transfer of visuomotor adaptation between arm and head pointing. An altered gain of display of pointing movements was used to induce a conflict between visual and somatosensory representations. Two subject groups participated in Experiment One: group 1 adapted shoulder pointing movements, and group 2 adapted wrist pointing movements to a 0.5 gain of display. Following the adaptation regimen, subjects performed a transfer test in which the shoulder group performed wrist movements and the wrist group performed shoulder movements. The results demonstrated that both groups displayed typical adaptation curves, initially undershooting the target followed by a return to baseline performance. Transfer tests revealed that both groups had high transfer of the acquired adaptation to the other joint. Experiment Two followed a similar design except that group 1 adapted head pointing movements and group 2 adapted arm pointing movements. The arm adaptation had high transfer to head pointing while the head adaptation had very little transfer to arm pointing. These results imply that, while the arm segments may share a common target representation for goal-directed actions, individual but functionally dependent target representations may exist for the control of head and arm movements.

  15. Patterns of transfer of adaptation among body segments

    NASA Technical Reports Server (NTRS)

    Seidler, R. D.; Bloomberg, J. J.; Stelmach, G. E.

    2001-01-01

    Two experiments were conducted in order to determine the patterns of transfer of visuomotor adaptation between arm and head pointing. An altered gain of display of pointing movements was used to induce a conflict between visual and somatosensory representations. Two subject groups participated in Experiment 1: group 1 adapted shoulder pointing movements, and group 2 adapted wrist pointing movements to a 0.5 gain of display. Following the adaptation regimen, subjects performed a transfer test in which the shoulder group performed wrist movements and the wrist group performed shoulder movements. The results demonstrated that both groups displayed typical adaptation curves, initially undershooting the target followed by a return to baseline performance. Transfer tests revealed that both groups had high transfer of the acquired adaptation to the other joint. Experiment 2 followed a similar design except that group 1 adapted head pointing movements and group 2 adapted arm pointing movements. The arm adaptation had high transfer to head pointing while the head adaptation had very little transfer to arm pointing. These results imply that, while the arm segments may share a common target representation for goal-directed actions, individual but functionally dependent target representations may exist for the control of head and arm movements.

  16. Segmentation and classification of burn images by color and texture information.

    PubMed

    Acha, Begoña; Serrano, Carmen; Acha, José I; Roa, Laura M

    2005-01-01

    In this paper, a burn color image segmentation and classification system is proposed. The aim of the system is to separate burn wounds from healthy skin, and to distinguish among the different types of burns (burn depths). Digital color photographs are used as inputs to the system. The system is based on color and texture information, since these are the characteristics observed by physicians in order to form a diagnosis. A perceptually uniform color space (L*u*v*) was used, since Euclidean distances calculated in this space correspond to perceptual color differences. After the burn is segmented, a set of color and texture features is calculated that serves as the input to a Fuzzy-ARTMAP neural network. The neural network classifies burns into three types of burn depths: superficial dermal, deep dermal, and full thickness. Clinical effectiveness of the method was demonstrated on 62 clinical burn wound images, yielding an average classification success rate of 82%.

  17. Segmentation and classification of burn images by color and texture information.

    PubMed

    Acha, Begoña; Serrano, Carmen; Acha, José I; Roa, Laura M

    2005-01-01

    In this paper, a burn color image segmentation and classification system is proposed. The aim of the system is to separate burn wounds from healthy skin, and to distinguish among the different types of burns (burn depths). Digital color photographs are used as inputs to the system. The system is based on color and texture information, since these are the characteristics observed by physicians in order to form a diagnosis. A perceptually uniform color space (L*u*v*) was used, since Euclidean distances calculated in this space correspond to perceptual color differences. After the burn is segmented, a set of color and texture features is calculated that serves as the input to a Fuzzy-ARTMAP neural network. The neural network classifies burns into three types of burn depths: superficial dermal, deep dermal, and full thickness. Clinical effectiveness of the method was demonstrated on 62 clinical burn wound images, yielding an average classification success rate of 82%. PMID:16229658

  18. The adaptive value of primate color vision for predator detection.

    PubMed

    Pessoa, Daniel Marques Almeida; Maia, Rafael; de Albuquerque Ajuz, Rafael Cavalcanti; De Moraes, Pedro Zurvaino Palmeira Melo Rosa; Spyrides, Maria Helena Constantino; Pessoa, Valdir Filgueiras

    2014-08-01

    The complex evolution of primate color vision has puzzled biologists for decades. Primates are the only eutherian mammals that evolved an enhanced capacity for discriminating colors in the green-red part of the spectrum (trichromatism). However, while Old World primates present three types of cone pigments and are routinely trichromatic, most New World primates exhibit a color vision polymorphism, characterized by the occurrence of trichromatic and dichromatic females and obligatory dichromatic males. Even though this has stimulated a prolific line of inquiry, the selective forces and relative benefits influencing color vision evolution in primates are still under debate, with current explanations focusing almost exclusively at the advantages in finding food and detecting socio-sexual signals. Here, we evaluate a previously untested possibility, the adaptive value of primate color vision for predator detection. By combining color vision modeling data on New World and Old World primates, as well as behavioral information from human subjects, we demonstrate that primates exhibiting better color discrimination (trichromats) excel those displaying poorer color visions (dichromats) at detecting carnivoran predators against the green foliage background. The distribution of color vision found in extant anthropoid primates agrees with our results, and may be explained by the advantages of trichromats and dichromats in detecting predators and insects, respectively. PMID:24535839

  19. The adaptive value of primate color vision for predator detection.

    PubMed

    Pessoa, Daniel Marques Almeida; Maia, Rafael; de Albuquerque Ajuz, Rafael Cavalcanti; De Moraes, Pedro Zurvaino Palmeira Melo Rosa; Spyrides, Maria Helena Constantino; Pessoa, Valdir Filgueiras

    2014-08-01

    The complex evolution of primate color vision has puzzled biologists for decades. Primates are the only eutherian mammals that evolved an enhanced capacity for discriminating colors in the green-red part of the spectrum (trichromatism). However, while Old World primates present three types of cone pigments and are routinely trichromatic, most New World primates exhibit a color vision polymorphism, characterized by the occurrence of trichromatic and dichromatic females and obligatory dichromatic males. Even though this has stimulated a prolific line of inquiry, the selective forces and relative benefits influencing color vision evolution in primates are still under debate, with current explanations focusing almost exclusively at the advantages in finding food and detecting socio-sexual signals. Here, we evaluate a previously untested possibility, the adaptive value of primate color vision for predator detection. By combining color vision modeling data on New World and Old World primates, as well as behavioral information from human subjects, we demonstrate that primates exhibiting better color discrimination (trichromats) excel those displaying poorer color visions (dichromats) at detecting carnivoran predators against the green foliage background. The distribution of color vision found in extant anthropoid primates agrees with our results, and may be explained by the advantages of trichromats and dichromats in detecting predators and insects, respectively.

  20. Image segmentation with implicit color standardization using spatially constrained expectation maximization: detection of nuclei.

    PubMed

    Monaco, James; Hipp, J; Lucas, D; Smith, S; Balis, U; Madabhushi, Anant

    2012-01-01

    Color nonstandardness--the propensity for similar objects to exhibit different color properties across images--poses a significant problem in the computerized analysis of histopathology. Though many papers propose means for improving color constancy, the vast majority assume image formation via reflective light instead of light transmission as in microscopy, and thus are inappropriate for histological analysis. Previously, we presented a novel Bayesian color segmentation algorithm for histological images that is highly robust to color nonstandardness; this algorithm employed the expectation maximization (EM) algorithm to dynamically estimate for each individual image the probability density functions that describe the colors of salient objects. However, our approach, like most EM-based algorithms, ignored important spatial constraints, such as those modeled by Markov random field (MRFs). Addressing this deficiency, we now present spatially-constrained EM (SCEM), a novel approach for incorporating Markov priors into the EM framework. With respect to our segmentation system, we replace EM with SCEM and then assess its improved ability to segment nuclei in H&E stained histopathology. Segmentation performance is evaluated over seven (nearly) identical sections of gastrointestinal tissue stained using different protocols (simulating severe color nonstandardness). Over this dataset, our system identifies nuclear regions with an area under the receiver operator characteristic curve (AUC) of 0.838. If we disregard spatial constraints, the AUC drops to 0.748.

  1. Adaptive distance metric learning for diffusion tensor image segmentation.

    PubMed

    Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C N; Chu, Winnie C W

    2014-01-01

    High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework.

  2. Adaptive Distance Metric Learning for Diffusion Tensor Image Segmentation

    PubMed Central

    Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C. N.; Chu, Winnie C. W.

    2014-01-01

    High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework. PMID:24651858

  3. Effects of inotropic stimulation on segmental left ventricular relaxation quantified by color kinesis.

    PubMed

    Carey, C F; Mor-Avi, V; Koch, R; Lang, R; Pérez, J E

    2000-06-15

    Although myocardial ischemia impairs left ventricular (LV) relaxation before contractile function, regional LV diastolic dysfunction is difficult to evaluate by conventional echocardiography. Because beta-adrenergic stimulation enhances myocardial relaxation, we sought to characterize segmental LV diastolic function (by color kinesis) during dobutamine stress echocardiography and compare it with independently assessed segmental systolic function. We studied 22 patients with suspected coronary artery disease with color kinesis by acquiring digital images with endocardial motion display throughout diastole. Quantification of LV segmental diastolic peak filling rate (SPFR, normalized to segmental end-diastolic area/s) was obtained at rest, low-dose, and peak dobutamine infusion in myocardial segments visualized from the short-axis and/or apical 4-chamber views. In patients with resting normal LV systolic function and a dobutamine-induced hypercontractile response (group I, n = 13 patients; 102 segments), progressive increases in SPFR (p <0.001) were seen in all segments. However, in LV segments with resting systolic wall motion abnormalities (group II, n = 9 patients; 74 segments) SPFR measured at rest was significantly lower than that in group I (p <0.005) and did not increase significantly in response to dobutamine. In both groups of patients, LV myocardial segments (n = 528; rest and after dobutamine)-systolic and quantitative diastolic function-were concordant in 84% and 77% as viewed from short-axis and apical views, respectively. Thus, segmental LV diastolic function can be measured with color kinesis at rest and after inotropic stimulation, allowing comparison with segmental systolic function during pharmacologic stress testing.

  4. Neonatal Brain Tissue Classification with Morphological Adaptation and Unified Segmentation.

    PubMed

    Beare, Richard J; Chen, Jian; Kelly, Claire E; Alexopoulos, Dimitrios; Smyser, Christopher D; Rogers, Cynthia E; Loh, Wai Y; Matthews, Lillian G; Cheong, Jeanie L Y; Spittle, Alicia J; Anderson, Peter J; Doyle, Lex W; Inder, Terrie E; Seal, Marc L; Thompson, Deanne K

    2016-01-01

    Measuring the distribution of brain tissue types (tissue classification) in neonates is necessary for studying typical and atypical brain development, such as that associated with preterm birth, and may provide biomarkers for neurodevelopmental outcomes. Compared with magnetic resonance images of adults, neonatal images present specific challenges that require the development of specialized, population-specific methods. This paper introduces MANTiS (Morphologically Adaptive Neonatal Tissue Segmentation), which extends the unified segmentation approach to tissue classification implemented in Statistical Parametric Mapping (SPM) software to neonates. MANTiS utilizes a combination of unified segmentation, template adaptation via morphological segmentation tools and topological filtering, to segment the neonatal brain into eight tissue classes: cortical gray matter, white matter, deep nuclear gray matter, cerebellum, brainstem, cerebrospinal fluid (CSF), hippocampus and amygdala. We evaluated the performance of MANTiS using two independent datasets. The first dataset, provided by the NeoBrainS12 challenge, consisted of coronal T 2-weighted images of preterm infants (born ≤30 weeks' gestation) acquired at 30 weeks' corrected gestational age (n = 5), coronal T 2-weighted images of preterm infants acquired at 40 weeks' corrected gestational age (n = 5) and axial T 2-weighted images of preterm infants acquired at 40 weeks' corrected gestational age (n = 5). The second dataset, provided by the Washington University NeuroDevelopmental Research (WUNDeR) group, consisted of T 2-weighted images of preterm infants (born <30 weeks' gestation) acquired shortly after birth (n = 12), preterm infants acquired at term-equivalent age (n = 12), and healthy term-born infants (born ≥38 weeks' gestation) acquired within the first 9 days of life (n = 12). For the NeoBrainS12 dataset, mean Dice scores comparing MANTiS with manual segmentations were all above 0.7, except for the cortical

  5. Neonatal Brain Tissue Classification with Morphological Adaptation and Unified Segmentation

    PubMed Central

    Beare, Richard J.; Chen, Jian; Kelly, Claire E.; Alexopoulos, Dimitrios; Smyser, Christopher D.; Rogers, Cynthia E.; Loh, Wai Y.; Matthews, Lillian G.; Cheong, Jeanie L. Y.; Spittle, Alicia J.; Anderson, Peter J.; Doyle, Lex W.; Inder, Terrie E.; Seal, Marc L.; Thompson, Deanne K.

    2016-01-01

    Measuring the distribution of brain tissue types (tissue classification) in neonates is necessary for studying typical and atypical brain development, such as that associated with preterm birth, and may provide biomarkers for neurodevelopmental outcomes. Compared with magnetic resonance images of adults, neonatal images present specific challenges that require the development of specialized, population-specific methods. This paper introduces MANTiS (Morphologically Adaptive Neonatal Tissue Segmentation), which extends the unified segmentation approach to tissue classification implemented in Statistical Parametric Mapping (SPM) software to neonates. MANTiS utilizes a combination of unified segmentation, template adaptation via morphological segmentation tools and topological filtering, to segment the neonatal brain into eight tissue classes: cortical gray matter, white matter, deep nuclear gray matter, cerebellum, brainstem, cerebrospinal fluid (CSF), hippocampus and amygdala. We evaluated the performance of MANTiS using two independent datasets. The first dataset, provided by the NeoBrainS12 challenge, consisted of coronal T2-weighted images of preterm infants (born ≤30 weeks' gestation) acquired at 30 weeks' corrected gestational age (n = 5), coronal T2-weighted images of preterm infants acquired at 40 weeks' corrected gestational age (n = 5) and axial T2-weighted images of preterm infants acquired at 40 weeks' corrected gestational age (n = 5). The second dataset, provided by the Washington University NeuroDevelopmental Research (WUNDeR) group, consisted of T2-weighted images of preterm infants (born <30 weeks' gestation) acquired shortly after birth (n = 12), preterm infants acquired at term-equivalent age (n = 12), and healthy term-born infants (born ≥38 weeks' gestation) acquired within the first 9 days of life (n = 12). For the NeoBrainS12 dataset, mean Dice scores comparing MANTiS with manual segmentations were all above 0.7, except for the cortical gray

  6. Responding to color: the regulation of complementary chromatic adaptation.

    PubMed

    Kehoe, David M; Gutu, Andrian

    2006-01-01

    The acclimation of photosynthetic organisms to changes in light color is ubiquitous and may be best illustrated by the colorful process of complementary chromatic adaptation (CCA). During CCA, cyanobacterial cells change from brick red to bright blue green, depending on their light color environment. The apparent simplicity of this spectacular, photoreversible event belies the complexity of the cellular response to changes in light color. Recent results have shown that the regulation of CCA is also complex and involves at least three pathways. One is controlled by a phytochrome-class photoreceptor that is responsive to green and red light and a complex two-component signal transduction pathway, whereas another is based on sensing redox state. Studies of CCA are uncovering the strategies used by photosynthetic organisms during light acclimation and the means by which they regulate these responses.

  7. Generalization of Hindi OCR Using Adaptive Segmentation and Font Files

    NASA Astrophysics Data System (ADS)

    Agrawal, Mudit; Ma, Huanfeng; Doermann, David

    In this chapter, we describe an adaptive Indic OCR system implemented as part of a rapidly retargetable language tool effort and extend work found in [20, 2]. The system includes script identification, character segmentation, training sample creation, and character recognition. For script identification, Hindi words are identified in bilingual or multilingual document images using features of the Devanagari script and support vector machine (SVM). Identified words are then segmented into individual characters, using a font-model-based intelligent character segmentation and recognition system. Using characteristics of structurally similar TrueType fonts, our system automatically builds a model to be used for the segmentation and recognition of the new script, independent of glyph composition. The key is a reliance on known font attributes. In our recognition system three feature extraction methods are used to demonstrate the importance of appropriate features for classification. The methods are tested on both Latin and non-Latin scripts. Results show that the character-level recognition accuracy exceeds 92% for non-Latin and 96% for Latin text on degraded documents. This work is a step toward the recognition of scripts of low-density languages which typically do not warrant the development of commercial OCR, yet often have complete TrueType font descriptions.

  8. Legibility of characters with different segmentations and colors

    NASA Astrophysics Data System (ADS)

    Reinig, H. J.

    The legibility of electronically presented information, e.g., public transport timetables, was tested. The minimal and the optimal legibility conditions of short words in 5X7 dot matrix and 14 line segment characters were compared with the legibility of continuous characters. The words were presented by screen projection with decreasing size of characters with fixed distance to the subject (minimum legibility). Optimal legibility was determined subjectively. The size of characters of negative contrast has to be increased by 20 compared with positive contrast. The 5X7 dot matrix characters are as legible as continuous letters. The 14 line segment characters must be presented 1.3 times higher for the same legibility. White characters on blue background were preferred by most subjects.

  9. Robust semi-automatic segmentation of single- and multichannel MRI volumes through adaptable class-specific representation

    NASA Astrophysics Data System (ADS)

    Nielsen, Casper F.; Passmore, Peter J.

    2002-05-01

    Segmentation of MRI volumes is complicated by noise, inhomogeneity and partial volume artefacts. Fully or semi-automatic methods often require time consuming or unintuitive initialization. Adaptable Class-Specific Representation (ACSR) is a semi-automatic segmentation framework implemented by the Path Growing Algorithm (PGA), which reduces artefacts near segment boundaries. The user visually defines the desired segment classes through the selection of class templates and the following segmentation process is fully automatic. Good results have previously been achieved with color cryo section segmentation and ACSR has been developed further for the MRI modality. In this paper we present two optimizations for robust ACSR segmentation of MRI volumes. Automatic template creation based on an initial segmentation step using Learning Vector Quantization is applied for higher robustness to noise. Inhomogeneity correction is added as a pre-processing step, comparing the EQ and N3 algorithms. Results based on simulated T1-weighed and multispectral (T1 and T2) MRI data from the BrainWeb database and real data from the Internet Brain Segmentation Repository are presented. We show that ACSR segmentation compares favorably to previously published results on the same volumes and discuss the pros and cons of using quantitative ground truth evaluation compared to qualitative visual assessment.

  10. Color segmentation as an aid to white balancing for digital still cameras

    NASA Astrophysics Data System (ADS)

    Cooper, Ted J.

    2000-12-01

    Digital Still Cameras employ automatic white balance techniques to adjust sensor amplifier gains so that white imaged objects appear white. A color cast detection algorithm is presented that uses histogram and segmentation techniques to select near-neutral objects in the image. Once identified and classified, these objects permit determination of the scene illuminant and implicitly the respective amplifier gains. Under certain circumstances, a scene may contain no near-neutral objects. By using the segmentation operations on non-neutral image objects, memory colors, from skin, sky, and foliage objects, may be identified. If identified, these memory colors provide enough chromatic information to predict the scene illuminant. By combining the approaches from near-neutral objects with those of memory color objects, a reasonable automatic white balance over a wide range of scenes is possible.

  11. Segmentation of branching vascular structures using adaptive subdivision surface fitting

    NASA Astrophysics Data System (ADS)

    Kitslaar, Pieter H.; van't Klooster, Ronald; Staring, Marius; Lelieveldt, Boudewijn P. F.; van der Geest, Rob J.

    2015-03-01

    This paper describes a novel method for segmentation and modeling of branching vessel structures in medical images using adaptive subdivision surfaces fitting. The method starts with a rough initial skeleton model of the vessel structure. A coarse triangular control mesh consisting of hexagonal rings and dedicated bifurcation elements is constructed from this skeleton. Special attention is paid to ensure a topological sound control mesh is created around the bifurcation areas. Then, a smooth tubular surface is obtained from this coarse mesh using a standard subdivision scheme. This subdivision surface is iteratively fitted to the image. During the fitting, the target update locations of the subdivision surface are obtained using a scanline search along the surface normals, finding the maximum gradient magnitude (of the imaging data). In addition to this surface fitting framework, we propose an adaptive mesh refinement scheme. In this step the coarse control mesh topology is updated based on the current segmentation result, enabling adaptation to varying vessel lumen diameters. This enhances the robustness and flexibility of the method and reduces the amount of prior knowledge needed to create the initial skeletal model. The method was applied to publicly available CTA data from the Carotid Bifurcation Algorithm Evaluation Framework resulting in an average dice index of 89.2% with the ground truth. Application of the method to the complex vascular structure of a coronary artery tree in CTA and to MRI images were performed to show the versatility and flexibility of the proposed framework.

  12. Weld Spot Detection by Color Segmentation and Template Convolution

    SciTech Connect

    Cambrini, Luigi; Biber, Juergen; Hoenigmann, Dieter; Loehndorf, Maike

    2007-12-26

    There is a need of non-destructive evaluation of the quality of steel spot welds. A computer-vision based solution is presented performing the analysis of the weld spot imprints left by the electrode on the protection bands. In this paper we propose two different methods to locate the position of the weld spot imprint as a first step in order to verify the quality of the welding process; both methods consist of two stages: (i) the use of the X channel of the XYZ color space as a proper representation, and (ii) the analysis of this image channel by employing specific algorithms.

  13. Level set segmentation for greenbelts by integrating wavelet texture and priori color knowledge

    NASA Astrophysics Data System (ADS)

    Yang, Tie-jun; Song, Zhi-hui; Jiang, Chuan-xian; Huang, Lin

    2013-09-01

    Segmenting greenbelts quickly and accurately in remote sensing images is an economic and effective method for the statistics of green coverage rate (GCR). Towards the problem of over-reliance on priori knowledge of the traditional level set segmentation model based on max-flow/min-cut Graph Cut principle and weighted Total Variation (GCTV), this paper proposes a level set segmentation method of combining regional texture features and priori knowledge of color and applies it to greenbelt segmentation in urban remote sensing images. For the color of greenbelts is not reliable for segmentation, Gabor wavelet transform is used to extract image texture features. Then we integrate the extracted features into the GCTV model which contains only priori knowledge of color, and use both the prior knowledge and the targets' texture to constrain the evolving of the level set which can solve the problem of over-reliance on priori knowledge. Meanwhile, the convexity of the corresponding energy functional is ensured by using relaxation and threshold method, and primal-dual algorithm with global relabeling is used to accelerate the evolution of the level set. The experiments show that our method can effectively reduce the dependence on priori knowledge of GCTV, and yields more accurate greenbelt segmentation results.

  14. Dissociation of equilibrium points for color-discrimination and color-appearance mechanisms in incomplete chromatic adaptation.

    PubMed

    Sato, Tomoharu; Nagai, Takehiro; Kuriki, Ichiro; Nakauchi, Shigeki

    2016-03-01

    We compared the color-discrimination thresholds and supra-threshold color differences (STCDs) obtained in complete chromatic adaptation (gray) and incomplete chromatic adaptation (red). The color-difference profiles were examined by evaluating the perceptual distances between various color pairs using maximum likelihood difference scaling. In the gray condition, the chromaticities corresponding with the smallest threshold and the largest color difference were almost identical. In contrast, in the red condition, they were dissociated. The peaks of the sensitivity functions derived from the color-discrimination thresholds and STCDs along the L-M axis were systematically different between the adaptation conditions. These results suggest that the color signals involved in color discrimination and STCD tasks are controlled by separate mechanisms with different characteristic properties.

  15. Improved Segmentation of White Matter Tracts with Adaptive Riemannian Metrics

    PubMed Central

    Hao, Xiang; Zygmunt, Kristen; Whitaker, Ross T.; Fletcher, P. Thomas

    2014-01-01

    We present a novel geodesic approach to segmentation of white matter tracts from diffusion tensor imaging (DTI). Compared to deterministic and stochastic tractography, geodesic approaches treat the geometry of the brain white matter as a manifold, often using the inverse tensor field as a Riemannian metric. The white matter pathways are then inferred from the resulting geodesics, which have the desirable property that they tend to follow the main eigenvectors of the tensors, yet still have the flexibility to deviate from these directions when it results in lower costs. While this makes such methods more robust to noise, the choice of Riemannian metric in these methods is ad hoc. A serious drawback of current geodesic methods is that geodesics tend to deviate from the major eigenvectors in high-curvature areas in order to achieve the shortest path. In this paper we propose a method for learning an adaptive Riemannian metric from the DTI data, where the resulting geodesics more closely follow the principal eigenvector of the diffusion tensors even in high-curvature regions. We also develop a way to automatically segment the white matter tracts based on the computed geodesics. We show the robustness of our method on simulated data with different noise levels. We also compare our method with tractography methods and geodesic approaches using other Riemannian metrics and demonstrate that the proposed method results in improved geodesics and segmentations using both synthetic and real DTI data. PMID:24211814

  16. Adaptive segmentation of wavelet transform coefficients for video compression

    NASA Astrophysics Data System (ADS)

    Wasilewski, Piotr

    2000-04-01

    This paper presents video compression algorithm suitable for inexpensive real-time hardware implementation. This algorithm utilizes Discrete Wavelet Transform (DWT) with the new Adaptive Spatial Segmentation Algorithm (ASSA). The algorithm was designed to obtain better or similar decompressed video quality in compare to H.263 recommendation and MPEG standard using lower computational effort, especially at high compression rates. The algorithm was optimized for hardware implementation in low-cost Field Programmable Gate Array (FPGA) devices. The luminance and chrominance components of every frame are encoded with 3-level Wavelet Transform with biorthogonal filters bank. The low frequency subimage is encoded with an ADPCM algorithm. For the high frequency subimages the new Adaptive Spatial Segmentation Algorithm is applied. It divides images into rectangular blocks that may overlap each other. The width and height of the blocks are set independently. There are two kinds of blocks: Low Variance Blocks (LVB) and High Variance Blocks (HVB). The positions of the blocks and the values of the WT coefficients belonging to the HVB are encoded with the modified zero-tree algorithms. LVB are encoded with the mean value. Obtained results show that presented algorithm gives similar or better quality of decompressed images in compare to H.263, even up to 5 dB in PSNR measure.

  17. An efficient fully unsupervised video object segmentation scheme using an adaptive neural-network classifier architecture.

    PubMed

    Doulamis, A; Doulamis, N; Ntalianis, K; Kollias, S

    2003-01-01

    In this paper, an unsupervised video object (VO) segmentation and tracking algorithm is proposed based on an adaptable neural-network architecture. The proposed scheme comprises: 1) a VO tracking module and 2) an initial VO estimation module. Object tracking is handled as a classification problem and implemented through an adaptive network classifier, which provides better results compared to conventional motion-based tracking algorithms. Network adaptation is accomplished through an efficient and cost effective weight updating algorithm, providing a minimum degradation of the previous network knowledge and taking into account the current content conditions. A retraining set is constructed and used for this purpose based on initial VO estimation results. Two different scenarios are investigated. The first concerns extraction of human entities in video conferencing applications, while the second exploits depth information to identify generic VOs in stereoscopic video sequences. Human face/ body detection based on Gaussian distributions is accomplished in the first scenario, while segmentation fusion is obtained using color and depth information in the second scenario. A decision mechanism is also incorporated to detect time instances for weight updating. Experimental results and comparisons indicate the good performance of the proposed scheme even in sequences with complicated content (object bending, occlusion).

  18. Low color distortion adaptive dimming scheme for power efficient LCDs

    NASA Astrophysics Data System (ADS)

    Nam, Hyoungsik; Song, Eun-Ji

    2013-06-01

    This paper demonstrates the color compensation algorithm to reduce the color distortion caused by mismatches between the reference gamma value of a dimming algorithm and the display gamma values of an LCD panel in a low power adaptive dimming scheme. In 2010, we presented the YrYgYb algorithm, which used the display gamma values extracted from the luminance data of red, green, and blue sub-pixels, Yr, Yg, and Yb, with the simulation results. It was based on the ideal panel model where the color coordinates were maintained at the fixed values over the gray levels. Whereas, this work introduces an XrYgZb color compensation algorithm which obtains the display gamma values of red, green, and blue from the different tri-stimulus data of Xr, Yg, and Zb, to obtain further reduction on the color distortion. Both simulation and measurement results ensure that a XrYgZb algorithm outperforms a previous YrYgYb algorithm. In simulation which has been conducted at the practical model derived from the measured data, the XrYgZb scheme achieves lower maximum and average color difference values of 3.7743 and 0.6230 over 24 test picture images, compared to 4.864 and 0.7156 in the YrYgYb one. In measurement of a 19-inch LCD panel, the XrYgZb method also accomplishes smaller color difference values of 1.444072 and 5.588195 over 49 combinations of red, green, and blue data, compared to 1.50578 and 6.00403 of the YrYgYb at the backlight dimming ratios of 0.85 and 0.4.

  19. A comparative study of some methods for color medical images segmentation

    NASA Astrophysics Data System (ADS)

    Stanescu, Liana; Dan Burdescu, Dumitru; Brezovan, Marius

    2011-12-01

    The aim of this article is to study the problem of color medical images segmentation. The images represent pathologies of the digestive tract such as ulcer, polyps, esophagites, colitis, or ulcerous tumors, gathered with the help of an endoscope. This article presents the results of an objective and quantitative study of three segmentation algorithms. Two of them are well known: the color set back-projection algorithm and the local variation algorithm. The third method chosen is our original visual feature-based algorithm. It uses a graph constructed on a hexagonal structure containing half of the image pixels in order to determine a forest of maximum spanning trees for connected component representing visual objects. This third method is a superior one taking into consideration the obtained results and temporal complexity. These three methods were successfully used in generic color images segmentation. In order to evaluate these segmentation algorithms, we used error measuring methods that quantify the consistency between them. These measures allow a principled comparison between segmentation results on different images, with differing numbers of regions generated by different algorithms with different parameters.

  20. Region-based multi-step optic disk and cup segmentation from color fundus image

    NASA Astrophysics Data System (ADS)

    Xiao, Di; Lock, Jane; Manresa, Javier Moreno; Vignarajan, Janardhan; Tay-Kearney, Mei-Ling; Kanagasingam, Yogesan

    2013-02-01

    Retinal optic cup-disk-ratio (CDR) is a one of important indicators of glaucomatous neuropathy. In this paper, we propose a novel multi-step 4-quadrant thresholding method for optic disk segmentation and a multi-step temporal-nasal segmenting method for optic cup segmentation based on blood vessel inpainted HSL lightness images and green images. The performance of the proposed methods was evaluated on a group of color fundus images and compared with the manual outlining results from two experts. Dice scores of detected disk and cup regions between the auto and manual results were computed and compared. Vertical CDRs were also compared among the three results. The preliminary experiment has demonstrated the robustness of the method for automatic optic disk and cup segmentation and its potential value for clinical application.

  1. Obstacle recognition using region-based color segmentation techniques for mobile robot navigation

    NASA Astrophysics Data System (ADS)

    McKeon, Robert T.; Krishnan, Mohan; Paulik, Mark

    2006-10-01

    This work has been performed in conjunction with the ECE Department's autonomous vehicle entry in the 2006 Intelligent Ground Vehicle Competition (www.igvc.org). The course to be traversed in the competition consists of a lane demarcated by paint lines on grass along with other challenging artifacts such as a sandpit, a ramp, potholes, colored tarps, and obstacles set up using orange and white construction barrels. In this paper an enhanced obstacle detection and mapping algorithm based on region-based color segmentation techniques is described. The main purpose of this algorithm is to detect obstacles which are not properly identified by the LADAR (Laser Detection and Ranging) system optimally mounted close to the ground, due to "shadowing" occasionally resulting in bad navigation decisions. On the other hand, the camera that is primarily used to detect the lane lines is mounted at 6 feet. In this work we concentrate on the identification of orange/red construction barrels. This paper proposes a generalized color segmentation technique which is potentially more versatile and faster than traditional full or partial color segmentation approaches. The developed algorithm identifies the shadowed items within the camera's field of vision and uses this to complement the LADAR information, thus facilitating an enhanced navigation strategy. The identification of barrels also aids in deleting bright objects from images which contain lane lines, which improves lane line identification.

  2. Ultrasound Color Doppler Image Segmentation and Feature Extraction in MCP and Wrist Region in Evaluation of Rheumatoid Arthritis.

    PubMed

    Snekhalatha, U; Muthubhairavi, V; Anburajan, M; Gupta, Neelkanth

    2016-09-01

    The present study focuses on automatically to segment the blood flow pattern of color Doppler ultrasound in hand region of rheumatoid arthritis patients and to correlate the extracted the statistical features and color Doppler parameters with standard parameters. Thirty patients with rheumatoid arthritis (RA) and their total of 300 joints of both the hands, i.e., 240 MCP and 60 wrists were examined in this study. Ultrasound color Doppler of both the hands of all the patients was obtained. Automated segmentation of color Doppler image was performed using color enhancement scaling based segmentation algorithm. The region of interest is fixed in the MCP joints and wrist of the hand. Features were extracted from the defined ROI of the segmented output image. The color fraction was measured using Mimics software. The standard parameters such as HAQ score, DAS 28 score, and ESR was obtained for all the patients. The color fraction tends to be increased in wrist and MCP3 joints which indicate the increased blood flow pattern and color Doppler activity as part of inflammation in hand joints of RA. The ESR correlated significantly with the feature extracted parameters such as mean, standard deviation and entropy in MCP3, MCP4 joint and the wrist region. The developed automated color image segmentation algorithm provides a quantitative analysis for diagnosis and assessment of RA. The correlation study between the color Doppler parameters with the standard parameters provides moral significance in quantitative analysis of RA in MCP3 joint and the wrist region.

  3. Studyed On The Externaldefects Segmentation Based On The Color Character Of Potatoes

    NASA Astrophysics Data System (ADS)

    Hao, Min; Ma, Shuoshi

    Potato quality detection in China remains at the stage of dependent on human sense organ to identify and judge. According to the characteristics and requests of potatoes’ detection, The original image was disposed fast and smoothly by the median filtering, and based on the threshold segmentation by setting up the values of B(blue), the background was effectively wiped off. By analyzing the circumscription of color characters between the normal and external defect potatoes, the external defect segmentation was realized. This way is simple and feasible.

  4. Studyed On The Externaldefects Segmentation Based On The Color Character Of Potatoes

    NASA Astrophysics Data System (ADS)

    Hao, Min; Ma, Shuoshi

    Potato quality detection in China remains at the stage of dependent on human sense organ to identify and judge. According to the characteristics and requests of potatoes' detection, The original image was disposed fast and smoothly by the median filtering, and based on the threshold segmentation by setting up the values of B(blue), the background was effectively wiped off. By analyzing the circumscription of color characters between the normal and external defect potatoes, the external defect segmentation was realized. This way is simple and feasible.

  5. Color tongue image segmentation using fuzzy Kohonen networks and genetic algorithm

    NASA Astrophysics Data System (ADS)

    Wang, Aimin; Shen, Lansun; Zhao, Zhongxu

    2000-04-01

    A Tongue Imaging and Analysis System is being developed to acquire digital color tongue images, and to automatically classify and quantify the tongue characteristics for traditional Chinese medical examinations. An important processing step is to segment the tongue pixels into two categories, the tongue body (no coating) and the coating. In this paper, we present a two-stage clustering algorithm that combines Fuzzy Kohonen Clustering Networks and Genetic Algorithm for the segmentation, of which the major concern is to increase the interclass distance and at the same time decrease the intraclass distance. Experimental results confirm the effectiveness of this algorithm.

  6. An adaptive level set segmentation on a triangulated mesh.

    PubMed

    Xu, Meihe; Thompson, Paul M; Toga, Arthur W

    2004-02-01

    Level set methods offer highly robust and accurate methods for detecting interfaces of complex structures. Efficient techniques are required to transform an interface to a globally defined level set function. In this paper, a novel level set method based on an adaptive triangular mesh is proposed for segmentation of medical images. Special attention is paid to an adaptive mesh refinement and redistancing technique for level set propagation, in order to achieve higher resolution at the interface with minimum expense. First, a narrow band around the interface is built in an upwind fashion. An active square technique is used to determine the shortest distance correspondence (SDC) for each grid vertex. Simultaneously, we also give an efficient approach for signing the distance field. Then, an adaptive improvement algorithm is proposed, which essentially combines two basic techniques: a long-edge-based vertex insertion strategy, and a local improvement. These guarantee that the refined triangulation is related to features along the front and has elements with appropriate size and shape, which fit the front well. We propose a short-edge elimination scheme to coarsen the refined triangular mesh, in order to reduce the extra storage. Finally, we reformulate the general evolution equation by updating 1) the velocities and 2) the gradient of level sets on the triangulated mesh. We give an approach for tracing contours from the level set on the triangulated mesh. Given a two-dimensional image with N grids along a side, the proposed algorithms run in O(kN) time at each iteration. Quantitative analysis shows that our algorithm is of first order accuracy; and when the interface-fitted property is involved in the mesh refinement, both the convergence speed and numerical accuracy are greatly improved. We also analyze the effect of redistancing frequency upon convergence speed and accuracy. Numerical examples include the extraction of inner and outer surfaces of the cerebral cortex

  7. Optimized adaptation algorithm for HEVC/H.265 dynamic adaptive streaming over HTTP using variable segment duration

    NASA Astrophysics Data System (ADS)

    Irondi, Iheanyi; Wang, Qi; Grecos, Christos

    2016-04-01

    Adaptive video streaming using HTTP has become popular in recent years for commercial video delivery. The recent MPEG-DASH standard allows interoperability and adaptability between servers and clients from different vendors. The delivery of the MPD (Media Presentation Description) files in DASH and the DASH client behaviours are beyond the scope of the DASH standard. However, the different adaptation algorithms employed by the clients do affect the overall performance of the system and users' QoE (Quality of Experience), hence the need for research in this field. Moreover, standard DASH delivery is based on fixed segments of the video. However, there is no standard segment duration for DASH where various fixed segment durations have been employed by different commercial solutions and researchers with their own individual merits. Most recently, the use of variable segment duration in DASH has emerged but only a few preliminary studies without practical implementation exist. In addition, such a technique requires a DASH client to be aware of segment duration variations, and this requirement and the corresponding implications on the DASH system design have not been investigated. This paper proposes a segment-duration-aware bandwidth estimation and next-segment selection adaptation strategy for DASH. Firstly, an MPD file extension scheme to support variable segment duration is proposed and implemented in a realistic hardware testbed. The scheme is tested on a DASH client, and the tests and analysis have led to an insight on the time to download next segment and the buffer behaviour when fetching and switching between segments of different playback durations. Issues like sustained buffering when switching between segments of different durations and slow response to changing network conditions are highlighted and investigated. An enhanced adaptation algorithm is then proposed to accurately estimate the bandwidth and precisely determine the time to download the next

  8. Nearest patch matching for color image segmentation supporting neural network classification in pulmonary tuberculosis identification

    NASA Astrophysics Data System (ADS)

    Rulaningtyas, Riries; Suksmono, Andriyan B.; Mengko, Tati L. R.; Saptawati, Putri

    2016-03-01

    Pulmonary tuberculosis is a deadly infectious disease which occurs in many countries in Asia and Africa. In Indonesia, many people with tuberculosis disease are examined in the community health center. Examination of pulmonary tuberculosis is done through sputum smear with Ziehl - Neelsen staining using conventional light microscope. The results of Ziehl - Neelsen staining will give effect to the appearance of tuberculosis (TB) bacteria in red color and sputum background in blue color. The first examination is to detect the presence of TB bacteria from its color, then from the morphology of the TB bacteria itself. The results of Ziehl - Neelsen staining in sputum smear give the complex color images, so that the clinicians have difficulty when doing slide examination manually because it is time consuming and needs highly training to detect the presence of TB bacteria accurately. The clinicians have heavy workload to examine many sputum smear slides from the patients. To assist the clinicians when reading the sputum smear slide, this research built computer aided diagnose with color image segmentation, feature extraction, and classification method. This research used K-means clustering with patch technique to segment digital sputum smear images which separated the TB bacteria images from the background images. This segmentation method gave the good accuracy 97.68%. Then, feature extraction based on geometrical shape of TB bacteria was applied to this research. The last step, this research used neural network with back propagation method to classify TB bacteria and non TB bacteria images in sputum slides. The classification result of neural network back propagation are learning time (42.69±0.02) second, the number of epoch 5000, error rate of learning 15%, learning accuracy (98.58±0.01)%, and test accuracy (96.54±0.02)%.

  9. Color Image Segmentation Based on Statistics of Location and Feature Similarity

    NASA Astrophysics Data System (ADS)

    Mori, Fumihiko; Yamada, Hiromitsu; Mizuno, Makoto; Sugano, Naotoshi

    The process of “image segmentation and extracting remarkable regions” is an important research subject for the image understanding. However, an algorithm based on the global features is hardly found. The requisite of such an image segmentation algorism is to reduce as much as possible the over segmentation and over unification. We developed an algorithm using the multidimensional convex hull based on the density as the global feature. In the concrete, we propose a new algorithm in which regions are expanded according to the statistics of the region such as the mean value, standard deviation, maximum value and minimum value of pixel location, brightness and color elements and the statistics are updated. We also introduced a new concept of conspicuity degree and applied it to the various 21 images to examine the effectiveness. The remarkable object regions, which were extracted by the presented system, highly coincided with those which were pointed by the sixty four subjects who attended the psychological experiment.

  10. Factors of Incomplete Adaptation for Color Reproduction Considering Subjective White Point Shift for Varying Illuminant

    NASA Astrophysics Data System (ADS)

    Lee, Sung-Hak; Lee, Myoung-Hwa; Sohng, Kyu-Ik

    In this paper, we investigated the effect of chromaticity and luminance of surround to decide subject neutral white, and conducted a mathematical model of adapting degree for environment. Factors for adapting degree consist of two parts, adapting degree of ambient chromaticity and color saturation. These can be applied to color appearance models (CAM), actually improve the performance of color matching of CAM, hence would produce the method of image reproduction to general display systems.

  11. CMEIAS color segmentation: an improved computing technology to process color images for quantitative microbial ecology studies at single-cell resolution.

    PubMed

    Gross, Colin A; Reddy, Chandan K; Dazzo, Frank B

    2010-02-01

    Quantitative microscopy and digital image analysis are underutilized in microbial ecology largely because of the laborious task to segment foreground object pixels from background, especially in complex color micrographs of environmental samples. In this paper, we describe an improved computing technology developed to alleviate this limitation. The system's uniqueness is its ability to edit digital images accurately when presented with the difficult yet commonplace challenge of removing background pixels whose three-dimensional color space overlaps the range that defines foreground objects. Image segmentation is accomplished by utilizing algorithms that address color and spatial relationships of user-selected foreground object pixels. Performance of the color segmentation algorithm evaluated on 26 complex micrographs at single pixel resolution had an overall pixel classification accuracy of 99+%. Several applications illustrate how this improved computing technology can successfully resolve numerous challenges of complex color segmentation in order to produce images from which quantitative information can be accurately extracted, thereby gain new perspectives on the in situ ecology of microorganisms. Examples include improvements in the quantitative analysis of (1) microbial abundance and phylotype diversity of single cells classified by their discriminating color within heterogeneous communities, (2) cell viability, (3) spatial relationships and intensity of bacterial gene expression involved in cellular communication between individual cells within rhizoplane biofilms, and (4) biofilm ecophysiology based on ribotype-differentiated radioactive substrate utilization. The stand-alone executable file plus user manual and tutorial images for this color segmentation computing application are freely available at http://cme.msu.edu/cmeias/ . This improved computing technology opens new opportunities of imaging applications where discriminating colors really matter most

  12. Length-adaptive graph search for automatic segmentation of pathological features in optical coherence tomography images

    NASA Astrophysics Data System (ADS)

    Keller, Brenton; Cunefare, David; Grewal, Dilraj S.; Mahmoud, Tamer H.; Izatt, Joseph A.; Farsiu, Sina

    2016-07-01

    We introduce a metric in graph search and demonstrate its application for segmenting retinal optical coherence tomography (OCT) images of macular pathology. Our proposed "adjusted mean arc length" (AMAL) metric is an adaptation of the lowest mean arc length search technique for automated OCT segmentation. We compare this method to Dijkstra's shortest path algorithm, which we utilized previously in our popular graph theory and dynamic programming segmentation technique. As an illustrative example, we show that AMAL-based length-adaptive segmentation outperforms the shortest path in delineating the retina/vitreous boundary of patients with full-thickness macular holes when compared with expert manual grading.

  13. Segmentation of Tracking Sequences Using Dynamically Updated Adaptive Learning

    PubMed Central

    Michailovich, Oleg; Tannenbaum, Allen

    2009-01-01

    The problem of segmentation of tracking sequences is of central importance in a multitude of applications. In the current paper, a different approach to the problem is discussed. Specifically, the proposed segmentation algorithm is implemented in conjunction with estimation of the dynamic parameters of moving objects represented by the tracking sequence. While the information on objects’ motion allows one to transfer some valuable segmentation priors along the tracking sequence, the segmentation allows substantially reducing the complexity of motion estimation, thereby facilitating the computation. Thus, in the proposed methodology, the processes of segmentation and motion estimation work simultaneously, in a sort of “collaborative” manner. The Bayesian estimation framework is used here to perform the segmentation, while Kalman filtering is used to estimate the motion and to convey useful segmentation information along the image sequence. The proposed method is demonstrated on a number of both computed-simulated and real-life examples, and the obtained results indicate its advantages over some alternative approaches. PMID:19004712

  14. Automated multimodality concurrent classification for segmenting vessels in 3D spectral OCT and color fundus images

    NASA Astrophysics Data System (ADS)

    Hu, Zhihong; Abràmoff, Michael D.; Niemeijer, Meindert; Garvin, Mona K.

    2011-03-01

    Segmenting vessels in spectral-domain optical coherence tomography (SD-OCT) volumes is particularly challenging in the region near and inside the neural canal opening (NCO). Furthermore, accurately segmenting them in color fundus photographs also presents a challenge near the projected NCO. However, both modalities also provide complementary information to help indicate vessels, such as a better NCO contrast from the NCO-aimed OCT projection image and a better vessel contrast inside the NCO from fundus photographs. We thus present a novel multimodal automated classification approach for simultaneously segmenting vessels in SD-OCT volumes and fundus photographs, with a particular focus on better segmenting vessels near and inside the NCO by using a combination of their complementary features. In particular, in each SD-OCT volume, the algorithm pre-segments the NCO using a graph-theoretic approach and then applies oriented Gabor wavelets with oriented NCO-based templates to generate OCT image features. After fundus-to-OCT registration, the fundus image features are computed using Gaussian filter banks and combined with OCT image features. A k-NN classifier is trained on 5 and tested on 10 randomly chosen independent image pairs of SD-OCT volumes and fundus images from 15 subjects with glaucoma. Using ROC analysis, we demonstrate an improvement over two closest previous works performed in single modal SD-OCT volumes with an area under the curve (AUC) of 0.87 (0.81 for our and 0.72 for Niemeijer's single modal approach) in the region around the NCO and 0.90 outside the NCO (0.84 for our and 0.81 for Niemeijer's single modal approach).

  15. Segmenting texts from outdoor images taken by mobile phones using color features

    NASA Astrophysics Data System (ADS)

    Liu, Zongyi; Zhou, Hanning

    2011-01-01

    Recognizing texts from images taken by mobile phones with low resolution has wide applications. It has been shown that a good image binarization can substantially improve the performances of OCR engines. In this paper, we present a framework to segment texts from outdoor images taken by mobile phones using color features. The framework consists of three steps: (i) the initial process including image enhancement, binarization and noise filtering, where we binarize the input images in each RGB channel, and apply component level noise filtering; (ii) grouping components into blocks using color features, where we compute the component similarities by dynamically adjusting the weights of RGB channels, and merge groups hierachically, and (iii) blocks selection, where we use the run-length features and choose the Support Vector Machine (SVM) as the classifier. We tested the algorithm using 13 outdoor images taken by an old-style LG-64693 mobile phone with 640x480 resolution. We compared the segmentation results with Tsar's algorithm, a state-of-the-art camera text detection algorithm, and show that our algorithm is more robust, particularly in terms of the false alarm rates. In addition, we also evaluated the impacts of our algorithm on the Abbyy's FineReader, one of the most popular commercial OCR engines in the market.

  16. Investigation of the effects of color on judgments of sweetness using a taste adaptation method.

    PubMed

    Hidaka, Souta; Shimoda, Kazumasa

    2014-01-01

    It has been reported that color can affect the judgment of taste. For example, a dark red color enhances the subjective intensity of sweetness. However, the underlying mechanisms of the effect of color on taste have not been fully investigated; in particular, it remains unclear whether the effect is based on cognitive/decisional or perceptual processes. Here, we investigated the effect of color on sweetness judgments using a taste adaptation method. A sweet solution whose color was subjectively congruent with sweetness was judged as sweeter than an uncolored sweet solution both before and after adaptation to an uncolored sweet solution. In contrast, subjective judgment of sweetness for uncolored sweet solutions did not differ between the conditions following adaptation to a colored sweet solution and following adaptation to an uncolored one. Color affected sweetness judgment when the target solution was colored, but the colored sweet solution did not modulate the magnitude of taste adaptation. Therefore, it is concluded that the effect of color on the judgment of taste would occur mainly in cognitive/decisional domains.

  17. Shape-model-based adaptation of 3D deformable meshes for segmentation of medical images

    NASA Astrophysics Data System (ADS)

    Pekar, Vladimir; Kaus, Michael R.; Lorenz, Cristian; Lobregt, Steven; Truyen, Roel; Weese, Juergen

    2001-07-01

    Segmentation methods based on adaptation of deformable models have found numerous applications in medical image analysis. Many efforts have been made in the recent years to improve their robustness and reliability. In particular, increasingly more methods use a priori information about the shape of the anatomical structure to be segmented. This reduces the risk of the model being attracted to false features in the image and, as a consequence, makes the need of close initialization, which remains the principal limitation of elastically deformable models, less crucial for the segmentation quality. In this paper, we present a novel segmentation approach which uses a 3D anatomical statistical shape model to initialize the adaptation process of a deformable model represented by a triangular mesh. As the first step, the anatomical shape model is parametrically fitted to the structure of interest in the image. The result of this global adaptation is used to initialize the local mesh refinement based on an energy minimization. We applied our approach to segment spine vertebrae in CT datasets. The segmentation quality was quantitatively assessed for 6 vertebrae, from 2 datasets, by computing the mean and maximum distance between the adapted mesh and a manually segmented reference shape. The results of the study show that the presented method is a promising approach for segmentation of complex anatomical structures in medical images.

  18. Adaptive Ambient Illumination Based on Color Harmony Model

    NASA Astrophysics Data System (ADS)

    Kikuchi, Ayano; Hirai, Keita; Nakaguchi, Toshiya; Tsumura, Norimichi; Miyake, Yoichi

    We investigated the relationship between ambient illumination and psychological effect by applying a modified color harmony model. We verified the proposed model by analyzing correlation between psychological value and modified color harmony score. Experimental results showed the possibility to obtain the best color for illumination using this model.

  19. Orientation and spatial frequency selectivity of adaptation to color and luminance gratings.

    PubMed

    Bradley, A; Switkes, E; De Valois, K

    1988-01-01

    Prolonged viewing of sinusoidal luminance gratings produces elevated contrast detection thresholds for test gratings that are similar in spatial frequency and orientation to the adaptation stimulus. We have used this technique to investigate orientation and spatial frequency selectivity in the processing of color contrast information. Adaptation to isoluminant red-green gratings produces elevated color contrast thresholds that are selective for grating orientation and spatial frequency. Only small elevations in color contrast thresholds occur after adaptation to luminance gratings, and vice versa. Although the color adaptation effects appear slightly less selective than those for luminance, our results suggest similar spatial processing of color and luminance contrast patterns by early stages of the human visual system.

  20. Skin Color Segmentation Using Coarse-to-Fine Region on Normalized RGB Chromaticity Diagram for Face Detection

    NASA Astrophysics Data System (ADS)

    Soetedjo, Aryuanto; Yamada, Koichi

    This paper describes a new color segmentation based on a normalized RGB chromaticity diagram for face detection. Face skin is extracted from color images using a coarse skin region with fixed boundaries followed by a fine skin region with variable boundaries. Two newly developed histograms that have prominent peaks of skin color and non-skin colors are employed to adjust the boundaries of the skin region. The proposed approach does not need a skin color model, which depends on a specific camera parameter and is usually limited to a particular environment condition, and no sample images are required. The experimental results using color face images of various races under varying lighting conditions and complex backgrounds, obtained from four different resources on the Internet, show a high detection rate of 87%. The results of the detection rate and computation time are comparable to the well known real-time face detection method proposed by Viola-Jones [11], [12].

  1. 3D segmentation of masses in DCE-MRI images using FCM and adaptive MRF

    NASA Astrophysics Data System (ADS)

    Zhang, Chengjie; Li, Lihua

    2014-03-01

    Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is a sensitive imaging modality for the detection of breast cancer. Automated segmentation of breast lesions in DCE-MRI images is challenging due to inherent signal-to-noise ratios and high inter-patient variability. A novel 3D segmentation method based on FCM and MRF is proposed in this study. In this method, a MRI image is segmented by spatial FCM, firstly. And then MRF segmentation is conducted to refine the result. We combined with the 3D information of lesion in the MRF segmentation process by using segmentation result of contiguous slices to constraint the slice segmentation. At the same time, a membership matrix of FCM segmentation result is used for adaptive adjustment of Markov parameters in MRF segmentation process. The proposed method was applied for lesion segmentation on 145 breast DCE-MRI examinations (86 malignant and 59 benign cases). An evaluation of segmentation was taken using the traditional overlap rate method between the segmented region and hand-drawing ground truth. The average overlap rates for benign and malignant lesions are 0.764 and 0.755 respectively. Then we extracted five features based on the segmentation region, and used an artificial neural network (ANN) to classify between malignant and benign cases. The ANN had a classification performance measured by the area under the ROC curve of AUC=0.73. The positive and negative predictive values were 0.86 and 0.58, respectively. The results demonstrate the proposed method not only achieves a better segmentation performance in accuracy also has a reasonable classification performance.

  2. Medical Image Segmentation using the HSI color space and Fuzzy Mathematical Morphology

    NASA Astrophysics Data System (ADS)

    Gasparri, J. P.; Bouchet, A.; Abras, G.; Ballarin, V.; Pastore, J. I.

    2011-12-01

    Diabetic retinopathy is the most common cause of blindness among the active population in developed countries. An early ophthalmologic examination followed by proper treatment can prevent blindness. The purpose of this work is develop an automated method for segmentation the vasculature in retinal images in order to assist the expert in the evolution of a specific treatment or in the diagnosis of a potential pathology. Since the HSI space has the ability to separate the intensity of the intrinsic color information, its use is recommended for the digital processing images when they are affected by lighting changes, characteristic of the images under study. By the application of color filters, is achieved artificially change the tone of blood vessels, to better distinguish them from the bottom. This technique, combined with the application of fuzzy mathematical morphology tools as the Top-Hat transformation, creates images of the retina, where vascular branches are markedly enhanced over the original. These images provide the visualization of blood vessels by the specialist.

  3. A weighted mean shift, normalized cuts initialized color gradient based geodesic active contour model: applications to histopathology image segmentation

    NASA Astrophysics Data System (ADS)

    Xu, Jun; Janowczyk, Andrew; Chandran, Sharat; Madabhushi, Anant

    2010-03-01

    While geodesic active contours (GAC) have become very popular tools for image segmentation, they are sensitive to model initialization. In order to get an accurate segmentation, the model typically needs to be initialized very close to the true object boundary. Apart from accuracy, automated initialization of the objects of interest is an important pre-requisite to being able to run the active contour model on very large images (such as those found in digitized histopathology). A second limitation of GAC model is that the edge detector function is based on gray scale gradients; color images typically being converted to gray scale prior to computing the gradient. For color images, however, the gray scale gradient results in broken edges and weak boundaries, since the other channels are not exploited for the gradient determination. In this paper we present a new geodesic active contour model that is driven by an accurate and rapid object initialization scheme-weighted mean shift normalized cuts (WNCut). WNCut draws its strength from the integration of two powerful segmentation strategies-mean shift clustering and normalized cuts. WNCut involves first defining a color swatch (typically a few pixels) from the object of interest. A multi-scale mean shift coupled normalized cuts algorithm then rapidly yields an initial accurate detection of all objects in the scene corresponding to the colors in the swatch. This detection result provides the initial boundary for GAC model. The edge-detector function of the GAC model employs a local structure tensor based color gradient, obtained by calculating the local min/max variations contributed from each color channel (e.g. R,G,B or H,S,V). Our color gradient based edge-detector function results in more prominent boundaries compared to classical gray scale gradient based function. We evaluate segmentation results of our new WNCut initialized color gradient based GAC (WNCut-CGAC) model against a popular region-based model (Chan

  4. Adaptive local multi-atlas segmentation: application to the heart and the caudate nucleus.

    PubMed

    van Rikxoort, Eva M; Isgum, Ivana; Arzhaeva, Yulia; Staring, Marius; Klein, Stefan; Viergever, Max A; Pluim, Josien P W; van Ginneken, Bram

    2010-02-01

    Atlas-based segmentation is a powerful generic technique for automatic delineation of structures in volumetric images. Several studies have shown that multi-atlas segmentation methods outperform schemes that use only a single atlas, but running multiple registrations on volumetric data is time-consuming. Moreover, for many scans or regions within scans, a large number of atlases may not be required to achieve good segmentation performance and may even deteriorate the results. It would therefore be worthwhile to include the decision which and how many atlases to use for a particular target scan in the segmentation process. To this end, we propose two generally applicable multi-atlas segmentation methods, adaptive multi-atlas segmentation (AMAS) and adaptive local multi-atlas segmentation (ALMAS). AMAS automatically selects the most appropriate atlases for a target image and automatically stops registering atlases when no further improvement is expected. ALMAS takes this concept one step further by locally deciding how many and which atlases are needed to segment a target image. The methods employ a computationally cheap atlas selection strategy, an automatic stopping criterion, and a technique to locally inspect registration results and determine how much improvement can be expected from further registrations. AMAS and ALMAS were applied to segmentation of the heart in computed tomography scans of the chest and compared to a conventional multi-atlas method (MAS). The results show that ALMAS achieves the same performance as MAS at a much lower computational cost. When the available segmentation time is fixed, both AMAS and ALMAS perform significantly better than MAS. In addition, AMAS was applied to an online segmentation challenge for delineation of the caudate nucleus in brain MRI scans where it achieved the best score of all results submitted to date.

  5. Fixation light hue bias revisited: implications for using adaptive optics to study color vision.

    PubMed

    Hofer, H J; Blaschke, J; Patolia, J; Koenig, D E

    2012-03-01

    Current vision science adaptive optics systems use near infrared wavefront sensor 'beacons' that appear as red spots in the visual field. Colored fixation targets are known to influence the perceived color of macroscopic visual stimuli (Jameson, D., & Hurvich, L. M. (1967). Fixation-light bias: An unwanted by-product of fixation control. Vision Research, 7, 805-809.), suggesting that the wavefront sensor beacon may also influence perceived color for stimuli displayed with adaptive optics. Despite its importance for proper interpretation of adaptive optics experiments on the fine scale interaction of the retinal mosaic and spatial and color vision, this potential bias has not yet been quantified or addressed. Here we measure the impact of the wavefront sensor beacon on color appearance for dim, monochromatic point sources in five subjects. The presence of the beacon altered color reports both when used as a fixation target as well as when displaced in the visual field with a chromatically neutral fixation target. This influence must be taken into account when interpreting previous experiments and new methods of adaptive correction should be used in future experiments using adaptive optics to study color.

  6. Color filter array demosaicing: an adaptive progressive interpolation based on the edge type

    NASA Astrophysics Data System (ADS)

    Dong, Qiqi; Liu, Zhaohui

    2015-10-01

    Color filter array (CFA) is one of the key points for single-sensor digital cameras to produce color images. Bayer CFA is the most commonly used pattern. In this array structure, the sampling frequency of green is two times of red or blue, which is consistent with the sensitivity of human eyes to colors. However, each sensor pixel only samples one of three primary color values. To render a full-color image, an interpolation process, commonly referred to CFA demosaicing, is required to estimate the other two missing color values at each pixel. In this paper, we explore an adaptive progressive interpolation based on the edge type algorithm. The proposed demosaicing method consists of two successive steps: an interpolation step that estimates missing color values according to various edges and a post-processing step by iterative interpolation.

  7. Functional photoreceptor loss revealed with adaptive optics: an alternate cause of color blindness.

    PubMed

    Carroll, Joseph; Neitz, Maureen; Hofer, Heidi; Neitz, Jay; Williams, David R

    2004-06-01

    There is enormous variation in the X-linked L/M (long/middle wavelength sensitive) gene array underlying "normal" color vision in humans. This variability has been shown to underlie individual variation in color matching behavior. Recently, red-green color blindness has also been shown to be associated with distinctly different genotypes. This has opened the possibility that there may be important phenotypic differences within classically defined groups of color blind individuals. Here, adaptive optics retinal imaging has revealed a mechanism for producing dichromatic color vision in which the expression of a mutant cone photopigment gene leads to the loss of the entire corresponding class of cone photoreceptor cells. Previously, the theory that common forms of inherited color blindness could be caused by the loss of photoreceptor cells had been discounted. We confirm that remarkably, this loss of one-third of the cones does not impair any aspect of vision other than color.

  8. A probabilistic approach to segmentation and classification of neoplasia in uterine cervix images using color and geometric features

    NASA Astrophysics Data System (ADS)

    Srinivasan, Yeshwanth; Hernes, Dana; Tulpule, Bhakti; Yang, Shuyu; Guo, Jiangling; Mitra, Sunanda; Yagneswaran, Sriraja; Nutter, Brian; Jeronimo, Jose; Phillips, Benny; Long, Rodney; Ferris, Daron

    2005-04-01

    Automated segmentation and classification of diagnostic markers in medical imagery are challenging tasks. Numerous algorithms for segmentation and classification based on statistical approaches of varying complexity are found in the literature. However, the design of an efficient and automated algorithm for precise classification of desired diagnostic markers is extremely image-specific. The National Library of Medicine (NLM), in collaboration with the National Cancer Institute (NCI), is creating an archive of 60,000 digitized color images of the uterine cervix. NLM is developing tools for the analysis and dissemination of these images over the Web for the study of visual features correlated with precancerous neoplasia and cancer. To enable indexing of images of the cervix, it is essential to develop algorithms for the segmentation of regions of interest, such as acetowhitened regions, and automatic identification and classification of regions exhibiting mosaicism and punctation. Success of such algorithms depends, primarily, on the selection of relevant features representing the region of interest. We present color and geometric features based statistical classification and segmentation algorithms yielding excellent identification of the regions of interest. The distinct classification of the mosaic regions from the non-mosaic ones has been obtained by clustering multiple geometric and color features of the segmented sections using various morphological and statistical approaches. Such automated classification methodologies will facilitate content-based image retrieval from the digital archive of uterine cervix and have the potential of developing an image based screening tool for cervical cancer.

  9. Effect of the Keck telescope`s segmented primary on the performance on the Keck adaptive optics system

    SciTech Connect

    Gavel, D.

    1997-06-01

    The 349 degree of freedom Keck adaptive optics system will be mapped on to the 36 segment Keck primary mirror. Each telescope segment is independently controlled in piston and tilt by an active control system and each segment also has its own set of aberrations. This presents a unique set of problems for the Keck adaptive optics system, not encountered with continuous primaries. To a certain extent the low order segment aberrations, beginning with focus, can be corrected statically by the adaptive optic system. However, the discontinuous surface at the segment edges present special problems in sensing and correcting wavefront with laser guide stars or natural guide stars.

  10. Adaptive Breast Radiation Therapy Using Modeling of Tissue Mechanics: A Breast Tissue Segmentation Study

    SciTech Connect

    Juneja, Prabhjot; Harris, Emma J.; Kirby, Anna M.; Evans, Philip M.

    2012-11-01

    Purpose: To validate and compare the accuracy of breast tissue segmentation methods applied to computed tomography (CT) scans used for radiation therapy planning and to study the effect of tissue distribution on the segmentation accuracy for the purpose of developing models for use in adaptive breast radiation therapy. Methods and Materials: Twenty-four patients receiving postlumpectomy radiation therapy for breast cancer underwent CT imaging in prone and supine positions. The whole-breast clinical target volume was outlined. Clinical target volumes were segmented into fibroglandular and fatty tissue using the following algorithms: physical density thresholding; interactive thresholding; fuzzy c-means with 3 classes (FCM3) and 4 classes (FCM4); and k-means. The segmentation algorithms were evaluated in 2 stages: first, an approach based on the assumption that the breast composition should be the same in both prone and supine position; and second, comparison of segmentation with tissue outlines from 3 experts using the Dice similarity coefficient (DSC). Breast datasets were grouped into nonsparse and sparse fibroglandular tissue distributions according to expert assessment and used to assess the accuracy of the segmentation methods and the agreement between experts. Results: Prone and supine breast composition analysis showed differences between the methods. Validation against expert outlines found significant differences (P<.001) between FCM3 and FCM4. Fuzzy c-means with 3 classes generated segmentation results (mean DSC = 0.70) closest to the experts' outlines. There was good agreement (mean DSC = 0.85) among experts for breast tissue outlining. Segmentation accuracy and expert agreement was significantly higher (P<.005) in the nonsparse group than in the sparse group. Conclusions: The FCM3 gave the most accurate segmentation of breast tissues on CT data and could therefore be used in adaptive radiation therapy-based on tissue modeling. Breast tissue segmentation

  11. Streak image denoising and segmentation using adaptive Gaussian guided filter.

    PubMed

    Jiang, Zhuocheng; Guo, Baoping

    2014-09-10

    In streak tube imaging lidar (STIL), streak images are obtained using a CCD camera. However, noise in the captured streak images can greatly affect the quality of reconstructed 3D contrast and range images. The greatest challenge for streak image denoising is reducing the noise while preserving details. In this paper, we propose an adaptive Gaussian guided filter (AGGF) for noise removal and detail enhancement of streak images. The proposed algorithm is based on a guided filter (GF) and part of an adaptive bilateral filter (ABF). In the AGGF, the details are enhanced by optimizing the offset parameter. AGGF-denoised streak images are significantly sharper than those denoised by the GF. Moreover, the AGGF is a fast linear time algorithm achieved by recursively implementing a Gaussian filter kernel. Experimentally, AGGF demonstrates its capacity to preserve edges and thin structures and outperforms the existing bilateral filter and domain transform filter in terms of both visual quality and peak signal-to-noise ratio performance.

  12. Streak image denoising and segmentation using adaptive Gaussian guided filter.

    PubMed

    Jiang, Zhuocheng; Guo, Baoping

    2014-09-10

    In streak tube imaging lidar (STIL), streak images are obtained using a CCD camera. However, noise in the captured streak images can greatly affect the quality of reconstructed 3D contrast and range images. The greatest challenge for streak image denoising is reducing the noise while preserving details. In this paper, we propose an adaptive Gaussian guided filter (AGGF) for noise removal and detail enhancement of streak images. The proposed algorithm is based on a guided filter (GF) and part of an adaptive bilateral filter (ABF). In the AGGF, the details are enhanced by optimizing the offset parameter. AGGF-denoised streak images are significantly sharper than those denoised by the GF. Moreover, the AGGF is a fast linear time algorithm achieved by recursively implementing a Gaussian filter kernel. Experimentally, AGGF demonstrates its capacity to preserve edges and thin structures and outperforms the existing bilateral filter and domain transform filter in terms of both visual quality and peak signal-to-noise ratio performance. PMID:25321679

  13. Adaptive local thresholding for robust nucleus segmentation utilizing shape priors

    NASA Astrophysics Data System (ADS)

    Wang, Xiuzhong; Srinivas, Chukka

    2016-03-01

    This paper describes a novel local thresholding method for foreground detection. First, a Canny edge detection method is used for initial edge detection. Then, tensor voting is applied on the initial edge pixels, using a nonsymmetric tensor field tailored to encode prior information about nucleus size, shape, and intensity spatial distribution. Tensor analysis is then performed to generate the saliency image and, based on that, the refined edge. Next, the image domain is divided into blocks. In each block, at least one foreground and one background pixel are sampled for each refined edge pixel. The saliency weighted foreground histogram and background histogram are then created. These two histograms are used to calculate a threshold by minimizing the background and foreground pixel classification error. The block-wise thresholds are then used to generate the threshold for each pixel via interpolation. Finally, the foreground is obtained by comparing the original image with the threshold image. The effective use of prior information, combined with robust techniques, results in far more reliable foreground detection, which leads to robust nucleus segmentation.

  14. MRI brain tumor segmentation and necrosis detection using adaptive Sobolev snakes

    NASA Astrophysics Data System (ADS)

    Nakhmani, Arie; Kikinis, Ron; Tannenbaum, Allen

    2014-03-01

    Brain tumor segmentation in brain MRI volumes is used in neurosurgical planning and illness staging. It is important to explore the tumor shape and necrosis regions at di erent points of time to evaluate the disease progression. We propose an algorithm for semi-automatic tumor segmentation and necrosis detection. Our algorithm consists of three parts: conversion of MRI volume to a probability space based on the on-line learned model, tumor probability density estimation, and adaptive segmentation in the probability space. We use manually selected acceptance and rejection classes on a single MRI slice to learn the background and foreground statistical models. Then, we propagate this model to all MRI slices to compute the most probable regions of the tumor. Anisotropic 3D di usion is used to estimate the probability density. Finally, the estimated density is segmented by the Sobolev active contour (snake) algorithm to select smoothed regions of the maximum tumor probability. The segmentation approach is robust to noise and not very sensitive to the manual initialization in the volumes tested. Also, it is appropriate for low contrast imagery. The irregular necrosis regions are detected by using the outliers of the probability distribution inside the segmented region. The necrosis regions of small width are removed due to a high probability of noisy measurements. The MRI volume segmentation results obtained by our algorithm are very similar to expert manual segmentation.

  15. Pulmonary airways tree segmentation from CT examinations using adaptive volume of interest

    NASA Astrophysics Data System (ADS)

    Park, Sang Cheol; Kim, Won Pil; Zheng, Bin; Leader, Joseph K.; Pu, Jiantao; Tan, Jun; Gur, David

    2009-02-01

    Airways tree segmentation is an important step in quantitatively assessing the severity of and changes in several lung diseases such as chronic obstructive pulmonary disease (COPD), asthma, and cystic fibrosis. It can also be used in guiding bronchoscopy. The purpose of this study is to develop an automated scheme for segmenting the airways tree structure depicted on chest CT examinations. After lung volume segmentation, the scheme defines the first cylinder-like volume of interest (VOI) using a series of images depicting the trachea. The scheme then iteratively defines and adds subsequent VOIs using a region growing algorithm combined with adaptively determined thresholds in order to trace possible sections of airways located inside the combined VOI in question. The airway tree segmentation process is automatically terminated after the scheme assesses all defined VOIs in the iteratively assembled VOI list. In this preliminary study, ten CT examinations with 1.25mm section thickness and two different CT image reconstruction kernels ("bone" and "standard") were selected and used to test the proposed airways tree segmentation scheme. The experiment results showed that (1) adopting this approach affectively prevented the scheme from infiltrating into the parenchyma, (2) the proposed method reasonably accurately segmented the airways trees with lower false positive identification rate as compared with other previously reported schemes that are based on 2-D image segmentation and data analyses, and (3) the proposed adaptive, iterative threshold selection method for the region growing step in each identified VOI enables the scheme to segment the airways trees reliably to the 4th generation in this limited dataset with successful segmentation up to the 5th generation in a fraction of the airways tree branches.

  16. Segmentation of brain PET-CT images based on adaptive use of complementary information

    NASA Astrophysics Data System (ADS)

    Xia, Yong; Wen, Lingfeng; Eberl, Stefan; Fulham, Michael; Feng, Dagan

    2009-02-01

    Dual modality PET-CT imaging provides aligned anatomical (CT) and functional (PET) images in a single scanning session, which can potentially be used to improve image segmentation of PET-CT data. The ability to distinguish structures for segmentation is a function of structure and modality and varies across voxels. Thus optimal contribution of a particular modality to segmentation is spatially variant. Existing segmentation algorithms, however, seldom account for this characteristic of PET-CT data and the results using these algorithms are not optimal. In this study, we propose a relative discrimination index (RDI) to characterize the relative abilities of PET and CT to correctly classify each voxel into the correct structure for segmentation. The definition of RDI is based on the information entropy of the probability distribution of the voxel's class label. If the class label derived from CT data for a particular voxel has more certainty than that derived from PET data, the corresponding RDI will have a higher value. We applied the RDI matrix to balance adaptively the contributions of PET and CT data to segmentation of brain PET-CT images on a voxel-by-voxel basis, with the aim to give the modality with higher discriminatory power a larger weight. The resultant segmentation approach is distinguished from traditional approaches by its innovative and adaptive use of the dual-modality information. We compared our approach to the non-RDI version and two commonly used PET-only based segmentation algorithms for simulation and clinical data. Our results show that the RDI matrix markedly improved PET-CT image segmentation.

  17. Demonstrating Hormonal Control of Vertebrate Adaptive Color Changes in Vitro.

    ERIC Educational Resources Information Center

    Hadley, Mac E.; Younggren, Newell A.

    1980-01-01

    Presented is a short discussion of factors causing color changes in animals. Also described is an activity which may be used to demonstrate the response of amphibian skin to a melanophore stimulating hormone in high school or college biology classes. (PEB)

  18. Adaptive Segmentation and Feature Quantization of Sublingual Veins of Healthy Humans

    NASA Astrophysics Data System (ADS)

    Yan, Zifei; Li, Naimin

    The Sublingual Vein Diagnosis, one part of Tongue Diagnosis, plays an important role in deciding the healthy condition of humans. This paper focuses on establishing a feature quantization framework for the inspection of sublingual veins of healthy humans, composed of two parts: the segmentation of sublingual veins of healthy humans and the feature quantization of them. Firstly, a novel technique of sublingual vein segmentation is proposed here. Sublingual Vein Color Model, which combines the Bayesian Decision with CIEYxy color space, is established based on a large number of labeled sublingual images. Experiments prove that the proposed method performs well on the segmentation of images from healthy humans with weak color contrast between sublingual vein and tongue proper. And then, a chromatic system in conformity with diagnostic standard of Traditional Chinese Medicine doctors is established to describe the chromatic feature of sublingual veins. Experimental results show that the geometrical and chromatic features quantized by the proposed framework are properly consistent with the diagnostic standard summarized by TCM doctors for healthy humans.

  19. Locally adaptive MR intensity models and MRF-based segmentation of multiple sclerosis lesions

    NASA Astrophysics Data System (ADS)

    Galimzianova, Alfiia; Lesjak, Žiga; Likar, Boštjan; Pernuš, Franjo; Špiclin, Žiga

    2015-03-01

    Neuroimaging biomarkers are an important paraclinical tool used to characterize a number of neurological diseases, however, their extraction requires accurate and reliable segmentation of normal and pathological brain structures. For MR images of healthy brains the intensity models of normal-appearing brain tissue (NABT) in combination with Markov random field (MRF) models are known to give reliable and smooth NABT segmentation. However, the presence of pathology, MR intensity bias and natural tissue-dependent intensity variability altogether represent difficult challenges for a reliable estimation of NABT intensity model based on MR images. In this paper, we propose a novel method for segmentation of normal and pathological structures in brain MR images of multiple sclerosis (MS) patients that is based on locally-adaptive NABT model, a robust method for the estimation of model parameters and a MRF-based segmentation framework. Experiments on multi-sequence brain MR images of 27 MS patients show that, compared to whole-brain model and compared to the widely used Expectation-Maximization Segmentation (EMS) method, the locally-adaptive NABT model increases the accuracy of MS lesion segmentation.

  20. Automatic Iceball Segmentation With Adapted Shape Priors for MRI-Guided Cryoablation

    PubMed Central

    Liu, Xinyang; Tuncali, Kemal; Wells, William M.; Zientara, Gary P.

    2014-01-01

    Purpose To develop and evaluate an automatic segmentation method that extracts the 3D configuration of the ablation zone, the iceball, from images acquired during the freezing phase of MRI-guided cryoablation. Materials and Methods Intraprocedural images at 63 timepoints from 13 kidney tumor cryoablation procedures were examined retrospectively. The images were obtained using a 3 Tesla wide-bore MRI scanner and axial HASTE sequence. Initialized with semiautomatically localized cryoprobes, the iceball was segmented automatically at each timepoint using the graph cut (GC) technique with adapted shape priors. Results The average Dice Similarity Coefficients (DSC), compared with manual segmentations, were 0.88, 0.92, 0.92, 0.93, and 0.93 at 3, 6, 9, 12, and 15 min time-points, respectively, and the average DSC of the total 63 segmentations was 0.92 ± 0.03. The proposed method improved the accuracy significantly compared with the approach without shape prior adaptation (P = 0.026). The number of probes involved in the procedure had no apparent influence on the segmentation results using our technique. The average computation time was 20 s, which was compatible with an intraprocedural setting. Conclusion Our automatic iceball segmentation method demonstrated high accuracy and robustness for practical use in monitoring the progress of MRI-guided cryoablation. PMID:24338961

  1. Research on a pulmonary nodule segmentation method combining fast self-adaptive FCM and classification.

    PubMed

    Liu, Hui; Zhang, Cai-Ming; Su, Zhi-Yuan; Wang, Kai; Deng, Kai

    2015-01-01

    The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms.

  2. Novel calibration and color adaptation schemes in three-fringe RGB photoelasticity

    NASA Astrophysics Data System (ADS)

    Swain, Digendranath; Thomas, Binu P.; Philip, Jeby; Pillai, S. Annamala

    2015-03-01

    Isochromatic demodulation in digital photoelasticity using RGB calibration is a two step process. The first step involves the construction of a look-up table (LUT) from a calibration experiment. In the second step, isochromatic data is demodulated by matching the colors of an analysis image with the colors existing in the LUT. As actual test and calibration experiment tint conditions vary due to different sources, color adaptation techniques for modifying an existing primary LUT are employed. However, the primary LUT is still generated from bending experiments. In this paper, RGB demodulation based on a theoretically constructed LUT has been attempted to exploit the advantages of color adaptation schemes. Thereby, the experimental mode of LUT generation and some uncertainties therein can be minimized. Additionally, a new color adaptation algorithm is proposed using quadratic Lagrangian interpolation polynomials, which is numerically better than the two-point linear interpolations available in the literature. The new calibration and color adaptation schemes are validated and applied to demodulate fringe orders in live models and stress frozen slices.

  3. Combined Spline and B-spline for an improved automatic skin lesion segmentation in dermoscopic images using optimal color channel.

    PubMed

    Abbas, A A; Guo, X; Tan, W H; Jalab, H A

    2014-08-01

    In a computerized image analysis environment, the irregularity of a lesion border has been used to differentiate between malignant melanoma and other pigmented skin lesions. The accuracy of the automated lesion border detection is a significant step towards accurate classification at a later stage. In this paper, we propose the use of a combined Spline and B-spline in order to enhance the quality of dermoscopic images before segmentation. In this paper, morphological operations and median filter were used first to remove noise from the original image during pre-processing. Then we proceeded to adjust image RGB values to the optimal color channel (green channel). The combined Spline and B-spline method was subsequently adopted to enhance the image before segmentation. The lesion segmentation was completed based on threshold value empirically obtained using the optimal color channel. Finally, morphological operations were utilized to merge the smaller regions with the main lesion region. Improvement on the average segmentation accuracy was observed in the experimental results conducted on 70 dermoscopic images. The average accuracy of segmentation achieved in this paper was 97.21 % (where, the average sensitivity and specificity were 94 % and 98.05 % respectively).

  4. A new intelligent method for minerals segmentation in thin sections based on a novel incremental color clustering

    NASA Astrophysics Data System (ADS)

    Izadi, Hossein; Sadri, Javad; Mehran, Nosrat-Agha

    2015-08-01

    Mineral segmentation in thin sections is a challenging, popular, and important research topic in computational geology, mineralogy, and mining engineering. Mineral segmentation in thin sections containing altered minerals, in which there are no evident and close boundaries, is a rather complex process. Most of the thin sections created in industries include altered minerals. However, intelligent mineral segmentation in thin sections containing altered minerals has not been widely investigated in the literature, and the current state of the art algorithms are not able to accurately segment minerals in such thin sections. In this paper, a novel method based on incremental learning for clustering pixels is proposed in order to segment index minerals in both thin sections with and without altered minerals. Our algorithm uses 12 color features that are extracted from thin section images. These features include red, green, blue, hue, saturation and intensity, under plane and cross polarized lights in maximum intensity situation. The proposed method has been tested on 155 igneous samples and the overall accuracy of 92.15% and 85.24% has been obtained for thin sections without altered minerals and thin sections containing altered minerals, respectively. Experimental results indicate that the proposed method outperforms the results of other similar methods in the literature, especially for segmenting thin sections containing altered minerals. The proposed algorithm could be applied in applications which require a real time segmentation or efficient identification map such as petroleum geology, petrography and NASA Mars explorations.

  5. Novel multiresolution mammographic density segmentation using pseudo 3D features and adaptive cluster merging

    NASA Astrophysics Data System (ADS)

    He, Wenda; Juette, Arne; Denton, Erica R. E.; Zwiggelaar, Reyer

    2015-03-01

    Breast cancer is the most frequently diagnosed cancer in women. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective ways to overcome the disease. Successful mammographic density segmentation is a key aspect in deriving correct tissue composition, ensuring an accurate mammographic risk assessment. However, mammographic densities have not yet been fully incorporated with non-image based risk prediction models, (e.g. the Gail and the Tyrer-Cuzick model), because of unreliable segmentation consistency and accuracy. This paper presents a novel multiresolution mammographic density segmentation, a concept of stack representation is proposed, and 3D texture features were extracted by adapting techniques based on classic 2D first-order statistics. An unsupervised clustering technique was employed to achieve mammographic segmentation, in which two improvements were made; 1) consistent segmentation by incorporating an optimal centroids initialisation step, and 2) significantly reduced the number of missegmentation by using an adaptive cluster merging technique. A set of full field digital mammograms was used in the evaluation. Visual assessment indicated substantial improvement on segmented anatomical structures and tissue specific areas, especially in low mammographic density categories. The developed method demonstrated an ability to improve the quality of mammographic segmentation via clustering, and results indicated an improvement of 26% in segmented image with good quality when compared with the standard clustering approach. This in turn can be found useful in early breast cancer detection, risk-stratified screening, and aiding radiologists in the process of decision making prior to surgery and/or treatment.

  6. Adaptive evolution of color vision genes in higher primates.

    PubMed

    Shyue, S K; Hewett-Emmett, D; Sperling, H G; Hunt, D M; Bowmaker, J K; Mollon, J D; Li, W H

    1995-09-01

    The intron 4 sequences of the three polymorphic alleles at the X-linked color photo-pigment locus in the squirrel monkey and the marmoset reveal that the alleles in each species are exceptionally divergent. The data further suggest either that each triallelic system has arisen independently in these two New World monkey lineages, or that in each species at least seven deletions and insertions (14 in the two species) in intron 4 have been transferred and homogenized among the alleles by gene conversion or recombination. In either case, the alleles in each species apparently have persisted more than 5 million years and probably have been maintained by overdominant selection.

  7. Multiobjective Image Color Quantization Algorithm Based on Self-Adaptive Hybrid Differential Evolution

    PubMed Central

    Xia, Xuewen

    2016-01-01

    In recent years, some researchers considered image color quantization as a single-objective problem and applied heuristic algorithms to solve it. This paper establishes a multiobjective image color quantization model with intracluster distance and intercluster separation as its objectives. Inspired by a multipopulation idea, a multiobjective image color quantization algorithm based on self-adaptive hybrid differential evolution (MoDE-CIQ) is then proposed to solve this model. Two numerical experiments on four common test images are conducted to analyze the effectiveness and competitiveness of the multiobjective model and the proposed algorithm. PMID:27738423

  8. Ecological genetics of adaptive color polymorphism in pocket mice: geographic variation in selected and neutral genes.

    PubMed

    Hoekstra, Hopi E; Drumm, Kristen E; Nachman, Michael W

    2004-06-01

    Patterns of geographic variation in phenotype or genotype may provide evidence for natural selection. Here, we compare phenotypic variation in color, allele frequencies of a pigmentation gene (the melanocortin-1 receptor, Mc1r), and patterns of neutral mitochondrial DNA (mtDNA) variation in rock pocket mice (Chaetodipus intermedius) across a habitat gradient in southern Arizona. Pocket mice inhabiting volcanic lava have dark coats with unbanded, uniformly melanic hairs, whereas mice from nearby light-colored granitic rocks have light coats with banded hairs. This color polymorphism is a presumed adaptation to avoid predation. Previous work has demonstrated that two Mc1r alleles, D and d, differ by four amino acids, and are responsible for the color polymorphism: DD and Dd genotypes are melanic whereas dd genotypes are light colored. To determine the frequency of the two Mc1r allelic classes across the dark-colored lava and neighboring light-colored granite, we sequenced the Mc1r gene in 175 individuals from a 35-km transect in the Pinacate lava region. We also sequenced two neutral mtDNA genes, COIII and ND3, in the same individuals. We found a strong correlation between Mc1r allele frequency and habitat color and no correlation between mtDNA markers and habitat color. Using estimates of migration from mtDNA haplotypes between dark- and light-colored sampling sites and Mc1r allele frequencies at each site, we estimated selection coefficients against mismatched Mc1r alleles, assuming a simple model of migration-selection balance. Habitat-dependent selection appears strong but asymmetric: selection is stronger against light mice on dark rock than against melanic mice on light rock. Together these results suggest that natural selection acts to match pocket mouse coat color to substrate color, despite high levels of gene flow between light and melanic populations.

  9. A color and shape based algorithm for segmentation of white blood cells in peripheral blood and bone marrow images.

    PubMed

    Arslan, Salim; Ozyurek, Emel; Gunduz-Demir, Cigdem

    2014-06-01

    Computer-based imaging systems are becoming important tools for quantitative assessment of peripheral blood and bone marrow samples to help experts diagnose blood disorders such as acute leukemia. These systems generally initiate a segmentation stage where white blood cells are separated from the background and other nonsalient objects. As the success of such imaging systems mainly depends on the accuracy of this stage, studies attach great importance for developing accurate segmentation algorithms. Although previous studies give promising results for segmentation of sparsely distributed normal white blood cells, only a few of them focus on segmenting touching and overlapping cell clusters, which is usually the case when leukemic cells are present. In this article, we present a new algorithm for segmentation of both normal and leukemic cells in peripheral blood and bone marrow images. In this algorithm, we propose to model color and shape characteristics of white blood cells by defining two transformations and introduce an efficient use of these transformations in a marker-controlled watershed algorithm. Particularly, these domain specific characteristics are used to identify markers and define the marking function of the watershed algorithm as well as to eliminate false white blood cells in a postprocessing step. Working on 650 white blood cells in peripheral blood and bone marrow images, our experiments reveal that the proposed algorithm improves the segmentation performance compared with its counterparts, leading to high accuracies for both sparsely distributed normal white blood cells and dense leukemic cell clusters.

  10. Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

    SciTech Connect

    Park, Sang Hyun; Gao, Yaozong; Shi, Yinghuan; Shen, Dinggang

    2014-11-01

    Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to

  11. Automated segmentation of geographic atrophy of the retinal epithelium via random forests in AREDS color fundus images☆

    PubMed Central

    Feeny, Albert K.; Tadarati, Mongkol; Freund, David E.; Bressler, Neil M.; Burlina, Philippe

    2015-01-01

    Background Age-related macular degeneration (AMD), left untreated, is the leading cause of vision loss in people older than 55. Severe central vision loss occurs in the advanced stage of the disease, characterized by either the in growth of choroidal neovascularization (CNV), termed the “wet” form, or by geographic atrophy (GA) of the retinal pigment epithelium (RPE) involving the center of the macula, termed the “dry” form. Tracking the change in GA area over time is important since it allows for the characterization of the effectiveness of GA treatments. Tracking GA evolution can be achieved by physicians performing manual delineation of GA area on retinal fundus images. However, manual GA delineation is time-consuming and subject to inter-and intra-observer variability. Methods We have developed a fully automated GA segmentation algorithm in color fundus images that uses a supervised machine learning approach employing a random forest classifier. This algorithm is developed and tested using a dataset of images from the NIH-sponsored Age Related Eye Disease Study (AREDS). GA segmentation output was compared against a manual delineation by a retina specialist. Results Using 143 color fundus images from 55 different patient eyes, our algorithm achieved PPV of 0.82±0.19, and NPV of 0:95±0.07. Discussion This is the first study, to our knowledge, applying machine learning methods to GA segmentation on color fundus images and using AREDS imagery for testing. These preliminary results show promising evidence that machine learning methods may have utility in automated characterization of GA from color fundus images. PMID:26318113

  12. Local adaptation for body color in Drosophila americana

    PubMed Central

    Wittkopp, P J; Smith-Winberry, G; Arnold, L L; Thompson, E M; Cooley, A M; Yuan, D C; Song, Q; McAllister, B F

    2011-01-01

    Pigmentation is one of the most variable traits within and between Drosophila species. Much of this diversity appears to be adaptive, with environmental factors often invoked as selective forces. Here, we describe the geographic structure of pigmentation in Drosophila americana and evaluate the hypothesis that it is a locally adapted trait. Body pigmentation was quantified using digital images and spectrometry in up to 10 flies from each of 93 isofemale lines collected from 17 locations across the United States and found to correlate most strongly with longitude. Sequence variation at putatively neutral loci showed no evidence of population structure and was inconsistent with an isolation-by-distance model, suggesting that the pigmentation cline exists despite extensive gene flow throughout the species range, and is most likely the product of natural selection. In all other Drosophila species examined to date, dark pigmentation is associated with arid habitats; however, in D. americana, the darkest flies were collected from the most humid regions. To investigate this relationship further, we examined desiccation resistance attributable to an allele that darkens pigmentation in D. americana. We found no significant effect of pigmentation on desiccation resistance in this experiment, suggesting that pigmentation and desiccation resistance are not unequivocally linked in all Drosophila species. PMID:20606690

  13. Local adaptive approach toward segmentation of microscopic images of activated sludge flocs

    NASA Astrophysics Data System (ADS)

    Khan, Muhammad Burhan; Nisar, Humaira; Ng, Choon Aun; Lo, Po Kim; Yap, Vooi Voon

    2015-11-01

    Activated sludge process is a widely used method to treat domestic and industrial effluents. The conditions of activated sludge wastewater treatment plant (AS-WWTP) are related to the morphological properties of flocs (microbial aggregates) and filaments, and are required to be monitored for normal operation of the plant. Image processing and analysis is a potential time-efficient monitoring tool for AS-WWTPs. Local adaptive segmentation algorithms are proposed for bright-field microscopic images of activated sludge flocs. Two basic modules are suggested for Otsu thresholding-based local adaptive algorithms with irregular illumination compensation. The performance of the algorithms has been compared with state-of-the-art local adaptive algorithms of Sauvola, Bradley, Feng, and c-mean. The comparisons are done using a number of region- and nonregion-based metrics at different microscopic magnifications and quantification of flocs. The performance metrics show that the proposed algorithms performed better and, in some cases, were comparable to the state-of the-art algorithms. The performance metrics were also assessed subjectively for their suitability for segmentations of activated sludge images. The region-based metrics such as false negative ratio, sensitivity, and negative predictive value gave inconsistent results as compared to other segmentation assessment metrics.

  14. A fully automatic framework for cell segmentation on non-confocal adaptive optics images

    NASA Astrophysics Data System (ADS)

    Liu, Jianfei; Dubra, Alfredo; Tam, Johnny

    2016-03-01

    By the time most retinal diseases are diagnosed, macroscopic irreversible cellular loss has already occurred. Earlier detection of subtle structural changes at the single photoreceptor level is now possible, using the adaptive optics scanning light ophthalmoscope (AOSLO). This work aims to develop a fully automatic segmentation framework to extract cell boundaries from non-confocal split-detection AOSLO images of the cone photoreceptor mosaic in the living human eye. Significant challenges include anisotropy, heterogeneous cell regions arising from shading effects, and low contrast between cells and background. To overcome these challenges, we propose the use of: 1) multi-scale Hessian response to detect heterogeneous cell regions, 2) convex hulls to create boundary templates, and 3) circularlyconstrained geodesic active contours to refine cell boundaries. We acquired images from three healthy subjects at eccentric retinal regions and manually contoured cells to generate ground-truth for evaluating segmentation accuracy. Dice coefficient, relative absolute area difference, and average contour distance were 82±2%, 11±6%, and 2.0±0.2 pixels (Mean±SD), respectively. We find that strong shading effects from vessels are a main factor that causes cell oversegmentation and false segmentation of non-cell regions. Our segmentation algorithm can automatically and accurately segment photoreceptor cells on non-confocal AOSLO images, which is the first step in longitudinal tracking of cellular changes in the individual eye over the time course of disease progression.

  15. Automatic segmentation of canine retinal OCT using adaptive gradient enhancement and region growing

    NASA Astrophysics Data System (ADS)

    He, Yufan; Sun, Yankui; Chen, Min; Zheng, Yuanjie; Liu, Hui; Leon, Cecilia; Beltran, William; Gee, James C.

    2016-03-01

    In recent years, several studies have shown that the canine retina model offers important insight for our understanding of human retinal diseases. Several therapies developed to treat blindness in such models have already moved onto human clinical trials, with more currently under development [1]. Optical coherence tomography (OCT) offers a high resolution imaging modality for performing in-vivo analysis of the retinal layers. However, existing algorithms for automatically segmenting and analyzing such data have been mostly focused on the human retina. As a result, canine retinal images are often still being analyzed using manual segmentations, which is a slow and laborious task. In this work, we propose a method for automatically segmenting 5 boundaries in canine retinal OCT. The algorithm employs the position relationships between different boundaries to adaptively enhance the gradient map. A region growing algorithm is then used on the enhanced gradient maps to find the five boundaries separately. The automatic segmentation was compared against manual segmentations showing an average absolute error of 5.82 +/- 4.02 microns.

  16. An adaptive grid for graph-based segmentation in retinal OCT

    PubMed Central

    Lang, Andrew; Carass, Aaron; Calabresi, Peter A.; Ying, Howard S.; Prince, Jerry L.

    2016-01-01

    Graph-based methods for retinal layer segmentation have proven to be popular due to their efficiency and accuracy. These methods build a graph with nodes at each voxel location and use edges connecting nodes to encode the hard constraints of each layer’s thickness and smoothness. In this work, we explore deforming the regular voxel grid to allow adjacent vertices in the graph to more closely follow the natural curvature of the retina. This deformed grid is constructed by fixing node locations based on a regression model of each layer’s thickness relative to the overall retina thickness, thus we generate a subject specific grid. Graph vertices are not at voxel locations, which allows for control over the resolution that the graph represents. By incorporating soft constraints between adjacent nodes, segmentation on this grid will favor smoothly varying surfaces consistent with the shape of the retina. Our final segmentation method then follows our previous work. Boundary probabilities are estimated using a random forest classifier followed by an optimal graph search algorithm on the new adaptive grid to produce a final segmentation. Our method is shown to produce a more consistent segmentation with an overall accuracy of 3.38 μm across all boundaries.

  17. Automated grading of left ventricular segmental wall motion by an artificial neural network using color kinesis images.

    PubMed

    Murta, L O; Ruiz, E E S; Pazin-Filho, A; Schmidt, A; Almeida-Filho, O C; Simões, M V; Marin-Neto, J A; Maciel, B C

    2006-01-01

    The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wall motion (WM) abnormalities based on color-coded echocardiographic WM images. An artificial neural network (ANN) was developed and validated for grading LV segmental WM using data from color kinesis (CK) images, a technique developed to display the timing and magnitude of global and regional WM in real time. We evaluated 21 normal subjects and 20 patients with LVWM abnormalities revealed by two-dimensional echocardiography. CK images were obtained in two sets of viewing planes. A method was developed to analyze CK images, providing quantitation of fractional area change in each of the 16 LV segments. Two experienced observers analyzed LVWM from two-dimensional images and scored them as: 1) normal, 2) mild hypokinesia, 3) moderate hypokinesia, 4) severe hypokinesia, 5) akinesia, and 6) dyskinesia. Based on expert analysis of 10 normal subjects and 10 patients, we trained a multilayer perceptron ANN using a back-propagation algorithm to provide automated grading of LVWM, and this ANN was then tested in the remaining subjects. Excellent concordance between expert and ANN analysis was shown by ROC curve analysis, with measured area under the curve of 0.975. An excellent correlation was also obtained for global LV segmental WM index by expert and ANN analysis (R2 = 0.99). In conclusion, ANN showed high accuracy for automated semi-quantitative grading of WM based on CK images. This technique can be an important aid, improving diagnostic accuracy and reducing inter-observer variability in scoring segmental LVWM.

  18. Visual Tracking Based on the Adaptive Color Attention Tuned Sparse Generative Object Model.

    PubMed

    Tian, Chunna; Gao, Xinbo; Wei, Wei; Zheng, Hong

    2015-12-01

    This paper presents a new visual tracking framework based on an adaptive color attention tuned local sparse model. The histograms of sparse coefficients of all patches in an object are pooled together according to their spatial distribution. A particle filter methodology is used as the location model to predict candidates for object verification during tracking. Since color is an important visual clue to distinguish objects from background, we calculate the color similarity between objects in the previous frames and the candidates in current frame, which is adopted as color attention to tune the local sparse representation-based appearance similarity measurement between the object template and candidates. The color similarity can be calculated efficiently with hash coded color names, which helps the tracker find more reliable objects during tracking. We use a flexible local sparse coding of the object to evaluate the degeneration degree of the appearance model, based on which we build a model updating mechanism to alleviate drifting caused by temporal varying multi-factors. Experiments on 76 challenging benchmark color sequences and the evaluation under the object tracking benchmark protocol demonstrate the superiority of the proposed tracker over the state-of-the-art methods in accuracy. PMID:26390460

  19. The Influence of a Low-Level Color or Figure Adaptation on a High-Level Face Perception

    NASA Astrophysics Data System (ADS)

    Song, Miao; Shinomori, Keizo; Zhang, Shiyong

    Visual adaptation is a universal phenomenon associated with human visual system. This adaptation affects not only the perception of low-level visual systems processing color, motion, and orientation, but also the perception of high-level visual systems processing complex visual patterns, such as facial identity and expression. Although it remains unclear for the mutual interaction mechanism between systems at different levels, this issue is the key to understand the hierarchical neural coding and computation mechanism. Thus, we examined whether the low-level adaptation influences on the high-level aftereffect by means of cross-level adaptation paradigm (i.e. color, figure adaptation versus facial identity adaptation). We measured the identity aftereffects within the real face test images on real face, color chip and figure adapting conditions. The cross-level mutual influence was evaluated by the aftereffect size among different adapting conditions. The results suggest that the adaptation to color and figure contributes to the high-level facial identity aftereffect. Besides, the real face adaptation obtained the significantly stronger aftereffect than the color chip or the figure adaptation. Our results reveal the possibility of cross-level adaptation propagation and implicitly indicate a high-level holistic facial neural representation. Based on these results, we discussed the theoretical implication of cross-level adaptation propagation for understanding the hierarchical sensory neural systems.

  20. An efficient topology adaptation system for parametric active contour segmentation of 3D images

    NASA Astrophysics Data System (ADS)

    Abhau, Jochen; Scherzer, Otmar

    2008-03-01

    Active contour models have already been used succesfully for segmentation of organs from medical images in 3D. In implicit models, the contour is given as the isosurface of a scalar function, and therefore topology adaptations are handled naturally during a contour evolution. Nevertheless, explicit or parametric models are often preferred since user interaction and special geometric constraints are usually easier to incorporate. Although many researchers have studied topology adaptation algorithms in explicit mesh evolutions, no stable algorithm is known for interactive applications. In this paper, we present a topology adaptation system, which consists of two novel ingredients: A spatial hashing technique is used to detect self-colliding triangles of the mesh whose expected running time is linear with respect to the number of mesh vertices. For the topology change procedure, we have developed formulas by homology theory. During a contour evolution, we just have to choose between a few possible mesh retriangulations by local triangle-triangle intersection tests. Our algorithm has several advantages compared to existing ones: Since the new algorithm does not require any global mesh reparametrizations, it is very efficient. Since the topology adaptation system does not require constant sampling density of the mesh vertices nor especially smooth meshes, mesh evolution steps can be performed in a stable way with a rather coarse mesh. We apply our algorithm to 3D ultrasonic data, showing that accurate segmentation is obtained in some seconds.

  1. An adaptive segment method for smoothing lidar signal based on noise estimation

    NASA Astrophysics Data System (ADS)

    Wang, Yuzhao; Luo, Pingping

    2014-10-01

    An adaptive segmentation smoothing method (ASSM) is introduced in the paper to smooth the signal and suppress the noise. In the ASSM, the noise is defined as the 3σ of the background signal. An integer number N is defined for finding the changing positions in the signal curve. If the difference of adjacent two points is greater than 3Nσ, the position is recorded as an end point of the smoothing segment. All the end points detected as above are recorded and the curves between them will be smoothed separately. In the traditional method, the end points of the smoothing windows in the signals are fixed. The ASSM creates changing end points in different signals and the smoothing windows could be set adaptively. The windows are always set as the half of the segmentations and then the average smoothing method will be applied in the segmentations. The Iterative process is required for reducing the end-point aberration effect in the average smoothing method and two or three times are enough. In ASSM, the signals are smoothed in the spacial area nor frequent area, that means the frequent disturbance will be avoided. A lidar echo was simulated in the experimental work. The echo was supposed to be created by a space-born lidar (e.g. CALIOP). And white Gaussian noise was added to the echo to act as the random noise resulted from environment and the detector. The novel method, ASSM, was applied to the noisy echo to filter the noise. In the test, N was set to 3 and the Iteration time is two. The results show that, the signal could be smoothed adaptively by the ASSM, but the N and the Iteration time might be optimized when the ASSM is applied in a different lidar.

  2. Dual-modality brain PET-CT image segmentation based on adaptive use of functional and anatomical information.

    PubMed

    Xia, Yong; Eberl, Stefan; Wen, Lingfeng; Fulham, Michael; Feng, David Dagan

    2012-01-01

    Dual medical imaging modalities, such as PET-CT, are now a routine component of clinical practice. Medical image segmentation methods, however, have generally only been applied to single modality images. In this paper, we propose the dual-modality image segmentation model to segment brain PET-CT images into gray matter, white matter and cerebrospinal fluid. This model converts PET-CT image segmentation into an optimization process controlled simultaneously by PET and CT voxel values and spatial constraints. It is innovative in the creation and application of the modality discriminatory power (MDP) coefficient as a weighting scheme to adaptively combine the functional (PET) and anatomical (CT) information on a voxel-by-voxel basis. Our approach relies upon allowing the modality with higher discriminatory power to play a more important role in the segmentation process. We compared the proposed approach to three other image segmentation strategies, including PET-only based segmentation, combination of the results of independent PET image segmentation and CT image segmentation, and simultaneous segmentation of joint PET and CT images without an adaptive weighting scheme. Our results in 21 clinical studies showed that our approach provides the most accurate and reliable segmentation for brain PET-CT images. PMID:21719257

  3. Dual-modality brain PET-CT image segmentation based on adaptive use of functional and anatomical information.

    PubMed

    Xia, Yong; Eberl, Stefan; Wen, Lingfeng; Fulham, Michael; Feng, David Dagan

    2012-01-01

    Dual medical imaging modalities, such as PET-CT, are now a routine component of clinical practice. Medical image segmentation methods, however, have generally only been applied to single modality images. In this paper, we propose the dual-modality image segmentation model to segment brain PET-CT images into gray matter, white matter and cerebrospinal fluid. This model converts PET-CT image segmentation into an optimization process controlled simultaneously by PET and CT voxel values and spatial constraints. It is innovative in the creation and application of the modality discriminatory power (MDP) coefficient as a weighting scheme to adaptively combine the functional (PET) and anatomical (CT) information on a voxel-by-voxel basis. Our approach relies upon allowing the modality with higher discriminatory power to play a more important role in the segmentation process. We compared the proposed approach to three other image segmentation strategies, including PET-only based segmentation, combination of the results of independent PET image segmentation and CT image segmentation, and simultaneous segmentation of joint PET and CT images without an adaptive weighting scheme. Our results in 21 clinical studies showed that our approach provides the most accurate and reliable segmentation for brain PET-CT images.

  4. Dosimetric Evaluation of Automatic Segmentation for Adaptive IMRT for Head-and-Neck Cancer

    SciTech Connect

    Tsuji, Stuart Y.; Hwang, Andrew; Weinberg, Vivian; Yom, Sue S.; Quivey, Jeanne M.; Xia Ping

    2010-07-01

    Purpose: Adaptive planning to accommodate anatomic changes during treatment requires repeat segmentation. This study uses dosimetric endpoints to assess automatically deformed contours. Methods and Materials: Sixteen patients with head-and-neck cancer had adaptive plans because of anatomic change during radiotherapy. Contours from the initial planning computed tomography (CT) were deformed to the mid-treatment CT using an intensity-based free-form registration algorithm then compared with the manually drawn contours for the same CT using the Dice similarity coefficient and an overlap index. The automatic contours were used to create new adaptive plans. The original and automatic adaptive plans were compared based on dosimetric outcomes of the manual contours and on plan conformality. Results: Volumes from the manual and automatic segmentation were similar; only the gross tumor volume (GTV) was significantly different. Automatic plans achieved lower mean coverage for the GTV: V95: 98.6 {+-} 1.9% vs. 89.9 {+-} 10.1% (p = 0.004) and clinical target volume: V95: 98.4 {+-} 0.8% vs. 89.8 {+-} 6.2% (p < 0.001) and a higher mean maximum dose to 1 cm{sup 3} of the spinal cord 39.9 {+-} 3.7 Gy vs. 42.8 {+-} 5.4 Gy (p = 0.034), but no difference for the remaining structures. Conclusions: Automatic segmentation is not robust enough to substitute for physician-drawn volumes, particularly for the GTV. However, it generates normal structure contours of sufficient accuracy when assessed by dosimetric end points.

  5. Context cue-dependent saccadic adaptation in rhesus macaques cannot be elicited using color.

    PubMed

    Cecala, Aaron L; Smalianchuk, Ivan; Khanna, Sanjeev B; Smith, Matthew A; Gandhi, Neeraj J

    2015-07-01

    When the head does not move, rapid movements of the eyes called saccades are used to redirect the line of sight. Saccades are defined by a series of metrical and kinematic (evolution of a movement as a function of time) relationships. For example, the amplitude of a saccade made from one visual target to another is roughly 90% of the distance between the initial fixation point (T0) and the peripheral target (T1). However, this stereotypical relationship between saccade amplitude and initial retinal error (T1-T0) may be altered, either increased or decreased, by surreptitiously displacing a visual target during an ongoing saccade. This form of motor learning (called saccadic adaptation) has been described in both humans and monkeys. Recent experiments in humans and monkeys have suggested that internal (proprioceptive) and external (target shape, color, and/or motion) cues may be used to produce context-dependent adaptation. We tested the hypothesis that an external contextual cue (target color) could be used to evoke differential gain (actual saccade/initial retinal error) states in rhesus monkeys. We did not observe differential gain states correlated with target color regardless of whether targets were displaced along the same vector as the primary saccade or perpendicular to it. Furthermore, this observation held true regardless of whether adaptation trials using various colors and intrasaccade target displacements were randomly intermixed or presented in short or long blocks of trials. These results are consistent with hypotheses that state that color cannot be used as a contextual cue and are interpreted in light of previous studies of saccadic adaptation in both humans and monkeys. PMID:25995353

  6. Context cue-dependent saccadic adaptation in rhesus macaques cannot be elicited using color.

    PubMed

    Cecala, Aaron L; Smalianchuk, Ivan; Khanna, Sanjeev B; Smith, Matthew A; Gandhi, Neeraj J

    2015-07-01

    When the head does not move, rapid movements of the eyes called saccades are used to redirect the line of sight. Saccades are defined by a series of metrical and kinematic (evolution of a movement as a function of time) relationships. For example, the amplitude of a saccade made from one visual target to another is roughly 90% of the distance between the initial fixation point (T0) and the peripheral target (T1). However, this stereotypical relationship between saccade amplitude and initial retinal error (T1-T0) may be altered, either increased or decreased, by surreptitiously displacing a visual target during an ongoing saccade. This form of motor learning (called saccadic adaptation) has been described in both humans and monkeys. Recent experiments in humans and monkeys have suggested that internal (proprioceptive) and external (target shape, color, and/or motion) cues may be used to produce context-dependent adaptation. We tested the hypothesis that an external contextual cue (target color) could be used to evoke differential gain (actual saccade/initial retinal error) states in rhesus monkeys. We did not observe differential gain states correlated with target color regardless of whether targets were displaced along the same vector as the primary saccade or perpendicular to it. Furthermore, this observation held true regardless of whether adaptation trials using various colors and intrasaccade target displacements were randomly intermixed or presented in short or long blocks of trials. These results are consistent with hypotheses that state that color cannot be used as a contextual cue and are interpreted in light of previous studies of saccadic adaptation in both humans and monkeys.

  7. Color

    ERIC Educational Resources Information Center

    Bowman, Bruce

    1975-01-01

    The color wheel, because it is an excellent way to teach color theory has become somewhat of a traditional assignment in most basic design courses. Article described a way to change this situation by re-designing and improving upon the basic color wheel. (Author/RK)

  8. Impact of resolution in multi-conjugate adaptive optics systems using segmented mirrors

    NASA Astrophysics Data System (ADS)

    Corej, Thomas A.; Schmidt, Jason D.

    2009-08-01

    In moderate-to-strong scintillation, multi-conjugate adaptive optics (MCAO) appears promising to compensate for amplitude and phase fluctuations. In this research, a MCAO system is simulated with a segmented deformable mirror (DM) reshaping the amplitude and the second DM (continuous) flattening the phase after propagation from the segmented mirror. A Gerchberg-Saxton (GS) type algorithm is used with Fresnel propagation between DM planes. The effects of varying the phase's apparent resolution on a segmented DM in the pupil plane is investigated. Results show the mean square error in the reshaped beam decreases as D/ro and Rytov number increase over the range of conditions tested (ro: 0.11 m - 0.36 m). The field-estimated Strehl ratio drops precipitously when the number of subapertures is increased beyond about 36 across, using a branch-pointtolerant unwrapper, due to the presence of branch points. On the second DM, by using the mean of the phase within each subaperture before back propagating to the first DM plane (inside the GS loop), the Strehl ratio was improved 6 - 11 percent using 4 - 19 actuators across. Further a novel method of cascading segmented DMs, of increasingly higher resolution, doing amplitude reshaping followed by a continuous DM to flatten the phase is explored.

  9. Adaptive deformable model for colonic polyp segmentation and measurement on CT colonography

    SciTech Connect

    Yao Jianhua; Summers, Ronald M.

    2007-05-15

    Polyp size is one important biomarker for the malignancy risk of a polyp. This paper presents an improved approach for colonic polyp segmentation and measurement on CT colonography images. The method is based on a combination of knowledge-guided intensity adjustment, fuzzy clustering, and adaptive deformable model. Since polyps on haustral folds are the most difficult to be segmented, we propose a dual-distance algorithm to first identify voxels on the folds, and then introduce a counter-force to control the model evolution. We derive linear and volumetric measurements from the segmentation. The experiment was conducted on 395 patients with 83 polyps, of which 43 polyps were on haustral folds. The results were validated against manual measurement from the optical colonoscopy and the CT colonography. The paired t-test showed no significant difference, and the R{sup 2} correlation was 0.61 for the linear measurement and 0.98 for the volumetric measurement. The mean Dice coefficient for volume overlap between automatic and manual segmentation was 0.752 (standard deviation 0.154)

  10. Separate channels for processing form, texture, and color: evidence from FMRI adaptation and visual object agnosia.

    PubMed

    Cavina-Pratesi, C; Kentridge, R W; Heywood, C A; Milner, A D

    2010-10-01

    Previous neuroimaging research suggests that although object shape is analyzed in the lateral occipital cortex, surface properties of objects, such as color and texture, are dealt with in more medial areas, close to the collateral sulcus (CoS). The present study sought to determine whether there is a single medial region concerned with surface properties in general or whether instead there are multiple foci independently extracting different surface properties. We used stimuli varying in their shape, texture, or color, and tested healthy participants and 2 object-agnosic patients, in both a discrimination task and a functional MR adaptation paradigm. We found a double dissociation between medial and lateral occipitotemporal cortices in processing surface (texture or color) versus geometric (shape) properties, respectively. In Experiment 2, we found that the medial occipitotemporal cortex houses separate foci for color (within anterior CoS and lingual gyrus) and texture (caudally within posterior CoS). In addition, we found that areas selective for shape, texture, and color individually were quite distinct from those that respond to all of these features together (shape and texture and color). These latter areas appear to correspond to those associated with the perception of complex stimuli such as faces and places.

  11. Region and edge-adaptive sampling and boundary completion for segmentation

    SciTech Connect

    Dillard, Scott E; Prasad, Lakshman; Grazzini, Jacopo A

    2010-01-01

    Edge detection produces a set of points that are likely to lie on discontinuities between objects within an image. We consider faces of the Gabriel graph of these points, a sub-graph of the Delaunay triangulation. Features are extracted by merging these faces using size, shape and color cues. We measure regional properties of faces using a novel shape-dependant sampling method that overcomes undesirable sampling bias of the Delaunay triangles. Instead, sampling is biased so as to smooth regional statistics within the detected object boundaries, and this smoothing adapts to local geometric features of the shape such as curvature, thickness and straightness.

  12. Multi-color space threshold segmentation and self-learning k-NN algorithm for surge test EUT status identification

    NASA Astrophysics Data System (ADS)

    Huang, Jian; Liu, Gui-xiong

    2016-09-01

    The identification of targets varies in different surge tests. A multi-color space threshold segmentation and self-learning k-nearest neighbor algorithm ( k-NN) for equipment under test status identification was proposed after using feature matching to identify equipment status had to train new patterns every time before testing. First, color space (L*a*b*, hue saturation lightness (HSL), hue saturation value (HSV)) to segment was selected according to the high luminance points ratio and white luminance points ratio of the image. Second, the unknown class sample S r was classified by the k-NN algorithm with training set T z according to the feature vector, which was formed from number of pixels, eccentricity ratio, compactness ratio, and Euler's numbers. Last, while the classification confidence coefficient equaled k, made S r as one sample of pre-training set T z '. The training set T z increased to T z+1 by T z ' if T z ' was saturated. In nine series of illuminant, indicator light, screen, and disturbances samples (a total of 21600 frames), the algorithm had a 98.65%identification accuracy, also selected five groups of samples to enlarge the training set from T 0 to T 5 by itself.

  13. Specific expression of the vacuolar iron transporter, TgVit, causes iron accumulation in blue-colored inner bottom segments of various tulip petals.

    PubMed

    Momonoi, Kazumi; Tsuji, Toshiaki; Kazuma, Kohei; Yoshida, Kumi

    2012-01-01

    Several flowers of Tulipa gesneriana exhibit a blue color in the bottom segments of the inner perianth. We have previously reported the inner-bottom tissue-specific iron accumulation and expression of the vacuolar iron transporter, TgVit1, in tulip cv. Murasakizuisho. To clarify whether the TgVit1-dependent iron accumulation and blue-color development in tulip petals are universal, we analyzed anthocyanin, its co-pigment components, iron contents and the expression of TgVit1 mRNA in 13 cultivars which show a blue color in the bottom segments of the inner perianth accompanying yellow- and white-colored inner-bottom petals. All of the blue bottom segments contained the same anthocyanin component, delphinidin 3-rutinoside. The flavonol composition varied with cultivar and tissue part. The major flavonol in the bottom segments of the inner perianth was rutin. The iron content in the upper part was less than that in the bottom segments of the inner perianth. The iron content in the yellow and white petals was higher in the bottom segment of the inner perianth than in the upper tissues. TgVit1 mRNA expression was apparent in all of the bottom tissues of the inner perianth. The result of a reproduction experiment by mixing the constituents suggests that the blue coloration in tulip petals is generally caused by iron complexation to delphinidin 3-rutinoside and that the iron complex is solubilized and stabilized by flavonol glycosides. TgVit1-dependent iron accumulation in the bottom segments of the inner perianth might be controlled by an unknown system that differentiated the upper parts and bottom segments of the inner perianth. PMID:22313773

  14. Specific expression of the vacuolar iron transporter, TgVit, causes iron accumulation in blue-colored inner bottom segments of various tulip petals.

    PubMed

    Momonoi, Kazumi; Tsuji, Toshiaki; Kazuma, Kohei; Yoshida, Kumi

    2012-01-01

    Several flowers of Tulipa gesneriana exhibit a blue color in the bottom segments of the inner perianth. We have previously reported the inner-bottom tissue-specific iron accumulation and expression of the vacuolar iron transporter, TgVit1, in tulip cv. Murasakizuisho. To clarify whether the TgVit1-dependent iron accumulation and blue-color development in tulip petals are universal, we analyzed anthocyanin, its co-pigment components, iron contents and the expression of TgVit1 mRNA in 13 cultivars which show a blue color in the bottom segments of the inner perianth accompanying yellow- and white-colored inner-bottom petals. All of the blue bottom segments contained the same anthocyanin component, delphinidin 3-rutinoside. The flavonol composition varied with cultivar and tissue part. The major flavonol in the bottom segments of the inner perianth was rutin. The iron content in the upper part was less than that in the bottom segments of the inner perianth. The iron content in the yellow and white petals was higher in the bottom segment of the inner perianth than in the upper tissues. TgVit1 mRNA expression was apparent in all of the bottom tissues of the inner perianth. The result of a reproduction experiment by mixing the constituents suggests that the blue coloration in tulip petals is generally caused by iron complexation to delphinidin 3-rutinoside and that the iron complex is solubilized and stabilized by flavonol glycosides. TgVit1-dependent iron accumulation in the bottom segments of the inner perianth might be controlled by an unknown system that differentiated the upper parts and bottom segments of the inner perianth.

  15. Genomic architecture of adaptive color pattern divergence and convergence in Heliconius butterflies.

    PubMed

    Supple, Megan A; Hines, Heather M; Dasmahapatra, Kanchon K; Lewis, James J; Nielsen, Dahlia M; Lavoie, Christine; Ray, David A; Salazar, Camilo; McMillan, W Owen; Counterman, Brian A

    2013-08-01

    Identifying the genetic changes driving adaptive variation in natural populations is key to understanding the origins of biodiversity. The mosaic of mimetic wing patterns in Heliconius butterflies makes an excellent system for exploring adaptive variation using next-generation sequencing. In this study, we use a combination of techniques to annotate the genomic interval modulating red color pattern variation, identify a narrow region responsible for adaptive divergence and convergence in Heliconius wing color patterns, and explore the evolutionary history of these adaptive alleles. We use whole genome resequencing from four hybrid zones between divergent color pattern races of Heliconius erato and two hybrid zones of the co-mimic Heliconius melpomene to examine genetic variation across 2.2 Mb of a partial reference sequence. In the intergenic region near optix, the gene previously shown to be responsible for the complex red pattern variation in Heliconius, population genetic analyses identify a shared 65-kb region of divergence that includes several sites perfectly associated with phenotype within each species. This region likely contains multiple cis-regulatory elements that control discrete expression domains of optix. The parallel signatures of genetic differentiation in H. erato and H. melpomene support a shared genetic architecture between the two distantly related co-mimics; however, phylogenetic analysis suggests mimetic patterns in each species evolved independently. Using a combination of next-generation sequencing analyses, we have refined our understanding of the genetic architecture of wing pattern variation in Heliconius and gained important insights into the evolution of novel adaptive phenotypes in natural populations.

  16. Genomic architecture of adaptive color pattern divergence and convergence in Heliconius butterflies

    PubMed Central

    Supple, Megan A.; Hines, Heather M.; Dasmahapatra, Kanchon K.; Lewis, James J.; Nielsen, Dahlia M.; Lavoie, Christine; Ray, David A.; Salazar, Camilo; McMillan, W. Owen; Counterman, Brian A.

    2013-01-01

    Identifying the genetic changes driving adaptive variation in natural populations is key to understanding the origins of biodiversity. The mosaic of mimetic wing patterns in Heliconius butterflies makes an excellent system for exploring adaptive variation using next-generation sequencing. In this study, we use a combination of techniques to annotate the genomic interval modulating red color pattern variation, identify a narrow region responsible for adaptive divergence and convergence in Heliconius wing color patterns, and explore the evolutionary history of these adaptive alleles. We use whole genome resequencing from four hybrid zones between divergent color pattern races of Heliconius erato and two hybrid zones of the co-mimic Heliconius melpomene to examine genetic variation across 2.2 Mb of a partial reference sequence. In the intergenic region near optix, the gene previously shown to be responsible for the complex red pattern variation in Heliconius, population genetic analyses identify a shared 65-kb region of divergence that includes several sites perfectly associated with phenotype within each species. This region likely contains multiple cis-regulatory elements that control discrete expression domains of optix. The parallel signatures of genetic differentiation in H. erato and H. melpomene support a shared genetic architecture between the two distantly related co-mimics; however, phylogenetic analysis suggests mimetic patterns in each species evolved independently. Using a combination of next-generation sequencing analyses, we have refined our understanding of the genetic architecture of wing pattern variation in Heliconius and gained important insights into the evolution of novel adaptive phenotypes in natural populations. PMID:23674305

  17. Local adaptation and matching habitat choice in female barn owls with respect to melanic coloration.

    PubMed

    Dreiss, A N; Antoniazza, S; Burri, R; Fumagalli, L; Sonnay, C; Frey, C; Goudet, J; Roulin, Alexandre

    2012-01-01

    Local adaptation is a major mechanism underlying the maintenance of phenotypic variation in spatially heterogeneous environments. In the barn owl (Tyto alba), dark and pale reddish-pheomelanic individuals are adapted to conditions prevailing in northern and southern Europe, respectively. Using a long-term dataset from Central Europe, we report results consistent with the hypothesis that the different pheomelanic phenotypes are adapted to specific local conditions in females, but not in males. Compared to whitish females, reddish females bred in sites surrounded by more arable fields and less forests. Colour-dependent habitat choice was apparently beneficial. First, whitish females produced more fledglings when breeding in wooded areas, whereas reddish females when breeding in sites with more arable fields. Second, cross-fostering experiments showed that female nestlings grew wings more rapidly when both their foster and biological mothers were of similar colour. The latter result suggests that mothers should particularly produce daughters in environments that best match their own coloration. Accordingly, whiter females produced fewer daughters in territories with more arable fields. In conclusion, females displaying alternative melanic phenotypes bred in habitats providing them with the highest fitness benefits. Although small in magnitude, matching habitat selection and local adaptation may help maintain variation in pheomelanin coloration in the barn owl. PMID:22070193

  18. Biological versus electronic adaptive coloration: how can one inform the other?

    PubMed Central

    Kreit, Eric; Mäthger, Lydia M.; Hanlon, Roger T.; Dennis, Patrick B.; Naik, Rajesh R.; Forsythe, Eric; Heikenfeld, Jason

    2013-01-01

    Adaptive reflective surfaces have been a challenge for both electronic paper (e-paper) and biological organisms. Multiple colours, contrast, polarization, reflectance, diffusivity and texture must all be controlled simultaneously without optical losses in order to fully replicate the appearance of natural surfaces and vividly communicate information. This review merges the frontiers of knowledge for both biological adaptive coloration, with a focus on cephalopods, and synthetic reflective e-paper within a consistent framework of scientific metrics. Currently, the highest performance approach for both nature and technology uses colourant transposition. Three outcomes are envisioned from this review: reflective display engineers may gain new insights from millions of years of natural selection and evolution; biologists will benefit from understanding the types of mechanisms, characterization and metrics used in synthetic reflective e-paper; all scientists will gain a clearer picture of the long-term prospects for capabilities such as adaptive concealment and signalling. PMID:23015522

  19. Adaptive color image watermarking based on the just noticeable distortion model in balanced multiwavelet domain

    NASA Astrophysics Data System (ADS)

    Zhang, Yuan; Ding, Yong

    2011-10-01

    In this paper, a novel adaptive color image watermarking scheme based on the just noticeable distortion (JND) model in balanced multiwavelet domain is proposed. The balanced multiwavelet transform can achieve orthogonality, symmetry, and high order of approximation simultaneously without requiring any input prefiltering, which makes it a good choice for image processing. According to the properties of the human visual system, a novel multiresolution JND model is proposed in balanced multiwavelet domain. This model incorporates the spatial contrast sensitivity function, the luminance adaptation effect, and the contrast masking effect via separating the sharp edge and the texture. Then, based on this model, the watermark is adaptively inserted into the most distortion tolerable locations of the luminance and chrominance components without introducing the perceivable distortions. Experimental results show that the proposed watermarking scheme is transparent and has a high robustness to various attacks such as low-pass filtering, noise attacking, JPEG and JPEG2000 compression.

  20. Do common mechanisms of adaptation mediate color discrimination and appearance? Uniform backgrounds.

    PubMed

    Hillis, James M; Brainard, David H

    2005-10-01

    Color vision is useful for detecting surface boundaries and identifying objects. Are the signals used to perform these two functions processed by common mechanisms, or has the visual system optimized its processing separately for each task? We measured the effect of mean chromaticity and luminance on color discriminability and on color appearance under well-matched stimulus conditions. In the discrimination experiments, a pedestal spot was presented in one interval and a pedestal + test in a second. Observers indicated which interval contained the test. In the appearance experiments, observers matched the appearance of test spots across a change in background. We analyzed the data using a variant of Fechner's proposal, that the rate of apparent stimulus change is proportional to visual sensitivity. We found that saturating visual response functions together with a model of adaptation that included multiplicative gain control and a subtractive term accounted for data from both tasks. This result suggests that effects of the contexts we studied on color appearance and discriminability are controlled by the same underlying mechanism.

  1. Directional adaptive deformable models for segmentation with application to 2D and 3D medical images

    NASA Astrophysics Data System (ADS)

    Rougon, Nicolas F.; Preteux, Francoise J.

    1993-09-01

    In this paper, we address the problem of adapting the functions controlling the material properties of 2D snakes, and show how introducing oriented smoothness constraints results in a novel class of active contour models for segmentation which extends standard isotropic inhomogeneous membrane/thin-plate stabilizers. These constraints, expressed as adaptive L2 matrix norms, are defined by two 2nd-order symmetric and positive definite tensors which are invariant with respect to rigid motions in the image plane. These tensors, equivalent to directional adaptive stretching and bending densities, are quadratic with respect to 1st- and 2nd-order derivatives of the image intensity, respectively. A representation theorem specifying their canonical form is established and a geometrical interpretation of their effects if developed. Within this framework, it is shown that, by achieving a directional control of regularization, such non-isotropic constraints consistently relate the differential properties (metric and curvature) of the deformable model with those of the underlying intensity surface, yielding a satisfying preservation of image contour characteristics.

  2. Hierarchical prediction and context adaptive coding for lossless color image compression.

    PubMed

    Kim, Seyun; Cho, Nam Ik

    2014-01-01

    This paper presents a new lossless color image compression algorithm, based on the hierarchical prediction and context-adaptive arithmetic coding. For the lossless compression of an RGB image, it is first decorrelated by a reversible color transform and then Y component is encoded by a conventional lossless grayscale image compression method. For encoding the chrominance images, we develop a hierarchical scheme that enables the use of upper, left, and lower pixels for the pixel prediction, whereas the conventional raster scan prediction methods use upper and left pixels. An appropriate context model for the prediction error is also defined and the arithmetic coding is applied to the error signal corresponding to each context. For several sets of images, it is shown that the proposed method further reduces the bit rates compared with JPEG2000 and JPEG-XR.

  3. An Adaptive Sensor Data Segments Selection Method for Wearable Health Care Services.

    PubMed

    Chen, Shih-Yeh; Lai, Chin-Feng; Hwang, Ren-Hung; Lai, Ying-Hsun; Wang, Ming-Shi

    2015-12-01

    As cloud computing and wearable devices technologies mature, relevant services have grown more and more popular in recent years. The healthcare field is one of the popular services for this technology that adopts wearable devices to sense signals of negative physiological events, and to notify users. The development and implementation of long-term healthcare monitoring that can prevent or quickly respond to the occurrence of disease and accidents present an interesting challenge for computing power and energy limits. This study proposed an adaptive sensor data segments selection method for wearable health care services, and considered the sensing frequency of the various signals from human body, as well as the data transmission among the devices. The healthcare service regulates the sensing frequency of devices by considering the overall cloud computing environment and the sensing variations of wearable health care services. The experimental results show that the proposed service can effectively transmit the sensing data and prolong the overall lifetime of health care services.

  4. Adaptation of multifractal analysis to segmentation of microcalcifications in digital mammograms

    NASA Astrophysics Data System (ADS)

    Stojić, Tomislav; Reljin, Irini; Reljin, Branimir

    2006-07-01

    A method for detecting microcalcifications in digital mammograms is proposed. After recognizing basic features of microcalcifications we introduced several modifications in multifractal analysis, obtaining an efficient method adapted to enhance only small light parts not belonging to surrounding tissue, possibly microcalcifications. Started with a mammogram image, a method creates corresponding multifractal image from which a radiologist has the freedom to change the level of segmentation in an interactive manner and to find suspicious regions, which may contain microcalcifications. Additional postprocessing, based on mathematical morphology, refines the procedure by selecting and outlining regions that contain clusters with microcalcifications. The proposed method was tested through referent mammograms from MiniMIAS database, which is available at public domain. The proposed method successfully extracted microcalcifications in all (clinically approved) cases belonging to this database.

  5. Automated segmentation of retinal pigment epithelium cells in fluorescence adaptive optics images.

    PubMed

    Rangel-Fonseca, Piero; Gómez-Vieyra, Armando; Malacara-Hernández, Daniel; Wilson, Mario C; Williams, David R; Rossi, Ethan A

    2013-12-01

    Adaptive optics (AO) imaging methods allow the histological characteristics of retinal cell mosaics, such as photoreceptors and retinal pigment epithelium (RPE) cells, to be studied in vivo. The high-resolution images obtained with ophthalmic AO imaging devices are rich with information that is difficult and/or tedious to quantify using manual methods. Thus, robust, automated analysis tools that can provide reproducible quantitative information about the cellular mosaics under examination are required. Automated algorithms have been developed to detect the position of individual photoreceptor cells; however, most of these methods are not well suited for characterizing the RPE mosaic. We have developed an algorithm for RPE cell segmentation and show its performance here on simulated and real fluorescence AO images of the RPE mosaic. Algorithm performance was compared to manual cell identification and yielded better than 91% correspondence. This method can be used to segment RPE cells for morphometric analysis of the RPE mosaic and speed the analysis of both healthy and diseased RPE mosaics.

  6. An efficient and self-adapted approach to the sharpening of color images.

    PubMed

    Kau, Lih-Jen; Lee, Tien-Lin

    2013-01-01

    An efficient approach to the sharpening of color images is proposed in this paper. For this, the image to be sharpened is first transformed to the HSV color model, and then only the channel of Value will be used for the process of sharpening while the other channels are left unchanged. We then apply a proposed edge detector and low-pass filter to the channel of Value to pick out pixels around boundaries. After that, those pixels detected as around edges or boundaries are adjusted so that the boundary can be sharpened, and those nonedge pixels are kept unaltered. The increment or decrement magnitude that is to be added to those edge pixels is determined in an adaptive manner based on global statistics of the image and local statistics of the pixel to be sharpened. With the proposed approach, the discontinuities can be highlighted while most of the original information contained in the image can be retained. Finally, the adjusted channel of Value and that of Hue and Saturation will be integrated to get the sharpened color image. Extensive experiments on natural images will be given in this paper to highlight the effectiveness and efficiency of the proposed approach. PMID:24348136

  7. Adaptive Spread-Transform Dither Modulation Using a New Perceptual Model for Color Image Watermarking

    NASA Astrophysics Data System (ADS)

    Ma, Lihong; Yu, Dong; Wei, Gang; Tian, Jing; Lu, Hanqing

    Major challenges of the conventional spread-transform dither modulation (STDM) watermarking approach are two-fold: (i) it exploits a fixed watermarking strength (more particularly, the quantization index step size) to the whole cover image; and (ii) it is fairly vulnerable to the amplitude changes. To tackle the above challenges, an adaptive spread-transform dither modulation (ASTDM) approach is proposed in this paper for conducting robust color image watermarking by incorporating a new perceptual model into the conventional STDM framework. The proposed approach exploits a new perceptual model to adjust the quantization index step sizes according to the local perceptual characteristics of a cover image. Furthermore, in contrast to the conventional Watson's model is vulnerable to the amplitude changes, our proposed new perceptual model makes the luminance masking thresholds be consistent with any amplitude change, while keeping the consistence to the properties of the human visual system. In addition, certain color artifacts could be incurred during the watermark embedding procedure, since some intensity values are perceptibly changed to label the watermark. For that, a color artifact suppression algorithm is proposed by mathematically deriving an upper bound for the intensity values according to the inherent relationship between the saturation and the intensity components. Extensive experiments are conducted using 500 images selected from Corel database to demonstrate the superior performance of the proposed ASTDM approach.

  8. Adaptive Stress Response in Segmental Progeria Resembles Long-Lived Dwarfism and Calorie Restriction in Mice

    PubMed Central

    Holcomb, Valerie B; von Lindern, Marieke; Jong, Willeke M. C; Zeeuw, Chris I. De; Suh, Yousin; Hasty, Paul; Hoeijmakers, Jan H. J; van der Horst, Gijsbertus T. J; Mitchell, James R

    2006-01-01

    How congenital defects causing genome instability can result in the pleiotropic symptoms reminiscent of aging but in a segmental and accelerated fashion remains largely unknown. Most segmental progerias are associated with accelerated fibroblast senescence, suggesting that cellular senescence is a likely contributing mechanism. Contrary to expectations, neither accelerated senescence nor acute oxidative stress hypersensitivity was detected in primary fibroblast or erythroblast cultures from multiple progeroid mouse models for defects in the nucleotide excision DNA repair pathway, which share premature aging features including postnatal growth retardation, cerebellar ataxia, and death before weaning. Instead, we report a prominent phenotypic overlap with long-lived dwarfism and calorie restriction during postnatal development (2 wk of age), including reduced size, reduced body temperature, hypoglycemia, and perturbation of the growth hormone/insulin-like growth factor 1 neuroendocrine axis. These symptoms were also present at 2 wk of age in a novel progeroid nucleotide excision repair-deficient mouse model (XPDG602D/R722W/XPA−/−) that survived weaning with high penetrance. However, despite persistent cachectic dwarfism, blood glucose and serum insulin-like growth factor 1 levels returned to normal by 10 wk, with hypoglycemia reappearing near premature death at 5 mo of age. These data strongly suggest changes in energy metabolism as part of an adaptive response during the stressful period of postnatal growth. Interestingly, a similar perturbation of the postnatal growth axis was not detected in another progeroid mouse model, the double-strand DNA break repair deficient Ku80−/− mouse. Specific (but not all) types of genome instability may thus engage a conserved response to stress that evolved to cope with environmental pressures such as food shortage. PMID:17173483

  9. A region-appearance-based adaptive variational model for 3D liver segmentation

    SciTech Connect

    Peng, Jialin; Dong, Fangfang; Chen, Yunmei; Kong, Dexing

    2014-04-15

    Purpose: Liver segmentation from computed tomography images is a challenging task owing to pixel intensity overlapping, ambiguous edges, and complex backgrounds. The authors address this problem with a novel active surface scheme, which minimizes an energy functional combining both edge- and region-based information. Methods: In this semiautomatic method, the evolving surface is principally attracted to strong edges but is facilitated by the region-based information where edge information is missing. As avoiding oversegmentation is the primary challenge, the authors take into account multiple features and appearance context information. Discriminative cues, such as multilayer consecutiveness and local organ deformation are also implicitly incorporated. Case-specific intensity and appearance constraints are included to cope with the typically large appearance variations over multiple images. Spatially adaptive balancing weights are employed to handle the nonuniformity of image features. Results: Comparisons and validations on difficult cases showed that the authors’ model can effectively discriminate the liver from adhering background tissues. Boundaries weak in gradient or with no local evidence (e.g., small edge gaps or parts with similar intensity to the background) were delineated without additional user constraint. With an average surface distance of 0.9 mm and an average volume overlap of 93.9% on the MICCAI data set, the authors’ model outperformed most state-of-the-art methods. Validations on eight volumes with different initial conditions had segmentation score variances mostly less than unity. Conclusions: The proposed model can efficiently delineate ambiguous liver edges from complex tissue backgrounds with reproducibility. Quantitative validations and comparative results demonstrate the accuracy and efficacy of the model.

  10. Automated Adaptive Brightness in Wireless Capsule Endoscopy Using Image Segmentation and Sigmoid Function.

    PubMed

    Shrestha, Ravi; Mohammed, Shahed K; Hasan, Md Mehedi; Zhang, Xuechao; Wahid, Khan A

    2016-08-01

    Wireless capsule endoscopy (WCE) plays an important role in the diagnosis of gastrointestinal (GI) diseases by capturing images of human small intestine. Accurate diagnosis of endoscopic images depends heavily on the quality of captured images. Along with image and frame rate, brightness of the image is an important parameter that influences the image quality which leads to the design of an efficient illumination system. Such design involves the choice and placement of proper light source and its ability to illuminate GI surface with proper brightness. Light emitting diodes (LEDs) are normally used as sources where modulated pulses are used to control LED's brightness. In practice, instances like under- and over-illumination are very common in WCE, where the former provides dark images and the later provides bright images with high power consumption. In this paper, we propose a low-power and efficient illumination system that is based on an automated brightness algorithm. The scheme is adaptive in nature, i.e., the brightness level is controlled automatically in real-time while the images are being captured. The captured images are segmented into four equal regions and the brightness level of each region is calculated. Then an adaptive sigmoid function is used to find the optimized brightness level and accordingly a new value of duty cycle of the modulated pulse is generated to capture future images. The algorithm is fully implemented in a capsule prototype and tested with endoscopic images. Commercial capsules like Pillcam and Mirocam were also used in the experiment. The results show that the proposed algorithm works well in controlling the brightness level accordingly to the environmental condition, and as a result, good quality images are captured with an average of 40% brightness level that saves power consumption of the capsule. PMID:27333609

  11. An Automatic Assessment System of Diabetic Foot Ulcers Based on Wound Area Determination, Color Segmentation, and Healing Score Evaluation

    PubMed Central

    Wang, Lei; Pedersen, Peder C.; Strong, Diane M.; Tulu, Bengisu; Agu, Emmanuel; Ignotz, Ron; He, Qian

    2015-01-01

    Background: For individuals with type 2 diabetes, foot ulcers represent a significant health issue. The aim of this study is to design and evaluate a wound assessment system to help wound clinics assess patients with foot ulcers in a way that complements their current visual examination and manual measurements of their foot ulcers. Methods: The physical components of the system consist of an image capture box, a smartphone for wound image capture and a laptop for analyzing the wound image. The wound image assessment algorithms calculate the overall wound area, color segmented wound areas, and a healing score, to provide a quantitative assessment of the wound healing status both for a single wound image and comparisons of subsequent images to an initial wound image. Results: The system was evaluated by assessing foot ulcers for 12 patients in the Wound Clinic at University of Massachusetts Medical School. As performance measures, the Matthews correlation coefficient (MCC) value for the wound area determination algorithm tested on 32 foot ulcer images was .68. The clinical validity of our healing score algorithm relative to the experienced clinicians was measured by Krippendorff’s alpha coefficient (KAC) and ranged from .42 to .81. Conclusion: Our system provides a promising real-time method for wound assessment based on image analysis. Clinical comparisons indicate that the optimized mean-shift-based algorithm is well suited for wound area determination. Clinical evaluation of our healing score algorithm shows its potential to provide clinicians with a quantitative method for evaluating wound healing status. PMID:26253144

  12. Cerebral Arteries Extraction using Level Set Segmentation and Adaptive Tracing for CT Angiography

    SciTech Connect

    Zhang Yong; Zhou Xiaobo; Srinivasan, Ranga; Wong, Stephen T. C.; Young, Geoff

    2007-11-02

    We propose an approach for extracting cerebral arteries from partial Computed Tomography Angiography (CTA). The challenges of extracting cerebral arteries from CTA come from the fact that arteries are usually surrounded by bones and veins in the lower portion of a CTA volume. There exists strong intensity-value overlap between vessels and surrounding objects. Besides, it is inappropriate to assume the 2D cross sections of arteries are circle or ellipse, especially for abnormal vessels. The navigation of the arteries could change suddenly in the 3D space. In this paper, a method based on level set segmentation is proposed to target this challenging problem. For the lower portion of a CTA volume, we use geodesic active contour method to detect cross section of arteries in the 2D space. The medial axis of the artery is obtained by adaptively tracking along its navigation path. This is done by finding the minimal cross section from cutting the arteries under different angles in the 3D spherical space. This method is highly automated, with minimum user input of providing only the starting point and initial navigation direction of the arteries of interests.

  13. Cerebral Arteries Extraction using Level Set Segmentation and Adaptive Tracing for CT Angiography

    NASA Astrophysics Data System (ADS)

    Zhang, Yong; Young, Geoff; Zhou, Xiaobo; Srinivasan, Ranga; Wong, Stephen T. C.

    2007-11-01

    We propose an approach for extracting cerebral arteries from partial Computed Tomography Angiography (CTA). The challenges of extracting cerebral arteries from CTA come from the fact that arteries are usually surrounded by bones and veins in the lower portion of a CTA volume. There exists strong intensity-value overlap between vessels and surrounding objects. Besides, it is inappropriate to assume the 2D cross sections of arteries are circle or ellipse, especially for abnormal vessels. The navigation of the arteries could change suddenly in the 3D space. In this paper, a method based on level set segmentation is proposed to target this challenging problem. For the lower portion of a CTA volume, we use geodesic active contour method to detect cross section of arteries in the 2D space. The medial axis of the artery is obtained by adaptively tracking along its navigation path. This is done by finding the minimal cross section from cutting the arteries under different angles in the 3D spherical space. This method is highly automated, with minimum user input of providing only the starting point and initial navigation direction of the arteries of interests.

  14. An Adaptive Sensor Data Segments Selection Method for Wearable Health Care Services.

    PubMed

    Chen, Shih-Yeh; Lai, Chin-Feng; Hwang, Ren-Hung; Lai, Ying-Hsun; Wang, Ming-Shi

    2015-12-01

    As cloud computing and wearable devices technologies mature, relevant services have grown more and more popular in recent years. The healthcare field is one of the popular services for this technology that adopts wearable devices to sense signals of negative physiological events, and to notify users. The development and implementation of long-term healthcare monitoring that can prevent or quickly respond to the occurrence of disease and accidents present an interesting challenge for computing power and energy limits. This study proposed an adaptive sensor data segments selection method for wearable health care services, and considered the sensing frequency of the various signals from human body, as well as the data transmission among the devices. The healthcare service regulates the sensing frequency of devices by considering the overall cloud computing environment and the sensing variations of wearable health care services. The experimental results show that the proposed service can effectively transmit the sensing data and prolong the overall lifetime of health care services. PMID:26490152

  15. Movement Analysis of Flexion and Extension of Honeybee Abdomen Based on an Adaptive Segmented Structure

    PubMed Central

    Zhao, Jieliang; Wu, Jianing; Yan, Shaoze

    2015-01-01

    Honeybees (Apis mellifera) curl their abdomens for daily rhythmic activities. Prior to determining this fact, people have concluded that honeybees could curl their abdomen casually. However, an intriguing but less studied feature is the possible unidirectional abdominal deformation in free-flying honeybees. A high-speed video camera was used to capture the curling and to analyze the changes in the arc length of the honeybee abdomen not only in free-flying mode but also in the fixed sample. Frozen sections and environment scanning electron microscope were used to investigate the microstructure and motion principle of honeybee abdomen and to explore the physical structure restricting its curling. An adaptive segmented structure, especially the folded intersegmental membrane (FIM), plays a dominant role in the flexion and extension of the abdomen. The structural features of FIM were utilized to mimic and exhibit movement restriction on honeybee abdomen. Combining experimental analysis and theoretical demonstration, a unidirectional bending mechanism of honeybee abdomen was revealed. Through this finding, a new perspective for aerospace vehicle design can be imitated. PMID:26223946

  16. Multi-segmented piezoelectric mirrors as active/adaptive optics components.

    PubMed

    Signorato, R; Hignette, O; Goulon, J

    1998-05-01

    The angular acceptance of piezoelectric (Pzt) bimorph mirrors is limited by the maximum length of commercially available Pzt ceramic plates. To overcome this limit and manufacture longer devices, several (2n + 1) 150 mm-long bimorph Pzt stacks were assembled side-to-side. Two prototype mirrors, 450 (n = 1) and 750 (n = 2) mm long, were designed, assembled, polished and optically characterized. They are fully UHV compatible and are now installed in the monochromatic section of the ESRF beamlines ID26 and ID32. Both mirrors cover the full range of required bending radii (1 km concave-3.5 km convex). Junctions between segments do not spoil the optical surface quality. The surface slope error r.m.s. can be kept well below 1 arcsec over the full bending range. Adaptive compensation for low-frequency figure errors was shown to be easy and reliable. After compensation, residual shape errors are of the order of 40 nm r.m.s. over 700 mm. PMID:15263657

  17. Active control of adaptive optics system in a large segmented mirror telescope

    NASA Astrophysics Data System (ADS)

    Nagashima, M.; Agrawal, B. N.

    2014-02-01

    For a large adaptive optics system such as a large segmented mirror telescope (SMT), it is often difficult, although not impossible, to directly apply common multi-input multi-output (MIMO) controller design methods due to the computational burden imposed by the large dimension of the system model. In this article, a practical controller design method is proposed which significantly reduces the system dimension for a system where the dimension required to represent the dynamics of the plant is much smaller than the dimension of the full plant model. The proposed method decouples the dynamic and static parts of the plant model by a modal decomposition technique to separately design a controller for each part. Two controllers are then combined using the so-called sensitivity decoupling method so that the resulting feedback loop becomes the superposition of the two individual feedback loops of the dynamic and static parts. A MIMO controller was designed by the proposed method using the H ∞ loop-shaping technique for an SMT model to be compared with other controllers proposed in the literature. Frequency-domain analysis and time-domain simulation results show the superior performance of the proposed controller.

  18. Adaptive optics retinal imaging reveals S-cone dystrophy in tritan color-vision deficiency

    NASA Astrophysics Data System (ADS)

    Baraas, Rigmor C.; Carroll, Joseph; Gunther, Karen L.; Chung, Mina; Williams, David R.; Foster, David H.; Neitz, Maureen

    2007-05-01

    Tritan color-vision deficiency is an autosomal dominant disorder associated with mutations in the short-wavelength-sensitive- (S-) cone-pigment gene. An unexplained feature of the disorder is that individuals with the same mutation manifest different degrees of deficiency. To date, it has not been possible to examine whether any loss of S-cone function is accompanied by physical disruption in the cone mosaic. Two related tritan subjects with the same novel mutation in their S-cone-opsin gene, but different degrees of deficiency, were examined. Adaptive optics was used to obtain high-resolution retinal images, which revealed distinctly different S-cone mosaics consistent with their discrepant phenotypes. In addition, a significant disruption in the regularity of the overall cone mosaic was observed in the subject completely lacking S-cone function. These results taken together with other recent findings from molecular genetics indicate that, with rare exceptions, tritan deficiency is progressive in nature.

  19. FMRI-adaptation to highly-rendered color photographs of animals and manipulable artifacts during a classification task.

    PubMed

    Chouinard, Philippe A; Goodale, Melvyn A

    2012-02-01

    We used fMRI to identify brain areas that adapted to either animals or manipulable artifacts while participants classified highly-rendered color photographs into subcategories. Several key brain areas adapted more strongly to one class of objects compared to the other. Namely, we observed stronger adaptation for animals in the lingual gyrus bilaterally, which are known to analyze the color of objects, and in the right frontal operculum and in the anterior insular cortex bilaterally, which are known to process emotional content. In contrast, the left anterior intraparietal sulcus, which is important for configuring the hand to match the three-dimensional structure of objects during grasping, adapted more strongly to manipulable artifacts. Contrary to what a previous study has found using gray-scale photographs, we did not replicate categorical-specific adaptation in the lateral fusiform gyrus for animals and categorical-specific adaptation in the medial fusiform gyrus for manipulable artifacts. Both categories of objects adapted strongly in the fusiform gyrus without any clear preference in location along its medial-lateral axis. We think that this is because the fusiform gyrus has an important role to play in color processing and hence its responsiveness to color stimuli could be very different than its responsiveness to gray-scale photographs. Nevertheless, on the basis of what we found, we propose that the recognition and subsequent classification of animals may depend primarily on perceptual properties, such as their color, and on their emotional content whereas other factors, such as their function, may play a greater role for classifying manipulable artifacts.

  20. Adaptive Morphological Feature-Based Object Classifier for a Color Imaging System

    NASA Technical Reports Server (NTRS)

    McDowell, Mark; Gray, Elizabeth

    2009-01-01

    Utilizing a Compact Color Microscope Imaging System (CCMIS), a unique algorithm has been developed that combines human intelligence along with machine vision techniques to produce an autonomous microscope tool for biomedical, industrial, and space applications. This technique is based on an adaptive, morphological, feature-based mapping function comprising 24 mutually inclusive feature metrics that are used to determine the metrics for complex cell/objects derived from color image analysis. Some of the features include: Area (total numbers of non-background pixels inside and including the perimeter), Bounding Box (smallest rectangle that bounds and object), centerX (x-coordinate of intensity-weighted, center-of-mass of an entire object or multi-object blob), centerY (y-coordinate of intensity-weighted, center-of-mass, of an entire object or multi-object blob), Circumference (a measure of circumference that takes into account whether neighboring pixels are diagonal, which is a longer distance than horizontally or vertically joined pixels), . Elongation (measure of particle elongation given as a number between 0 and 1. If equal to 1, the particle bounding box is square. As the elongation decreases from 1, the particle becomes more elongated), . Ext_vector (extremal vector), . Major Axis (the length of a major axis of a smallest ellipse encompassing an object), . Minor Axis (the length of a minor axis of a smallest ellipse encompassing an object), . Partial (indicates if the particle extends beyond the field of view), . Perimeter Points (points that make up a particle perimeter), . Roundness [(4(pi) x area)/perimeter(squared)) the result is a measure of object roundness, or compactness, given as a value between 0 and 1. The greater the ratio, the rounder the object.], . Thin in center (determines if an object becomes thin in the center, (figure-eight-shaped), . Theta (orientation of the major axis), . Smoothness and color metrics for each component (red, green, blue

  1. Automatic Segmentation and Online virtualCT in Head-and-Neck Adaptive Radiation Therapy

    SciTech Connect

    Peroni, Marta; Ciardo, Delia; Spadea, Maria Francesca; Riboldi, Marco; Comi, Stefania; Alterio, Daniela; Baroni, Guido; Orecchia, Roberto

    2012-11-01

    Purpose: The purpose of this work was to develop and validate an efficient and automatic strategy to generate online virtual computed tomography (CT) scans for adaptive radiation therapy (ART) in head-and-neck (HN) cancer treatment. Method: We retrospectively analyzed 20 patients, treated with intensity modulated radiation therapy (IMRT), for an HN malignancy. Different anatomical structures were considered: mandible, parotid glands, and nodal gross tumor volume (nGTV). We generated 28 virtualCT scans by means of nonrigid registration of simulation computed tomography (CTsim) and cone beam CT images (CBCTs), acquired for patient setup. We validated our approach by considering the real replanning CT (CTrepl) as ground truth. We computed the Dice coefficient (DSC), center of mass (COM) distance, and root mean square error (RMSE) between correspondent points located on the automatically segmented structures on CBCT and virtualCT. Results: Residual deformation between CTrepl and CBCT was below one voxel. Median DSC was around 0.8 for mandible and parotid glands, but only 0.55 for nGTV, because of the fairly homogeneous surrounding soft tissues and of its small volume. Median COM distance and RMSE were comparable with image resolution. No significant correlation between RMSE and initial or final deformation was found. Conclusion: The analysis provides evidence that deformable image registration may contribute significantly in reducing the need of full CT-based replanning in HN radiation therapy by supporting swift and objective decision-making in clinical practice. Further work is needed to strengthen algorithm potential in nGTV localization.

  2. Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy C-Means Clustering.

    PubMed

    Elazab, Ahmed; Wang, Changmiao; Jia, Fucang; Wu, Jianhuang; Li, Guanglin; Hu, Qingmao

    2015-01-01

    An adaptively regularized kernel-based fuzzy C-means clustering framework is proposed for segmentation of brain magnetic resonance images. The framework can be in the form of three algorithms for the local average grayscale being replaced by the grayscale of the average filter, median filter, and devised weighted images, respectively. The algorithms employ the heterogeneity of grayscales in the neighborhood and exploit this measure for local contextual information and replace the standard Euclidean distance with Gaussian radial basis kernel functions. The main advantages are adaptiveness to local context, enhanced robustness to preserve image details, independence of clustering parameters, and decreased computational costs. The algorithms have been validated against both synthetic and clinical magnetic resonance images with different types and levels of noises and compared with 6 recent soft clustering algorithms. Experimental results show that the proposed algorithms are superior in preserving image details and segmentation accuracy while maintaining a low computational complexity. PMID:26793269

  3. Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy C-Means Clustering.

    PubMed

    Elazab, Ahmed; Wang, Changmiao; Jia, Fucang; Wu, Jianhuang; Li, Guanglin; Hu, Qingmao

    2015-01-01

    An adaptively regularized kernel-based fuzzy C-means clustering framework is proposed for segmentation of brain magnetic resonance images. The framework can be in the form of three algorithms for the local average grayscale being replaced by the grayscale of the average filter, median filter, and devised weighted images, respectively. The algorithms employ the heterogeneity of grayscales in the neighborhood and exploit this measure for local contextual information and replace the standard Euclidean distance with Gaussian radial basis kernel functions. The main advantages are adaptiveness to local context, enhanced robustness to preserve image details, independence of clustering parameters, and decreased computational costs. The algorithms have been validated against both synthetic and clinical magnetic resonance images with different types and levels of noises and compared with 6 recent soft clustering algorithms. Experimental results show that the proposed algorithms are superior in preserving image details and segmentation accuracy while maintaining a low computational complexity.

  4. Adaptive segmentation of nuclei in H&S stained tendon microscopy

    NASA Astrophysics Data System (ADS)

    Chuang, Bo-I.; Wu, Po-Ting; Hsu, Jian-Han; Jou, I.-Ming; Su, Fong-Chin; Sun, Yung-Nien

    2015-12-01

    Tendiopathy is a popular clinical issue in recent years. In most cases like trigger finger or tennis elbow, the pathology change can be observed under H and E stained tendon microscopy. However, the qualitative analysis is too subjective and thus the results heavily depend on the observers. We develop an automatic segmentation procedure which segments and counts the nuclei in H and E stained tendon microscopy fast and precisely. This procedure first determines the complexity of images and then segments the nuclei from the image. For the complex images, the proposed method adopts sampling-based thresholding to segment the nuclei. While for the simple images, the Laplacian-based thresholding is employed to re-segment the nuclei more accurately. In the experiments, the proposed method is compared with the experts outlined results. The nuclei number of proposed method is closed to the experts counted, and the processing time of proposed method is much faster than the experts'.

  5. Optree: a learning-based adaptive watershed algorithm for neuron segmentation.

    PubMed

    Uzunbaş, Mustafa Gökhan; Chen, Chao; Metaxas, Dimitris

    2014-01-01

    We present a new algorithm for automatic and interactive segmentation of neuron structures from electron microscopy (EM) images. Our method selects a collection of nodes from the watershed mergng tree as the proposed segmentation. This is achieved by building a onditional random field (CRF) whose underlying graph is the merging tree. The maximum a posteriori (MAP) prediction of the CRF is the output segmentation. Our algorithm outperforms state-of-the-art methods. Both the inference and the training are very efficient as the graph is tree-structured. Furthermore, we develop an interactive segmentation framework which selects uncertain regions for a user to proofread. The uncertainty is measured by the marginals of the graphical model. Based on user corrections, our framework modifies the merging tree and thus improves the segmentation globally. PMID:25333106

  6. Adaptive segmentation of an x-ray CT image using vector quantization

    NASA Astrophysics Data System (ADS)

    Li, Lihua; Qian, Wei; Clarke, Laurence P.

    1997-04-01

    This paper is part of a feasibility study of using an image segmentation method to automatically identify the tumor or target boundaries in each axial slice or to assist an expert physician to manually draw these boundaries.A two-stage segmentation method is proposed. In the first step, the outlying bone structure is removed from the raw CT data and the brain parenchymal area is extracted. Then a VQ-based method is applied for the segmentation of the soft tissue inside the brain area. Representative results for two sets of x-ray CT axial slice images from tow patients are presented. Problems and further modifications are discussed.

  7. Color canals modification with canny edge detection and morphological reconstruction for cell nucleus segmentation and area measurement in normal Pap smear images

    NASA Astrophysics Data System (ADS)

    Riana, Dwiza; Dewi, Dyah Ekashanti Octorina; Widyantoro, Dwi H.; Mengko, Tati Latifah R.

    2014-03-01

    This paper presents a cell nucleus segmentation and area measurement of Pap smear images by means of modification of color canals with Canny edge detection and morphological reconstruction methods. Cell nucleus characterization plays an important role for classifying the degree of abnormality in cervical cancer. The aim of this work is to find the matched measurement method with the manual nucleus area measurement. In this work, we utilized pap smear single cell images from Herlev data bank in RGB mode. The cell images were selected from 90 normal class subjects that include: Normal Superficial, Normal Intermediate, and Normal Columnar classes. The nucleus of each cell image was cropped manually to localize from the cytoplasm. The color canals modification was performed on each cropped nucleus image by, first, separating each R, G, B, and grayscale canals, then implementing addition operation based on color canals (R+G+B, R+G, R+B, G+B, and grayscale). The Canny edge detection was applied on those modifications resulting in binary edge images. The nucleus segmentation was implemented on the edge images by performing region filling based on morphological reconstruction. The area property was calculated based on the segmented nucleus area. The nucleus area from the proposed method was verified to the existing manual measurement (ground truth) of the Herlev data bank. Based on thorough observation upon the selected color canals and Canny edge detection. It can be concluded that Canny edge detection with R+G+B canal is the most significant for all Normal classes (r 0,305, p-value 0.05). While for Normal Superficial and Normal Intermediate, Canny edge detection is significant for all RGB modifications with (r 0.414 - 0.817 range, , p-value 0.05), and for Normal Columnar, Canny edge detection is significant for R+B canal (r 0.505, p-value 0.05).

  8. Comparative analysis of different adaptive filters for tracking lower segments of a human body using inertial motion sensors

    NASA Astrophysics Data System (ADS)

    Öhberg, Fredrik; Lundström, Ronnie; Grip, Helena

    2013-08-01

    For all segments and tests, a modified Kalman filter and a quasi-static sensor fusion algorithm were equally accurate (precision and accuracy ˜2-3°) compared to normalized least mean squares filtering, recursive least-squares filtering and standard Kalman filtering. The aims were to: (1) compare adaptive filtering techniques used for sensor fusion and (2) evaluate the precision and accuracy for a chosen adaptive filter. Motion sensors (based on inertial measurement units) are limited by accumulative integration errors arising from sensor bias. This drift can partly be handled with adaptive filtering techniques. To advance the measurement technique in this area, a new modified Kalman filter is developed. Differences in accuracy were observed during different tests especially drift in the internal/external rotation angle. This drift can be minimized if the sensors include magnetometers.

  9. Spatially adapted augmentation of age-specific atlas-based segmentation using patch-based priors

    NASA Astrophysics Data System (ADS)

    Liu, Mengyuan; Seshamani, Sharmishtaa; Harrylock, Lisa; Kitsch, Averi; Miller, Steven; Chau, Van; Poskitt, Kenneth; Rousseau, Francois; Studholme, Colin

    2014-03-01

    One of the most common approaches to MRI brain tissue segmentation is to employ an atlas prior to initialize an Expectation- Maximization (EM) image labeling scheme using a statistical model of MRI intensities. This prior is commonly derived from a set of manually segmented training data from the population of interest. However, in cases where subject anatomy varies significantly from the prior anatomical average model (for example in the case where extreme developmental abnormalities or brain injuries occur), the prior tissue map does not provide adequate information about the observed MRI intensities to ensure the EM algorithm converges to an anatomically accurate labeling of the MRI. In this paper, we present a novel approach for automatic segmentation of such cases. This approach augments the atlas-based EM segmentation by exploring methods to build a hybrid tissue segmentation scheme that seeks to learn where an atlas prior fails (due to inadequate representation of anatomical variation in the statistical atlas) and utilize an alternative prior derived from a patch driven search of the atlas data. We describe a framework for incorporating this patch-based augmentation of EM (PBAEM) into a 4D age-specific atlas-based segmentation of developing brain anatomy. The proposed approach was evaluated on a set of MRI brain scans of premature neonates with ages ranging from 27.29 to 46.43 gestational weeks (GWs). Results indicated superior performance compared to the conventional atlas-based segmentation method, providing improved segmentation accuracy for gray matter, white matter, ventricles and sulcal CSF regions.

  10. An adaptive approach to centerline extraction for CT colonography using MAP-EM segmentation and distance field

    NASA Astrophysics Data System (ADS)

    Peng, Hao; Li, Lihong C.; Wang, Huafeng; Han, Hao; Pickhardt, Perry J.; Liang, Zhengrong

    2014-03-01

    In this paper, we present an adaptive approach for fully automatic centerline extraction and small intestine removal based on partial volume (PV) image segmentation and distance field modeling. Computed tomographic colonography (CTC) volume image is first segmented for the colon wall mucosa layer, which represents the PV effect around the colon wall. Then centerline extraction is performed in the presence of colon collapse and small intestine touch by the use of distance field within the segmented PV mucosa layer, where centerline breakings due to collapse are recovered and centerline branches due to small intestine tough are removed. Experimental results from 24 patient CTC scans with small intestine touch rendered 100% removal of the touch, while only 16 out of the 24 could be done by the well-known isolated component method. Our voxel-by-voxel marking strategy in the automated procedure preserves the topology and validity of the colon structure. The marked inner and outer boundaries on cleansed colon are very close to those labeled by the experts. Experimental results demonstrated the robustness and efficiency of the presented adaptive approach for CTC utility.

  11. Adaptive shell color plasticity during the early ontogeny of an intertidal keystone snail.

    PubMed

    Manríquez, Patricio H; Lagos, Nelson A; Jara, María Elisa; Castilla, Juan Carlos

    2009-09-22

    We report a mechanism of crypsis present during the vulnerable early post-metamorphic ontogeny (95%) of specimens bearing patterns of shell coloration (dark or light colored) that matched the background coloration provided by patches of Concholepas' most abundant prey (mussels or barnacles respectively). The variation in shell color was positively associated with the color of the most common prey (r = 0.99). In laboratory experiments, shell coloration of C. concholepas depended on the prey-substrate used to induce metamorphosis and for the post-metamorphic rearing. The snail shell color matched the color of the prey offered during rearing. Laboratory manipulation experiments, switching the prey during rearing, showed a corresponding change in snail shell color along the outermost shell edge. As individuals grew and became increasingly indistinguishable from the surrounding background, cryptic individuals had higher survival (71%) than the non cryptic ones (4%) when they were reared in the presence of the predatory crab Acanthocyclus hassleri. These results suggest that the evolution of shell color plasticity during the early ontogeny of C. concholepas, depends on the color of the more abundant of the consumed prey available in the natural habitat where settlement has taken place; this in turn has important consequences for their fitness and survivorship in the presence of visual predators.

  12. Adaptive evolution of cone opsin genes in two colorful cyprinids, Opsariichthys pachycephalus and Candidia barbatus.

    PubMed

    Wang, Feng Yu; Chung, Wen Sung; Yan, Hong Young; Tzeng, Chyng Shyan

    2008-07-01

    Opsariichthys pachycephalus and Candidia barbatus are two phylogenetically related freshwater cyprinids that both exhibit colorful, yet quite different nuptial coloration. This study was designed to test the hypothesis that differences in nuptial coloration between two species could reflect differences in color perception ability and the opsin genes that coded for it. Genes encoding the visual pigments of these two species were cloned and sequenced, lambda(max) of cone photoreceptors and the reflectance spectra of their body coloration were measured to test the hypothesis. The 14-nm spectral shift between green-light-sensitive photoreceptors of these two cyprinids is found to correlate well with differences in their reflective spectra. The spectral shift could result from differential expression of opsin genes and the interactive effects of the amino acid replacements in various minor sites. These results support our hypothesis that nuptial coloration is tied to color perception ability and opsin genes.

  13. Multiple-Site Hemodynamic Analysis of Doppler Ultrasound with an Adaptive Color Relation Classifier for Arteriovenous Access Occlusion Evaluation

    PubMed Central

    Wu, Jian-Xing; Du, Yi-Chun; Wu, Ming-Jui; Li, Chien-Ming; Lin, Chia-Hung; Chen, Tainsong

    2014-01-01

    This study proposes multiple-site hemodynamic analysis of Doppler ultrasound with an adaptive color relation classifier for arteriovenous access occlusion evaluation in routine examinations. The hemodynamic analysis is used to express the properties of blood flow through a vital access or a tube, using dimensionless numbers. An acoustic measurement is carried out to detect the peak-systolic and peak-diastolic velocities of blood flow from the arterial anastomosis sites (A) to the venous anastomosis sites (V). The ratio of the supracritical Reynolds (Resupra) number and the resistive (Res) index quantitates the degrees of stenosis (DOS) at multiple measurement sites. Then, an adaptive color relation classifier is designed as a nonlinear estimate model to survey the occlusion level in monthly examinations. For 30 long-term follow-up patients, the experimental results show the proposed screening model efficiently evaluates access occlusion. PMID:24892039

  14. SU-E-J-208: Fast and Accurate Auto-Segmentation of Abdominal Organs at Risk for Online Adaptive Radiotherapy

    SciTech Connect

    Gupta, V; Wang, Y; Romero, A; Heijmen, B; Hoogeman, M; Myronenko, A; Jordan, P

    2014-06-01

    Purpose: Various studies have demonstrated that online adaptive radiotherapy by real-time re-optimization of the treatment plan can improve organs-at-risk (OARs) sparing in the abdominal region. Its clinical implementation, however, requires fast and accurate auto-segmentation of OARs in CT scans acquired just before each treatment fraction. Autosegmentation is particularly challenging in the abdominal region due to the frequently observed large deformations. We present a clinical validation of a new auto-segmentation method that uses fully automated non-rigid registration for propagating abdominal OAR contours from planning to daily treatment CT scans. Methods: OARs were manually contoured by an expert panel to obtain ground truth contours for repeat CT scans (3 per patient) of 10 patients. For the non-rigid alignment, we used a new non-rigid registration method that estimates the deformation field by optimizing local normalized correlation coefficient with smoothness regularization. This field was used to propagate planning contours to repeat CTs. To quantify the performance of the auto-segmentation, we compared the propagated and ground truth contours using two widely used metrics- Dice coefficient (Dc) and Hausdorff distance (Hd). The proposed method was benchmarked against translation and rigid alignment based auto-segmentation. Results: For all organs, the auto-segmentation performed better than the baseline (translation) with an average processing time of 15 s per fraction CT. The overall improvements ranged from 2% (heart) to 32% (pancreas) in Dc, and 27% (heart) to 62% (spinal cord) in Hd. For liver, kidneys, gall bladder, stomach, spinal cord and heart, Dc above 0.85 was achieved. Duodenum and pancreas were the most challenging organs with both showing relatively larger spreads and medians of 0.79 and 2.1 mm for Dc and Hd, respectively. Conclusion: Based on the achieved accuracy and computational time we conclude that the investigated auto-segmentation

  15. The genetic basis of color-related local adaptation in a ring-like colonization around the Mediterranean.

    PubMed

    Burri, Reto; Antoniazza, Sylvain; Gaigher, Arnaud; Ducrest, Anne-Lyse; Simon, Céline; Fumagalli, Luca; Goudet, Jérôme; Roulin, Alexandre

    2016-01-01

    Uncovering the genetic basis of phenotypic variation and the population history under which it established is key to understand the trajectories along which local adaptation evolves. Here, we investigated the genetic basis and evolutionary history of a clinal plumage color polymorphism in European barn owls (Tyto alba). Our results suggest that barn owls colonized the Western Palearctic in a ring-like manner around the Mediterranean and meet in secondary contact in Greece. Rufous coloration appears to be linked to a recently evolved nonsynonymous-derived variant of the melanocortin 1 receptor (MC1R) gene, which according to quantitative genetic analyses evolved under local adaptation during or following the colonization of Central Europe. Admixture patterns and linkage disequilibrium between the neutral genetic background and color found exclusively within the secondary contact zone suggest limited introgression at secondary contact. These results from a system reminiscent of ring species provide a striking example of how local adaptation can evolve from derived genetic variation. PMID:26773815

  16. An adaptive image segmentation process for the classification of lung biopsy images

    NASA Astrophysics Data System (ADS)

    McKee, Daniel W.; Land, Walker H., Jr.; Zhukov, Tatyana; Song, Dansheng; Qian, Wei

    2006-03-01

    The purpose of this study was to develop a computer-based second opinion diagnostic tool that could read microscope images of lung tissue and classify the tissue sample as normal or cancerous. This problem can be broken down into three areas: segmentation, feature extraction and measurement, and classification. We introduce a kernel-based extension of fuzzy c-means to provide a coarse initial segmentation, with heuristically-based mechanisms to improve the accuracy of the segmentation. The segmented image is then processed to extract and quantify features. Finally, the measured features are used by a Support Vector Machine (SVM) to classify the tissue sample. The performance of this approach was tested using a database of 85 images collected at the Moffitt Cancer Center and Research Institute. These images represent a wide variety of normal lung tissue samples, as well as multiple types of lung cancer. When used with a subset of the data containing images from the normal and adenocarcinoma classes, we were able to correctly classify 78% of the images, with a ROC A Z of 0.758.

  17. Adaptive color polymorphism and unusually high local genetic diversity in the side-blotched lizard, Uta stansburiana.

    PubMed

    Micheletti, Steven; Parra, Eliseo; Routman, Eric J

    2012-01-01

    Recently, studies of adaptive color variation have become popular as models for examining the genetics of natural selection. We examined color pattern polymorphism and genetic variation in a population of side-blotched lizards (Uta stansburiana) that is found in habitats with both dark (lava) and light colored (granite) substrates. We conducted a limited experiment for adult phenotypic plasticity in laboratory conditions. We recorded both substrate and lizard color patterns in the field to determine whether lizards tended to match their substrate. Finally we examined genetic variation in a gene (melanocortin 1 receptor) that has been shown to affect lizard color in other species and in a presumably neutral gene (mitochondrial cytochrome b). Populations were sampled in the immediate area of the lava flows as well as from a more distant site to examine the role of population structure. Our captive Uta did not change color to match their background. We show that side-blotched lizards tend to match the substrate on which it was caught in the field and that variation in the melanocortin 1 receptor gene does not correlate well with color pattern in this population. Perhaps the most remarkable result is that this population of side-blotched lizards shows extremely high levels of variation at both genetic markers, in the sense of allele numbers, with relatively low levels of between-allele sequence variation. Genetic variation across this small region was as great or greater than that seen in samples of pelagic fish species collected worldwide. Statistical analysis of genetic variation suggests rapid population expansion may be responsible for the high levels of variation.

  18. Multi-Allelic Major Effect Genes Interact with Minor Effect QTLs to Control Adaptive Color Pattern Variation in Heliconius erato

    PubMed Central

    Papa, Riccardo; Kapan, Durrell D.; Counterman, Brian A.; Maldonado, Karla; Lindstrom, Daniel P.; Reed, Robert D.; Nijhout, H. Frederik; Hrbek, Tomas; McMillan, W. Owen

    2013-01-01

    Recent studies indicate that relatively few genomic regions are repeatedly involved in the evolution of Heliconius butterfly wing patterns. Although this work demonstrates a number of cases where homologous loci underlie both convergent and divergent wing pattern change among different Heliconius species, it is still unclear exactly how many loci underlie pattern variation across the genus. To address this question for Heliconius erato, we created fifteen independent crosses utilizing the four most distinct color pattern races and analyzed color pattern segregation across a total of 1271 F2 and backcross offspring. Additionally, we used the most variable brood, an F2 cross between H. himera and the east Ecuadorian H. erato notabilis, to perform a quantitative genetic analysis of color pattern variation and produce a detailed map of the loci likely involved in the H. erato color pattern radiation. Using AFLP and gene based markers, we show that fewer major genes than previously envisioned control the color pattern variation in H. erato. We describe for the first time the genetic architecture of H. erato wing color pattern by assessing quantitative variation in addition to traditional linkage mapping. In particular, our data suggest three genomic intervals modulate the bulk of the observed variation in color. Furthermore, we also identify several modifier loci of moderate effect size that contribute to the quantitative wing pattern variation. Our results are consistent with the two-step model for the evolution of mimetic wing patterns in Heliconius and support a growing body of empirical data demonstrating the importance of major effect loci in adaptive change. PMID:23533571

  19. Multi-allelic major effect genes interact with minor effect QTLs to control adaptive color pattern variation in Heliconius erato.

    PubMed

    Papa, Riccardo; Kapan, Durrell D; Counterman, Brian A; Maldonado, Karla; Lindstrom, Daniel P; Reed, Robert D; Nijhout, H Frederik; Hrbek, Tomas; McMillan, W Owen

    2013-01-01

    Recent studies indicate that relatively few genomic regions are repeatedly involved in the evolution of Heliconius butterfly wing patterns. Although this work demonstrates a number of cases where homologous loci underlie both convergent and divergent wing pattern change among different Heliconius species, it is still unclear exactly how many loci underlie pattern variation across the genus. To address this question for Heliconius erato, we created fifteen independent crosses utilizing the four most distinct color pattern races and analyzed color pattern segregation across a total of 1271 F2 and backcross offspring. Additionally, we used the most variable brood, an F2 cross between H. himera and the east Ecuadorian H. erato notabilis, to perform a quantitative genetic analysis of color pattern variation and produce a detailed map of the loci likely involved in the H. erato color pattern radiation. Using AFLP and gene based markers, we show that fewer major genes than previously envisioned control the color pattern variation in H. erato. We describe for the first time the genetic architecture of H. erato wing color pattern by assessing quantitative variation in addition to traditional linkage mapping. In particular, our data suggest three genomic intervals modulate the bulk of the observed variation in color. Furthermore, we also identify several modifier loci of moderate effect size that contribute to the quantitative wing pattern variation. Our results are consistent with the two-step model for the evolution of mimetic wing patterns in Heliconius and support a growing body of empirical data demonstrating the importance of major effect loci in adaptive change. PMID:23533571

  20. Adaptive Color Polymorphism and Unusually High Local Genetic Diversity in the Side-Blotched Lizard, Uta stansburiana

    PubMed Central

    Micheletti, Steven; Parra, Eliseo; Routman, Eric J.

    2012-01-01

    Recently, studies of adaptive color variation have become popular as models for examining the genetics of natural selection. We examined color pattern polymorphism and genetic variation in a population of side-blotched lizards (Uta stansburiana) that is found in habitats with both dark (lava) and light colored (granite) substrates. We conducted a limited experiment for adult phenotypic plasticity in laboratory conditions. We recorded both substrate and lizard color patterns in the field to determine whether lizards tended to match their substrate. Finally we examined genetic variation in a gene (melanocortin 1 receptor) that has been shown to affect lizard color in other species and in a presumably neutral gene (mitochondrial cytochrome b). Populations were sampled in the immediate area of the lava flows as well as from a more distant site to examine the role of population structure. Our captive Uta did not change color to match their background. We show that side-blotched lizards tend to match the substrate on which it was caught in the field and that variation in the melanocortin 1 receptor gene does not correlate well with color pattern in this population. Perhaps the most remarkable result is that this population of side-blotched lizards shows extremely high levels of variation at both genetic markers, in the sense of allele numbers, with relatively low levels of between-allele sequence variation. Genetic variation across this small region was as great or greater than that seen in samples of pelagic fish species collected worldwide. Statistical analysis of genetic variation suggests rapid population expansion may be responsible for the high levels of variation. PMID:23133520

  1. Adaptation of Pelage Color and Pigment Variations in Israeli Subterranean Blind Mole Rats, Spalax Ehrenbergi

    PubMed Central

    Singaravelan, Natarajan; Raz, Shmuel; Tzur, Shay; Belifante, Shirli; Pavlicek, Tomas; Beiles, Avigdor; Ito, Shosuke; Wakamatsu, Kazumasa; Nevo, Eviatar

    2013-01-01

    Background Concealing coloration in rodents is well established. However, only a few studies examined how soil color, pelage color, hair-melanin content, and genetics (i.e., the causal chain) synergize to configure it. This study investigates the causal chain of dorsal coloration in Israeli subterranean blind mole rats, Spalax ehrenbergi. Methods We examined pelage coloration of 128 adult animals from 11 populations belonging to four species of Spalax ehrenbergi superspecies (Spalax galili, Spalax golani, Spalax carmeli, and Spalax judaei) and the corresponding coloration of soil samples from the collection sites using a digital colorimeter. Additionally, we quantified hair-melanin contents of 67 animals using HPLC and sequenced the MC1R gene in 68 individuals from all four mole rat species. Results Due to high variability of soil colors, the correlation between soil and pelage color coordinates was weak and significant only between soil hue and pelage lightness. Multiple stepwise forward regression revealed that soil lightness was significantly associated with all pelage color variables. Pelage color lightness among the four species increased with the higher southward aridity in accordance to Gloger's rule (darker in humid habitats and lighter in arid habitats). Darker and lighter pelage colors are associated with darker basalt and terra rossa, and lighter rendzina soils, respectively. Despite soil lightness varying significantly, pelage lightness and eumelanin converged among populations living in similar soil types. Partial sequencing of the MC1R gene identified three allelic variants, two of which were predominant in northern species (S. galili and S. golani), and the third was exclusive to southern species (S. carmeli and S. judaei), which might have caused the differences found in pheomelanin/eumelanin ratio. Conclusion/Significance Darker dorsal pelage in darker basalt and terra rossa soils in the north and lighter pelage in rendzina and loess soils in the

  2. Evolution of color variation in dragon lizards: quantitative tests of the role of crypsis and local adaptation.

    PubMed

    Stuart-Fox, Devi M; Moussalli, Adnan; Johnston, Gregory R; Owens, Ian P F

    2004-07-01

    Many animal species display striking color differences with respect to geographic location, sex, and body region. Traditional adaptive explanations for such complex patterns invoke an interaction between selection for conspicuous signals and natural selection for crypsis. Although there is now a substantial body of evidence supporting the role of sexual selection for signaling functions, quantitative studies of crypsis remain comparatively rare. Here, we combine objective measures of coloration with information on predator visual sensitivities to study the role of crypsis in the evolution of color variation in an Australian lizard species complex (Ctenophorus decresii). We apply a model that allows us to quantify crypsis in terms of the visual contrast of the lizards against their natural backgrounds, as perceived by potential avian predators. We then use these quantitative estimates of crypsis to answer the following questions. Are there significant differences in crypsis/conspicuousness among populations? Are there significant differences in crypsis conspicuousness between the sexes? Are body regions "exposed" to visual predators more cryptic than "hidden" body regions? Is there evidence for local adaptation with respect to crypsis against different substrates? In general, our results confirmed that there are real differences in crypsis/conspicuousness both between populations and between sexes; that exposed body regions were significantly more cryptic than hidden ones, particularly in females; and that females, but not males, are more cryptic against their own local background than against the background of other populations [corrected]. Body regions that varied most in contrast between the sexes and between populations were also most conspicuous and are emphasized by males during social and sexual signaling. However, results varied with respect to the aspect of coloration studied. Results based on chromatic contrast ("hue" of color) provided better support for

  3. Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm.

    PubMed

    Onoma, D P; Ruan, S; Thureau, S; Nkhali, L; Modzelewski, R; Monnehan, G A; Vera, P; Gardin, I

    2014-12-01

    A segmentation algorithm based on the random walk (RW) method, called 3D-LARW, has been developed to delineate small tumors or tumors with a heterogeneous distribution of FDG on PET images. Based on the original algorithm of RW [1], we propose an improved approach using new parameters depending on the Euclidean distance between two adjacent voxels instead of a fixed one and integrating probability densities of labels into the system of linear equations used in the RW. These improvements were evaluated and compared with the original RW method, a thresholding with a fixed value (40% of the maximum in the lesion), an adaptive thresholding algorithm on uniform spheres filled with FDG and FLAB method, on simulated heterogeneous spheres and on clinical data (14 patients). On these three different data, 3D-LARW has shown better segmentation results than the original RW algorithm and the three other methods. As expected, these improvements are more pronounced for the segmentation of small or tumors having heterogeneous FDG uptake.

  4. Intra-patient semi-automated segmentation of the cervix-uterus in CT-images for adaptive radiotherapy of cervical cancer.

    PubMed

    Bondar, M Luiza; Hoogeman, Mischa; Schillemans, Wilco; Heijmen, Ben

    2013-08-01

    For online adaptive radiotherapy of cervical cancer, fast and accurate image segmentation is required to facilitate daily treatment adaptation. Our aim was twofold: (1) to test and compare three intra-patient automated segmentation methods for the cervix-uterus structure in CT-images and (2) to improve the segmentation accuracy by including prior knowledge on the daily bladder volume or on the daily coordinates of implanted fiducial markers. The tested methods were: shape deformation (SD) and atlas-based segmentation (ABAS) using two non-rigid registration methods: demons and a hierarchical algorithm. Tests on 102 CT-scans of 13 patients demonstrated that the segmentation accuracy significantly increased by including the bladder volume predicted with a simple 1D model based on a manually defined bladder top. Moreover, manually identified implanted fiducial markers significantly improved the accuracy of the SD method. For patients with large cervix-uterus volume regression, the use of CT-data acquired toward the end of the treatment was required to improve segmentation accuracy. Including prior knowledge, the segmentation results of SD (Dice similarity coefficient 85 ± 6%, error margin 2.2 ± 2.3 mm, average time around 1 min) and of ABAS using hierarchical non-rigid registration (Dice 82 ± 10%, error margin 3.1 ± 2.3 mm, average time around 30 s) support their use for image guided online adaptive radiotherapy of cervical cancer.

  5. Intra-patient semi-automated segmentation of the cervix-uterus in CT-images for adaptive radiotherapy of cervical cancer

    NASA Astrophysics Data System (ADS)

    Luiza Bondar, M.; Hoogeman, Mischa; Schillemans, Wilco; Heijmen, Ben

    2013-08-01

    For online adaptive radiotherapy of cervical cancer, fast and accurate image segmentation is required to facilitate daily treatment adaptation. Our aim was twofold: (1) to test and compare three intra-patient automated segmentation methods for the cervix-uterus structure in CT-images and (2) to improve the segmentation accuracy by including prior knowledge on the daily bladder volume or on the daily coordinates of implanted fiducial markers. The tested methods were: shape deformation (SD) and atlas-based segmentation (ABAS) using two non-rigid registration methods: demons and a hierarchical algorithm. Tests on 102 CT-scans of 13 patients demonstrated that the segmentation accuracy significantly increased by including the bladder volume predicted with a simple 1D model based on a manually defined bladder top. Moreover, manually identified implanted fiducial markers significantly improved the accuracy of the SD method. For patients with large cervix-uterus volume regression, the use of CT-data acquired toward the end of the treatment was required to improve segmentation accuracy. Including prior knowledge, the segmentation results of SD (Dice similarity coefficient 85 ± 6%, error margin 2.2 ± 2.3 mm, average time around 1 min) and of ABAS using hierarchical non-rigid registration (Dice 82 ± 10%, error margin 3.1 ± 2.3 mm, average time around 30 s) support their use for image guided online adaptive radiotherapy of cervical cancer.

  6. Signatures of functional constraint at aye-aye opsin genes: the potential of adaptive color vision in a nocturnal primate.

    PubMed

    Perry, George H; Martin, Robert D; Verrelli, Brian C

    2007-09-01

    While color vision perception is thought to be adaptively correlated with foraging efficiency for diurnal mammals, those that forage exclusively at night may not need color vision nor have the capacity for it. Indeed, although the basic condition for mammals is dichromacy, diverse nocturnal mammals have only monochromatic vision, resulting from functional loss of the short-wavelength sensitive opsin gene. However, many nocturnal primates maintain intact two opsin genes and thus have dichromatic capacity. The evolutionary significance of this surprising observation has not yet been elucidated. We used a molecular population genetics approach to test evolutionary hypotheses for the two intact opsin genes of the fully nocturnal aye-aye (Daubentonia madagascariensis), a highly unusual and endangered Madagascar primate. No evidence of gene degradation in either opsin gene was observed for any of 8 aye-aye individuals examined. Furthermore, levels of nucleotide diversity for opsin gene functional sites were lower than those for 15 neutrally evolving intergenic regions (>25 kb in total), which is consistent with a history of purifying selection on aye-aye opsin genes. The most likely explanation for these findings is that dichromacy is advantageous for aye-ayes despite their nocturnal activity pattern. We speculate that dichromatic nocturnal primates may be able to perceive color while foraging under moonlight conditions, and suggest that behavioral and ecological comparisons among dichromatic and monochromatic nocturnal primates will help to elucidate the specific activities for which color vision perception is advantageous.

  7. SU-C-9A-01: Parameter Optimization in Adaptive Region-Growing for Tumor Segmentation in PET

    SciTech Connect

    Tan, S; Xue, M; Chen, W; D'Souza, W; Lu, W; Li, H

    2014-06-01

    Purpose: To design a reliable method to determine the optimal parameter in the adaptive region-growing (ARG) algorithm for tumor segmentation in PET. Methods: The ARG uses an adaptive similarity criterion m - fσ ≤ I-PET ≤ m + fσ, so that a neighboring voxel is appended to the region based on its similarity to the current region. When increasing the relaxing factor f (f ≥ 0), the resulting volumes monotonically increased with a sharp increase when the region just grew into the background. The optimal f that separates the tumor from the background is defined as the first point with the local maximum curvature on an Error function fitted to the f-volume curve. The ARG was tested on a tumor segmentation Benchmark that includes ten lung cancer patients with 3D pathologic tumor volume as ground truth. For comparison, the widely used 42% and 50% SUVmax thresholding, Otsu optimal thresholding, Active Contours (AC), Geodesic Active Contours (GAC), and Graph Cuts (GC) methods were tested. The dice similarity index (DSI), volume error (VE), and maximum axis length error (MALE) were calculated to evaluate the segmentation accuracy. Results: The ARG provided the highest accuracy among all tested methods. Specifically, the ARG has an average DSI, VE, and MALE of 0.71, 0.29, and 0.16, respectively, better than the absolute 42% thresholding (DSI=0.67, VE= 0.57, and MALE=0.23), the relative 42% thresholding (DSI=0.62, VE= 0.41, and MALE=0.23), the absolute 50% thresholding (DSI=0.62, VE=0.48, and MALE=0.21), the relative 50% thresholding (DSI=0.48, VE=0.54, and MALE=0.26), OTSU (DSI=0.44, VE=0.63, and MALE=0.30), AC (DSI=0.46, VE= 0.85, and MALE=0.47), GAC (DSI=0.40, VE= 0.85, and MALE=0.46) and GC (DSI=0.66, VE= 0.54, and MALE=0.21) methods. Conclusions: The results suggest that the proposed method reliably identified the optimal relaxing factor in ARG for tumor segmentation in PET. This work was supported in part by National Cancer Institute Grant R01 CA172638; The

  8. Overlapping cell nuclei segmentation using a spatially adaptive active physical model.

    PubMed

    Plissiti, Marina E; Nikou, Christophoros

    2012-11-01

    A method for the segmentation of overlapping nuclei is presented, which combines local characteristics of the nuclei boundary and a priori knowledge about the expected shape of the nuclei. A deformable model whose behavior is driven by physical principles is trained on images containing a single nuclei, and attributes of the shapes of the nuclei are expressed in terms of modal analysis. Based on the estimated modal distribution and driven by the image characteristics, we develop a framework to detect and describe the unknown nuclei boundaries in images containing two overlapping nuclei. The problem of the estimation of an accurate nucleus boundary in the overlapping areas is successfully addressed with the use of appropriate weight parameters that control the contribution of the image force in the total energy of the deformable model. The proposed method was evaluated using 152 images of conventional Pap smears, each containing two overlapping nuclei. Comparisons with other segmentation methods indicate that our method produces more accurate nuclei boundaries which are closer to the ground truth.

  9. Patient-specific organ dose estimation during transcatheter arterial embolization using Monte Carlo method and adaptive organ segmentation

    NASA Astrophysics Data System (ADS)

    Tsai, Hui-Yu; Lin, Yung-Chieh; Tyan, Yeu-Sheng

    2014-11-01

    The purpose of this study was to evaluate organ doses for individual patients undergoing interventional transcatheter arterial embolization (TAE) for hepatocellular carcinoma (HCC) using measurement-based Monte Carlo simulation and adaptive organ segmentation. Five patients were enrolled in this study after institutional ethical approval and informed consent. Gafchromic XR-RV3 films were used to measure entrance surface dose to reconstruct the nonuniform fluence distribution field as the input data in the Monte Carlo simulation. XR-RV3 films were used to measure entrance surface doses due to their lower energy dependence compared with that of XR-RV2 films. To calculate organ doses, each patient's three-dimensional dose distribution was incorporated into CT DICOM images with image segmentation using thresholding and k-means clustering. Organ doses for all patients were estimated. Our dose evaluation system not only evaluated entrance surface doses based on measurements, but also evaluated the 3D dose distribution within patients using simulations. When film measurements were unavailable, the peak skin dose (between 0.68 and 0.82 of a fraction of the cumulative dose) can be calculated from the cumulative dose obtained from TAE dose reports. Successful implementation of this dose evaluation system will aid radiologists and technologists in determining the actual dose distributions within patients undergoing TAE.

  10. Adaptive radiation of gobies in the interstitial habitats of gravel beaches accompanied by body elongation and excessive vertebral segmentation

    PubMed Central

    Yamada, Tomohiko; Sugiyama, Tomoshige; Tamaki, Nana; Kawakita, Atsushi; Kato, Makoto

    2009-01-01

    Background The seacoasts of the Japanese Arc are fringed by many gravel beaches owing to active tectonic uplift and intense denudation caused by heavy rainfall. These gravel beaches are inhabited by gobies of the genus Luciogobius that burrow into the gravel sediment and live interstitially. Although their habitat and morphology (e. g., reduced fins, elongated, scale-less body, and highly segmented vertebral column) are highly unusual among fishes, little is known on how their morphological evolution has facilitated the colonization of interstitial habitats and promoted extensive diversification. We conducted thorough sampling of Luciogobius and related species throughout Japan, and performed molecular phylogenetic analysis to explore the patterns of morphological evolution associated with gravel beach colonization. Results An analysis of the mitochondrial cytochrome b gene suggested a remarkable diversity of previously unrecognized species. The species-level phylogeny based on six protein-coding nuclear genes clearly indicated that interstitial species cluster into two distinct clades, and that transitions from benthic or demersal habits to interstitial habits are strongly correlated with an increase in vertebral number. Colonization of gravel beach habitats is estimated to have occurred ca. 10 Ma, which coincides with the period of active orogenesis of the Japanese landmass. Different species of interstitial Luciogobius inhabit sediments with different granulometric properties, suggesting that microhabitat partitioning has been an important mechanism facilitating speciation in these fishes. Conclusion This is the first study to document the adaptation to interstitial habitats by a vertebrate. Body elongation and excessive vertebral segmentation had been the key aspects enhancing body flexibility and fishes' ability to burrow into the gravel sediment. The rich diversity of coastal gravel habitats of the Japanese Arc has likely promoted the adaptive radiation of

  11. Personalized articulated atlas with a dynamic adaptation strategy for bone segmentation in CT or CT/MR head and neck images

    NASA Astrophysics Data System (ADS)

    Steger, Sebastian; Jung, Florian; Wesarg, Stefan

    2014-03-01

    This paper presents a novel segmentation method for the joint segmentation of individual bones in CT- or CT/MR- head and neck images. It is based on an articulated atlas for CT images that learned the shape and appearance of the individual bones along with the articulation between them from annotated training instances. First, a novel dynamic adaptation strategy for the atlas is presented in order to increase the rate of successful adaptations. Then, if a corresponding CT image is available the atlas can be enriched with personalized information about shape, appearance and size of the individual bones from that image. Using mutual information, this personalized atlas is adapted to an MR image in order to propagate segmentations. For evaluation, a head and neck bone atlas created from 15 manually annotated training images was adapted to 58 clinically acquired head andneck CT datasets. Visual inspection showed that the automatic dynamic adaptation strategy was successful for all bones in 86% of the cases. This is a 22% improvement compared to the traditional gradient descent based approach. In leave-one-out cross validation manner the average surface distance of the correctly adapted items was found to be 0.6 8mm. In 20 cases corresponding CT/MR image pairs were available and the atlas could be personalized and adapted to the MR image. This was successful in 19 cases.

  12. Adaptive multi-level conditional random fields for detection and segmentation of small enhanced pathology in medical images.

    PubMed

    Karimaghaloo, Zahra; Arnold, Douglas L; Arbel, Tal

    2016-01-01

    Detection and segmentation of large structures in an image or within a region of interest have received great attention in the medical image processing domains. However, the problem of small pathology detection and segmentation still remains an unresolved challenge due to the small size of these pathologies, their low contrast and variable position, shape and texture. In many contexts, early detection of these pathologies is critical in diagnosis and assessing the outcome of treatment. In this paper, we propose a probabilistic Adaptive Multi-level Conditional Random Fields (AMCRF) with the incorporation of higher order cliques for detecting and segmenting such pathologies. In the first level of our graphical model, a voxel-based CRF is used to identify candidate lesions. In the second level, in order to further remove falsely detected regions, a new CRF is developed that incorporates higher order textural features, which are invariant to rotation and local intensity distortions. At this level, higher order textures are considered together with the voxel-wise cliques to refine boundaries and is therefore adaptive. The proposed algorithm is tested in the context of detecting enhancing Multiple Sclerosis (MS) lesions in brain MRI, where the problem is further complicated as many of the enhancing voxels are associated with normal structures (i.e. blood vessels) or noise in the MRI. The algorithm is trained and tested on large multi-center clinical trials from Relapsing-Remitting MS patients. The effect of several different parameter learning and inference techniques is further investigated. When tested on 120 cases, the proposed method reaches a lesion detection rate of 90%, with very few false positive lesion counts on average, ranging from 0.17 for very small (3-5 voxels) to 0 for very large (50+ voxels) regions. The proposed model is further tested on a very large clinical trial containing 2770 scans where a high sensitivity of 91% with an average false positive

  13. Influences of structural mismatch on morphology, phase transition temperature, segmental dynamics and color-transition behaviors of polydiacetylene vesicles.

    PubMed

    Pattanatornchai, Thanutpon; Charoenthai, Nipaphat; Traiphol, Rakchart

    2014-10-15

    In this contribution, we report a systematic study of polydiacetylene (PDA) vesicles fabricated by mixing two types of monomers, 10,12-tricosadiynoic acid (TCDA) and 10,12-pentacosadiynoic acid (PCDA). These diacetylene (DA) monomers constitute the same head group but different alkyl chain length, which in turn causes structural mismatch within the PDA layers. The PCDA:TCDA ratios are 100, 75, 50, 25 and 0mol%. Morphologies and properties of these PDA vesicles are explored by utilizing laser light scattering, transmission electron microscopy, differential scanning calorimetry, temperature-dependent nuclear magnetic resonance spectroscopy (NMR) and spin-lattice relaxation time (T1) measurements. An increase in DA mole ratio to 50mol% leads to significant increase in particle size. The mixed PDA vesicles also exhibit irregular shape with rather rough surface. The mismatch of alkyl side chain causes the drop of phase transition temperature. For the system of mixed poly(PCDA50:TCDA50), its transition temperature is lower than those of the pure PDAs. The NMR line shape analysis detects an abrupt change of proton signal adjacent to the PDA head group during the blue/red color-transition process. The T1 measurements also reveal different local environments of PDA alkyl side chains in the blue and red phases. The mismatch of PDA side chains causes significant drop of the color-transition temperature. PMID:25086392

  14. Influences of structural mismatch on morphology, phase transition temperature, segmental dynamics and color-transition behaviors of polydiacetylene vesicles.

    PubMed

    Pattanatornchai, Thanutpon; Charoenthai, Nipaphat; Traiphol, Rakchart

    2014-10-15

    In this contribution, we report a systematic study of polydiacetylene (PDA) vesicles fabricated by mixing two types of monomers, 10,12-tricosadiynoic acid (TCDA) and 10,12-pentacosadiynoic acid (PCDA). These diacetylene (DA) monomers constitute the same head group but different alkyl chain length, which in turn causes structural mismatch within the PDA layers. The PCDA:TCDA ratios are 100, 75, 50, 25 and 0mol%. Morphologies and properties of these PDA vesicles are explored by utilizing laser light scattering, transmission electron microscopy, differential scanning calorimetry, temperature-dependent nuclear magnetic resonance spectroscopy (NMR) and spin-lattice relaxation time (T1) measurements. An increase in DA mole ratio to 50mol% leads to significant increase in particle size. The mixed PDA vesicles also exhibit irregular shape with rather rough surface. The mismatch of alkyl side chain causes the drop of phase transition temperature. For the system of mixed poly(PCDA50:TCDA50), its transition temperature is lower than those of the pure PDAs. The NMR line shape analysis detects an abrupt change of proton signal adjacent to the PDA head group during the blue/red color-transition process. The T1 measurements also reveal different local environments of PDA alkyl side chains in the blue and red phases. The mismatch of PDA side chains causes significant drop of the color-transition temperature.

  15. Ontogenetic behavior and migration of Volga River Russian sturgeon, Acipenser gueldenstaedtii, with a note on adaptive significance of body color

    USGS Publications Warehouse

    Kynard, B.; Zhuang, P.; Zhang, L.; Zhang, T.; Zhang, Z.

    2002-01-01

    We conducted laboratory experiments with Volga River Russian sturgeon, Acipenser gueldenstaedtii, to develop a conceptual model of early behavior. We daily observed fish from day-0 (embryos, first life interval after hatching) to day-29 feeding larvae for preference of bright habitat and cover, swimming distance above the bottom, up- and downstream movement, and diel activity. Hatchling embryos initiated a downstream migration, which suggests that predation risk of embryos at spawning sites is high. Migration peaked on days 0-5 and ceased on day 7 (8-day migration). Migrants preferred bright, open habitat and early migrants swam-up far above the bottom (maximum daily median, 140 cm) in a vertical swim tube. Post-migrant embryos did not prefer bright illumination but continued to prefer white substrate, increased use of cover habitat, and swam on the bottom. Larvae initiated feeding on day 10 after 170.6 cumulative temperature degree-days. Larvae did not migrate, weakly preferred bright illumination, preferred white substrate and open habitat, and swam near the bottom (daily median 5-78 cm). The lack of a strong preference by larvae for bright illumination suggests foraging relies more on olfaction than vision for locating prey. A short migration by embryos would disperse wild sturgeon from a spawning area, but larvae did not migrate, so a second later migration by juveniles disperses young sturgeon to the sea (2-step migration). Embryo and larva body color was light tan and tail color was black. The migration, behavior, and light body color of Russian sturgeon embryos was similar to species of Acipenser and Scaphirhynchus in North America and to Acipenser in Asia that migrate after hatching as embryos. The similarity in migration style and body color among species with diverse phylogenies likely reflects convergence for common adaptations across biogeographic regions. ?? 2002 Kluwer Academic Publishers.

  16. Robust Adaptive 3-D Segmentation of Vessel Laminae From Fluorescence Confocal Microscope Images and Parallel GPU Implementation

    PubMed Central

    Narayanaswamy, Arunachalam; Dwarakapuram, Saritha; Bjornsson, Christopher S.; Cutler, Barbara M.; Shain, William

    2010-01-01

    This paper presents robust 3-D algorithms to segment vasculature that is imaged by labeling laminae, rather than the lumenal volume. The signal is weak, sparse, noisy, nonuniform, low-contrast, and exhibits gaps and spectral artifacts, so adaptive thresholding and Hessian filtering based methods are not effective. The structure deviates from a tubular geometry, so tracing algorithms are not effective. We propose a four step approach. The first step detects candidate voxels using a robust hypothesis test based on a model that assumes Poisson noise and locally planar geometry. The second step performs an adaptive region growth to extract weakly labeled and fine vessels while rejecting spectral artifacts. To enable interactive visualization and estimation of features such as statistical confidence, local curvature, local thickness, and local normal, we perform the third step. In the third step, we construct an accurate mesh representation using marching tetrahedra, volume-preserving smoothing, and adaptive decimation algorithms. To enable topological analysis and efficient validation, we describe a method to estimate vessel centerlines using a ray casting and vote accumulation algorithm which forms the final step of our algorithm. Our algorithm lends itself to parallel processing, and yielded an 8× speedup on a graphics processor (GPU). On synthetic data, our meshes had average error per face (EPF) values of (0.1–1.6) voxels per mesh face for peak signal-to-noise ratios from (110–28 dB). Separately, the error from decimating the mesh to less than 1% of its original size, the EPF was less than 1 voxel/face. When validated on real datasets, the average recall and precision values were found to be 94.66% and 94.84%, respectively. PMID:20199906

  17. Automatic adaptive parameterization in local phase feature-based bone segmentation in ultrasound.

    PubMed

    Hacihaliloglu, Ilker; Abugharbieh, Rafeef; Hodgson, Antony J; Rohling, Robert N

    2011-10-01

    Intensity-invariant local phase features based on Log-Gabor filters have been recently shown to produce highly accurate localizations of bone surfaces from three-dimensional (3-D) ultrasound. A key challenge, however, remains in the proper selection of filter parameters, whose values have so far been chosen empirically and kept fixed for a given image. Since Log-Gabor filter responses widely change when varying the filter parameters, actual parameter selection can significantly affect the quality of extracted features. This article presents a novel method for contextual parameter selection that autonomously adapts to image content. Our technique automatically selects the scale, bandwidth and orientation parameters of Log-Gabor filters for optimizing local phase symmetry. The proposed approach incorporates principle curvature computed from the Hessian matrix and directional filter banks in a phase scale-space framework. Evaluations performed on carefully designed in vitro experiments demonstrate 35% improvement in accuracy of bone surface localization compared with empirically-set parameterization results. Results from a pilot in vivo study on human subjects, scanned in the operating room, show similar improvements.

  18. Image colorization based on texture map

    NASA Astrophysics Data System (ADS)

    Liu, Shiguang; Zhang, Xiang

    2013-01-01

    Colorizing grayscale images so that the resulting image appears natural is a hard problem. Previous colorization algorithms generally use just the luminance information and ignore the rich texture information, which means that regions with the same luminance but different textures may mistakenly be assigned the same color. A novel automatic texture-map-based grayscale image colorization method is proposed. The texture map is generated with bilateral decomposition and a Gaussian high pass filter, which is further optimized using statistical adaptive gamma correction method. The segmentation of the spatial map is performed using locally weighted linear regression on its histogram in order to match the grayscale image and the source image. Within each of the spatial segmentation, a weighted color-luminance correspondence is achieved by the results of locally weighted linear regression. The luminance-color correspondence between the grayscale image and the source image can thus be used to colorize the grayscale image directly. By considering the consistency of both color information and texture information between two images, various plausible colorization results are generated using this new method.

  19. Robust crop and weed segmentation under uncontrolled outdoor illumination

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A new machine vision for weed detection was developed from RGB color model images. Processes included in the algorithm for the detection were excessive green conversion, threshold value computation by statistical analysis, adaptive image segmentation by adjusting the threshold value, median filter, ...

  20. Involvement of melanin-concentrating hormone 2 in background color adaptation of barfin flounder Verasper moseri.

    PubMed

    Mizusawa, Kanta; Kawashima, Yusuke; Sunuma, Toshikazu; Hamamoto, Akie; Kobayashi, Yuki; Kodera, Yoshio; Saito, Yumiko; Takahashi, Akiyoshi

    2015-04-01

    In teleosts, melanin-concentrating hormone (MCH) plays a key role in skin color changes. MCH is released into general circulation from the neurohypophysis, which causes pigment aggregation in the skin chromatophores. Recently, a novel MCH (MCH2) precursor gene, which is orthologous to the mammalian MCH precursor gene, has been identified in some teleosts using genomic data mining. The physiological function of MCH2 remains unclear. In the present study, we cloned the cDNA for MCH2 from barfin flounder, Verasper moseri. The putative prepro-MCH2 contains 25 amino acids of MCH2 peptide region. Liquid chromatography-electrospray ionization mass spectrometry with a high resolution mass analyzer were used for confirming the amino acid sequences of MCH1 and MCH2 peptides from the pituitary extract. In vitro synthesized MCH1 and MCH2 induced pigment aggregation in a dose-dependent manner. A mammalian cell-based assay indicated that both MCH1 and MCH2 functionally interacted with both the MCH receptor types 1 and 2. Mch1 and mch2 are exclusively expressed in the brain and pituitary. The levels of brain mch2 transcript were three times higher in the fish that were chronically acclimated to a white background than those acclimated to a black background. These results suggest that in V. moseri, MCH1 and MCH2 are involved in the response to changes in background colors, during the process of chromatophore control.

  1. Laser diode edge sensors for adaptive optics segmented arrays: Part 1--external cavity coupling and detector current

    NASA Astrophysics Data System (ADS)

    Remo, John L.

    1994-05-01

    An analytical study of laser diode (LD) operation coupled to external cavity scattering elements, which function as variably coupling reflectors (VCRs), is carried out with the purpose of determining the interrelationship between cavity coupling and intracavity optical intensity which determine the current generated at the rear facet PIN detector. If the external cavity coupling is position sensitive it can allow the relative position between the LD and the external cavity to be determined from the PIN or other detector mounted with the LD. If the LD and external cavity element are placed on opposite edges of two adjacent adaptive optics segments they can provide the basis for a self aligning position sensor; the amount of current detected at the PIN or other detector will depend on the relative displacement between the LD and external coupling element. Schematics of the edge sensors, the basic electronic configuration, and the optics of the external cavity are given. The ratio of the internal cavity intensity, Ic, to the saturation intensity, Is, is plotted as a function of the external cavity coupling. When this ratio approaches one, large-signal output is not a linear function of large-signal output. For operation well below saturation, the PIN detector current is directly related to Ic and may serve as a reliable detector.

  2. Adaptive evolution of color vision of the Comoran coelacanth (Latimeria chalumnae).

    PubMed

    Yokoyama, S; Zhang, H; Radlwimmer, F B; Blow, N S

    1999-05-25

    The coelacanth, a "living fossil," lives near the coast of the Comoros archipelago in the Indian Ocean. Living at a depth of about 200 m, the Comoran coelacanth receives only a narrow range of light, at about 480 nm. To detect the entire range of "color" at this depth, the coelacanth appears to use only two closely related paralogous RH1 and RH2 visual pigments with the optimum light sensitivities (lambdamax) at 478 nm and 485 nm, respectively. The lambdamax values are shifted about 20 nm toward blue compared with those of the corresponding orthologous pigments. Mutagenesis experiments show that each of these coadapted changes is fully explained by two amino acid replacements.

  3. Effect of chromatic adaptation on the achromatic locus: the role of contrast, luminance and background color.

    PubMed

    Werner, J S; Walraven, J

    1982-01-01

    Two superposed annular test lights of complementary spectral composition were presented as 60-90' incremental test flashes on 480' steady backgrounds. Two observers adjusted the ratio of the two test lights to maintain an achromatic appearance under conditions of adaptation that varied with respect to background luminance, chromaticity and stimulus contrast. The shift in chromaticity of the achromatic point was in the direction of the chromaticity of the background, while the magnitude of the shift increased as an increasing function of background luminance and as a decreasing function of contrast. These data confirm and extend a model of chromatic adaptation that has the following properties: (1) non-additivity of transient test and steady background fields, in the sense that the background, although physically adding to the test flash, only affects its hue by way of altering the gain of cone pathways; (2) Vos-Walraven cone spectral sensitivities; and (3) adaptation sites in the cone pathways having the same action spectra as Stiles' pi 5, pi 4 and (modified) pi 1 mechanisms, and which generate receptor-specific attenuation factors (von Kries Coefficients) according to Stiles' generalized threshold vs intensity function, zeta (x).

  4. Comparative evaluation of effects of bleaching on color stability and marginal adaptation of discolored direct and indirect composite laminate veneers under in vivo conditions

    PubMed Central

    Jain, Veena; Das, Taposh K.; Pruthi, Gunjan; Shah, Naseem; Rajendiran, Suresh

    2015-01-01

    Statement of Problem: Change in color and loss of marginal adaptation of tooth colored restorative materials is not acceptable. Bleaching is commonly used for treating discolored teeth. However, the literature is scanty regarding its effect on color and marginal adaptation of direct and indirect composite laminate veneers (CLVs) under in vivo conditions. Purpose: Purpose of the study was to determine the effect of bleaching on color change and marginal adaptation of direct and indirect CLVs over a period of time when exposed to the oral environment. Materials and Methods: For this purpose, a total of 14 subjects irrespective of age and sex indicated for CLV restorations on maxillary anterior teeth were selected following the inclusion and exclusion criteria. For each subject, indirect CLVs were fabricated and looted in the first quadrant (Group 1) and direct CLV's (Group 2), were given in the second quadrant. Color change was assessed clinically using intra-oral digital spectrophotometer and marginal adaptation was assessed on epoxy resin replica of the tooth-restoration interface under scanning electron microscope. After 6 months, the subjects underwent a home bleaching regimen for 14 days using 10% carbamide peroxide. The assessment of color change and marginal adaptation was done at 6 months after veneering (0–180 days), immediately after the bleaching regimen (0–194 days) and 3 months after the bleaching regimen (0–284 days). Results: The difference in median color change (ΔE) between the groups was tested using Wilcoxon rank sum test while the median color change with time within the groups was tested using Wilcoxon signed rank test. The difference in the rates of marginal adaptation was tested between the groups using Chi-square/Fisher's exact test. Bleaching led to statistically significant color change at cervical (CE), middle and incisal (IE) regions when direct and indirect composites were compared (P < 0.05). During intra-group comparison, direct

  5. Fully automatic segmentation of multiple sclerosis lesions in brain MR FLAIR images using adaptive mixtures method and Markov random field model.

    PubMed

    Khayati, Rasoul; Vafadust, Mansur; Towhidkhah, Farzad; Nabavi, Massood

    2008-03-01

    In this paper, an approach is proposed for fully automatic segmentation of MS lesions in fluid attenuated inversion recovery (FLAIR) Magnetic Resonance (MR) images. The proposed approach, based on a Bayesian classifier, utilizes the adaptive mixtures method (AMM) and Markov random field (MRF) model to obtain and upgrade the class conditional probability density function (CCPDF) and the a priori probability of each class. To compare the performance of the proposed approach with those of previous approaches including manual segmentation, the similarity criteria of different slices related to 20 MS patients were calculated. Also, volumetric comparison of lesions volume between the fully automated segmentation and the gold standard was performed using correlation coefficient (CC). The results showed a better performance for the proposed approach, compared to those of previous works.

  6. Adaptive evolution of color vision as seen through the eyes of butterflies.

    PubMed

    Frentiu, Francesca D; Bernard, Gary D; Cuevas, Cristina I; Sison-Mangus, Marilou P; Prudic, Kathleen L; Briscoe, Adriana D

    2007-05-15

    Butterflies and primates are interesting for comparative color vision studies, because both have evolved middle- (M) and long-wavelength- (L) sensitive photopigments with overlapping absorbance spectrum maxima (lambda(max) values). Although positive selection is important for the maintenance of spectral variation within the primate pigments, it remains an open question whether it contributes similarly to the diversification of butterfly pigments. To examine this issue, we performed epimicrospectrophotometry on the eyes of five Limenitis butterfly species and found a 31-nm range of variation in the lambda(max) values of the L-sensitive photopigments (514-545 nm). We cloned partial Limenitis L opsin gene sequences and found a significant excess of replacement substitutions relative to polymorphisms among species. Mapping of these L photopigment lambda(max) values onto a phylogeny revealed two instances within Lepidoptera of convergently evolved L photopigment lineages whose lambda(max) values were blue-shifted. A codon-based maximum-likelihood analysis indicated that, associated with the two blue spectral shifts, four amino acid sites (Ile17Met, Ala64Ser, Asn70Ser, and Ser137Ala) have evolved substitutions in parallel and exhibit significant d(N)/d(S) >1. Homology modeling of the full-length Limenitis arthemis astyanax L opsin placed all four substitutions within the chromophore-binding pocket. Strikingly, the Ser137Ala substitution is in the same position as a site that in primates is responsible for a 5- to 7-nm blue spectral shift. Our data show that some of the same amino acid sites are under positive selection in the photopigments of both butterflies and primates, spanning an evolutionary distance >500 million years.

  7. Building roof segmentation from aerial images using a lineand region-based watershed segmentation technique.

    PubMed

    El Merabet, Youssef; Meurie, Cyril; Ruichek, Yassine; Sbihi, Abderrahmane; Touahni, Raja

    2015-02-02

    In this paper, we present a novel strategy for roof segmentation from aerial images (orthophotoplans) based on the cooperation of edge- and region-based segmentation methods. The proposed strategy is composed of three major steps. The first one, called the pre-processing step, consists of simplifying the acquired image with an appropriate couple of invariant and gradient, optimized for the application, in order to limit illumination changes (shadows, brightness, etc.) affecting the images. The second step is composed of two main parallel treatments: on the one hand, the simplified image is segmented by watershed regions. Even if the first segmentation of this step provides good results in general, the image is often over-segmented. To alleviate this problem, an efficient region merging strategy adapted to the orthophotoplan particularities, with a 2D modeling of roof ridges technique, is applied. On the other hand, the simplified image is segmented by watershed lines. The third step consists of integrating both watershed segmentation strategies into a single cooperative segmentation scheme in order to achieve satisfactory segmentation results. Tests have been performed on orthophotoplans containing 100 roofs with varying complexity, and the results are evaluated with the VINETcriterion using ground-truth image segmentation. A comparison with five popular segmentation techniques of the literature demonstrates the effectiveness and the reliability of the proposed approach. Indeed, we obtain a good segmentation rate of 96% with the proposed method compared to 87.5% with statistical region merging (SRM), 84% with mean shift, 82% with color structure code (CSC), 80% with efficient graph-based segmentation algorithm (EGBIS) and 71% with JSEG.

  8. Segmentation of Planar Surfaces from Laser Scanning Data Using the Magnitude of Normal Position Vector for Adaptive Neighborhoods.

    PubMed

    Kim, Changjae; Habib, Ayman; Pyeon, Muwook; Kwon, Goo-rak; Jung, Jaehoon; Heo, Joon

    2016-01-01

    Diverse approaches to laser point segmentation have been proposed since the emergence of the laser scanning system. Most of these segmentation techniques, however, suffer from limitations such as sensitivity to the choice of seed points, lack of consideration of the spatial relationships among points, and inefficient performance. In an effort to overcome these drawbacks, this paper proposes a segmentation methodology that: (1) reduces the dimensions of the attribute space; (2) considers the attribute similarity and the proximity of the laser point simultaneously; and (3) works well with both airborne and terrestrial laser scanning data. A neighborhood definition based on the shape of the surface increases the homogeneity of the laser point attributes. The magnitude of the normal position vector is used as an attribute for reducing the dimension of the accumulator array. The experimental results demonstrate, through both qualitative and quantitative evaluations, the outcomes' high level of reliability. The proposed segmentation algorithm provided 96.89% overall correctness, 95.84% completeness, a 0.25 m overall mean value of centroid difference, and less than 1° of angle difference. The performance of the proposed approach was also verified with a large dataset and compared with other approaches. Additionally, the evaluation of the sensitivity of the thresholds was carried out. In summary, this paper proposes a robust and efficient segmentation methodology for abstraction of an enormous number of laser points into plane information. PMID:26805849

  9. Segmentation of Planar Surfaces from Laser Scanning Data Using the Magnitude of Normal Position Vector for Adaptive Neighborhoods.

    PubMed

    Kim, Changjae; Habib, Ayman; Pyeon, Muwook; Kwon, Goo-rak; Jung, Jaehoon; Heo, Joon

    2016-01-22

    Diverse approaches to laser point segmentation have been proposed since the emergence of the laser scanning system. Most of these segmentation techniques, however, suffer from limitations such as sensitivity to the choice of seed points, lack of consideration of the spatial relationships among points, and inefficient performance. In an effort to overcome these drawbacks, this paper proposes a segmentation methodology that: (1) reduces the dimensions of the attribute space; (2) considers the attribute similarity and the proximity of the laser point simultaneously; and (3) works well with both airborne and terrestrial laser scanning data. A neighborhood definition based on the shape of the surface increases the homogeneity of the laser point attributes. The magnitude of the normal position vector is used as an attribute for reducing the dimension of the accumulator array. The experimental results demonstrate, through both qualitative and quantitative evaluations, the outcomes' high level of reliability. The proposed segmentation algorithm provided 96.89% overall correctness, 95.84% completeness, a 0.25 m overall mean value of centroid difference, and less than 1° of angle difference. The performance of the proposed approach was also verified with a large dataset and compared with other approaches. Additionally, the evaluation of the sensitivity of the thresholds was carried out. In summary, this paper proposes a robust and efficient segmentation methodology for abstraction of an enormous number of laser points into plane information.

  10. Segmentation of Planar Surfaces from Laser Scanning Data Using the Magnitude of Normal Position Vector for Adaptive Neighborhoods

    PubMed Central

    Kim, Changjae; Habib, Ayman; Pyeon, Muwook; Kwon, Goo-rak; Jung, Jaehoon; Heo, Joon

    2016-01-01

    Diverse approaches to laser point segmentation have been proposed since the emergence of the laser scanning system. Most of these segmentation techniques, however, suffer from limitations such as sensitivity to the choice of seed points, lack of consideration of the spatial relationships among points, and inefficient performance. In an effort to overcome these drawbacks, this paper proposes a segmentation methodology that: (1) reduces the dimensions of the attribute space; (2) considers the attribute similarity and the proximity of the laser point simultaneously; and (3) works well with both airborne and terrestrial laser scanning data. A neighborhood definition based on the shape of the surface increases the homogeneity of the laser point attributes. The magnitude of the normal position vector is used as an attribute for reducing the dimension of the accumulator array. The experimental results demonstrate, through both qualitative and quantitative evaluations, the outcomes’ high level of reliability. The proposed segmentation algorithm provided 96.89% overall correctness, 95.84% completeness, a 0.25 m overall mean value of centroid difference, and less than 1° of angle difference. The performance of the proposed approach was also verified with a large dataset and compared with other approaches. Additionally, the evaluation of the sensitivity of the thresholds was carried out. In summary, this paper proposes a robust and efficient segmentation methodology for abstraction of an enormous number of laser points into plane information. PMID:26805849

  11. Color-Blindness Study: Color Discrimination on the TICCIT System.

    ERIC Educational Resources Information Center

    Asay, Calvin S.; Schneider, Edward W.

    The question studied whether the specific seven TICCIT system colors used within color coding schemes can be a source of confusion, or not seen at all, by the color-blind segment of target populations. Subjects were 11 color-blind and three normally sighted students at Brigham Young University. After a preliminary training exercise to acquaint the…

  12. ACTIVE-EYES: an adaptive pixel-by-pixel image-segmentation sensor architecture for high-dynamic-range hyperspectral imaging.

    PubMed

    Christensen, Marc P; Euliss, Gary W; McFadden, Michael J; Coyle, Kevin M; Milojkovic, Predrag; Haney, Michael W; van der Gracht, Joeseph; Athale, Ravindra A

    2002-10-10

    The ACTIVE-EYES (adaptive control for thermal imagers via electro-optic elements to yield an enhanced sensor) architecture, an adaptive image-segmentation and processing architecture, based on digital micromirror (DMD) array technology, is described. The concept provides efficient front-end processing of multispectral image data by adaptively segmenting and routing portions of the scene data concurrently to an imager and a spectrometer. The goal is to provide a large reduction in the amount of data required to be sensed in a multispectral imager by means of preprocessing the data to extract the most useful spatial and spectral information during detection. The DMD array provides the flexibility to perform a wide range of spatial and spectral analyses on the scene data. The spatial and spectral processing for different portions of the input scene can be tailored in real time to achieve a variety of preprocessing functions. Since the detected intensity of individual pixels may be controlled, the spatial image can be analyzed with gain varied on a pixel-by-pixel basis to enhance dynamic range. Coarse or fine spectral resolution can be achieved in the spectrometer by use of dynamically controllable or addressable dispersion elements. An experimental prototype, which demonstrated the segmentation between an imager and a grating spectrometer, was demonstrated and shown to achieve programmable pixelated intensity control. An information theoretic analysis of the dynamic-range control aspect was conducted to predict the performance enhancements that might be achieved with this architecture. The results indicate that, with a properly configured algorithm, the concept achieves the greatest relative information recovery from a detected image when the scene is made up of a relatively large area of moderate-dynamic-range pixels and a relatively smaller area of strong pixels that would tend to saturate a conventional sensor. PMID:12389978

  13. Adaptive thresholding algorithm based on SAR images and wind data to segment oil spills along the northwest coast of the Iberian Peninsula.

    PubMed

    Mera, David; Cotos, José M; Varela-Pet, José; Garcia-Pineda, Oscar

    2012-10-01

    Satellite Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillage on the ocean's surface. Several surveillance applications have been developed based on this technology. Environmental variables such as wind speed should be taken into account for better SAR image segmentation. This paper presents an adaptive thresholding algorithm for detecting oil spills based on SAR data and a wind field estimation as well as its implementation as a part of a functional prototype. The algorithm was adapted to an important shipping route off the Galician coast (northwest Iberian Peninsula) and was developed on the basis of confirmed oil spills. Image testing revealed 99.93% pixel labelling accuracy. By taking advantage of multi-core processor architecture, the prototype was optimized to get a nearly 30% improvement in processing time.

  14. Validation of various adaptive threshold methods of segmentation applied to follicular lymphoma digital images stained with 3,3’-Diaminobenzidine&Haematoxylin

    PubMed Central

    2013-01-01

    The comparative study of the results of various segmentation methods for the digital images of the follicular lymphoma cancer tissue section is described in this paper. The sensitivity and specificity and some other parameters of the following adaptive threshold methods of segmentation: the Niblack method, the Sauvola method, the White method, the Bernsen method, the Yasuda method and the Palumbo method, are calculated. Methods are applied to three types of images constructed by extraction of the brown colour information from the artificial images synthesized based on counterpart experimentally captured images. This paper presents usefulness of the microscopic image synthesis method in evaluation as well as comparison of the image processing results. The results of thoughtful analysis of broad range of adaptive threshold methods applied to: (1) the blue channel of RGB, (2) the brown colour extracted by deconvolution and (3) the ’brown component’ extracted from RGB allows to select some pairs: method and type of image for which this method is most efficient considering various criteria e.g. accuracy and precision in area detection or accuracy in number of objects detection and so on. The comparison shows that the White, the Bernsen and the Sauvola methods results are better than the results of the rest of the methods for all types of monochromatic images. All three methods segments the immunopositive nuclei with the mean accuracy of 0.9952, 0.9942 and 0.9944 respectively, when treated totally. However the best results are achieved for monochromatic image in which intensity shows brown colour map constructed by colour deconvolution algorithm. The specificity in the cases of the Bernsen and the White methods is 1 and sensitivities are: 0.74 for White and 0.91 for Bernsen methods while the Sauvola method achieves sensitivity value of 0.74 and the specificity value of 0.99. According to Bland-Altman plot the Sauvola method selected objects are segmented without

  15. Segmentation of 3D tubular objects with adaptive front propagation and minimal tree extraction for 3D medical imaging.

    PubMed

    Cohen, Laurent D; Deschamps, Thomas

    2007-08-01

    We present a new fast approach for segmentation of thin branching structures, like vascular trees, based on Fast-Marching (FM) and Level Set (LS) methods. FM allows segmentation of tubular structures by inflating a "long balloon" from a user given single point. However, when the tubular shape is rather long, the front propagation may blow up through the boundary of the desired shape close to the starting point. Our contribution is focused on a method to propagate only the useful part of the front while freezing the rest of it. We demonstrate its ability to segment quickly and accurately tubular and tree-like structures. We also develop a useful stopping criterion for the causal front propagation. We finally derive an efficient algorithm for extracting an underlying 1D skeleton of the branching objects, with minimal path techniques. Each branch being represented by its centerline, we automatically detect the bifurcations, leading to the "Minimal Tree" representation. This so-called "Minimal Tree" is very useful for visualization and quantification of the pathologies in our anatomical data sets. We illustrate our algorithms by applying it to several arteries datasets.

  16. Segmentation of 3D tubular objects with adaptive front propagation and minimal tree extraction for 3D medical imaging.

    PubMed

    Cohen, Laurent D; Deschamps, Thomas

    2007-08-01

    We present a new fast approach for segmentation of thin branching structures, like vascular trees, based on Fast-Marching (FM) and Level Set (LS) methods. FM allows segmentation of tubular structures by inflating a "long balloon" from a user given single point. However, when the tubular shape is rather long, the front propagation may blow up through the boundary of the desired shape close to the starting point. Our contribution is focused on a method to propagate only the useful part of the front while freezing the rest of it. We demonstrate its ability to segment quickly and accurately tubular and tree-like structures. We also develop a useful stopping criterion for the causal front propagation. We finally derive an efficient algorithm for extracting an underlying 1D skeleton of the branching objects, with minimal path techniques. Each branch being represented by its centerline, we automatically detect the bifurcations, leading to the "Minimal Tree" representation. This so-called "Minimal Tree" is very useful for visualization and quantification of the pathologies in our anatomical data sets. We illustrate our algorithms by applying it to several arteries datasets. PMID:17671862

  17. A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI.

    PubMed

    Iglesias, Juan Eugenio; Augustinack, Jean C; Nguyen, Khoa; Player, Christopher M; Player, Allison; Wright, Michelle; Roy, Nicole; Frosch, Matthew P; McKee, Ann C; Wald, Lawrence L; Fischl, Bruce; Van Leemput, Koen

    2015-07-15

    Automated analysis of MRI data of the subregions of the hippocampus requires computational atlases built at a higher resolution than those that are typically used in current neuroimaging studies. Here we describe the construction of a statistical atlas of the hippocampal formation at the subregion level using ultra-high resolution, ex vivo MRI. Fifteen autopsy samples were scanned at 0.13 mm isotropic resolution (on average) using customized hardware. The images were manually segmented into 13 different hippocampal substructures using a protocol specifically designed for this study; precise delineations were made possible by the extraordinary resolution of the scans. In addition to the subregions, manual annotations for neighboring structures (e.g., amygdala, cortex) were obtained from a separate dataset of in vivo, T1-weighted MRI scans of the whole brain (1mm resolution). The manual labels from the in vivo and ex vivo data were combined into a single computational atlas of the hippocampal formation with a novel atlas building algorithm based on Bayesian inference. The resulting atlas can be used to automatically segment the hippocampal subregions in structural MRI images, using an algorithm that can analyze multimodal data and adapt to variations in MRI contrast due to differences in acquisition hardware or pulse sequences. The applicability of the atlas, which we are releasing as part of FreeSurfer (version 6.0), is demonstrated with experiments on three different publicly available datasets with different types of MRI contrast. The results show that the atlas and companion segmentation method: 1) can segment T1 and T2 images, as well as their combination, 2) replicate findings on mild cognitive impairment based on high-resolution T2 data, and 3) can discriminate between Alzheimer's disease subjects and elderly controls with 88% accuracy in standard resolution (1mm) T1 data, significantly outperforming the atlas in FreeSurfer version 5.3 (86% accuracy) and

  18. A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI.

    PubMed

    Iglesias, Juan Eugenio; Augustinack, Jean C; Nguyen, Khoa; Player, Christopher M; Player, Allison; Wright, Michelle; Roy, Nicole; Frosch, Matthew P; McKee, Ann C; Wald, Lawrence L; Fischl, Bruce; Van Leemput, Koen

    2015-07-15

    Automated analysis of MRI data of the subregions of the hippocampus requires computational atlases built at a higher resolution than those that are typically used in current neuroimaging studies. Here we describe the construction of a statistical atlas of the hippocampal formation at the subregion level using ultra-high resolution, ex vivo MRI. Fifteen autopsy samples were scanned at 0.13 mm isotropic resolution (on average) using customized hardware. The images were manually segmented into 13 different hippocampal substructures using a protocol specifically designed for this study; precise delineations were made possible by the extraordinary resolution of the scans. In addition to the subregions, manual annotations for neighboring structures (e.g., amygdala, cortex) were obtained from a separate dataset of in vivo, T1-weighted MRI scans of the whole brain (1mm resolution). The manual labels from the in vivo and ex vivo data were combined into a single computational atlas of the hippocampal formation with a novel atlas building algorithm based on Bayesian inference. The resulting atlas can be used to automatically segment the hippocampal subregions in structural MRI images, using an algorithm that can analyze multimodal data and adapt to variations in MRI contrast due to differences in acquisition hardware or pulse sequences. The applicability of the atlas, which we are releasing as part of FreeSurfer (version 6.0), is demonstrated with experiments on three different publicly available datasets with different types of MRI contrast. The results show that the atlas and companion segmentation method: 1) can segment T1 and T2 images, as well as their combination, 2) replicate findings on mild cognitive impairment based on high-resolution T2 data, and 3) can discriminate between Alzheimer's disease subjects and elderly controls with 88% accuracy in standard resolution (1mm) T1 data, significantly outperforming the atlas in FreeSurfer version 5.3 (86% accuracy) and

  19. Luminance and opponent-color contributions to visual detection and adaptation and to temporal and spatial integration.

    PubMed

    King-Smith, P E; Carden, D

    1976-07-01

    We show how the processes of visual detection and of temporal and spatial summation may be analyzed in terms of parallel luminance (achromatic) and opponent-color systems; a test flash is detected if it exceeds the threshold of either system. The spectral sensitivity of the luminance system may be determined by a flicker method, and has a single broad peak near 555 nm; the spectral sensitivity of the opponent-color system corresponds to the color recognition threshold, and has three peaks at about 440, 530, and 600 nm (on a white background). The temporal and spatial integration of the opponent-color system are generally greater than for the luminance system; further, a white background selectively depresses the sensitivity of the luminance system relative to the opponent-color system. Thus relatively large (1 degree) and long (200 msec) spectral test flashes on a white background are detected by the opponent-color system except near 570 nm; the contribution of the luminance system becomes more prominent if the size or duration of the test flash is reduced, or if the white background is extinguished. The present analysis is discussed in relation to Stiles' model of independent eta mechanisms.

  20. Adaptation to recent conflict in the classical color-word Stroop-task mainly involves facilitation of processing of task-relevant information

    PubMed Central

    Purmann, Sascha; Pollmann, Stefan

    2015-01-01

    To process information selectively and to continuously fine-tune selectivity of information processing are important abilities for successful goal-directed behavior. One phenomenon thought to represent this fine-tuning are conflict adaptation effects in interference tasks, i.e., reduction of interference after an incompatible trial and when incompatible trials are frequent. The neurocognitive mechanisms of these effects are currently only partly understood and results from brainimaging studies so far are mixed. In our study we validate and extend recent findings by examining adaption to recent conflict in the classical Stroop task using functional magnetic resonance imaging. Consistent with previous research we found increased activity in a fronto-parietal network comprising the medial prefrontal cortex, ventro-lateral prefrontal cortex, and posterior parietal cortex when contrasting incompatible with compatible trials. These areas have been associated with attentional processes and might reflect increased cognitive conflict and resolution thereof during incompatible trials. While carefully controlling for non-attentional sequential effects we found smaller Stroop interference after an incompatible trial (conflict adaptation effect). These behavioral conflict adaptation effects were accompanied by changes in activity in visual color-selective areas (V4, V4α), while there was no modulation by previous trial compatibility in a visual word-selective area (VWFA). Our results provide further evidence for the notion, that adaptation to recent conflict seems to be based mainly on enhancement of processing of the task-relevant information. PMID:25784868

  1. Adaptive skin detection based on online training

    NASA Astrophysics Data System (ADS)

    Zhang, Ming; Tang, Liang; Zhou, Jie; Rong, Gang

    2007-11-01

    Skin is a widely used cue for porn image classification. Most conventional methods are off-line training schemes. They usually use a fixed boundary to segment skin regions in the images and are effective only in restricted conditions: e.g. good lightness and unique human race. This paper presents an adaptive online training scheme for skin detection which can handle these tough cases. In our approach, skin detection is considered as a classification problem on Gaussian mixture model. For each image, human face is detected and the face color is used to establish a primary estimation of skin color distribution. Then an adaptive online training algorithm is used to find the real boundary between skin color and background color in current image. Experimental results on 450 images showed that the proposed method is more robust in general situations than the conventional ones.

  2. Building Roof Segmentation from Aerial Images Using a Line-and Region-Based Watershed Segmentation Technique

    PubMed Central

    Merabet, Youssef El; Meurie, Cyril; Ruichek, Yassine; Sbihi, Abderrahmane; Touahni, Raja

    2015-01-01

    In this paper, we present a novel strategy for roof segmentation from aerial images (orthophotoplans) based on the cooperation of edge- and region-based segmentation methods. The proposed strategy is composed of three major steps. The first one, called the pre-processing step, consists of simplifying the acquired image with an appropriate couple of invariant and gradient, optimized for the application, in order to limit illumination changes (shadows, brightness, etc.) affecting the images. The second step is composed of two main parallel treatments: on the one hand, the simplified image is segmented by watershed regions. Even if the first segmentation of this step provides good results in general, the image is often over-segmented. To alleviate this problem, an efficient region merging strategy adapted to the orthophotoplan particularities, with a 2D modeling of roof ridges technique, is applied. On the other hand, the simplified image is segmented by watershed lines. The third step consists of integrating both watershed segmentation strategies into a single cooperative segmentation scheme in order to achieve satisfactory segmentation results. Tests have been performed on orthophotoplans containing 100 roofs with varying complexity, and the results are evaluated with the VINETcriterion using ground-truth image segmentation. A comparison with five popular segmentation techniques of the literature demonstrates the effectiveness and the reliability of the proposed approach. Indeed, we obtain a good segmentation rate of 96% with the proposed method compared to 87.5% with statistical region merging (SRM), 84% with mean shift, 82% with color structure code (CSC), 80% with efficient graph-based segmentation algorithm (EGBIS) and 71% with JSEG. PMID:25648706

  3. Relative Luminance and Figure-Background Segmentation Problems: Using AMLA to Avoid Nondiscernible Stimulus Pairs in Common and Color Blind Observers

    ERIC Educational Resources Information Center

    Jover, Julio Lillo; Moreira, Humberto

    2005-01-01

    Four experiments evaluated AMLA temporal version accuracy to measure relative luminosity in people with and without color blindness and, consequently, to provide the essential information to avoid poor figure-background combinations in any possible "specific screen-specific observer" pair. Experiment 1 showed that two very different apparatus, a…

  4. SU-E-J-220: Evaluation of Atlas-Based Auto-Segmentation (ABAS) in Head-And-Neck Adaptive Radiotherapy

    SciTech Connect

    Liu, Q; Yan, D

    2014-06-01

    Purpose: Evaluate the accuracy of atlas-based auto segmentation of organs at risk (OARs) on both helical CT (HCT) and cone beam CT (CBCT) images in head and neck (HN) cancer adaptive radiotherapy (ART). Methods: Six HN patients treated in the ART process were included in this study. For each patient, three images were selected: pretreatment planning CT (PreTx-HCT), in treatment CT for replanning (InTx-HCT) and a CBCT acquired in the same day of the InTx-HCT. Three clinical procedures of auto segmentation and deformable registration performed in the ART process were evaluated: a) auto segmentation on PreTx-HCT using multi-subject atlases, b) intra-patient propagation of OARs from PreTx-HCT to InTx-HCT using deformable HCT-to-HCT image registration, and c) intra-patient propagation of OARs from PreTx-HCT to CBCT using deformable CBCT-to-HCT image registration. Seven OARs (brainstem, cord, L/R parotid, L/R submandibular gland and mandible) were manually contoured on PreTx-HCT and InTx-HCT for comparison. In addition, manual contours on InTx-CT were copied on the same day CBCT, and a local region rigid body registration was performed accordingly for each individual OAR. For procedures a) and b), auto contours were compared to manual contours, and for c) auto contours were compared to those rigidly transferred contours on CBCT. Dice similarity coefficients (DSC) and mean surface distances of agreement (MSDA) were calculated for evaluation. Results: For procedure a), the mean DSC/MSDA of most OARs are >80%/±2mm. For intra-patient HCT-to-HCT propagation, the Resultimproved to >85%/±1.5mm. Compared to HCT-to-HCT, the mean DSC for HCT-to-CBCT propagation drops ∼2–3% and MSDA increases ∼0.2mm. This Resultindicates that the inferior imaging quality of CBCT seems only degrade auto propagation performance slightly. Conclusion: Auto segmentation and deformable propagation can generate OAR structures on HCT and CBCT images with clinically acceptable accuracy. Therefore

  5. Light piping driven photosynthesis in the soil: Low-light adapted active photosynthetic apparatus in the under-soil hypocotyl segments of bean (Phaseolus vulgaris).

    PubMed

    Kakuszi, Andrea; Sárvári, Éva; Solti, Ádám; Czégény, Gyula; Hideg, Éva; Hunyadi-Gulyás, Éva; Bóka, Károly; Böddi, Béla

    2016-08-01

    Photosynthetic activity was identified in the under-soil hypocotyl part of 14-day-old soil-grown bean plants (Phaseolus vulgaris L. cv. Magnum) cultivated in pots under natural light-dark cycles. Electron microscopic, proteomic and fluorescence kinetic and imaging methods were used to study the photosynthetic apparatus and its activity. Under-soil shoots at 0-2cm soil depth featured chloroplasts with low grana and starch grains and with pigment-protein compositions similar to those of the above-soil green shoot parts. However, the relative amounts of photosystem II (PSII) supercomplexes were higher; in addition a PIP-type aquaporin protein was identified in the under-soil thylakoids. Chlorophyll-a fluorescence induction measurements showed that the above- and under-soil hypocotyl segments had similar photochemical yields at low (10-55μmolphotonsm(-2)s(-1)) light intensities. However, at higher photon flux densities the electron transport rate decreased in the under-soil shoot parts due to inactivation of the PSII reaction centers. These properties show the development of a low-light adapted photosynthetic apparatus driven by light piping of the above-soil shoot. The results of this paper demonstrate that the classic model assigning source and sink functions to above- and under-soil tissues is to be refined, and a low-light adapted photosynthetic apparatus in under-soil bean hypocotyls is capable of contributing to its own carbon supply.

  6. Light piping driven photosynthesis in the soil: Low-light adapted active photosynthetic apparatus in the under-soil hypocotyl segments of bean (Phaseolus vulgaris).

    PubMed

    Kakuszi, Andrea; Sárvári, Éva; Solti, Ádám; Czégény, Gyula; Hideg, Éva; Hunyadi-Gulyás, Éva; Bóka, Károly; Böddi, Béla

    2016-08-01

    Photosynthetic activity was identified in the under-soil hypocotyl part of 14-day-old soil-grown bean plants (Phaseolus vulgaris L. cv. Magnum) cultivated in pots under natural light-dark cycles. Electron microscopic, proteomic and fluorescence kinetic and imaging methods were used to study the photosynthetic apparatus and its activity. Under-soil shoots at 0-2cm soil depth featured chloroplasts with low grana and starch grains and with pigment-protein compositions similar to those of the above-soil green shoot parts. However, the relative amounts of photosystem II (PSII) supercomplexes were higher; in addition a PIP-type aquaporin protein was identified in the under-soil thylakoids. Chlorophyll-a fluorescence induction measurements showed that the above- and under-soil hypocotyl segments had similar photochemical yields at low (10-55μmolphotonsm(-2)s(-1)) light intensities. However, at higher photon flux densities the electron transport rate decreased in the under-soil shoot parts due to inactivation of the PSII reaction centers. These properties show the development of a low-light adapted photosynthetic apparatus driven by light piping of the above-soil shoot. The results of this paper demonstrate that the classic model assigning source and sink functions to above- and under-soil tissues is to be refined, and a low-light adapted photosynthetic apparatus in under-soil bean hypocotyls is capable of contributing to its own carbon supply. PMID:27318297

  7. Adapt

    NASA Astrophysics Data System (ADS)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  8. Shape and Color Features for Object Recognition Search

    NASA Technical Reports Server (NTRS)

    Duong, Tuan A.; Duong, Vu A.; Stubberud, Allen R.

    2012-01-01

    A bio-inspired shape feature of an object of interest emulates the integration of the saccadic eye movement and horizontal layer in vertebrate retina for object recognition search where a single object can be used one at a time. The optimal computational model for shape-extraction-based principal component analysis (PCA) was also developed to reduce processing time and enable the real-time adaptive system capability. A color feature of the object is employed as color segmentation to empower the shape feature recognition to solve the object recognition in the heterogeneous environment where a single technique - shape or color - may expose its difficulties. To enable the effective system, an adaptive architecture and autonomous mechanism were developed to recognize and adapt the shape and color feature of the moving object. The bio-inspired object recognition based on bio-inspired shape and color can be effective to recognize a person of interest in the heterogeneous environment where the single technique exposed its difficulties to perform effective recognition. Moreover, this work also demonstrates the mechanism and architecture of the autonomous adaptive system to enable the realistic system for the practical use in the future.

  9. Multimodal Segmentation of Optic Disc and Cup From SD-OCT and Color Fundus Photographs Using a Machine-Learning Graph-Based Approach.

    PubMed

    Miri, Mohammad Saleh; Abràmoff, Michael D; Lee, Kyungmoo; Niemeijer, Meindert; Wang, Jui-Kai; Kwon, Young H; Garvin, Mona K

    2015-09-01

    In this work, a multimodal approach is proposed to use the complementary information from fundus photographs and spectral domain optical coherence tomography (SD-OCT) volumes in order to segment the optic disc and cup boundaries. The problem is formulated as an optimization problem where the optimal solution is obtained using a machine-learning theoretical graph-based method. In particular, first the fundus photograph is registered to the 2D projection of the SD-OCT volume. Three in-region cost functions are designed using a random forest classifier corresponding to three regions of cup, rim, and background. Next, the volumes are resampled to create radial scans in which the Bruch's Membrane Opening (BMO) endpoints are easier to detect. Similar to in-region cost function design, the disc-boundary cost function is designed using a random forest classifier for which the features are created by applying the Haar Stationary Wavelet Transform (SWT) to the radial projection image. A multisurface graph-based approach utilizes the in-region and disc-boundary cost images to segment the boundaries of optic disc and cup under feasibility constraints. The approach is evaluated on 25 multimodal image pairs from 25 subjects in a leave-one-out fashion (by subject). The performances of the graph-theoretic approach using three sets of cost functions are compared: 1) using unimodal (OCT only) in-region costs, 2) using multimodal in-region costs, and 3) using multimodal in-region and disc-boundary costs. Results show that the multimodal approaches outperform the unimodal approach in segmenting the optic disc and cup.

  10. Multimodal Segmentation of Optic Disc and Cup from SD-OCT and Color Fundus Photographs Using a Machine-Learning Graph-Based Approach

    PubMed Central

    Miri, Mohammad Saleh; Abràmoff, Michael D.; Lee, Kyungmoo; Niemeijer, Meindert; Wang, Jui-Kai; Kwon, Young H.

    2015-01-01

    In this work, a multimodal approach is proposed to use the complementary information from fundus photographs and spectral domain optical coherence tomography (SD-OCT) volumes in order to segment the optic disc and cup boundaries. The problem is formulated as an optimization problem where the optimal solution is obtained using a machine-learning theoretical graph-based method. In particular, first the fundus photograph is registered to the 2D projection of the SD-OCT volume. Three in-region cost functions are designed using a random forest classifier corresponding to three regions of cup, rim, and background. Next, the volumes are resampled to create radial scans in which the Bruch’s Membrane Opening (BMO) endpoints are easier to detect. Similar to in-region cost function design, the disc-boundary cost function is designed using a random forest classifier for which the features are created by applying the Haar Stationary Wavelet Transform (SWT) to the radial projection image. A multisurface graph-based approach utilizes the in-region and disc-boundary cost images to segment the boundaries of optic disc and cup under feasibility constraints. The approach is evaluated on 25 multimodal image pairs from 25 subjects in a leave-one-out fashion (by subject). The performances of the graph-theoretic approach using three sets of cost functions are compared: 1) using unimodal (OCT only) in-region costs, 2) using multimodal in-region costs, and 3) using multimodal in-region and disc-boundary costs. Results show that the multimodal approaches outperform the unimodal approach in segmenting the optic disc and cup. PMID:25781623

  11. Flaw detection and segmentation in textile inspection

    NASA Astrophysics Data System (ADS)

    Millán, María S.; Ralló, Miquel; Escofet, Jaume

    2008-04-01

    We present a new method to automatically segment local defects in a woven fabric that does not require any additional defect-free reference for comparison. Firstly, the structural features of the repetition pattern of the minimal weave repeat are extracted from the Fourier spectrum of the sample under inspection. The corresponding peaks are automatically identified and removed from the fabric frequency spectrum. Secondly, we define a set of multi-scale oriented bandpass filters, adapted to the specific structure of the sample, that operate in the Fourier domain. The filter design is the key part of the method. Using the set of filters, local defects can be extracted. Thirdly, the filtered images obtained at different scales are inverse Fourier transformed, binarized and merged to obtain an output image where flaws are segmented from the fabric background. The method can be applied to fabrics of uniform color as well as to fabrics woven with threads of different colors. It is Euclidean motion invariant and texture adaptive and it is useful for automatic inspection both online and off-line. The whole process is fully automatic and can be implemented either optical or electronically. A variety of experimental results are presented and discussed.

  12. Exo-planet Direct Imaging with On-Axis and/or Segmented Apertures in Space: Adaptive Compensation of Aperture Discontinuities

    NASA Astrophysics Data System (ADS)

    Soummer, Remi

    Capitalizing on a recent breakthrough in wavefront control theory for obscured apertures made by our group, we propose to demonstrate a method to achieve high contrast exoplanet imaging with on-axis obscured apertures. Our new algorithm, which we named Adaptive Compensation of Aperture Discontinuities (ACAD), provides the ability to compensate for aperture discontinuities (segment gaps and/or secondary mirror supports) by controlling deformable mirrors in a nonlinear wavefront control regime not utilized before but conceptually similar to the beam reshaping used in PIAA coronagraphy. We propose here an in-air demonstration at 1E- 7 contrast, enabled by adding a second deformable mirror to our current test-bed. This expansion of the scope of our current efforts in exoplanet imaging technologies will enabling us to demonstrate an integrated solution for wavefront control and starlight suppression on complex aperture geometries. It is directly applicable at scales from moderate-cost exoplanet probe missions to the 2.4 m AFTA telescopes to future flagship UVOIR observatories with apertures potentially 16-20 m. Searching for nearby habitable worlds with direct imaging is one of the top scientific priorities established by the Astro2010 Decadal Survey. Achieving this ambitious goal will require 1e-10 contrast on a telescope large enough to provide angular resolution and sensitivity to planets around a significant sample of nearby stars. Such a mission must of course also be realized at an achievable cost. Lightweight segmented mirror technology allows larger diameter optics to fit in any given launch vehicle as compared to monolithic mirrors, and lowers total life-cycle costs from construction through integration & test, making it a compelling option for future large space telescopes. At smaller scales, on-axis designs with secondary obscurations and supports are less challenging to fabricate and thus more affordable than the off-axis unobscured primary mirror designs

  13. Color Addition and Subtraction Apps

    NASA Astrophysics Data System (ADS)

    Ruiz, Frances; Ruiz, Michael J.

    2015-10-01

    Color addition and subtraction apps in HTML5 have been developed for students as an online hands-on experience so that they can more easily master principles introduced through traditional classroom demonstrations. The evolution of the additive RGB color model is traced through the early IBM color adapters so that students can proceed step by step in understanding mathematical representations of RGB color. Finally, color addition and subtraction are presented for the X11 colors from web design to illustrate yet another real-life application of color mixing.

  14. Color Blindness

    MedlinePlus

    ... three color cone cells to determine our color perception. Color blindness can occur when one or more ... Anyone who experiences a significant change in color perception should see an ophthalmologist (Eye M.D.). Next ...

  15. Color blindness

    MedlinePlus

    Color deficiency; Blindness - color ... Color blindness occurs when there is a problem with the pigments in certain nerve cells of the eye that sense color. These cells are called cones. They are found ...

  16. Color Blindness

    MedlinePlus

    ... rose in full bloom. If you have a color vision defect, you may see these colors differently than most people. There are three main kinds of color vision defects. Red-green color vision defects are the ...

  17. Efficient graph-cut tattoo segmentation

    NASA Astrophysics Data System (ADS)

    Kim, Joonsoo; Parra, Albert; Li, He; Delp, Edward J.

    2015-03-01

    Law enforcement is interested in exploiting tattoos as an information source to identify, track and prevent gang-related crimes. Many tattoo image retrieval systems have been described. In a retrieval system tattoo segmentation is an important step for retrieval accuracy since segmentation removes background information in a tattoo image. Existing segmentation methods do not extract the tattoo very well when the background includes textures and color similar to skin tones. In this paper we describe a tattoo segmentation approach by determining skin pixels in regions near the tattoo. In these regions graph-cut segmentation using a skin color model and a visual saliency map is used to find skin pixels. After segmentation we determine which set of skin pixels are connected with each other that form a closed contour including a tattoo. The regions surrounded by the closed contours are considered tattoo regions. Our method segments tattoos well when the background includes textures and color similar to skin.

  18. Improved automatic detection and segmentation of cell nuclei in histopathology images.

    PubMed

    Al-Kofahi, Yousef; Lassoued, Wiem; Lee, William; Roysam, Badrinath

    2010-04-01

    Automatic segmentation of cell nuclei is an essential step in image cytometry and histometry. Despite substantial progress, there is a need to improve accuracy, speed, level of automation, and adaptability to new applications. This paper presents a robust and accurate novel method for segmenting cell nuclei using a combination of ideas. The image foreground is extracted automatically using a graph-cuts-based binarization. Next, nuclear seed points are detected by a novel method combining multiscale Laplacian-of-Gaussian filtering constrained by distance-map-based adaptive scale selection. These points are used to perform an initial segmentation that is refined using a second graph-cuts-based algorithm incorporating the method of alpha expansions and graph coloring to reduce computational complexity. Nuclear segmentation results were manually validated over 25 representative images (15 in vitro images and 10 in vivo images, containing more than 7400 nuclei) drawn from diverse cancer histopathology studies, and four types of segmentation errors were investigated. The overall accuracy of the proposed segmentation algorithm exceeded 86%. The accuracy was found to exceed 94% when only over- and undersegmentation errors were considered. The confounding image characteristics that led to most detection/segmentation errors were high cell density, high degree of clustering, poor image contrast and noisy background, damaged/irregular nuclei, and poor edge information. We present an efficient semiautomated approach to editing automated segmentation results that requires two mouse clicks per operation.

  19. Hard color-shrinkage for color-image processing of a digital color camera

    NASA Astrophysics Data System (ADS)

    Saito, Takahiro; Ueda, Yasutaka; Fujii, Nobuhiro; Komatsu, Takashi

    2010-01-01

    The classic shrinkage works well for monochrome-image denoising. To utilize inter-channel color correlations, a noisy image undergoes the color-transformation from the RGB to the luminance-and-chrominance color space, and the luminance and the chrominance components are separately denoised. However, this approach cannot cope with signaldependent noise of a digital color camera. To utilize the noise's signal-dependencies, previously we have proposed the soft color-shrinkage where the inter-channel color correlations are directly utilized in the RGB color space. The soft color-shrinkage works well; but involves a large amount of computations. To alleviate the drawback, taking up the l0-l2 optimization problem whose solution yields the hard shrinkage, we introduce the l0 norms of color differences and the l0 norms of color sums into the model, and derive hard color-shrinkage as its solution. For each triplet of three primary colors, the hard color-shrinkage has 24 feasible solutions, and from among them selects the optimal feasible solution giving the minimal energy. We propose a method to control its shrinkage parameters spatially-adaptively according to both the local image statistics and the noise's signal-dependencies, and apply the spatially-adaptive hard color-shrinkage to removal of signal-dependent noise in a shift-invariant wavelet transform domain. The hard color-shrinkage performs mostly better than the soft color-shrinkage, from objective and subjective viewpoints.

  20. Age-related differences in adaptation during childhood: the influences of muscular power production and segmental energy flow caused by muscles.

    PubMed

    Korff, Thomas; Jensen, Jody L

    2007-03-01

    Acquisition of skillfulness is not only characterized by a task-appropriate application of muscular forces but also by the ability to adapt performance to changing task demands. Previous research suggests that there is a different developmental schedule for adaptation at the kinematic compared to the neuro-muscular level. The purpose of this study was to determine how age-related differences in neuro-muscular organization affect the mechanical construction of pedaling at different levels of the task. By quantifying the flow of segmental energy caused by muscles, we determined the muscular synergies that construct the movement outcome across movement speeds. Younger children (5-7 years; n = 11), older children (8-10 years; n = 8), and adults (22-31 years; n = 8) rode a stationary ergometer at five discrete cadences (60, 75, 90, 105, and 120 rpm) at 10% of their individually predicted peak power output. Using a forward dynamics simulation, we determined the muscular contributions to crank power, as well as muscular power delivered to the crank directly and indirectly (through energy absorption and transfer) during the downstroke and the upstroke of the crank cycle. We found significant age x cadence interactions for (1) peak muscular power at the hip joint [Wilks' Lambda = 0.441, F(8,42) = 2.65, p = 0.019] indicating that at high movement speeds children produced less peak power at the hip than adults, (2) muscular power delivered to the crank during the downstroke and the upstroke of the crank cycle [Wilks' Lambda = 0.399, F(8,42) = 3.07, p = 0.009] indicating that children delivered a greater proportion of the power to the crank during the upstroke when compared to adults, (3) hip power contribution to limb power [Wilks' Lambda = 0.454, F(8,42) = 2.54, p = 0.023] indicating a cadence-dependence of age-related differences in the muscular synergy between hip extensors and plantarflexors. The results demonstrate that in spite of a successful performance, children

  1. Color Addition and Subtraction Apps

    ERIC Educational Resources Information Center

    Ruiz, Frances; Ruiz, Michael J.

    2015-01-01

    Color addition and subtraction apps in HTML5 have been developed for students as an online hands-on experience so that they can more easily master principles introduced through traditional classroom demonstrations. The evolution of the additive RGB color model is traced through the early IBM color adapters so that students can proceed step by step…

  2. Adaptive sequence evolution in a color gene involved in the formation of the characteristic egg-dummies of male haplochromine cichlid fishes

    PubMed Central

    Salzburger, Walter; Braasch, Ingo; Meyer, Axel

    2007-01-01

    Background The exceptionally diverse species flocks of cichlid fishes in East Africa are prime examples of parallel adaptive radiations. About 80% of East Africa's more than 1 800 endemic cichlid species, and all species of the flocks of Lakes Victoria and Malawi, belong to a particularly rapidly evolving lineage, the haplochromines. One characteristic feature of the haplochromines is their possession of egg-dummies on the males' anal fins. These egg-spots mimic real eggs and play an important role in the mating system of these maternal mouthbrooding fish. Results Here, we show that the egg-spots of haplochromines are made up of yellow pigment cells, xanthophores, and that a gene coding for a type III receptor tyrosine kinase, colony-stimulating factor 1 receptor a (csf1ra), is expressed in egg-spot tissue. Molecular evolutionary analyses reveal that the extracellular ligand-binding and receptor-interacting domain of csf1ra underwent adaptive sequence evolution in the ancestral lineage of the haplochromines, coinciding with the emergence of egg-dummies. We also find that csf1ra is expressed in the egg-dummies of a distantly related cichlid species, the ectodine cichlid Ophthalmotilapia ventralis, in which markings with similar functions evolved on the pelvic fin in convergence to those of the haplochromines. Conclusion We conclude that modifications of existing signal transduction mechanisms might have evolved in the haplochromine lineage in association with the origination of anal fin egg-dummies. That positive selection has acted during the evolution of a color gene that seems to be involved in the morphogenesis of a sexually selected trait, the egg-dummies, highlights the importance of further investigations of the comparative genomic basis of the phenotypic diversification of cichlid fishes. PMID:18005399

  3. Color vision of the coelacanth (Latimeria chalumnae) and adaptive evolution of rhodopsin (RH1) and rhodopsin-like (RH2) pigments.

    PubMed

    Yokoyama, S

    2000-01-01

    The coelacanth, a "living fossil," lives at a depth of about 200 m near the coast of the Comoros archipelago in the Indian Ocean and receives only a narrow range of light at about 480 nm. To see the entire range of "color" the Comoran coelacanth appears to use only rod-specific RH1 and cone-specific RH2 visual pigments, with the optimum light sensitivities (lambda max) at 478 nm and 485 nm, respectively. These blue-shifted lambda max values of RH1 and RH2 pigments are fully explained by independent double amino acid replacements E122Q/A292S and E122Q/M207L, respectively. More generally, currently available mutagenesis experiments identify only 10 amino acid changes that shift the lambda max values of visual pigments more than 5 nm. Among these, D83N, E1220, M207L, and A292S are associated strongly with the adaptive blue shifts in the lambda max values of RH1 and RH2 pigments in vertebrates.

  4. Automatic segmentation and classification of mycobacterium tuberculosis with conventional light microscopy

    NASA Astrophysics Data System (ADS)

    Xu, Chao; Zhou, Dongxiang; Zhai, Yongping; Liu, Yunhui

    2015-12-01

    This paper realizes the automatic segmentation and classification of Mycobacterium tuberculosis with conventional light microscopy. First, the candidate bacillus objects are segmented by the marker-based watershed transform. The markers are obtained by an adaptive threshold segmentation based on the adaptive scale Gaussian filter. The scale of the Gaussian filter is determined according to the color model of the bacillus objects. Then the candidate objects are extracted integrally after region merging and contaminations elimination. Second, the shape features of the bacillus objects are characterized by the Hu moments, compactness, eccentricity, and roughness, which are used to classify the single, touching and non-bacillus objects. We evaluated the logistic regression, random forest, and intersection kernel support vector machines classifiers in classifying the bacillus objects respectively. Experimental results demonstrate that the proposed method yields to high robustness and accuracy. The logistic regression classifier performs best with an accuracy of 91.68%.

  5. Properties of lateral interaction in color and brightness induction.

    PubMed

    Bachy, Romain; Zaidi, Qasim

    2016-03-01

    In a visual scene, when objects are surrounded by other components, neural mechanisms increase the perceived color and brightness difference between an object and its surround, potentially enhancing an observer's ability to segment objects. Despite almost two centuries of empirical investigations, the nature of induction mechanisms remains elusive. To elucidate the nature of these mechanisms, we introduce a new method for measuring color and brightness induction that allows separate manipulation of lateral interactions and adaptation, and controls for eye-movement-related effects. We use the method to examine the function relating induction magnitude to contrast change in the surround, the symmetry of induction in complementary directions for the three cardinal color axes, and the effect of blur between the test and the surround. On average, brightness induction was more linear than chromatic induction. The induction magnitude was similar for surrounds of complementary colors on average and for many conditions, and when individual observers deviated from symmetry it could be on either side. Edge blur did not change the induction magnitude. For slower presentations, light/dark induction increased to further reduce asymmetry, suggesting that previously found light/dark induction asymmetry is not due to lateral interactions or prolonged adaptation. Lateral interactions underlying induction are thus mostly symmetric for color and brightness axes and involve spatially opponent filters of modest widths, rather than edge extraction.

  6. Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation

    SciTech Connect

    Keller, Brad M.; Nathan, Diane L.; Wang Yan; Zheng Yuanjie; Gee, James C.; Conant, Emily F.; Kontos, Despina

    2012-08-15

    Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., 'FOR PROCESSING') and vendor postprocessed (i.e., 'FOR PRESENTATION'), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then

  7. Random geometric prior forest for multiclass object segmentation.

    PubMed

    Liu, Xiao; Song, Mingli; Tao, Dacheng; Bu, Jiajun; Chen, Chun

    2015-10-01

    Recent advances in object detection have led to the development of segmentation by detection approaches that integrate top-down geometric priors for multiclass object segmentation. A key yet under-addressed issue in utilizing top-down cues for the problem of multiclass object segmentation by detection is efficiently generating robust and accurate geometric priors. In this paper, we propose a random geometric prior forest scheme to obtain object-adaptive geometric priors efficiently and robustly. In the scheme, a testing object first searches for training neighbors with similar geometries using the random geometric prior forest, and then the geometry of the testing object is reconstructed by linearly combining the geometries of its neighbors. Our scheme enjoys several favorable properties when compared with conventional methods. First, it is robust and very fast because its inference does not suffer from bad initializations, poor local minimums or complex optimization. Second, the figure/ground geometries of training samples are utilized in a multitask manner. Third, our scheme is object-adaptive but does not require the labeling of parts or poselets, and thus, it is quite easy to implement. To demonstrate the effectiveness of the proposed scheme, we integrate the obtained top-down geometric priors with conventional bottom-up color cues in the frame of graph cut. The proposed random geometric prior forest achieves the best segmentation results of all of the methods tested on VOC2010/2012 and is 90 times faster than the current state-of-the-art method. PMID:25974937

  8. Number of discernible object colors is a conundrum.

    PubMed

    Masaoka, Kenichiro; Berns, Roy S; Fairchild, Mark D; Moghareh Abed, Farhad

    2013-02-01

    Widely varying estimates of the number of discernible object colors have been made by using various methods over the past 100 years. To clarify the source of the discrepancies in the previous, inconsistent estimates, the number of discernible object colors is estimated over a wide range of color temperatures and illuminance levels using several chromatic adaptation models, color spaces, and color difference limens. Efficient and accurate models are used to compute optimal-color solids and count the number of discernible colors. A comprehensive simulation reveals limitations in the ability of current color appearance models to estimate the number of discernible colors even if the color solid is smaller than the optimal-color solid. The estimates depend on the color appearance model, color space, and color difference limen used. The fundamental problem lies in the von Kries-type chromatic adaptation transforms, which have an unknown effect on the ranking of the number of discernible colors at different color temperatures.

  9. Reasoning about color in Prolog

    NASA Astrophysics Data System (ADS)

    Batchelor, Bruce G.; Whelan, Paul F.

    1994-10-01

    The use of color as a basis for segmenting images is attractive for a wide variety of industrial inspection applications, especially in the manufacturing of domestic goods, food, pharmaceuticals, toiletries and electronics. Human beings define colors, not formulae, or computer programs. Moreover, no two people have an identical view of what a color set, such as 'canary yellow' is. The article argues that teaching by showing is more relevant than the accepted methods of Color Science, in the design of factory-floor vision systems. Fast hardware for color recognition has been available for several years but has not yet received universal acceptance. This article explains how this equipment can be used in conjunction with symbolic processing software, based on the Artificial Intelligence language Prolog. Using this hardware-software system, a programmer is able to express ideas about colors in a natural way. The concepts of color set union, intersection, generalization and interpolation are all discussed.

  10. Automatic classification of skin lesions using color mathematical morphology-based texture descriptors

    NASA Astrophysics Data System (ADS)

    Gonzalez-Castro, Victor; Debayle, Johan; Wazaefi, Yanal; Rahim, Mehdi; Gaudy-Marqueste, Caroline; Grob, Jean-Jacques; Fertil, Bernard

    2015-04-01

    In this paper an automatic classification method of skin lesions from dermoscopic images is proposed. This method is based on color texture analysis based both on color mathematical morphology and Kohonen Self-Organizing Maps (SOM), and it does not need any previous segmentation process. More concretely, mathematical morphology is used to compute a local descriptor for each pixel of the image, while the SOM is used to cluster them and, thus, create the texture descriptor of the global image. Two approaches are proposed, depending on whether the pixel descriptor is computed using classical (i.e. spatially invariant) or adaptive (i.e. spatially variant) mathematical morphology by means of the Color Adaptive Neighborhoods (CANs) framework. Both approaches obtained similar areas under the ROC curve (AUC): 0.854 and 0.859 outperforming the AUC built upon dermatologists' predictions (0.792).

  11. Colorful Chemistry.

    ERIC Educational Resources Information Center

    Williams, Suzanne

    1991-01-01

    Described is an color-making activity where students use food coloring, eyedroppers, and water to make various colored solutions. Included are the needed materials and procedures. Students are asked to write up the formulas for making their favorite color. (KR)

  12. Color Vision Defects: What Teachers Should Know.

    ERIC Educational Resources Information Center

    Lewis, Barbara A.; And Others

    1990-01-01

    Discusses the nature of color vision defects as they relate to reading instruction. Suggests ways that teachers can adapt instruction to help provide maximal learning opportunities for the color deficient child. (RS)

  13. Development of hot slumping technique and last optical performances obtained on a 500mm diameter slumped segment prototype for adaptive optics

    NASA Astrophysics Data System (ADS)

    Ghigo, M.; Basso, S.; Canestrari, R.; Proserpio, L.

    2009-08-01

    In the framework of the E-ELT Design Study financed by the European Community under OPTICON-FP6, the INAF Astronomical Observatory of Brera (INAF-OAB) has developed a technique for the manufacturing of thin optical segments. Thin glass segments are produced by mean of an hot slumping technique that makes use of an optical quality ceramic mould and a precise thermal circle to impart the desired shape to a glass sheet. In the present paper we summarize the results obtained during this study and report the last results of the effort in scaling-up the procedure: in particular the overall process has been refined in order to optimize the parameters (such as time, maximum temperature and amount of pressure) used to slump a 500 mm diameter glass segment. The thickness of these glass segments is of about 1.7 mm, making the optical surface very floppy and easy to be deformed. For this reason optical tests have been performed using a astatic support implemented into a vertical optical bench.

  14. Automatic segmentation of psoriasis lesions

    NASA Astrophysics Data System (ADS)

    Ning, Yang; Shi, Chenbo; Wang, Li; Shu, Chang

    2014-10-01

    The automatic segmentation of psoriatic lesions is widely researched these years. It is an important step in Computer-aid methods of calculating PASI for estimation of lesions. Currently those algorithms can only handle single erythema or only deal with scaling segmentation. In practice, scaling and erythema are often mixed together. In order to get the segmentation of lesions area - this paper proposes an algorithm based on Random forests with color and texture features. The algorithm has three steps. The first step, the polarized light is applied based on the skin's Tyndall-effect in the imaging to eliminate the reflection and Lab color space are used for fitting the human perception. The second step, sliding window and its sub windows are used to get textural feature and color feature. In this step, a feature of image roughness has been defined, so that scaling can be easily separated from normal skin. In the end, Random forests will be used to ensure the generalization ability of the algorithm. This algorithm can give reliable segmentation results even the image has different lighting conditions, skin types. In the data set offered by Union Hospital, more than 90% images can be segmented accurately.

  15. Human preference for individual colors

    NASA Astrophysics Data System (ADS)

    Palmer, Stephen E.; Schloss, Karen B.

    2010-02-01

    Color preference is an important aspect of human behavior, but little is known about why people like some colors more than others. Recent results from the Berkeley Color Project (BCP) provide detailed measurements of preferences among 32 chromatic colors as well as other relevant aspects of color perception. We describe the fit of several color preference models, including ones based on cone outputs, color-emotion associations, and Palmer and Schloss's ecological valence theory. The ecological valence theory postulates that color serves an adaptive "steering' function, analogous to taste preferences, biasing organisms to approach advantageous objects and avoid disadvantageous ones. It predicts that people will tend to like colors to the extent that they like the objects that are characteristically that color, averaged over all such objects. The ecological valence theory predicts 80% of the variance in average color preference ratings from the Weighted Affective Valence Estimates (WAVEs) of correspondingly colored objects, much more variance than any of the other models. We also describe how hue preferences for single colors differ as a function of gender, expertise, culture, social institutions, and perceptual experience.

  16. Uncalibrated color

    NASA Astrophysics Data System (ADS)

    Moroney, Nathan

    2006-01-01

    Color calibration or the use of color measurement processes to characterize the color properties of a device or workflow is often expected or assumed for many color reproduction applications. However it is interesting to consider applications or situations in which color calibration is not as critical. In the first case it is possible to imagine an implicit color calibration resulting from a standardization or convergence of the colorant and substrate spectrum. In the second case it is possible to imagine cases where the device color variability is significantly less than the user color thresholds or expectations for color consistency. There are still general requirements for this form of pragmatic color but they are generally lower than for the higher end of digital color reproduction. Finally it is possible to imagine an implicit calibration that leverages in some way the highly accurate memory color for the hue of common objects. This scenario culminates with a challenge to create a natural capture calibration standard that does not require individual calibration, is spectrally diverse, is inexpensive and is environmentally friendly.

  17. Object Recognition using Feature- and Color-Based Methods

    NASA Technical Reports Server (NTRS)

    Duong, Tuan; Duong, Vu; Stubberud, Allen

    2008-01-01

    An improved adaptive method of processing image data in an artificial neural network has been developed to enable automated, real-time recognition of possibly moving objects under changing (including suddenly changing) conditions of illumination and perspective. The method involves a combination of two prior object-recognition methods one based on adaptive detection of shape features and one based on adaptive color segmentation to enable recognition in situations in which either prior method by itself may be inadequate. The chosen prior feature-based method is known as adaptive principal-component analysis (APCA); the chosen prior color-based method is known as adaptive color segmentation (ACOSE). These methods are made to interact with each other in a closed-loop system to obtain an optimal solution of the object-recognition problem in a dynamic environment. One of the results of the interaction is to increase, beyond what would otherwise be possible, the accuracy of the determination of a region of interest (containing an object that one seeks to recognize) within an image. Another result is to provide a minimized adaptive step that can be used to update the results obtained by the two component methods when changes of color and apparent shape occur. The net effect is to enable the neural network to update its recognition output and improve its recognition capability via an adaptive learning sequence. In principle, the improved method could readily be implemented in integrated circuitry to make a compact, low-power, real-time object-recognition system. It has been proposed to demonstrate the feasibility of such a system by integrating a 256-by-256 active-pixel sensor with APCA, ACOSE, and neural processing circuitry on a single chip. It has been estimated that such a system on a chip would have a volume no larger than a few cubic centimeters, could operate at a rate as high as 1,000 frames per second, and would consume in the order of milliwatts of power.

  18. Color realism and color science.

    PubMed

    Byrne, Alex; Hilbert, David R

    2003-02-01

    The target article is an attempt to make some progress on the problem of color realism. Are objects colored? And what is the nature of the color properties? We defend the view that physical objects (for instance, tomatoes, radishes, and rubies) are colored, and that colors are physical properties, specifically, types of reflectance. This is probably a minority opinion, at least among color scientists. Textbooks frequently claim that physical objects are not colored, and that the colors are "subjective" or "in the mind." The article has two other purposes: First, to introduce an interdisciplinary audience to some distinctively philosophical tools that are useful in tackling the problem of color realism and, second, to clarify the various positions and central arguments in the debate. The first part explains the problem of color realism and makes some useful distinctions. These distinctions are then used to expose various confusions that often prevent people from seeing that the issues are genuine and difficult, and that the problem of color realism ought to be of interest to anyone working in the field of color science. The second part explains the various leading answers to the problem of color realism, and (briefly) argues that all views other than our own have serious difficulties or are unmotivated. The third part explains and motivates our own view, that colors are types of reflectances and defends it against objections made in the recent literature that are often taken as fatal.

  19. Color realism and color science.

    PubMed

    Byrne, Alex; Hilbert, David R

    2003-02-01

    The target article is an attempt to make some progress on the problem of color realism. Are objects colored? And what is the nature of the color properties? We defend the view that physical objects (for instance, tomatoes, radishes, and rubies) are colored, and that colors are physical properties, specifically, types of reflectance. This is probably a minority opinion, at least among color scientists. Textbooks frequently claim that physical objects are not colored, and that the colors are "subjective" or "in the mind." The article has two other purposes: First, to introduce an interdisciplinary audience to some distinctively philosophical tools that are useful in tackling the problem of color realism and, second, to clarify the various positions and central arguments in the debate. The first part explains the problem of color realism and makes some useful distinctions. These distinctions are then used to expose various confusions that often prevent people from seeing that the issues are genuine and difficult, and that the problem of color realism ought to be of interest to anyone working in the field of color science. The second part explains the various leading answers to the problem of color realism, and (briefly) argues that all views other than our own have serious difficulties or are unmotivated. The third part explains and motivates our own view, that colors are types of reflectances and defends it against objections made in the recent literature that are often taken as fatal. PMID:14598439

  20. Motion detection in color image sequence and shadow elimination

    NASA Astrophysics Data System (ADS)

    Shen, Jun

    2004-01-01

    Most of the researches are concentrated on motion detection in gray value image sequences and the methods for motion detection are based on background subtraction or on temporal gray value derivatives. The methods based on background subtraction, including auto-adaptive ones, meet difficulties in presence of illumination changes and of slowly moving objects and need to be re-initialized from time to time. The methods based on temporal derivatives are in general sensible to noise. Color images containing much richer information than the gray value ones, it would be interesting to use them to better detect moving objects. In this paper, we address the problem of motion detection in color image sequences and the problems of illumination changes and shadow elimination. Our motion detection method is based on fuzzy segmentation of the color difference image in help of non-symmetrical π membership functions. The elimination of false moving objects detected due to illumination change is realized by combining the background subtraction method with the temporal derivative method and motion continuity. Shadows are removed by comparing the color of mobile pixels detected in the current frame with that in the precedent frame in HSL color space. Experimental results are reported.

  1. Entropy, color, and color rendering.

    PubMed

    Price, Luke L A

    2012-12-01

    The Shannon entropy [Bell Syst. Tech J.27, 379 (1948)] of spectral distributions is applied to the problem of color rendering. With this novel approach, calculations for visual white entropy, spectral entropy, and color rendering are proposed, indices that are unreliant on the subjectivity inherent in reference spectra and color samples. The indices are tested against real lamp spectra, showing a simple and robust system for color rendering assessment. The discussion considers potential roles for white entropy in several areas of color theory and psychophysics and nonextensive entropy generalizations of the entropy indices in mathematical color spaces.

  2. Seeing Color

    ERIC Educational Resources Information Center

    Texley, Juliana

    2005-01-01

    Colors are powerful tools for engaging children, from the youngest years onward. We hang brightly patterned mobiles above their cribs and help them learn the names of colors as they begin to record their own ideas in pictures and words. Colors can also open the door to an invisible world of electromagnetism, even when children can barely imagine…

  3. Automatic segmentation and classification of tendon nuclei from IHC stained images

    NASA Astrophysics Data System (ADS)

    Kuok, Chan-Pang; Wu, Po-Ting; Jou, I.-Ming; Su, Fong-Chin; Sun, Yung-Nien

    2015-12-01

    Immunohistochemical (IHC) staining is commonly used for detecting cells in microscopy. It is used for analyzing many types of diseases, e.g. breast cancer. Dispersion problem often exist at cell staining which will affect the accuracy of automatic counting. In this paper, we introduce a new method to overcome this problem. Otsu's thresholding method is first applied to exclude the background, so that only cells with dispersed staining are left at foreground, and then refinement will be applied by local adaptive thresholding method according to the irregularity index of the segmented shape at foreground. The segmentation results are also compared to the refinement results using Otsu's thresholding method. Cell classification based on the shape and color indices obtained from the segmentation result is applied to determine the cell condition into normal, abnormal and suspected abnormal cases.

  4. Color Terms and Color Concepts

    ERIC Educational Resources Information Center

    Davidoff, Jules

    2006-01-01

    In their lead articles, both Kowalski and Zimiles (2006) and O'Hanlon and Roberson (2006) declare a general relation between color term knowledge and the ability to conceptually represent color. Kowalski and Zimiles, in particular, argue for a priority for the conceptual representation in color term acquisition. The complexities of the interaction…

  5. Color Categories and Color Appearance

    ERIC Educational Resources Information Center

    Webster, Michael A.; Kay, Paul

    2012-01-01

    We examined categorical effects in color appearance in two tasks, which in part differed in the extent to which color naming was explicitly required for the response. In one, we measured the effects of color differences on perceptual grouping for hues that spanned the blue-green boundary, to test whether chromatic differences across the boundary…

  6. Color Analysis

    NASA Astrophysics Data System (ADS)

    Wrolstad, Ronald E.; Smith, Daniel E.

    Color, flavor, and texture are the three principal quality attributes that determine food acceptance, and color has a far greater influence on our judgment than most of us appreciate. We use color to determine if a banana is at our preferred ripeness level, and a discolored meat product can warn us that the product may be spoiled. The marketing departments of our food corporations know that, for their customers, the color must be "right." The University of California Davis scorecard for wine quality designates four points out of 20, or 20% of the total score, for color and appearance (1). Food scientists who establish quality control specifications for their product are very aware of the importance of color and appearance. While subjective visual assessment and use of visual color standards are still used in the food industry, instrumental color measurements are extensively employed. Objective measurement of color is desirable for both research and industrial applications, and the ruggedness, stability, and ease of use of today's color measurement instruments have resulted in their widespread adoption.

  7. Color categories and color appearance

    PubMed Central

    Webster, Michael A.; Kay, Paul

    2011-01-01

    We examined categorical effects in color appearance in two tasks, which in part differed in the extent to which color naming was explicitly required for the response. In one, we measured the effects of color differences on perceptual grouping for hues that spanned the blue–green boundary, to test whether chromatic differences across the boundary were perceptually exaggerated. This task did not require overt judgments of the perceived colors, and the tendency to group showed only a weak and inconsistent categorical bias. In a second case, we analyzed results from two prior studies of hue scaling of chromatic stimuli (De Valois, De Valois, Switkes, & Mahon, 1997; Malkoc, Kay, & Webster, 2005), to test whether color appearance changed more rapidly around the blue–green boundary. In this task observers directly judge the perceived color of the stimuli and these judgments tended to show much stronger categorical effects. The differences between these tasks could arise either because different signals mediate color grouping and color appearance, or because linguistic categories might differentially intrude on the response to color and/or on the perception of color. Our results suggest that the interaction between language and color processing may be highly dependent on the specific task and cognitive demands and strategies of the observer, and also highlight pronounced individual differences in the tendency to exhibit categorical responses. PMID:22176751

  8. Simulating coronas in color.

    PubMed

    Gedzelman, Stanley D; Lock, James A

    2003-01-20

    Coronas are simulated in color by use of the Mie scattering theory of light by small droplets through clouds of finite optical thickness embedded in a Rayleigh scattering atmosphere. The primary factors that affect color, visibility, and number of rings of coronas are droplet size, width of the size distribution, and cloud optical thickness. The color sequence of coronas and iridescence varies when the droplet radius is smaller than approximately 6-microm. As radius increases to approximately 3.5 microm, new color bands appear at the center of the corona and fade as they move outward. As the radius continues to increase to approximately 6 microm, successively more inner rings become fixed in the manner described by classical diffraction theory, while outer rings continue their outward migration. Wave clouds or rippled cloud segments produce the brightest and most vivid multiple ringed coronas and iridescence because their integrated dropsize distributions along sunbeams are much narrower than in convective or stratiform clouds. The visibility of coronas and the appearance of the background sky vary with cloud optical depth tau. First the corona becomes visible as a white aureole in a blue sky when tau approximately 0.001. Color purity then rapidly increases to an almost flat maximum in the range 0.05 < or = tau < or = 0.5 and then decreases, so coronas are almost completely washed out by a bright gray background when tau > or = 4.

  9. Processing of Color Words Activates Color Representations

    ERIC Educational Resources Information Center

    Richter, Tobias; Zwaan, Rolf A.

    2009-01-01

    Two experiments were conducted to investigate whether color representations are routinely activated when color words are processed. Congruency effects of colors and color words were observed in both directions. Lexical decisions on color words were faster when preceding colors matched the color named by the word. Color-discrimination responses…

  10. [Hair colorants].

    PubMed

    Urbanek-Karłowska, B; Luks, E; Jedra, M; Kiss, E; Malanowska, M

    1997-01-01

    The properties, mode of action and its duration of the preparations used for hair dyeing are described, together with their chemical components, and also preparations of herbal origin. The chemical reactions are described in detail which lead the development of a color polymer occurring during hair dyeing. The studies are presented which are used for toxicological assessment of the raw materials which are the components of the colorants, and the list is included of hair colorants permitted for use in Poland. PMID:9562811

  11. Leukocytes segmentation using Markov random fields.

    PubMed

    Reta, C; Gonzalez, J A; Diaz, R; Guichard, J S

    2011-01-01

    The segmentation of leukocytes and their components plays an important role in the extraction of geometric, texture, and morphological characteristics used to diagnose different diseases. This paper presents a novel method to segment leukocytes and their respective nucleus and cytoplasm from microscopic bone marrow leukemia cell images. Our method uses color and texture contextual information of image pixels to extract cellular elements from images, which show heterogeneous color and texture staining and high-cell population. The CIEL ( ∗ ) a ( ∗ ) b ( ∗ ) color space is used to extract color features, whereas a 2D Wold Decomposition model is applied to extract structural and stochastic texture features. The color and texture contextual information is incorporated into an unsupervised binary Markov Random Field segmentation model. Experimental results show the performance of the proposed method on both synthetic and real leukemia cell images. An average accuracy of 95% was achieved in the segmentation of real cell images by comparing those results with manually segmented cell images.

  12. Polar Color

    NASA Technical Reports Server (NTRS)

    2004-01-01

    [figure removed for brevity, see original site]

    Released 3 May 2004 This nighttime visible color image was collected on January 1, 2003 during the Northern Summer season near the North Polar Troughs.

    This daytime visible color image was collected on September 4, 2002 during the Northern Spring season in Vastitas Borealis. The THEMIS VIS camera is capable of capturing color images of the martian surface using its five different color filters. In this mode of operation, the spatial resolution and coverage of the image must be reduced to accommodate the additional data volume produced from the use of multiple filters. To make a color image, three of the five filter images (each in grayscale) are selected. Each is contrast enhanced and then converted to a red, green, or blue intensity image. These three images are then combined to produce a full color, single image. Because the THEMIS color filters don't span the full range of colors seen by the human eye, a color THEMIS image does not represent true color. Also, because each single-filter image is contrast enhanced before inclusion in the three-color image, the apparent color variation of the scene is exaggerated. Nevertheless, the color variation that does appear is representative of some change in color, however subtle, in the actual scene. Note that the long edges of THEMIS color images typically contain color artifacts that do not represent surface variation.

    Image information: VIS instrument. Latitude 79, Longitude 346 East (14 West). 19 meter/pixel resolution.

    Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with

  13. Quantum Color

    ScienceCinema

    Lincoln, Don

    2016-07-20

    The idea of electric charges and electricity in general is a familiar one to the science savvy viewer. However, electromagnetism is but one of the four fundamental forces and not the strongest one. The strongest of the fundamental forces is called the strong nuclear force and it has its own associated charge. Physicists call this charge “color” in analogy with the primary colors, although there is no real connection with actual color. In this video, Fermilab’s Dr. Don Lincoln explains why it is that we live in a colorful world.

  14. An automatic segmentation method for multi-tomatoes image under complicated natural background

    NASA Astrophysics Data System (ADS)

    Yin, Jianjun; Mao, Hanping; Hu, Yongguang; Wang, Xinzhong; Chen, Shuren

    2006-12-01

    It is a fundamental work to realize intelligent fruit-picking that mature fruits are distinguished from complicated backgrounds and determined their three-dimensional location. Various methods for fruit identification can be found from the literatures. However, surprisingly little attention has been paid to image segmentation of multi-fruits which growth states are separated, connected, overlapped and partially covered by branches and leaves of plant under the natural illumination condition. In this paper we present an automatic segmentation method that comprises of three main steps. Firstly, Red and Green component image are extracted from RGB color image, and Green component subtracted from Red component gives RG of chromatic aberration gray-level image. Gray-level value between objects and background has obviously difference in RG image. By the feature, Ostu's threshold method is applied to do adaptive RG image segmentation. And then, marker-controlled watershed segmentation based on morphological grayscale reconstruction is applied into Red component image to search boundary of connected or overlapped tomatoes. Finally, intersection operation is done by operation results of above two steps to get binary image of final segmentation. The tests show that the automatic segmentation method has satisfactory effect upon multi-tomatoes image of various growth states under the natural illumination condition. Meanwhile, it has very robust for different maturity of multi-tomatoes image.

  15. Proposal for adaptive management to conserve biotic integrity in a regulated segment of the Tallapoosa River, Alabama, U.S.A

    USGS Publications Warehouse

    Irwin, Elise R.; Freeman, Mary C.

    2002-01-01

    Conserving river biota will require innovative approaches that foster and utilize scientific understanding of ecosystem responses to alternative river-management scenarios. We describe ecological and societal issues involved in flow management of a section of the Tallapoosa River (Alabama, U.S.A.) in which a species-rich native fauna is adversely affected by flow alteration by an upstream hydropower dam. We hypothesize that depleted Iow flows, flow instability and thermal alteration resulting from pulsed flow releases at the hydropower dam are most responsible for changes in the Tallapoosa River biota. However, existing data are insufficient to prescribe with certainty minimum flow levels or the frequency and duration of stable flow periods that would be necessary or sufficient to protect riverine biotic integrity. Rather than negotiate a specific change in the flow regime, we propose that stakeholders--including management agencies, the power utility, and river advocates--engage in a process of adaptive-flow management. This process would require that stakeholders (1) develop and agree to management objectives; (2) model hypothesized relations between dam operations and management objectives; (3) implement a change in dam operations; and (4) evaluate biological responses and other stakeholder benefits through an externally reviewed monitoring program. Models would be updated with monitoring data and stakeholders would agree to further modify flow regimes as necessary to achieve management objectives. A primary obstacle to adaptive management will be a perceived uncertainty of future costs for the power utility and other stakeholders. However, an adaptive, iterative approach offers the best opportunity for improving flow regimes for native biota while gaining information critical to guiding management decisions in other flow-regulated rivers.

  16. Digitized locksmith forensics: automated detection and segmentation of toolmarks on highly structured surfaces

    NASA Astrophysics Data System (ADS)

    Clausing, Eric; Vielhauer, Claus

    2014-02-01

    Locksmith forensics is an important area in crime scene forensics. Due to new optical, contactless, nanometer range sensing technology, such traces can be captured, digitized and analyzed more easily allowing a complete digital forensic investigation. In this paper we present a significantly improved approach for the detection and segmentation of toolmarks on surfaces of locking cylinder components (using the example of the locking cylinder component 'key pin') acquired by a 3D Confocal Laser Scanning Microscope. This improved approach is based on our prior work1 using a block-based classification approach with textural features. In this prior work1 we achieve a solid detection rate of 75-85% for the detection of toolmarks originating from illegal opening methods. Here, in this paper we improve, expand and fuse this prior approach with additional features from acquired surface topography data, color data and an image processing approach using adapted Gabor filters. In particular we are able of raising the detection and segmentation rates above 90% with our test set of 20 key pins with approximately 700 single toolmark traces of four different opening methods. We can provide a precise pixel- based segmentation as opposed to the rather imprecise segmentation of our prior block-based approach and as the use of the two additional data types (color and especially topography) require a specific pre-processing, we furthermore propose an adequate approach for this purpose.

  17. Efficient threshold for volumetric segmentation

    NASA Astrophysics Data System (ADS)

    Burdescu, Dumitru D.; Brezovan, Marius; Stanescu, Liana; Stoica Spahiu, Cosmin; Ebanca, Daniel

    2015-07-01

    Image segmentation plays a crucial role in effective understanding of digital images. However, the research on the existence of general purpose segmentation algorithm that suits for variety of applications is still very much active. Among the many approaches in performing image segmentation, graph based approach is gaining popularity primarily due to its ability in reflecting global image properties. Volumetric image segmentation can simply result an image partition composed by relevant regions, but the most fundamental challenge in segmentation algorithm is to precisely define the volumetric extent of some object, which may be represented by the union of multiple regions. The aim in this paper is to present a new method to detect visual objects from color volumetric images and efficient threshold. We present a unified framework for volumetric image segmentation and contour extraction that uses a virtual tree-hexagonal structure defined on the set of the image voxels. The advantage of using a virtual tree-hexagonal network superposed over the initial image voxels is that it reduces the execution time and the memory space used, without losing the initial resolution of the image.

  18. Automatic image segmentation by dynamic region growth and multiresolution merging.

    PubMed

    Ugarriza, Luis Garcia; Saber, Eli; Vantaram, Sreenath Rao; Amuso, Vincent; Shaw, Mark; Bhaskar, Ranjit

    2009-10-01

    Image segmentation is a fundamental task in many computer vision applications. In this paper, we propose a new unsupervised color image segmentation algorithm, which exploits the information obtained from detecting edges in color images in the CIE L *a *b * color space. To this effect, by using a color gradient detection technique, pixels without edges are clustered and labeled individually to identify some initial portion of the input image content. Elements that contain higher gradient densities are included by the dynamic generation of clusters as the algorithm progresses. Texture modeling is performed by color quantization and local entropy computation of the quantized image. The obtained texture and color information along with a region growth map consisting of all fully grown regions are used to perform a unique multiresolution merging procedure to blend regions with similar characteristics. Experimental results obtained in comparison to published segmentation techniques demonstrate the performance advantages of the proposed method. PMID:19535323

  19. Hierarchical temporal video segmentation and content characterization

    NASA Astrophysics Data System (ADS)

    Gunsel, Bilge; Fu, Yue; Tekalp, A. Murat

    1997-10-01

    This paper addresses the segmentation of a video sequence into shots, specification of edit effects and subsequent characterization of shots in terms of color and motion content. The proposed scheme uses DC images extracted from MPEG compressed video and performs an unsupervised clustering for the extraction of camera shots. The specification of edit effects, such as fade-in/out and dissolve is based on the analysis of distribution of mean value for the luminance components. This step is followed by the representation of visual content of temporal segments in terms of key frames selected by similarity analysis of mean color histograms. For characterization of the similar temporal segments, motion and color characteristics are classified into different categories using a set of different features derived from motion vectors of triangular meshes and mean histograms of video shots.

  20. Color images in telepathology: how many colors do we need?

    PubMed

    Doolittle, M H; Doolittle, K W; Winkelman, Z; Weinberg, D S

    1997-01-01

    It is generally assumed that for telepathology, accurate depiction of microscopic images requires the use of "true color" (ie, 24 bits, eight bits each for red, green, and blue) in the digitized image used for transmission. If such a 24-bit color image file, which provides a palette of 16.7 million colors, could be reduced in size by decreasing the possible numbers of colors displayed in the image to 8 bits (palette of 256 colors), the image files would require less storage space, could be transmitted more rapidly, and would require less telecommunications bandwidth. However, such color reduction must not result in detectable image degradation, especially if the images are to be used for diagnosis. Therefore, we performed a carefully controlled study to determine whether pathologists could detect differences in the quality of microscopic images that were reduced from 24 to 8 bits of color. Thirty pathologists were each asked to view a set of 30 image pairs displayed on a computer monitor. Each image pair consisted of the original 24-bit color version and an 8-bit color-reduced version, derived using an adaptive color reduction algorithm with diffusion dithering. Observers were asked whether they could detect any difference in quality between the image pairs. Then, regardless of their answer, they were asked to choose the better quality image of the pair. Overall, there was not a statistically significant ability to consciously detect differences between the image pairs (P < .750). However, when forced to choose, there was a significant preference for the 8-bit images as being of "better quality" (P < .005). We conclude that telepathology applications may be able to take advantage of adaptive color reduction algorithms to reduce image file size without sacrificing image quality. Additional studies must be performed to determine the minimal image requirements for accurate diagnosis by telepatholgy.

  1. Segmental neuromyotonia

    PubMed Central

    Panwar, Ajay; Junewar, Vivek; Sahu, Ritesh; Shukla, Rakesh

    2015-01-01

    Unilateral focal neuromyotonia has been rarely reported in fingers or extraocular muscles. We report a case of segmental neuromyotonia in a 20-year-old boy who presented to us with intermittent tightness in right upper limb. Electromyography revealed myokymic and neuromyotonic discharges in proximal as well as distal muscles of the right upper limb. Patient's symptoms responded well to phenytoin therapy. Such an atypical involvement of two contiguous areas of a single limb in neuromyotonia has not been reported previously. Awareness of such an atypical presentation of the disease can be important in timely diagnosis and treatment of a patient. PMID:26167035

  2. Hierarchical image segmentation for learning object priors

    SciTech Connect

    Prasad, Lakshman; Yang, Xingwei; Latecki, Longin J; Li, Nan

    2010-11-10

    The proposed segmentation approach naturally combines experience based and image based information. The experience based information is obtained by training a classifier for each object class. For a given test image, the result of each classifier is represented as a probability map. The final segmentation is obtained with a hierarchial image segmentation algorithm that considers both the probability maps and the image features such as color and edge strength. We also utilize image region hierarchy to obtain not only local but also semi-global features as input to the classifiers. Moreover, to get robust probability maps, we take into account the region context information by averaging the probability maps over different levels of the hierarchical segmentation algorithm. The obtained segmentation results are superior to the state-of-the-art supervised image segmentation algorithms.

  3. A novel algorithm based on visual saliency attention for localization and segmentation in rapidly-stained leukocyte images.

    PubMed

    Zheng, Xin; Wang, Yong; Wang, Guoyou; Chen, Zhong

    2014-01-01

    In this paper, we propose a fast hierarchical framework of leukocyte localization and segmentation in rapidly-stained leukocyte images (RSLI) with complex backgrounds and varying illumination. The proposed framework contains two main steps. First, a nucleus saliency model based on average absolute difference is built, which locates each leukocyte precisely while effectively removes dyeing impurities and erythrocyte fragments. Secondly, two different schemes are presented for segmenting the nuclei and cytoplasm respectively. As for nuclei segmentation, to solve the overlap problem between leukocytes, we extract the nucleus lobes first and further group them. The lobes extraction is realized by the histogram-based contrast map and watershed segmentation, taking into account the saliency and similarity of nucleus color. Meanwhile, as for cytoplasm segmentation, to extract the blurry contour of the cytoplasm under instable illumination, we propose a cytoplasm enhancement based on tri-modal histogram specification, which specifically improves the contrast of cytoplasm while maintaining others. Then, the contour of cytoplasm is quickly obtained by extraction based on parameter-controlled adaptive attention window. Furthermore, the contour is corrected by concave points matching in order to solve the overlap between leukocytes and impurities. The experiments show the effectiveness of the proposed nucleus saliency model, which achieves average localization accuracy with F1-measure greater than 95%. In addition, the comparison of single leukocyte segmentation accuracy and running time has demonstrated that the proposed segmentation scheme outperforms the former approaches in RSLI.

  4. Color Blind or Color Conscious?

    ERIC Educational Resources Information Center

    Tatum, Beverly Daniel

    1999-01-01

    A color-blind approach often signifies that an educator has not considered what racial/ethnic identity means to youngsters. Students want to find themselves reflected in the faces of teachers and other students. Color-conscious teachers seek out materials that positively reflect students' identities and initiate discussions about race and racism.…

  5. Contour adaptation.

    PubMed

    Anstis, Stuart

    2013-01-01

    It is known that adaptation to a disk that flickers between black and white at 3-8 Hz on a gray surround renders invisible a congruent gray test disk viewed afterwards. This is contrast adaptation. We now report that adapting simply to the flickering circular outline of the disk can have the same effect. We call this "contour adaptation." This adaptation does not transfer interocularly, and apparently applies only to luminance, not color. One can adapt selectively to only some of the contours in a display, making only these contours temporarily invisible. For instance, a plaid comprises a vertical grating superimposed on a horizontal grating. If one first adapts to appropriate flickering vertical lines, the vertical components of the plaid disappears and it looks like a horizontal grating. Also, we simulated a Cornsweet (1970) edge, and we selectively adapted out the subjective and objective contours of a Kanisza (1976) subjective square. By temporarily removing edges, contour adaptation offers a new technique to study the role of visual edges, and it demonstrates how brightness information is concentrated in edges and propagates from them as it fills in surfaces.

  6. Terrain segmentation using laser radar range data.

    PubMed

    Letalick, D; Millnert, M; Renhorn, I

    1992-05-20

    A novel approach to segmentation of laser radar range images is presented. The approach is based on modeling horizontal and vertical scans of the terrain as piecewise-constant or piecewise-linear functions. The approach uses adaptive estimation based on Kalman filtering techniques. The performance of the segmentation algorithm is evaluated by application to laser range measurements. We also discuss how the output from the segmentation algorithm can be used for, e.g., object detection.

  7. Edge detection of color images using the HSL color space

    NASA Astrophysics Data System (ADS)

    Weeks, Arthur R.; Felix, Carlos E.; Myler, Harley R.

    1995-03-01

    Various edge detectors have been proposed as well as several different types of adaptive edge detectors, but the performance of many of these edge detectors depends on the features and the noise present in the grayscale image. Attempts have been made to extend edge detection to color images by applying grayscale edge detection methods to each of the individual red, blue, and green color components as well as to the hue, saturation, and intensity color components of the color image. The modulus 2(pi) nature of the hue color component makes its detection difficult. For example, a hue of 0 and 2(pi) yields the same color tint. Normal edge detection of a color image containing adjacent pixels with hue of 0 and 2(pi) could yield the presence of an edge when an edge is really not present. This paper presents a method of mapping the 2(pi) modulus hue space to a linear space enabling the edge detection of the hue color component using the Sobel edge detector. The results of this algorithm are compared against the edge detection methods using the red, blue, and green color components. By combining the hue edge image with the intensity and saturation edge images, more edge information is observed.

  8. Color vision.

    PubMed

    Gegenfurtner, Karl R; Kiper, Daniel C

    2003-01-01

    Color vision starts with the absorption of light in the retinal cone photoreceptors, which transduce electromagnetic energy into electrical voltages. These voltages are transformed into action potentials by a complicated network of cells in the retina. The information is sent to the visual cortex via the lateral geniculate nucleus (LGN) in three separate color-opponent channels that have been characterized psychophysically, physiologically, and computationally. The properties of cells in the retina and LGN account for a surprisingly large body of psychophysical literature. This suggests that several fundamental computations involved in color perception occur at early levels of processing. In the cortex, information from the three retino-geniculate channels is combined to enable perception of a large variety of different hues. Furthermore, recent evidence suggests that color analysis and coding cannot be separated from the analysis and coding of other visual attributes such as form and motion. Though there are some brain areas that are more sensitive to color than others, color vision emerges through the combined activity of neurons in many different areas.

  9. CT-based manual segmentation and evaluation of paranasal sinuses.

    PubMed

    Pirner, S; Tingelhoff, K; Wagner, I; Westphal, R; Rilk, M; Wahl, F M; Bootz, F; Eichhorn, Klaus W G

    2009-04-01

    Manual segmentation of computed tomography (CT) datasets was performed for robot-assisted endoscope movement during functional endoscopic sinus surgery (FESS). Segmented 3D models are needed for the robots' workspace definition. A total of 50 preselected CT datasets were each segmented in 150-200 coronal slices with 24 landmarks being set. Three different colors for segmentation represent diverse risk areas. Extension and volumetric measurements were performed. Three-dimensional reconstruction was generated after segmentation. Manual segmentation took 8-10 h for each CT dataset. The mean volumes were: right maxillary sinus 17.4 cm(3), left side 17.9 cm(3), right frontal sinus 4.2 cm(3), left side 4.0 cm(3), total frontal sinuses 7.9 cm(3), sphenoid sinus right side 5.3 cm(3), left side 5.5 cm(3), total sphenoid sinus volume 11.2 cm(3). Our manually segmented 3D-models present the patient's individual anatomy with a special focus on structures in danger according to the diverse colored risk areas. For safe robot assistance, the high-accuracy models represent an average of the population for anatomical variations, extension and volumetric measurements. They can be used as a database for automatic model-based segmentation. None of the segmentation methods so far described provide risk segmentation. The robot's maximum distance to the segmented border can be adjusted according to the differently colored areas.

  10. Segmentation of knee injury swelling on infrared images

    NASA Astrophysics Data System (ADS)

    Puentes, John; Langet, Hélène; Herry, Christophe; Frize, Monique

    2011-03-01

    Interpretation of medical infrared images is complex due to thermal noise, absence of texture, and small temperature differences in pathological zones. Acute inflammatory response is a characteristic symptom of some knee injuries like anterior cruciate ligament sprains, muscle or tendons strains, and meniscus tear. Whereas artificial coloring of the original grey level images may allow to visually assess the extent inflammation in the area, their automated segmentation remains a challenging problem. This paper presents a hybrid segmentation algorithm to evaluate the extent of inflammation after knee injury, in terms of temperature variations and surface shape. It is based on the intersection of rapid color segmentation and homogeneous region segmentation, to which a Laplacian of a Gaussian filter is applied. While rapid color segmentation enables to properly detect the observed core of swollen area, homogeneous region segmentation identifies possible inflammation zones, combining homogeneous grey level and hue area segmentation. The hybrid segmentation algorithm compares the potential inflammation regions partially detected by each method to identify overlapping areas. Noise filtering and edge segmentation are then applied to common zones in order to segment the swelling surfaces of the injury. Experimental results on images of a patient with anterior cruciate ligament sprain show the improved performance of the hybrid algorithm with respect to its separated components. The main contribution of this work is a meaningful automatic segmentation of abnormal skin temperature variations on infrared thermography images of knee injury swelling.

  11. Wavelength-adaptive dehazing using histogram merging-based classification for UAV images.

    PubMed

    Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

    2015-03-19

    Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results.

  12. Wavelength-Adaptive Dehazing Using Histogram Merging-Based Classification for UAV Images

    PubMed Central

    Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

    2015-01-01

    Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results. PMID:25808767

  13. Wavelength-adaptive dehazing using histogram merging-based classification for UAV images.

    PubMed

    Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

    2015-01-01

    Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results. PMID:25808767

  14. Integrated segmentation of cellular structures

    NASA Astrophysics Data System (ADS)

    Ajemba, Peter; Al-Kofahi, Yousef; Scott, Richard; Donovan, Michael; Fernandez, Gerardo

    2011-03-01

    Automatic segmentation of cellular structures is an essential step in image cytology and histology. Despite substantial progress, better automation and improvements in accuracy and adaptability to novel applications are needed. In applications utilizing multi-channel immuno-fluorescence images, challenges include misclassification of epithelial and stromal nuclei, irregular nuclei and cytoplasm boundaries, and over and under-segmentation of clustered nuclei. Variations in image acquisition conditions and artifacts from nuclei and cytoplasm images often confound existing algorithms in practice. In this paper, we present a robust and accurate algorithm for jointly segmenting cell nuclei and cytoplasm using a combination of ideas to reduce the aforementioned problems. First, an adaptive process that includes top-hat filtering, Eigenvalues-of-Hessian blob detection and distance transforms is used to estimate the inverse illumination field and correct for intensity non-uniformity in the nuclei channel. Next, a minimum-error-thresholding based binarization process and seed-detection combining Laplacian-of-Gaussian filtering constrained by a distance-map-based scale selection is used to identify candidate seeds for nuclei segmentation. The initial segmentation using a local maximum clustering algorithm is refined using a minimum-error-thresholding technique. Final refinements include an artifact removal process specifically targeted at lumens and other problematic structures and a systemic decision process to reclassify nuclei objects near the cytoplasm boundary as epithelial or stromal. Segmentation results were evaluated using 48 realistic phantom images with known ground-truth. The overall segmentation accuracy exceeds 94%. The algorithm was further tested on 981 images of actual prostate cancer tissue. The artifact removal process worked in 90% of cases. The algorithm has now been deployed in a high-volume histology analysis application.

  15. Phasing piston error in segmented telescopes.

    PubMed

    Jiang, Junlun; Zhao, Weirui

    2016-08-22

    To achieve a diffraction-limited imaging, the piston errors between the segments of the segmented primary mirror telescope should be reduced to λ/40 RMS. We propose a method to detect the piston error by analyzing the intensity distribution on the image plane according to the Fourier optics principle, which can capture segments with the piston errors as large as the coherence length of the input light and reduce these to 0.026λ RMS (λ = 633nm). This method is adaptable to any segmented and deployable primary mirror telescope. Experiments have been carried out to validate the feasibility of the method. PMID:27557192

  16. Parallel Fuzzy Segmentation of Multiple Objects.

    PubMed

    Garduño, Edgar; Herman, Gabor T

    2008-01-01

    The usefulness of fuzzy segmentation algorithms based on fuzzy connectedness principles has been established in numerous publications. New technologies are capable of producing larger-and-larger datasets and this causes the sequential implementations of fuzzy segmentation algorithms to be time-consuming. We have adapted a sequential fuzzy segmentation algorithm to multi-processor machines. We demonstrate the efficacy of such a distributed fuzzy segmentation algorithm by testing it with large datasets (of the order of 50 million points/voxels/items): a speed-up factor of approximately five over the sequential implementation seems to be the norm. PMID:19444333

  17. Phasing piston error in segmented telescopes.

    PubMed

    Jiang, Junlun; Zhao, Weirui

    2016-08-22

    To achieve a diffraction-limited imaging, the piston errors between the segments of the segmented primary mirror telescope should be reduced to λ/40 RMS. We propose a method to detect the piston error by analyzing the intensity distribution on the image plane according to the Fourier optics principle, which can capture segments with the piston errors as large as the coherence length of the input light and reduce these to 0.026λ RMS (λ = 633nm). This method is adaptable to any segmented and deployable primary mirror telescope. Experiments have been carried out to validate the feasibility of the method.

  18. Parallel Fuzzy Segmentation of Multiple Objects*

    PubMed Central

    Garduño, Edgar; Herman, Gabor T.

    2009-01-01

    The usefulness of fuzzy segmentation algorithms based on fuzzy connectedness principles has been established in numerous publications. New technologies are capable of producing larger-and-larger datasets and this causes the sequential implementations of fuzzy segmentation algorithms to be time-consuming. We have adapted a sequential fuzzy segmentation algorithm to multi-processor machines. We demonstrate the efficacy of such a distributed fuzzy segmentation algorithm by testing it with large datasets (of the order of 50 million points/voxels/items): a speed-up factor of approximately five over the sequential implementation seems to be the norm. PMID:19444333

  19. Color superconductivity

    SciTech Connect

    Wilczek, F.

    1997-09-22

    The asymptotic freedom of QCD suggests that at high density - where one forms a Fermi surface at very high momenta - weak coupling methods apply. These methods suggest that chiral symmetry is restored and that an instability toward color triplet condensation (color superconductivity) sets in. Here I attempt, using variational methods, to estimate these effects more precisely. Highlights include demonstration of a negative pressure in the uniform density chiral broken phase for any non-zero condensation, which we take as evidence for the philosophy of the MIT bag model; and demonstration that the color gap is substantial - several tens of MeV - even at modest densities. Since the superconductivity is in a pseudoscalar channel, parity is spontaneously broken.

  20. Into the blue: gene duplication and loss underlie color vision adaptations in a deep-sea chimaera, the elephant shark Callorhinchus milii.

    PubMed

    Davies, Wayne L; Carvalho, Livia S; Tay, Boon-Hui; Brenner, Sydney; Hunt, David M; Venkatesh, Byrappa

    2009-03-01

    The cartilaginous fishes reside at the base of the gnathostome lineage as the oldest extant group of jawed vertebrates. Recently, the genome of the elephant shark, Callorhinchus milii, a chimaerid holocephalan, has been sequenced and therefore becomes the first cartilaginous fish to be analyzed in this way. The chimaeras have been largely neglected and very little is known about the visual systems of these fishes. By searching the elephant shark genome, we have identified gene fragments encoding a rod visual pigment, Rh1, and three cone visual pigments, the middle wavelength-sensitive or Rh2 pigment, and two isoforms of the long wavelength-sensitive or LWS pigment, LWS1 and LWS2, but no evidence for the two short wavelength-sensitive cone classes, SWS1 and SWS2. Expression of these genes in the retina was confirmed by RT-PCR. Full-length coding sequences were used for in vitro expression and gave the following peak absorbances: Rh1 496 nm, Rh2 442 nm, LWS1 499 nm, and LWS2 548 nm. Unusually, therefore, for a deep-sea fish, the elephant shark possesses cone pigments and the potential for trichromacy. Compared with other vertebrates, the elephant shark Rh2 and LWS1 pigments are the shortest wavelength-shifted pigments of their respective classes known to date. The mechanisms for this are discussed and we provide experimental evidence that the elephant shark LWS1 pigment uses a novel tuning mechanism to achieve the short wavelength shift to 499 nm, which inactivates the chloride-binding site. Our findings have important implications for the present knowledge of color vision evolution in early vertebrates.

  1. Unsupervised defect segmentation of patterned materials under NIR illumination

    NASA Astrophysics Data System (ADS)

    Millán, María S.; Escofet, Jaume; Ralló, Miquel

    2011-01-01

    An unsupervised detection method for automatic flaw segmentation in patterned materials (textile, non-woven, paper) that has no need of any defect-free references or a training stage is presented in this paper. Printed materials having a pattern of colored squares, bands, etc. superimposed to the background texture can be advantageously analyzed using NIR illumination and a camera with enough sensitivity to this region of the spectrum. The contrast reduction of the pattern in the NIR image facilitates material inspection and defect segmentation. Underdetection and misdetection errors can be reduced in comparison with the inspection performed under visible illumination. For woven fabrics, with periodic structure, the algorithm is based on the structural feature extraction of the weave repeat from the Fourier transform of the sample image. These features are used to define a set of multiresolution bandpass filters adapted to the fabric structure that operate in the Fourier domain. Inverse Fourier transformation, binarization and merging of the information obtained at different scales lead to the output image that contains flaws segmented from the fabric background. For non-woven and random textured materials, the algorithm combines the multiresolution Gabor analysis of the sample image with a statistical analysis of the wavelet coefficients corresponding to each detail. The information of all the channels is merged in a single binary output image where the defect appears segmented from the background. The method is applicable to random, non-periodic, and periodic textures. Since all the information to inspect a sample is obtained from the sample itself, the method is proof against heterogeneities between different samples of the material, in-plane positioning errors, scale variations and lack of homogeneous illumination. Experimental results are presented for a variety of materials and defects.

  2. Color Sense

    ERIC Educational Resources Information Center

    Johnson, Heidi S. S.; Maki, Jennifer A.

    2009-01-01

    This article reports a study conducted by members of the WellU Academic Integration Subcommittee of The College of St. Scholastica's College's Healthy Campus Initiative plan whose purpose was to determine whether changing color in the classroom could have a measurable effect on students. One simple improvement a school can make in a classroom is…

  3. Categorical encoding of color in the brain.

    PubMed

    Bird, Chris M; Berens, Samuel C; Horner, Aidan J; Franklin, Anna

    2014-03-25

    The areas of the brain that encode color categorically have not yet been reliably identified. Here, we used functional MRI adaptation to identify neuronal populations that represent color categories irrespective of metric differences in color. Two colors were successively presented within a block of trials. The two colors were either from the same or different categories (e.g., "blue 1 and blue 2" or "blue 1 and green 1"), and the size of the hue difference was varied. Participants performed a target detection task unrelated to the difference in color. In the middle frontal gyrus of both hemispheres and to a lesser extent, the cerebellum, blood-oxygen level-dependent response was greater for colors from different categories relative to colors from the same category. Importantly, activation in these regions was not modulated by the size of the hue difference, suggesting that neurons in these regions represent color categorically, regardless of metric color difference. Representational similarity analyses, which investigated the similarity of the pattern of activity across local groups of voxels, identified other regions of the brain (including the visual cortex), which responded to metric but not categorical color differences. Therefore, categorical and metric hue differences appear to be coded in qualitatively different ways and in different brain regions. These findings have implications for the long-standing debate on the origin and nature of color categories, and also further our understanding of how color is processed by the brain.

  4. An entropy-based automated cell nuclei segmentation and quantification: application in analysis of wound healing process.

    PubMed

    Oswal, Varun; Belle, Ashwin; Diegelmann, Robert; Najarian, Kayvan

    2013-01-01

    The segmentation and quantification of cell nuclei are two very significant tasks in the analysis of histological images. Accurate results of cell nuclei segmentation are often adapted to a variety of applications such as the detection of cancerous cell nuclei and the observation of overlapping cellular events occurring during wound healing process in the human body. In this paper, an automated entropy-based thresholding system for segmentation and quantification of cell nuclei from histologically stained images has been presented. The proposed translational computation system aims to integrate clinical insight and computational analysis by identifying and segmenting objects of interest within histological images. Objects of interest and background regions are automatically distinguished by dynamically determining 3 optimal threshold values for the 3 color components of an input image. The threshold values are determined by means of entropy computations that are based on probability distributions of the color intensities of pixels and the spatial similarity of pixel intensities within neighborhoods. The effectiveness of the proposed system was tested over 21 histologically stained images containing approximately 1800 cell nuclei, and the overall performance of the algorithm was found to be promising, with high accuracy and precision values.

  5. A Discrete Model for Color Naming

    NASA Astrophysics Data System (ADS)

    Menegaz, G.; Le Troter, A.; Sequeira, J.; Boi, J. M.

    2006-12-01

    The ability to associate labels to colors is very natural for human beings. Though, this apparently simple task hides very complex and still unsolved problems, spreading over many different disciplines ranging from neurophysiology to psychology and imaging. In this paper, we propose a discrete model for computational color categorization and naming. Starting from the 424 color specimens of the OSA-UCS set, we propose a fuzzy partitioning of the color space. Each of the 11 basic color categories identified by Berlin and Kay is modeled as a fuzzy set whose membership function is implicitly defined by fitting the model to the results of an ad hoc psychophysical experiment (Experiment 1). Each OSA-UCS sample is represented by a feature vector whose components are the memberships to the different categories. The discrete model consists of a three-dimensional Delaunay triangulation of the CIELAB color space which associates each OSA-UCS sample to a vertex of a 3D tetrahedron. Linear interpolation is used to estimate the membership values of any other point in the color space. Model validation is performed both directly, through the comparison of the predicted membership values to the subjective counterparts, as evaluated via another psychophysical test (Experiment 2), and indirectly, through the investigation of its exploitability for image segmentation. The model has proved to be successful in both cases, providing an estimation of the membership values in good agreement with the subjective measures as well as a semantically meaningful color-based segmentation map.

  6. Qualitative and quantitative comparisons of multispectral night vision colorization techniques

    NASA Astrophysics Data System (ADS)

    Zheng, Yufeng; Dong, Wenjie; Blasch, Erik P.

    2012-08-01

    Multispectral images enable robust night vision (NV) object assessment over day-night conditions. Furthermore, colorized multispectral NV images can enhance human vision by improving observer object classification and reaction times, especially for low light conditions. NV colorization techniques can produce the colorized images that closely resemble natural scenes. Qualitative (subjective) and quantitative (objective) comparisons of NV colorization techniques proposed in the past decade are made and two categories of coloring methods, color fusion and color mapping, are discussed and compared. Color fusion directly combines multispectral NV images into a color-version image by mixing pixel intensities at different color planes, of which a channel-based color fusion method is reviewed. Color-mapping usually maps the color properties of a false-colored NV image (source) onto that of a true-color daylight target picture (reference). Four coloring-mapping methods-statistical matching, histogram matching, joint histogram matching, and look-up table (LUT)-are presented and compared, including a new color-mapping method called joint-histogram matching (JHM). The experimental NV imagery includes visible (Red-Green-Blue), image-intensified, near infrared, and long-wave infrared images. The qualitative evaluations are conducted by visual inspections of the colorized images, whereas the quantitative evaluations are achieved by a newly proposed metric, objective evaluation index. From the experimental results according to both qualitative and quantitative evaluations, the following conclusions can be drawn: the segmentation-based colorization method produces very impressive and realistic colors but requires intense computations; color fusion and LUT-based methods run very fast but with less realistic results; the statistic-matching method always provides acceptable results; histogram matching and joint-histogram matching can generate impressive and vivid colors when the color

  7. CFA-aware features for steganalysis of color images

    NASA Astrophysics Data System (ADS)

    Goljan, Miroslav; Fridrich, Jessica

    2015-03-01

    Color interpolation is a form of upsampling, which introduces constraints on the relationship between neighboring pixels in a color image. These constraints can be utilized to substantially boost the accuracy of steganography detectors. In this paper, we introduce a rich model formed by 3D co-occurrences of color noise residuals split according to the structure of the Bayer color filter array to further improve detection. Some color interpolation algorithms, AHD and PPG, impose pixel constraints so tight that extremely accurate detection becomes possible with merely eight features eliminating the need for model richification. We carry out experiments on non-adaptive LSB matching and the content-adaptive algorithm WOW on five different color interpolation algorithms. In contrast to grayscale images, in color images that exhibit traces of color interpolation the security of WOW is significantly lower and, depending on the interpolation algorithm, may even be lower than non-adaptive LSB matching.

  8. Segmented Coil Fails In Steps

    NASA Technical Reports Server (NTRS)

    Stedman, Ronald S.

    1990-01-01

    Electromagnetic coil degrades in steps when faults occur, continues to operate at reduced level instead of failing catastrophically. Made in segments connected in series and separated by electrically insulating barriers. Fault does not damage adjacent components or create hazard. Used to control valves in such critical applications as cooling systems of power generators and chemical process equipment, where flammable liquids or gases handled. Also adapts to electrical control of motors.

  9. Eleven Colors That Are Almost Never Confused

    NASA Astrophysics Data System (ADS)

    Boynton, Robert M.

    1989-08-01

    1.1. Three functions of color vision. Setting aside the complex psychological effects of color, related to esthetics, fashion, and mood, three relatively basic functions of color vision, which can be examined scientifically, are discernable. (1) With the eye in a given state of adaptation, color vision allows the perception of signals that otherwise would be below threshold, and therefore lost to perception. Evidence for this comes from a variety of two-color threshold experiments. (2) Visible contours can be maintained by color differences alone, regardless of the relative radiances of the two parts of the field whose junction defines the border. For achromatic vision, contour disappears at the isoluminant point. (3) Color specifies what seems to be an absolute property of a surface, one that enhances its recognizability and allows a clearer separation and classification of non-contiguous elements in the visual field.

  10. Biomimetics, color, and the arts

    NASA Astrophysics Data System (ADS)

    Schenk, Franziska

    2015-03-01

    Color as dramatic, dynamic and dazzling as the iridescent hues on the wings of certain butterflies has never been encountered in the art world. Unlike and unmatched by the chemical pigments of the artists' palette, this changeable color is created by transparent, colorless nanostructures that, as with prisms, diffract and reflect light to render spectral color visible. Until now, iridescent colors, by their very nature, have defied artists' best efforts to fully capture these rainbow hues. Now, for the first time, the artist and researcher Franziska Schenk employs latest nature-inspired color-shift technology to actually simulate the iridescence of butterflies and beetles on canvas. Crucially, studying the ingenious ways in which a range of such displays are created by insects has provided the artist with vital clues on how to adapt and adopt these challenging optical nano-materials for painting. And indeed, after years of meticulous and painstaking research both in the lab and studio, the desired effect is achieved. The resulting paintings, like an iridescent insect, do in fact fluctuate in perceived color - depending on the light and viewing angle. In tracing the artist's respective biomimetic approach, the paper not only provides an insight into the new color technology's evolution and innovative artistic possibilities, but also suggests what artists can learn from nature.

  11. Optimum color filters for CCD digital cameras.

    PubMed

    Engelhardt, K; Seitz, P

    1993-06-01

    A procedure for the definition of optimum spectral transmission curves for any solid-state (especially silicon-based CCD) color camera is presented. The design of the target curves is based on computer simulation of the camera system and on the use of test colors with known spectral reflectances. Color errors are measured in a uniform color space (CIELUV) and by application of the Commission Internationale de l'Eclairage color difference formula. Dielectric filter stacks were designed by simulated thermal annealing, and a stripe filter pattern was fabricated with transmission properties close to the specifications. Optimization of the color transformation minimizes the residual average color error and an average color error of ~1 just noticeable difference should be feasible. This means that color differences on a side-to-side comparison of original and reproduced color are practically imperceptible. In addition, electrical cross talk within the solid-state imager can be compensated by adapting the color matrixing coefficients. The theoretical findings of this work were employed for the design and fabrication of a high-resolution digital CCD color camera with high calorimetric accuracy. PMID:20829908

  12. Automated Fake Color Separation: Combining Computer Vision And Computer Graphics

    NASA Astrophysics Data System (ADS)

    Walters, Deborah

    1987-05-01

    A system is described for the automation of the color separation process. In current color separation systems, humans must visually segment line-art images, and using pen and ink, delineate the segments in a manner that enables a computer graphics system to be used interactively to color in each segment. The goal of this research was to remove the labor-intensive human visual segmentation, by adding rudimentary visual processing capabilities to the computer graphics system. This is possible through the use of computer vision algorithms which incorporate general knowledge about line-art, and are based on image features that are used by the human visual system in the early stages of visual processing. A major color separation company is planning the hardware implementation of a vision-graphics system based on these algorithms, and the State University of New York is applying for two patents based on this research.

  13. Introduction To Color Vision

    NASA Astrophysics Data System (ADS)

    Thorell, Lisa G.

    1983-08-01

    Several human cognitive studies have reported that color facilitates certain learning, memory and search tasks. Consideration of the color-opponent organization of human color vision and the spatial modulation transfer function for color suggests several simple sensory explanations.

  14. Coloring the Mu transpososome

    PubMed Central

    Darcy, Isabel K; Chang, Jeff; Druivenga, Nathan; McKinney, Colin; Medikonduri, Ram K; Mills, Stacy; Navarra-Madsen, Junalyn; Ponnusamy, Arun; Sweet, Jesse; Thompson, Travis

    2006-01-01

    Background Tangle analysis has been applied successfully to study proteins which bind two segments of DNA and can knot and link circular DNA. We show how tangle analysis can be extended to model any stable protein-DNA complex. Results We discuss a computational method for finding the topological conformation of DNA bound within a protein complex. We use an elementary invariant from knot theory called colorability to encode and search for possible DNA conformations. We apply this method to analyze the experimental results of Pathania, Jayaram, and Harshey (Cell 2002). We show that the only topological DNA conformation bound by Mu transposase which is biologically likely is the five crossing solution found by Pathania et al (although other possibilities are discussed). Conclusion Our algorithm can be used to analyze the results of the experimental technique described in Pathania et al in order to determine the topological conformation of DNA bound within a stable protein-DNA complex. PMID:17022825

  15. Automatic and quantitative measurement of collagen gel contraction using model-guided segmentation

    NASA Astrophysics Data System (ADS)

    Chen, Hsin-Chen; Yang, Tai-Hua; Thoreson, Andrew R.; Zhao, Chunfeng; Amadio, Peter C.; Sun, Yung-Nien; Su, Fong-Chin; An, Kai-Nan

    2013-08-01

    Quantitative measurement of collagen gel contraction plays a critical role in the field of tissue engineering because it provides spatial-temporal assessment (e.g., changes of gel area and diameter during the contraction process) reflecting the cell behavior and tissue material properties. So far the assessment of collagen gels relies on manual segmentation, which is time-consuming and suffers from serious intra- and inter-observer variability. In this study, we propose an automatic method combining various image processing techniques to resolve these problems. The proposed method first detects the maximal feasible contraction range of circular references (e.g., culture dish) and avoids the interference of irrelevant objects in the given image. Then, a three-step color conversion strategy is applied to normalize and enhance the contrast between the gel and background. We subsequently introduce a deformable circular model which utilizes regional intensity contrast and circular shape constraint to locate the gel boundary. An adaptive weighting scheme was employed to coordinate the model behavior, so that the proposed system can overcome variations of gel boundary appearances at different contraction stages. Two measurements of collagen gels (i.e., area and diameter) can readily be obtained based on the segmentation results. Experimental results, including 120 gel images for accuracy validation, showed high agreement between the proposed method and manual segmentation with an average dice similarity coefficient larger than 0.95. The results also demonstrated obvious improvement in gel contours obtained by the proposed method over two popular, generic segmentation methods.

  16. Color normalization for robust evaluation of microscopy images

    NASA Astrophysics Data System (ADS)

    Švihlík, Jan; Kybic, Jan; Habart, David

    2015-09-01

    This paper deals with color normalization of microscopy images of Langerhans islets in order to increase robustness of the islet segmentation to illumination changes. The main application is automatic quantitative evaluation of the islet parameters, useful for determining the feasibility of islet transplantation in diabetes. First, background illumination inhomogeneity is compensated and a preliminary foreground/background segmentation is performed. The color normalization itself is done in either lαβ or logarithmic RGB color spaces, by comparison with a reference image. The color-normalized images are segmented using color-based features and pixel-wise logistic regression, trained on manually labeled images. Finally, relevant statistics such as the total islet area are evaluated in order to determine the success likelihood of the transplantation.

  17. Hidden Color

    NASA Astrophysics Data System (ADS)

    Ji, C.-R.

    2014-10-01

    With the acceptance of QCD as the fundamental theory of strong interactions, one of the basic problems in the analysis of nuclear phenomena became how to consistently account for the effects of the underlying quark/gluon structure of nucleons and nuclei. Besides providing more detailed understanding of conventional nuclear physics, QCD may also point to novel phenomena accessible by new or upgraded nuclear experimental facilities. We discuss a few interesting applications of QCD to nuclear physics with an emphasis on the hidden color degrees of freedom.

  18. The evolution of vertebrate color vision.

    PubMed

    Jacobs, Gerald H

    2012-01-01

    Color vision is conventionally defined as the ability of animals to reliably discriminate among objects and lights based solely on differences in their spectral properties. Although the nature of color vision varies widely in different animals, a large majority of all vertebrate species possess some color vision and that fact attests to the adaptive importance this capacity holds as a tool for analyzing the environment. In recent years dramatic advances have been made in our understanding of the nature of vertebrate color vision and of the evolution of the biological mechanisms underlying this capacity. In this chapter I review and comment on these advances.

  19. Do focal colors look particularly "colorful"?

    PubMed

    Witzel, Christoph; Franklin, Anna

    2014-04-01

    If the most typical red, yellow, green, and blue were particularly colorful (i.e., saturated), they would "jump out to the eye." This would explain why even fundamentally different languages have distinct color terms for these focal colors, and why unique hues play a prominent role in subjective color appearance. In this study, the subjective saturation of 10 colors around each of these focal colors was measured through a pairwise matching task. Results show that subjective saturation changes systematically across hues in a way that is strongly correlated to the visual gamut, and exponentially related to sensitivity but not to focal colors.

  20. [Research on developping the spectral dataset for Dunhuang typical colors based on color constancy].

    PubMed

    Liu, Qiang; Wan, Xiao-Xia; Liu, Zhen; Li, Chan; Liang, Jin-Xing

    2013-11-01

    The present paper aims at developping a method to reasonably set up the typical spectral color dataset for different kinds of Chinese cultural heritage in color rendering process. The world famous wall paintings dating from more than 1700 years ago in Dunhuang Mogao Grottoes was taken as typical case in this research. In order to maintain the color constancy during the color rendering workflow of Dunhuang culture relics, a chromatic adaptation based method for developping the spectral dataset of typical colors for those wall paintings was proposed from the view point of human vision perception ability. Under the help and guidance of researchers in the art-research institution and protection-research institution of Dunhuang Academy and according to the existing research achievement of Dunhuang Research in the past years, 48 typical known Dunhuang pigments were chosen and 240 representative color samples were made with reflective spectral ranging from 360 to 750 nm was acquired by a spectrometer. In order to find the typical colors of the above mentioned color samples, the original dataset was devided into several subgroups by clustering analysis. The grouping number, together with the most typical samples for each subgroup which made up the firstly built typical color dataset, was determined by wilcoxon signed rank test according to the color inconstancy index comprehensively calculated under 6 typical illuminating conditions. Considering the completeness of gamut of Dunhuang wall paintings, 8 complementary colors was determined and finally the typical spectral color dataset was built up which contains 100 representative spectral colors. The analytical calculating results show that the median color inconstancy index of the built dataset in 99% confidence level by wilcoxon signed rank test was 3.28 and the 100 colors are distributing in the whole gamut uniformly, which ensures that this dataset can provide reasonable reference for choosing the color with highest

  1. Visual enhancement of unmixed multispectral imagery using adaptive smoothing

    USGS Publications Warehouse

    Lemeshewsky, G.P.; Rahman, Z.-U.; Schowengerdt, R.A.; Reichenbach, S.E.

    2004-01-01

    Adaptive smoothing (AS) has been previously proposed as a method to smooth uniform regions of an image, retain contrast edges, and enhance edge boundaries. The method is an implementation of the anisotropic diffusion process which results in a gray scale image. This paper discusses modifications to the AS method for application to multi-band data which results in a color segmented image. The process was used to visually enhance the three most distinct abundance fraction images produced by the Lagrange constraint neural network learning-based unmixing of Landsat 7 Enhanced Thematic Mapper Plus multispectral sensor data. A mutual information-based method was applied to select the three most distinct fraction images for subsequent visualization as a red, green, and blue composite. A reported image restoration technique (partial restoration) was applied to the multispectral data to reduce unmixing error, although evaluation of the performance of this technique was beyond the scope of this paper. The modified smoothing process resulted in a color segmented image with homogeneous regions separated by sharpened, coregistered multiband edges. There was improved class separation with the segmented image, which has importance to subsequent operations involving data classification.

  2. An image segmentation method for apple sorting and grading using support vector machine and Otsu's method

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Segmentation is the first step in image analysis to subdivide an image into meaningful regions. The segmentation result directly affects the subsequent image analysis. The objective of the research was to develop an automatic adjustable algorithm for segmentation of color images, using linear suppor...

  3. A Bayesian Approach for Image Segmentation with Shape Priors

    SciTech Connect

    Chang, Hang; Yang, Qing; Parvin, Bahram

    2008-06-20

    Color and texture have been widely used in image segmentation; however, their performance is often hindered by scene ambiguities, overlapping objects, or missingparts. In this paper, we propose an interactive image segmentation approach with shape prior models within a Bayesian framework. Interactive features, through mouse strokes, reduce ambiguities, and the incorporation of shape priors enhances quality of the segmentation where color and/or texture are not solely adequate. The novelties of our approach are in (i) formulating the segmentation problem in a well-de?ned Bayesian framework with multiple shape priors, (ii) ef?ciently estimating parameters of the Bayesian model, and (iii) multi-object segmentation through user-speci?ed priors. We demonstrate the effectiveness of our method on a set of natural and synthetic images.

  4. Segmentation assisted food classification for dietary assessment

    NASA Astrophysics Data System (ADS)

    Zhu, Fengqing; Bosch, Marc; Schap, TusaRebecca; Khanna, Nitin; Ebert, David S.; Boushey, Carol J.; Delp, Edward J.

    2011-03-01

    Accurate methods and tools to assess food and nutrient intake are essential for the association between diet and health. Preliminary studies have indicated that the use of a mobile device with a built-in camera to obtain images of the food consumed may provide a less burdensome and more accurate method for dietary assessment. We are developing methods to identify food items using a single image acquired from the mobile device. Our goal is to automatically determine the regions in an image where a particular food is located (segmentation) and correctly identify the food type based on its features (classification or food labeling). Images of foods are segmented using Normalized Cuts based on intensity and color. Color and texture features are extracted from each segmented food region. Classification decisions for each segmented region are made using support vector machine methods. The segmentation of each food region is refined based on feedback from the output of classifier to provide more accurate estimation of the quantity of food consumed.

  5. Cognitive aspects of color

    NASA Astrophysics Data System (ADS)

    Derefeldt, Gunilla A. M.; Menu, Jean-Pierre; Swartling, Tiina

    1995-04-01

    This report surveys cognitive aspects of color in terms of behavioral, neuropsychological, and neurophysiological data. Color is usually defined as psychophysical color or as perceived color. Behavioral data on categorical color perception, absolute judgement of colors, color coding, visual search, and visual awareness refer to the more cognitive aspects of color. These are of major importance in visual synthesis and spatial organization, as already shown by the Gestalt psychologists. Neuropsychological and neurophysiological findings provide evidence for an interrelation between cognitive color and spatial organization. Color also enhances planning strategies, as has been shown by studies on color and eye movements. Memory colors and the color- language connections in the brain also belong among the cognitive aspects of color.

  6. Image-based color ink diffusion rendering.

    PubMed

    Wang, Chung-Ming; Wang, Ren-Jie

    2007-01-01

    This paper proposes an image-based painterly rendering algorithm for automatically synthesizing an image with color ink diffusion. We suggest a mathematical model with a physical base to simulate the phenomenon of color colloidal ink diffusing into absorbent paper. Our algorithm contains three main parts: a feature extraction phase, a Kubelka-Munk (KM) color mixing phase, and a color ink diffusion synthesis phase. In the feature extraction phase, the information of the reference image is simplified by luminance division and color segmentation. In the color mixing phase, the KM theory is employed to approximate the result when one pigment is painted upon another pigment layer. Then, in the color ink diffusion synthesis phase, the physically-based model that we propose is employed to simulate the result of color ink diffusion in absorbent paper using a texture synthesis technique. Our image-based ink diffusing rendering (IBCIDR) algorithm eliminates the drawback of conventional Chinese ink simulations, which are limited to the black ink domain, and our approach demonstrates that, without using any strokes, a color image can be automatically converted to the diffused ink style with a visually pleasing appearance.

  7. Pet fur color and texture classification

    NASA Astrophysics Data System (ADS)

    Yen, Jonathan; Mukherjee, Debarghar; Lim, SukHwan; Tretter, Daniel

    2007-01-01

    Object segmentation is important in image analysis for imaging tasks such as image rendering and image retrieval. Pet owners have been known to be quite vocal about how important it is to render their pets perfectly. We present here an algorithm for pet (mammal) fur color classification and an algorithm for pet (animal) fur texture classification. Per fur color classification can be applied as a necessary condition for identifying the regions in an image that may contain pets much like the skin tone classification for human flesh detection. As a result of the evolution, fur coloration of all mammals is caused by a natural organic pigment called Melanin and Melanin has only very limited color ranges. We have conducted a statistical analysis and concluded that mammal fur colors can be only in levels of gray or in two colors after the proper color quantization. This pet fur color classification algorithm has been applied for peteye detection. We also present here an algorithm for animal fur texture classification using the recently developed multi-resolution directional sub-band Contourlet transform. The experimental results are very promising as these transforms can identify regions of an image that may contain fur of mammals, scale of reptiles and feather of birds, etc. Combining the color and texture classification, one can have a set of strong classifiers for identifying possible animals in an image.

  8. A global/local affinity graph for image segmentation.

    PubMed

    Xiaofang Wang; Yuxing Tang; Masnou, Simon; Liming Chen

    2015-04-01

    Construction of a reliable graph capturing perceptual grouping cues of an image is fundamental for graph-cut based image segmentation methods. In this paper, we propose a novel sparse global/local affinity graph over superpixels of an input image to capture both short- and long-range grouping cues, and thereby enabling perceptual grouping laws, including proximity, similarity, continuity, and to enter in action through a suitable graph-cut algorithm. Moreover, we also evaluate three major visual features, namely, color, texture, and shape, for their effectiveness in perceptual segmentation and propose a simple graph fusion scheme to implement some recent findings from psychophysics, which suggest combining these visual features with different emphases for perceptual grouping. In particular, an input image is first oversegmented into superpixels at different scales. We postulate a gravitation law based on empirical observations and divide superpixels adaptively into small-, medium-, and large-sized sets. Global grouping is achieved using medium-sized superpixels through a sparse representation of superpixels' features by solving a ℓ0-minimization problem, and thereby enabling continuity or propagation of local smoothness over long-range connections. Small- and large-sized superpixels are then used to achieve local smoothness through an adjacent graph in a given feature space, and thus implementing perceptual laws, for example, similarity and proximity. Finally, a bipartite graph is also introduced to enable propagation of grouping cues between superpixels of different scales. Extensive experiments are carried out on the Berkeley segmentation database in comparison with several state-of-the-art graph constructions. The results show the effectiveness of the proposed approach, which outperforms state-of-the-art graphs using four different objective criteria, namely, the probabilistic rand index, the variation of information, the global consistency error, and the

  9. A global/local affinity graph for image segmentation.

    PubMed

    Xiaofang Wang; Yuxing Tang; Masnou, Simon; Liming Chen

    2015-04-01

    Construction of a reliable graph capturing perceptual grouping cues of an image is fundamental for graph-cut based image segmentation methods. In this paper, we propose a novel sparse global/local affinity graph over superpixels of an input image to capture both short- and long-range grouping cues, and thereby enabling perceptual grouping laws, including proximity, similarity, continuity, and to enter in action through a suitable graph-cut algorithm. Moreover, we also evaluate three major visual features, namely, color, texture, and shape, for their effectiveness in perceptual segmentation and propose a simple graph fusion scheme to implement some recent findings from psychophysics, which suggest combining these visual features with different emphases for perceptual grouping. In particular, an input image is first oversegmented into superpixels at different scales. We postulate a gravitation law based on empirical observations and divide superpixels adaptively into small-, medium-, and large-sized sets. Global grouping is achieved using medium-sized superpixels through a sparse representation of superpixels' features by solving a ℓ0-minimization problem, and thereby enabling continuity or propagation of local smoothness over long-range connections. Small- and large-sized superpixels are then used to achieve local smoothness through an adjacent graph in a given feature space, and thus implementing perceptual laws, for example, similarity and proximity. Finally, a bipartite graph is also introduced to enable propagation of grouping cues between superpixels of different scales. Extensive experiments are carried out on the Berkeley segmentation database in comparison with several state-of-the-art graph constructions. The results show the effectiveness of the proposed approach, which outperforms state-of-the-art graphs using four different objective criteria, namely, the probabilistic rand index, the variation of information, the global consistency error, and the

  10. Segment alignment control system

    NASA Technical Reports Server (NTRS)

    Aubrun, JEAN-N.; Lorell, Ken R.

    1988-01-01

    The segmented primary mirror for the LDR will require a special segment alignment control system to precisely control the orientation of each of the segments so that the resulting composite reflector behaves like a monolith. The W.M. Keck Ten Meter Telescope will utilize a primary mirror made up of 36 actively controlled segments. Thus the primary mirror and its segment alignment control system are directly analogous to the LDR. The problems of controlling the segments in the face of disturbances and control/structures interaction, as analyzed for the TMT, are virtually identical to those for the LDR. The two systems are briefly compared.

  11. Object knowledge changes visual appearance: semantic effects on color afterimages.

    PubMed

    Lupyan, Gary

    2015-10-01

    According to predictive coding models of perception, what we see is determined jointly by the current input and the priors established by previous experience, expectations, and other contextual factors. The same input can thus be perceived differently depending on the priors that are brought to bear during viewing. Here, I show that expected (diagnostic) colors are perceived more vividly than arbitrary or unexpected colors, particularly when color input is unreliable. Participants were tested on a version of the 'Spanish Castle Illusion' in which viewing a hue-inverted image renders a subsequently shown achromatic version of the image in vivid color. Adapting to objects with intrinsic colors (e.g., a pumpkin) led to stronger afterimages than adapting to arbitrarily colored objects (e.g., a pumpkin-colored car). Considerably stronger afterimages were also produced by scenes containing intrinsically colored elements (grass, sky) compared to scenes with arbitrarily colored objects (books). The differences between images with diagnostic and arbitrary colors disappeared when the association between the image and color priors was weakened by, e.g., presenting the image upside-down, consistent with the prediction that color appearance is being modulated by color knowledge. Visual inputs that conflict with prior knowledge appear to be phenomenologically discounted, but this discounting is moderated by input certainty, as shown by the final study which uses conventional images rather than afterimages. As input certainty is increased, unexpected colors can become easier to detect than expected ones, a result consistent with predictive-coding models. PMID:26386775

  12. Sipunculans and segmentation

    PubMed Central

    Kristof, Alen; Brinkmann, Nora

    2009-01-01

    Comparative molecular, developmental and morphogenetic analyses show that the three major segmented animal groups—Lophotrochozoa, Ecdysozoa and Vertebrata—use a wide range of ontogenetic pathways to establish metameric body organization. Even in the life history of a single specimen, different mechanisms may act on the level of gene expression, cell proliferation, tissue differentiation and organ system formation in individual segments. Accordingly, in some polychaete annelids the first three pairs of segmental peripheral neurons arise synchronously, while the metameric commissures of the ventral nervous system form in anterior-posterior progression. Contrary to traditional belief, loss of segmentation may have occurred more often than commonly assumed, as exemplified in the sipunculans, which show remnants of segmentation in larval stages but are unsegmented as adults. The developmental plasticity and potential evolutionary lability of segmentation nourishes the controversy of a segmented bilaterian ancestor versus multiple independent evolution of segmentation in respective metazoan lineages. PMID:19513266

  13. Station Tour: Russian Segment

    NASA Video Gallery

    Expedition 33 Commander Suni Williams concludes her tour of the International Space Station with a visit to the Russian segment, which includes Zarya, the first segment of the station launched in 1...

  14. Artificial life approach to color contrast manipulation

    NASA Astrophysics Data System (ADS)

    Oliver, William R.

    1999-02-01

    Contrast enhancement methods have a long history of use in image processing for forensics and have been used to effect in the evaluation patterned injury of the skin. Most contrast enhancement methods, however, were developed for the evaluation of greyscale images and involve the manipulation of one dimension of data at a time. Contrast enhancement in a three- or more dimensional space poses challenges to the implementation of histogram equalization and similar algorithms. A number of approaches to dealing with this problem have been suggested, including performing operations on each channel independently or by various color `explosion' methods. Our laboratory has been investigating dispersion- and diffusion-based methods by modeling changes in color space as biological processes. In short, we model the migration and dispersion of points in color space as migration and differentiation. In this model, biological differentiation signals are used for segmentation in color space (color quantization) and chemoattractant and diffusion models are used for swarming and dispersal. The results of this method are compared with more traditional methods. Implementation issues are discussed. Extensions to the use of reaction-diffusion equations for color-space segmentation are discussed.

  15. [Segmentation of Winter Wheat Canopy Image Based on Visual Spectral and Random Forest Algorithm].

    PubMed

    Liu, Ya-dong; Cui, Ri-xian

    2015-12-01

    Digital image analysis has been widely used in non-destructive monitoring of crop growth and nitrogen nutrition status due to its simplicity and efficiency. It is necessary to segment winter wheat plant from soil background for accessing canopy cover, intensity level of visible spectrum (R, G, and B) and other color indices derived from RGB. In present study, according to the variation in R, G, and B components of sRGB color space and L*, a*, and b* components of CIEL* a* b* color space between wheat plant and soil background, the segmentation of wheat plant from soil background were conducted by the Otsu's method based on a* component of CIEL* a* b* color space, and RGB based random forest method, and CIEL* a* b* based random forest method, respectively. Also the ability to segment wheat plant from soil background was evaluated with the value of segmentation accuracy. The results showed that all three methods had revealed good ability to segment wheat plant from soil background. The Otsu's method had lowest segmentation accuracy in comparison with the other two methods. There were only little difference in segmentation error between the two random forest methods. In conclusion, the random forest method had revealed its capacity to segment wheat plant from soil background with only the visual spectral information of canopy image without any color components combinations or any color space transformation.

  16. [Segmentation of Winter Wheat Canopy Image Based on Visual Spectral and Random Forest Algorithm].

    PubMed

    Liu, Ya-dong; Cui, Ri-xian

    2015-12-01

    Digital image analysis has been widely used in non-destructive monitoring of crop growth and nitrogen nutrition status due to its simplicity and efficiency. It is necessary to segment winter wheat plant from soil background for accessing canopy cover, intensity level of visible spectrum (R, G, and B) and other color indices derived from RGB. In present study, according to the variation in R, G, and B components of sRGB color space and L*, a*, and b* components of CIEL* a* b* color space between wheat plant and soil background, the segmentation of wheat plant from soil background were conducted by the Otsu's method based on a* component of CIEL* a* b* color space, and RGB based random forest method, and CIEL* a* b* based random forest method, respectively. Also the ability to segment wheat plant from soil background was evaluated with the value of segmentation accuracy. The results showed that all three methods had revealed good ability to segment wheat plant from soil background. The Otsu's method had lowest segmentation accuracy in comparison with the other two methods. There were only little difference in segmentation error between the two random forest methods. In conclusion, the random forest method had revealed its capacity to segment wheat plant from soil background with only the visual spectral information of canopy image without any color components combinations or any color space transformation. PMID:26964234

  17. Masking the Color Wheel.

    ERIC Educational Resources Information Center

    Greene, Charlene

    1982-01-01

    Describes an art activity in which sixth graders made mirror-image masks using only two primary colors and one secondary color. Students discussed the effect of color combinations and the use of masks in folk and modern cultures. (AM)

  18. LED Color Characteristics

    SciTech Connect

    2012-01-01

    Color quality is an important consideration when evaluating LED-based products for general illumination. This fact sheet reviews the basics regarding light and color and summarizes the most important color issues related to white-light LED systems.

  19. Segmentation of prostate cancer tissue microarray images

    NASA Astrophysics Data System (ADS)

    Cline, Harvey E.; Can, Ali; Padfield, Dirk

    2006-02-01

    Prostate cancer is diagnosed by histopathology interpretation of hematoxylin and eosin (H and E)-stained tissue sections. Gland and nuclei distributions vary with the disease grade. The morphological features vary with the advance of cancer where the epithelial regions grow into the stroma. An efficient pathology slide image analysis method involved using a tissue microarray with known disease stages. Digital 24-bit RGB images were acquired for each tissue element on the slide with both 10X and 40X objectives. Initial segmentation at low magnification was accomplished using prior spectral characteristics from a training tissue set composed of four tissue clusters; namely, glands, epithelia, stroma and nuclei. The segmentation method was automated by using the training RGB values as an initial guess and iterating the averaging process 10 times to find the four cluster centers. Labels were assigned to the nearest cluster center in red-blue spectral feature space. An automatic threshold algorithm separated the glands from the tissue. A visual pseudo color representation of 60 segmented tissue microarray image was generated where white, pink, red, blue colors represent glands, epithelia, stroma and nuclei, respectively. The higher magnification images provided refined nuclei morphology. The nuclei were detected with a RGB color space principle component analysis that resulted in a grey scale image. The shape metrics such as compactness, elongation, minimum and maximum diameters were calculated based on the eigenvalues of the best-fitting ellipses to the nuclei.

  20. Basic Color Theory and Color in Computers.

    ERIC Educational Resources Information Center

    Stroh, Charles

    1997-01-01

    Discusses the nature of light and its relationship to color, particularly two models of color production: the additive and subtractive models. Explains the importance of these models for understanding how computers and printers generate colors. Argues that it is important to understand these processes given the prevalence of computers in art. (DSK)

  1. What is a segment?

    PubMed

    Hannibal, Roberta L; Patel, Nipam H

    2013-12-17

    Animals have been described as segmented for more than 2,000 years, yet a precise definition of segmentation remains elusive. Here we give the history of the definition of segmentation, followed by a discussion on current controversies in defining a segment. While there is a general consensus that segmentation involves the repetition of units along the anterior-posterior (a-p) axis, long-running debates exist over whether a segment can be composed of only one tissue layer, whether the most anterior region of the arthropod head is considered segmented, and whether and how the vertebrate head is segmented. Additionally, we discuss whether a segment can be composed of a single cell in a column of cells, or a single row of cells within a grid of cells. We suggest that 'segmentation' be used in its more general sense, the repetition of units with a-p polarity along the a-p axis, to prevent artificial classification of animals. We further suggest that this general definition be combined with an exact description of what is being studied, as well as a clearly stated hypothesis concerning the specific nature of the potential homology of structures. These suggestions should facilitate dialogue among scientists who study vastly differing segmental structures.

  2. Neurogeometry of color vision.

    PubMed

    Alleysson, David; Méary, David

    2012-01-01

    In neurogeometry, principles of differential geometry and neuron dynamics are used to model the representation of forms in the primary visual cortex, V1. This approach is well-suited for explaining the perception of illusory contours such as Kanizsa's figure (see Petitot (2008) for a review). In its current version, neurogeometry uses achromatic inputs to the visual system as the starting-point for form estimation. Here we ask how neurogeometry operates when the input is chromatic as in color vision. We propose that even when considering only the perception of form, the random nature of the cone mosaic must be taken into account. The main challenge for neurogeometry is to explain how achromatic information could be estimated from the sparse chromatic sampling provided by the cone mosaic. This article also discusses the non-linearity involved in a neural geometry for chromatic processing. We present empirical results on color discrimination to illustrate the geometric complexity for the discrimination contour when the adaptation state of the observer is not conditioned. The underlying non-linear geometry must conciliate both mosaic sampling and regulation of visual information in the visual system. PMID:22480445

  3. Color constancy and hue scaling.

    PubMed

    Schultz, Sven; Doerschner, Katja; Maloney, Laurence T

    2006-01-01

    In this study, we used a hue scaling technique to examine human color constancy performance in simulated three-dimensional scenes. These scenes contained objects of various shapes and materials and a matte test patch at the center of the scene. Hue scaling settings were made for test patches under five different illuminations. Results show that subjects had nearly stable hue scalings for a given test surface across different illuminants. In a control experiment, only the test surfaces that belonged to one illumination condition were presented, blocked in front of a black background. Surprisingly, the hue scalings of the subjects in the blocked control experiment were not simply determined by the color codes of the test surface. Rather, they depended on the sequence of previously presented test stimuli. In contrast, subjects' hue scalings in a second control experiment (with order of presentations randomized) were completely determined by the color codes of the test surface. Our results show that hue scaling is a useful technique to investigate color constancy in a more phenomenological sense. Furthermore, the results from the blocked control experiment underline the important role of slow chromatic adaptation for color constancy.

  4. Autophagy supports color vision.

    PubMed

    Zhou, Zhenqing; Vinberg, Frans; Schottler, Frank; Doggett, Teresa A; Kefalov, Vladimir J; Ferguson, Thomas A

    2015-01-01

    Cones comprise only a small portion of the photoreceptors in mammalian retinas. However, cones are vital for color vision and visual perception, and their loss severely diminishes the quality of life for patients with retinal degenerative diseases. Cones function in bright light and have higher demand for energy than rods; yet, the mechanisms that support the energy requirements of cones are poorly understood. One such pathway that potentially could sustain cones under basal and stress conditions is macroautophagy. We addressed the role of macroautophagy in cones by examining how the genetic block of this pathway affects the structural integrity, survival, and function of these neurons. We found that macroautophagy was not detectable in cones under normal conditions but was readily observed following 24 h of fasting. Consistent with this, starvation induced phosphorylation of AMPK specifically in cones indicating cellular starvation. Inhibiting macroautophagy in cones by deleting the essential macroautophagy gene Atg5 led to reduced cone function following starvation suggesting that cones are sensitive to systemic changes in nutrients and activate macroautophagy to maintain their function. ATG5-deficiency rendered cones susceptible to light-induced damage and caused accumulation of damaged mitochondria in the inner segments, shortening of the outer segments, and degeneration of all cone types, revealing the importance of mitophagy in supporting cone metabolic needs. Our results demonstrate that macroautophagy supports the function and long-term survival of cones providing for their unique metabolic requirements and resistance to stress. Targeting macroautophagy has the potential to preserve cone-mediated vision during retinal degenerative diseases. PMID:26292183

  5. Autophagy supports color vision

    PubMed Central

    Zhou, Zhenqing; Vinberg, Frans; Schottler, Frank; Doggett, Teresa A; Kefalov, Vladimir J; Ferguson, Thomas A

    2015-01-01

    Cones comprise only a small portion of the photoreceptors in mammalian retinas. However, cones are vital for color vision and visual perception, and their loss severely diminishes the quality of life for patients with retinal degenerative diseases. Cones function in bright light and have higher demand for energy than rods; yet, the mechanisms that support the energy requirements of cones are poorly understood. One such pathway that potentially could sustain cones under basal and stress conditions is macroautophagy. We addressed the role of macroautophagy in cones by examining how the genetic block of this pathway affects the structural integrity, survival, and function of these neurons. We found that macroautophagy was not detectable in cones under normal conditions but was readily observed following 24 h of fasting. Consistent with this, starvation induced phosphorylation of AMPK specifically in cones indicating cellular starvation. Inhibiting macroautophagy in cones by deleting the essential macroautophagy gene Atg5 led to reduced cone function following starvation suggesting that cones are sensitive to systemic changes in nutrients and activate macroautophagy to maintain their function. ATG5-deficiency rendered cones susceptible to light-induced damage and caused accumulation of damaged mitochondria in the inner segments, shortening of the outer segments, and degeneration of all cone types, revealing the importance of mitophagy in supporting cone metabolic needs. Our results demonstrate that macroautophagy supports the function and long-term survival of cones providing for their unique metabolic requirements and resistance to stress. Targeting macroautophagy has the potential to preserve cone-mediated vision during retinal degenerative diseases. PMID:26292183

  6. Autophagy supports color vision.

    PubMed

    Zhou, Zhenqing; Vinberg, Frans; Schottler, Frank; Doggett, Teresa A; Kefalov, Vladimir J; Ferguson, Thomas A

    2015-01-01

    Cones comprise only a small portion of the photoreceptors in mammalian retinas. However, cones are vital for color vision and visual perception, and their loss severely diminishes the quality of life for patients with retinal degenerative diseases. Cones function in bright light and have higher demand for energy than rods; yet, the mechanisms that support the energy requirements of cones are poorly understood. One such pathway that potentially could sustain cones under basal and stress conditions is macroautophagy. We addressed the role of macroautophagy in cones by examining how the genetic block of this pathway affects the structural integrity, survival, and function of these neurons. We found that macroautophagy was not detectable in cones under normal conditions but was readily observed following 24 h of fasting. Consistent with this, starvation induced phosphorylation of AMPK specifically in cones indicating cellular starvation. Inhibiting macroautophagy in cones by deleting the essential macroautophagy gene Atg5 led to reduced cone function following starvation suggesting that cones are sensitive to systemic changes in nutrients and activate macroautophagy to maintain their function. ATG5-deficiency rendered cones susceptible to light-induced damage and caused accumulation of damaged mitochondria in the inner segments, shortening of the outer segments, and degeneration of all cone types, revealing the importance of mitophagy in supporting cone metabolic needs. Our results demonstrate that macroautophagy supports the function and long-term survival of cones providing for their unique metabolic requirements and resistance to stress. Targeting macroautophagy has the potential to preserve cone-mediated vision during retinal degenerative diseases.

  7. Generalization of color-difference formulas for any illuminant and any observer by assuming perfect color constancy in a color-vision model based on the OSA-UCS system.

    PubMed

    Oleari, Claudio; Melgosa, Manuel; Huertas, Rafael

    2011-11-01

    The most widely used color-difference formulas are based on color-difference data obtained under D65 illumination or similar and for a 10° visual field; i.e., these formulas hold true for the CIE 1964 observer adapted to D65 illuminant. This work considers the psychometric color-vision model based on the Optical Society of America-Uniform Color Scales (OSA-UCS) system previously published by the first author [J. Opt. Soc. Am. A 21, 677 (2004); Color Res. Appl. 30, 31 (2005)] with the additional hypothesis that complete illuminant adaptation with perfect color constancy exists in the visual evaluation of color differences. In this way a computational procedure is defined for color conversion between different illuminant adaptations, which is an alternative to the current chromatic adaptation transforms. This color conversion allows the passage between different observers, e.g., CIE 1964 and CIE 1931. An application of this color conversion is here made in the color-difference evaluation for any observer and in any illuminant adaptation: these transformations convert tristimulus values related to any observer and illuminant adaptation to those related to the observer and illuminant adaptation of the definition of the color-difference formulas, i.e., to the CIE 1964 observer adapted to the D65 illuminant, and then the known color-difference formulas can be applied. The adaptations to the illuminants A, C, F11, D50, Planckian and daylight at any color temperature and for CIE 1931 and CIE 1964 observers are considered as examples, and all the corresponding transformations are given for practical use.

  8. Segmented cold cathode display panel

    NASA Technical Reports Server (NTRS)

    Payne, Leslie (Inventor)

    1998-01-01

    The present invention is a video display device that utilizes the novel concept of generating an electronically controlled pattern of electron emission at the output of a segmented photocathode. This pattern of electron emission is amplified via a channel plate. The result is that an intense electronic image can be accelerated toward a phosphor thus creating a bright video image. This novel arrangement allows for one to provide a full color flat video display capable of implementation in large formats. In an alternate arrangement, the present invention is provided without the channel plate and a porous conducting surface is provided instead. In this alternate arrangement, the brightness of the image is reduced but the cost of the overall device is significantly lowered because fabrication complexity is significantly decreased.

  9. Vane segment support and alignment device

    DOEpatents

    McLaurin, L.D.; Sizemore, J.D.

    1999-07-13

    A support and alignment assembly for supporting and aligning a vane segment is provided. The support and alignment assembly comprises a torque plate which defines an opening for receiving an eccentric pin and a locking end member for receiving a lock socket member. An eccentric pin adjustably supported by the torque plate opening for supporting and aligning a vane segment is provided. A lock socket member adapted to securely receive the eccentric pin and rotated therewith, and adjustably engage the torque plate locking end is provided. The lock socket member receives the eccentric pin, such that when the eccentric pin is adjusted to align the vane segment, the lock socket member engages the torque plate locking end to secure the vane segment in the desired position. 5 figs.

  10. Vane segment support and alignment device

    DOEpatents

    McLaurin, Leroy Dixon; Sizemore, John Derek

    1999-01-01

    A support and alignment assembly for supporting and aligning a vane segment is provided. The support and alignment assembly comprises a torque plate which defines an opening for receiving an eccentric pin and a locking end member for receiving a lock socket member. An eccentric pin adjustably supported by the torque plate opening for supporting and aligning a vane segment is provided. A lock socket member adapted to securely receive the eccentric pin and rotated therewith, and adjustably engage the torque plate locking end is provided. The lock socket member receives the eccentric pin, such that when the eccentric pin is adjusted to align the vane segment, the lock socket member engages the torque plate locking end to secure the vane segment in the desired position.

  11. Segmentation of moving object in complex environment

    NASA Astrophysics Data System (ADS)

    Yong, Yang; Wang, Jingru; Zhang, Qiheng

    2005-02-01

    This paper presents a new automatic image segmentation method for segmenting moving object in complex environment by combining the motion information with edge information. We propose an adaptive optical flow method based on the Horn-Schunck algorithm to estimate the optical flow field. Our method puts different smoothness constraints on different directions and optical flow constraint is used according to the gradient magnitude. Canny edge detector can obtain the most edge information but miss some pixels. In order to restore these missing pixels the edge has a growing based on the continuity of optical flow field. Next, by remaining the block that has the longest edge could delete the noise in the background, and then the last segmentation result is obtained. The experimental result demonstrates that this method can segment the moving object in complex environment precisely.

  12. Scale and orientation invariant text segmentation for born-digital compound images.

    PubMed

    Yang, Huan; Wu, Shiqian; Deng, Chenwei; Lin, Weisi

    2015-03-01

    Many recent applications require text segmentation for born-digital compound images. To this end, we propose a coarse-to-fine framework for segmenting texts of arbitrary scales and orientations in born-digital compound images. In the coarse stage, the local image activity measure is designed based upon the variation distribution of characters, to highlight the difference between textual and pictorial regions. This stage outputs a coarse textual layer including textual regions as well as a few pictorial regions with high activity. In the fine stage, a textual connected component (TCC) based refinement is proposed to eliminate the survived pictorial regions. In particular, a scale and orientation invariant grouping algorithm is proposed to adaptively generate TCCs with uniform statistical features. The minimum average distance and morphological operations are employed to assist the formation of candidate TCCs. Then, three string-level features (i.e., shapeness, color similarity, and mean activity level) are designed to distinguish the true TCCs from the false positive ones that are formed by connecting the high activity pictorial components. Extensive experiments show that the proposed framework can segment textual regions precisely from born-digital compound images, while preserving the integrity of texts with varied scales and orientations, and avoiding over-connection of textual regions. PMID:24988601

  13. Unsupervised flaw segmentation in textile materials under visible and NIR illumination

    NASA Astrophysics Data System (ADS)

    Millán, María S.; Escofet, Jaume; Ralló, Miquel

    2010-05-01

    An unsupervised novelty detection method for automatic flaw segmentation in textile materials that has no need of any defect-free references or a training stage is presented in this paper. The algorithm is based on the structural feature extraction of the weave repeat from the Fourier transform of the sample image. These features are used to define a set of multiresolution bandpass filters adapted to the fabric structure that operate in the Fourier domain. Inverse Fourier transformation, binarization and merging of the information obtained at different scales lead to the output image that contains flaws segmented from the fabric background. The whole process is fully automatic and can be implemented either optical or electronically. Fabrics having a superstructure of colored squares, bands, etc. superimposed to the basic web structure can be advantageously analyzed using NIR illumination and a camera sensitive to this region of the spectrum. The contrast reduction of the superstructure signal in the NIR image facilitates fabric structure inspection and defect segmentation. Underdetection and misdetection errors can be noticeably reduced in comparison with the inspection performed under visible illumination. Experimental results are presented and discussed for a variety of fabrics and defects.

  14. An extended framework for adaptive playback-based video summarization

    NASA Astrophysics Data System (ADS)

    Peker, Kadir A.; Divakaran, Ajay

    2003-11-01

    In our previous work, we described an adaptive fast playback framework for video summarization where we changed the playback rate using the motion activity feature so as to maintain a constant "pace." This method provides an effective way of skimming through video, especially when the motion is not too complex and the background is mostly still, such as in surveillance video. In this paper, we present an extended summarization framework that, in addition to motion activity, uses semantic cues such as face or skin color appearance, speech and music detection, or other domain dependent semantically significant events to control the playback rate. The semantic features we use are computationally inexpensive and can be computed in compressed domain, yet are robust, reliable, and have a wide range of applicability across different content types. The presented framework also allows for adaptive summaries based on preference, for example, to include more dramatic vs. action elements, or vice versa. The user can switch at any time between the skimming and the normal playback modes. The continuity of the video is preserved, and complete omission of segments that may be important to the user is avoided by using adaptive fast playback instead of skipping over long segments. The rule-set and the input parameters can be further modified to fit a certain domain or application. Our framework can be used by itself, or as a subsequent presentation stage for a summary produced by any other summarization technique that relies on generating a sub-set of the content.

  15. Opponent-colors approach to color rendering.

    PubMed

    Worthey, J A

    1982-01-01

    Starting with an opponent-colors formulation of color vision, two parameters, t and d, may be defined that express an illuminant's ability to realize red-green and blue-yellow contrasts of objects. For instance, calculation of t and d for daylight shows that on a gray day, color contrasts are actually reduced. By these measures, many common vapor-discharge illuminants systematically distort object colors. Because red-green contrasts contribute to border distinctness, and both types of color contrast contribute to brightness, such systematic distortions probably affect the overall clarity and brightness of what is perceived visually, Experimental data are consistent with this idea. In relation to color-constancy (retinex) experiments, it is approximately true that the visual system discounts the color of an illuminant but not its t and d.

  16. What is a segment?

    PubMed Central

    2013-01-01

    Animals have been described as segmented for more than 2,000 years, yet a precise definition of segmentation remains elusive. Here we give the history of the definition of segmentation, followed by a discussion on current controversies in defining a segment. While there is a general consensus that segmentation involves the repetition of units along the anterior-posterior (a-p) axis, long-running debates exist over whether a segment can be composed of only one tissue layer, whether the most anterior region of the arthropod head is considered segmented, and whether and how the vertebrate head is segmented. Additionally, we discuss whether a segment can be composed of a single cell in a column of cells, or a single row of cells within a grid of cells. We suggest that ‘segmentation’ be used in its more general sense, the repetition of units with a-p polarity along the a-p axis, to prevent artificial classification of animals. We further suggest that this general definition be combined with an exact description of what is being studied, as well as a clearly stated hypothesis concerning the specific nature of the potential homology of structures. These suggestions should facilitate dialogue among scientists who study vastly differing segmental structures. PMID:24345042

  17. Spectral information and spatial color computation

    NASA Astrophysics Data System (ADS)

    Rizzi, Alessandro; Gadia, Davide; Marini, Daniele

    2005-01-01

    In real world no color exists. Only spectral light distributions interact to form the final color sensation. This paper presents preliminary experiments whose purpose is to test the robustness of a spatial color computation in relation to changes in the acquisition of spectral information. The basic idea is that human vision system has evolved into a robust system to acquire visual information, in this case the color, adapting to varying illumination conditions to guarantee color constancy. The presented experiments test changes in the output of a Retinex-derived tone mapping operator, varying illuminants and color matching function curves. Synthetic high dynamic range multispectral images have been computed by a photometric ray tracer using different illuminants. Then, using standard and modified color matching functions, a set of high dynamic range RGB images has been created. This set has been converted to standard RGB images using a linear tone mapping algorithm with no spatial color computation and one based on Retinex, performing a spatial color normalization. A discussion of the results is presented.

  18. Spectral information and spatial color computation

    NASA Astrophysics Data System (ADS)

    Rizzi, Alessandro; Gadia, Davide; Marini, Daniele

    2004-12-01

    In real world no color exists. Only spectral light distributions interact to form the final color sensation. This paper presents preliminary experiments whose purpose is to test the robustness of a spatial color computation in relation to changes in the acquisition of spectral information. The basic idea is that human vision system has evolved into a robust system to acquire visual information, in this case the color, adapting to varying illumination conditions to guarantee color constancy. The presented experiments test changes in the output of a Retinex-derived tone mapping operator, varying illuminants and color matching function curves. Synthetic high dynamic range multispectral images have been computed by a photometric ray tracer using different illuminants. Then, using standard and modified color matching functions, a set of high dynamic range RGB images has been created. This set has been converted to standard RGB images using a linear tone mapping algorithm with no spatial color computation and one based on Retinex, performing a spatial color normalization. A discussion of the results is presented.

  19. Color change as a potential behavioral strategy

    PubMed Central

    Korzan, Wayne J.; Robison, Rex R.; Zhao, Sheng; Fernald, Russell D.

    2008-01-01

    Within species, color morphs may enhance camouflage, improve communication and/or confer reproductive advantage. However, in the male cichlid Astatotilapia burtoni, body color may also signal a behavioral strategy. A. burtoni live in a lek-like social system in Lake Tanganyika, Africa where bright blue or yellow territorial (T) males (together ~ 10–30% of the population) are reproductively capable and defend territories containing food with a spawning site. In contrast, nonterritorial (NT) males are smaller, cryptically colored, shoal with females and have regressed gonads. Importantly, males switch between these social states depending on their success in aggressive encounters. Yellow and blue morphs were thought to be adaptations to particular habitats, but they co-exist both in nature and in the laboratory. Importantly, individual males can switch colors so we asked whether color influences behavioral and hormonal profiles. When pairing territorial males with opposite colored fish, yellow males became dominant over blue males significantly more frequently. Moreover, yellow T males had significantly higher levels of 11-ketotosterone than blue T males while only blue NT males had higher levels of the stress hormone cortisol compared to the other groups. Thus color differences alone predict dominance status and hormone profiles in T males. Since T males can and do change color, this suggests that A. burtoni may use color as a flexible behavioral strategy. PMID:18586245

  20. Deformable segmentation via sparse shape representation.

    PubMed

    Zhang, Shaoting; Zhan, Yiqiang; Dewan, Maneesh; Huang, Junzhou; Metaxas, Dimitris N; Zhou, Xiang Sean

    2011-01-01

    Appearance and shape are two key elements exploited in medical image segmentation. However, in some medical image analysis tasks, appearance cues are weak/misleading due to disease/artifacts and often lead to erroneous segmentation. In this paper, a novel deformable model is proposed for robust segmentation in the presence of weak/misleading appearance cues. Owing to the less trustable appearance information, this method focuses on the effective shape modeling with two contributions. First, a shape composition method is designed to incorporate shape prior on-the-fly. Based on two sparsity observations, this method is robust to false appearance information and adaptive to statistically insignificant shape modes. Second, shape priors are modeled and used in a hierarchical fashion. More specifically, by using affinity propagation method, our deformable surface is divided into multiple partitions, on which local shape models are built independently. This scheme facilitates a more compact shape prior modeling and hence a more robust and efficient segmentation. Our deformable model is applied on two very diverse segmentation problems, liver segmentation in PET-CT images and rodent brain segmentation in MR images. Compared to state-of-art methods, our method achieves better performance in both studies. PMID:21995060

  1. Color Me Understood.

    ERIC Educational Resources Information Center

    Harris, Judy J.

    2000-01-01

    Describes the "color system" as a way of grouping children into different personality types based on a certain color: orange, blue, green, and gold. Lists stress producers for specific color people. Asserts that, through making groups of different colors, children begin to see the various specialties others can bring to the group and learn to…

  2. Color identification testing device

    NASA Technical Reports Server (NTRS)

    Brawner, E. L.; Martin, R.; Pate, W.

    1970-01-01

    Testing device, which determines ability of a technician to identify color-coded electric wires, is superior to standard color blindness tests. It tests speed of wire selection, detects partial color blindness, allows rapid testing, and may be administered by a color blind person.

  3. Color: An Unsuspected Influence.

    ERIC Educational Resources Information Center

    Scargall, Hollie

    1999-01-01

    Discusses the appropriate use of colors in school libraries. Highlights include how colors affect students' learning and behavior; influences on users' moods; users' ages; the use of colors to bring out the best physical attributes; and the use of color for floor coverings, window treatments, furnishings, and accessories. (LRW)

  4. Segmented Trough Reflector

    NASA Technical Reports Server (NTRS)

    Szmyd, W. R.

    1985-01-01

    Segmented troughlike reflector for solar cells approach concentration effectiveness of true parabolic reflector yet simpler and less expensive. Walls of segmented reflector composed of reflective aluminized membrane. Lengthwise guide wire applies tension to each wall, thereby dividing each into two separate planes. Planes tend to focus Sunlight on solar cells at center of trough between walls. Segmented walls provide higher Sunlight concentration ratios than do simple walls.

  5. A Retinal Mechanism Inspired Color Constancy Model.

    PubMed

    Zhang, Xian-Shi; Gao, Shao-Bing; Li, Ruo-Xuan; Du, Xin-Yu; Li, Chao-Yi; Li, Yong-Jie

    2016-03-01

    In this paper, we propose a novel model for the computational color constancy, inspired by the amazing ability of the human vision system (HVS) to perceive the color of objects largely constant as the light source color changes. The proposed model imitates the color processing mechanisms in the specific level of the retina, the first stage of the HVS, from the adaptation emerging in the layers of cone photoreceptors and horizontal cells (HCs) to the color-opponent mechanism and disinhibition effect of the non-classical receptive field in the layer of retinal ganglion cells (RGCs). In particular, HC modulation provides a global color correction with cone-specific lateral gain control, and the following RGCs refine the processing with iterative adaptation until all the three opponent channels reach their stable states (i.e., obtain stable outputs). Instead of explicitly estimating the scene illuminant(s), such as most existing algorithms, our model directly removes the effect of scene illuminant. Evaluations on four commonly used color constancy data sets show that the proposed model produces competitive results in comparison with the state-of-the-art methods for the scenes under either single or multiple illuminants. The results indicate that single opponency, especially the disinhibitory effect emerging in the receptive field's subunit-structured surround of RGCs, plays an important role in removing scene illuminant(s) by inherently distinguishing the spatial structures of surfaces from extensive illuminant(s). PMID:26766375

  6. A Raven in a Coal Scuttle: Theodore Roosevelt & the Animal Coloration Controversy.

    ERIC Educational Resources Information Center

    Hendrick, Robert

    1995-01-01

    Recounts a debate between Theodore Roosevelt and Abbott Thayer in 1909-12 over whether animal coloration was an adaptation resulting from natural selection or whether the animal's environment acted directly on it to form its color patterns. (ZWH)

  7. Fully automatic segmentation of complex organ systems: example of trachea, esophagus and heart segmentation in CT images

    NASA Astrophysics Data System (ADS)

    Meyer, Carsten; Peters, Jochen; Weese, Jürgen

    2011-03-01

    Automatic segmentation is a prerequisite to efficiently analyze the large amount of image data produced by modern imaging modalities. Many algorithms exist to segment individual organs or organ systems. However, new clinical applications and the progress in imaging technology will require the segmentation of more and more complex organ systems composed of a number of substructures, e.g., the heart, the trachea, and the esophagus. The goal of this work is to demonstrate that such complex organ systems can be successfully segmented by integrating the individual organs into a general model-based segmentation framework, without tailoring the core adaptation engine to the individual organs. As an example, we address the fully automatic segmentation of the trachea (around its main bifurcation, including the proximal part of the two main bronchi) and the esophagus in addition to the heart with all chambers and attached major vessels. To this end, we integrate the trachea and the esophagus into a model-based cardiac segmentation framework. Specifically, in a first parametric adaptation step of the segmentation workflow, the trachea and the esophagus share global model transformations with adjacent heart structures. This allows to obtain a robust, approximate segmentation for the trachea even if it is only partly inside the field-of-view, and for the esophagus in spite of limited contrast. The segmentation is then refined in a subsequent deformable adaptation step. We obtained a mean segmentation error of about 0.6mm for the trachea and 2.3mm for the esophagus on a database of 23 volumetric cardiovascular CT images. Furthermore, we show by quantitative evaluation that our integrated framework outperforms individual esophagus segmentation, and individual trachea segmentation if the trachea is only partly inside the field-of-view.

  8. Impact assisted segmented cutterhead

    DOEpatents

    Morrell, Roger J.; Larson, David A.; Ruzzi, Peter L.

    1992-01-01

    An impact assisted segmented cutterhead device is provided for cutting various surfaces from coal to granite. The device comprises a plurality of cutting bit segments deployed in side by side relationship to form a continuous cutting face and a plurality of impactors individually associated with respective cutting bit segments. An impactor rod of each impactor connects that impactor to the corresponding cutting bit segment. A plurality of shock mounts dampening the vibration from the associated impactor. Mounting brackets are used in mounting the cutterhead to a base machine.

  9. Adapting to the Environment.

    ERIC Educational Resources Information Center

    Kovach, Amy L.

    2003-01-01

    Presents an activity on natural selection and how the peppered moth's adaptive values for their colors changed during the Industrial Revolution in Manchester, England, influencing their survival and ultimately affecting the survival of their offspring. Includes activity objectives. (Author/KHR)

  10. Molecular evolution of color vision in vertebrates.

    PubMed

    Yokoyama, Shozo

    2002-10-30

    Visual systems of vertebrates exhibit a striking level of diversity, reflecting their adaptive responses to various color environments. The photosensitive molecules, visual pigments, can be synthesized in vitro and their absorption spectra can be determined. Comparing the amino acid sequences and absorption spectra of various visual pigments, we can identify amino acid changes that have modified the absorption spectra of visual pigments. These hypotheses can then be tested using the in vitro assay. This approach has been a powerful tool in elucidating not only the molecular bases of color vision, but the processes of adaptive evolution at the molecular level.

  11. Motion and color analysis for animat perception

    SciTech Connect

    Rabie, T.F.; Terzopoulos, D.

    1996-12-31

    We propose novel gaze control algorithms for active perception in mobile autonomous agents with directable, foveated vision sensors. Our agents are realistic artificial animals, or animals, situated in physics-based virtual worlds. Their active perception systems continuously analyze photorealistic retinal image streams to glean information useful for controlling the animal`s eyes and body. The vision system computes optical flow and segments moving targets in the low-resolution visual periphery. It then matches segmented targets against mental models of colored objects of interest. The eyes saccade to increase acuity by foveating objects, The resulting sensorimotor control loop supports complex behaviors, such as predation.

  12. Assessment of left ventricular regional wall motion by color kinesis technique: comparison with angiographic findings.

    PubMed

    Vermes, E; Guyon, P; Weingrod, M; Otmani, A; Soussana, C; Halphen, C; Leroy, G; Haïat, R

    2000-08-01

    The analysis of segmental wall motion using two-dimensional (2-D) echocardiography is subjective with high interobserver variability. Color kinesis is a new technique providing a color-encoded map of endocardial motion. We evaluated the accuracy of color kinesis and 2-D for assessment of regional asynergy compared with left ventricular angiography as a reference method. Fifteen patients admitted for myocardial infarction were studied by echocardiography the day before left ventricular angiography. The left ventricle was divided into seven segments. Each segment was classified by two independent observers as normal or abnormal in 2-D and color kinesis. Accuracy of color kinesis and 2-D was evaluated and compared to left ventricular angiography. Color kinesis is significantly superior to 2-D for all seven segments (mean 0.80/0.68, P = 0.05), except for the septum (0.67/0.60, P = NS). Interobserver variability studied by chi-square statistic is lower with color kinesis (0.70) than with 2-D (0.57). We conclude that these data suggest that color kinesis is a useful method for assessing systolic wall motion in all segments, except the septum and for improving the accuracy of segmental ventricular function and interobserver variability.

  13. Microscale halftone color image analysis: perspective of spectral color prediction modeling

    NASA Astrophysics Data System (ADS)

    Rahaman, G. M. Atiqur; Norberg, Ole; Edström, Per

    2014-01-01

    A method has been proposed, whereby k-means clustering technique is applied to segment microscale single color halftone image into three components—solid ink, ink/paper mixed area and unprinted paper. The method has been evaluated using impact (offset) and non-impact (electro-photography) based single color prints halftoned by amplitude modulation (AM) and frequency modulation (FM) technique. The print samples have also included a range of variations in paper substrates. The colors of segmented regions have been analyzed in CIELAB color space to reveal the variations, in particular those present in mixed regions. The statistics of intensity distribution in the segmented areas have been utilized to derive expressions that can be used to calculate simple thresholds. However, the segmented results have been employed to study dot gain in comparison with traditional estimation technique using Murray-Davies formula. The performance of halftone reflectance prediction by spectral Murray-Davies model has been reported using estimated and measured parameters. Finally, a general idea has been proposed to expand the classical Murray-Davies model based on experimetal observations. Hence, the present study primarily presents the outcome of experimental efforts to characterize halftone print media interactions in respect to the color prediction models. Currently, most regression-based color prediction models rely on mathematical optimization to estimate the parameters using measured average reflectance of a large area compared to the dot size. While this general approach has been accepted as a useful tool, experimental investigations can enhance understanding of the physical processes and facilitate exploration of new modeling strategies. Furthermore, reported findings may help reduce the required number of samples that are printed and measured in the process of multichannel printer characterization and calibration.

  14. Texture descriptors based on adaptive neighborhoods for classification of pigmented skin lesions

    NASA Astrophysics Data System (ADS)

    González-Castro, Víctor; Debayle, Johan; Wazaefi, Yanal; Rahim, Mehdi; Gaudy-Marqueste, Caroline; Grob, Jean-Jacques; Fertil, Bernard

    2015-11-01

    Different texture descriptors are proposed for the automatic classification of skin lesions from dermoscopic images. They are based on color texture analysis obtained from (1) color mathematical morphology (MM) and Kohonen self-organizing maps (SOMs) or (2) local binary patterns (LBPs), computed with the use of local adaptive neighborhoods of the image. Neither of these two approaches needs a previous segmentation process. In the first proposed descriptor, the adaptive neighborhoods are used as structuring elements to carry out adaptive MM operations which are further combined by using Kohonen SOM; this has been compared with a nonadaptive version. In the second one, the adaptive neighborhoods enable geometrical feature maps to be defined, from which LBP histograms are computed. This has also been compared with a classical LBP approach. A receiver operating characteristics analysis of the experimental results shows that the adaptive neighborhood-based LBP approach yields the best results. It outperforms the nonadaptive versions of the proposed descriptors and the dermatologists' visual predictions.

  15. Assessment of left ventricular dyssynergy by color kinesis.

    PubMed

    Vitarelli, A; Sciomer, S; Penco, M; Dagianti, A; Pugliese, M

    1998-06-18

    Color kinesis is a new echocardiographic technique based on acoustic quantification. It has been developed to facilitate the ability to identify contraction abnormalities and has been incorporated into a commercially available ultrasound imaging system. The potential of this technique to improve the qualitative and quantitative assessment of wall motion abnormalities is described. Evaluation of color-encoded images allows detection of decreased amplitude of endocardial motion in abnormally contracting segments as well as a shorter time of endocardial excursion in segments with severely decreased motion. Compared with off-line quantitative studies, color kinesis has the advantage to be used on-line, without time-consuming manual tracing of endocardial boundaries. In addition, a single end-systolic color image contains the entire picture of spatial and temporal contraction and can be digitally stored and retrieved. In patients with proven coronary artery disease, color kinesis had a sensitivity of 88%, a specificity of 77%, and an overall accuracy of 86% in identifying the presence of segmental dysfunction. The practical application of color kinesis might be to improve our ability to distinguish normal from hypokinesis, something that has always been difficult in clinical echocardiography. Segmental analysis of color kinesis images allows objective detection of dobutamine-induced regional wall motion abnormalities in agreement with conventional visual interpretation of the corresponding 2-dimensional views. A method for objective assessment of wall dynamics during dobutamine stress echocardiography would be of particular clinical value, because these images are even more difficult to interpret than conventional echocardiograms. Quantitative assessment of diastolic function may allow objective evaluation of segmental relaxation abnormalities, especially under conditions of pharmacologic stress testing. Acquisition of color kinesis images during dobutamine stress

  16. Segmentation of the human spinal cord.

    PubMed

    De Leener, Benjamin; Taso, Manuel; Cohen-Adad, Julien; Callot, Virginie

    2016-04-01

    Segmenting the spinal cord contour is a necessary step for quantifying spinal cord atrophy in various diseases. Delineating gray matter (GM) and white matter (WM) is also useful for quantifying GM atrophy or for extracting multiparametric MRI metrics into specific WM tracts. Spinal cord segmentation in clinical research is not as developed as brain segmentation, however with the substantial improvement of MR sequences adapted to spinal cord MR investigations, the field of spinal cord MR segmentation has advanced greatly within the last decade. Segmentation techniques with variable accuracy and degree of complexity have been developed and reported in the literature. In this paper, we review some of the existing methods for cord and WM/GM segmentation, including intensity-based, surface-based, and image-based methods. We also provide recommendations for validating spinal cord segmentation techniques, as it is important to understand the intrinsic characteristics of the methods and to evaluate their performance and limitations. Lastly, we illustrate some applications in the healthy and pathological spinal cord. One conclusion of this review is that robust and automatic segmentation is clinically relevant, as it would allow for longitudinal and group studies free from user bias as well as reproducible multicentric studies in large populations, thereby helping to further our understanding of the spinal cord pathophysiology and to develop new criteria for early detection of subclinical evolution for prognosis prediction and for patient management. Another conclusion is that at the present time, no single method adequately segments the cord and its substructure in all the cases encountered (abnormal intensities, loss of contrast, deformation of the cord, etc.). A combination of different approaches is thus advised for future developments, along with the introduction of probabilistic shape models. Maturation of standardized frameworks, multiplatform availability, inclusion

  17. Evidence for color and luminance invariance of global form mechanisms.

    PubMed

    Rentzeperis, Ilias; Kiper, Daniel C

    2010-01-01

    Human visual cortex contains mechanisms that pool local orientation information over large areas of visual space to support percepts of global form. Initial studies concluded that some of these mechanisms are cue invariant, in that they yield form percepts irrespective of whether the visual signals contain luminance or chromatic information. Later studies reported that these mechanisms are chromatically selective, albeit with a broad tuning in color space. We used Glass patterns and the phenomenon of adaptation to determine whether Glass pattern perception is mediated by mechanisms that are color and/or luminance selective, or not. Subjects were adapted to either a radial or concentric Glass pattern of a given color or luminance polarity. We measured the effect of adaptation on subsequent detection of Glass patterns with the same or different visual attributes. Our results show that adapting to a concentric or radial pattern significantly elevates threshold for the subsequent detection of patterns of the same form, irrespective of their color or luminance polarity, but that adaptation to luminance leads to higher threshold elevations than adaptation to color. We conclude that Glass pattern perception is mediated by perceptual mechanisms that are color invariant but not totally insensitive to the difference between color and luminance information.

  18. Hospital benefit segmentation.

    PubMed

    Finn, D W; Lamb, C W

    1986-12-01

    Market segmentation is an important topic to both health care practitioners and researchers. The authors explore the relative importance that health care consumers attach to various benefits available in a major metropolitan area hospital. The purposes of the study are to test, and provide data to illustrate, the efficacy of one approach to hospital benefit segmentation analysis.

  19. Biotechnological production of colorants.

    PubMed

    de Boer, Lex

    2014-01-01

    The color of food and drinks is important, as it is associated with freshness and taste. Despite that natural colorants are more expensive to produce, less stable to heat and light, and less consistent in color range, natural colorants have been gaining market share in recent years. The background is that artificial colorants are often associated with negative health aspects. Considerable progress has been made towards the fermentative production of some colorants. Because colorant biosynthesis is under close metabolic control, extensive strain and process development are needed in order to establish an economical production process. Another approach is the synthesis of colors by means of biotransformation of adequate precursors. Algae represent a promising group of microorganisms that have shown a high potential for the production of different colorants, and dedicated fermentation and downstream technologies have been developed. This chapter reviews the available information with respect to these approaches. PMID:24037500

  20. Color rendering indices in global illumination methods

    NASA Astrophysics Data System (ADS)

    Geisler-Moroder, David; Dür, Arne

    2009-02-01

    Human perception of material colors depends heavily on the nature of the light sources used for illumination. One and the same object can cause highly different color impressions when lit by a vapor lamp or by daylight, respectively. Based on state-of-the-art colorimetric methods we present a modern approach for calculating color rendering indices (CRI), which were defined by the International Commission on Illumination (CIE) to characterize color reproduction properties of illuminants. We update the standard CIE method in three main points: firstly, we use the CIELAB color space, secondly, we apply a Bradford transformation for chromatic adaptation, and finally, we evaluate color differences using the CIEDE2000 total color difference formula. Moreover, within a real-world scene, light incident on a measurement surface is composed of a direct and an indirect part. Neumann and Schanda1 have shown for the cube model that interreflections can influence the CRI of an illuminant. We analyze how color rendering indices vary in a real-world scene with mixed direct and indirect illumination and recommend the usage of a spectral rendering engine instead of an RGB based renderer for reasons of accuracy of CRI calculations.

  1. Carotenoid-based coloration in cichlid fishes

    PubMed Central

    Sefc, Kristina M.; Brown, Alexandria C.; Clotfelter, Ethan D.

    2014-01-01

    Animal colors play important roles in communication, ecological interactions and speciation. Carotenoid pigments are responsible for many yellow, orange and red hues in animals. Whereas extensive knowledge on the proximate mechanisms underlying carotenoid coloration in birds has led to testable hypotheses on avian color evolution and signaling, much less is known about the expression of carotenoid coloration in fishes. Here, we promote cichlid fishes (Perciformes: Cichlidae) as a system in which to study the physiological and evolutionary significance of carotenoids. Cichlids include some of the best examples of adaptive radiation and color pattern diversification in vertebrates. In this paper, we examine fitness correlates of carotenoid pigmentation in cichlids and review hypotheses regarding the signal content of carotenoid-based ornaments. Carotenoid-based coloration is influenced by diet and body condition and is positively related to mating success and social dominance. Gaps in our knowledge are discussed in the last part of this review, particularly in the understanding of carotenoid metabolism pathways and the genetics of carotenoid coloration. We suggest that carotenoid metabolism and transport are important proximate mechanisms responsible for individual and population-differences in cichlid coloration that may ultimately contribute to diversification and speciation. PMID:24667558

  2. Robust image modeling technique with a bioluminescence image segmentation application

    NASA Astrophysics Data System (ADS)

    Zhong, Jianghong; Wang, Ruiping; Tian, Jie

    2009-02-01

    A robust pattern classifier algorithm for the variable symmetric plane model, where the driving noise is a mixture of a Gaussian and an outlier process, is developed. The veracity and high-speed performance of the pattern recognition algorithm is proved. Bioluminescence tomography (BLT) has recently gained wide acceptance in the field of in vivo small animal molecular imaging. So that it is very important for BLT to how to acquire the highprecision region of interest in a bioluminescence image (BLI) in order to decrease loss of the customers because of inaccuracy in quantitative analysis. An algorithm in the mode is developed to improve operation speed, which estimates parameters and original image intensity simultaneously from the noise corrupted image derived from the BLT optical hardware system. The focus pixel value is obtained from the symmetric plane according to a more realistic assumption for the noise sequence in the restored image. The size of neighborhood is adaptive and small. What's more, the classifier function is base on the statistic features. If the qualifications for the classifier are satisfied, the focus pixel intensity is setup as the largest value in the neighborhood.Otherwise, it will be zeros.Finally,pseudo-color is added up to the result of the bioluminescence segmented image. The whole process has been implemented in our 2D BLT optical system platform and the model is proved.

  3. Semi-automatic segmentation and tracking of CVH data.

    PubMed

    Qu, Yingge; Heng, Pheng Ann; Wong, Tien-Tsin

    2006-01-01

    Construction of speed function is crucial in applying level set method for medical image segmentation. We present a unified approach for segmenting and tracking of the high-resolution Chinese Visible Human (CVH) data. The underlying link of these two parts relies on the proposed variational framework for the speed function. Our proposed method can be applied to segmenting the first slice of the volume data, in the first step; It can also be adapted to track the boundaries of the homogeneous organs in the following serial images. In addition to promising segmentation results, the tracking procedure shows the advantage of less amount of user intervention.

  4. Image segmentation and 3D visualization for MRI mammography

    NASA Astrophysics Data System (ADS)

    Li, Lihua; Chu, Yong; Salem, Angela F.; Clark, Robert A.

    2002-05-01

    MRI mammography has a number of advantages, including the tomographic, and therefore three-dimensional (3-D) nature, of the images. It allows the application of MRI mammography to breasts with dense tissue, post operative scarring, and silicon implants. However, due to the vast quantity of images and subtlety of difference in MR sequence, there is a need for reliable computer diagnosis to reduce the radiologist's workload. The purpose of this work was to develop automatic breast/tissue segmentation and visualization algorithms to aid physicians in detecting and observing abnormalities in breast. Two segmentation algorithms were developed: one for breast segmentation, the other for glandular tissue segmentation. In breast segmentation, the MRI image is first segmented using an adaptive growing clustering method. Two tracing algorithms were then developed to refine the breast air and chest wall boundaries of breast. The glandular tissue segmentation was performed using an adaptive thresholding method, in which the threshold value was spatially adaptive using a sliding window. The 3D visualization of the segmented 2D slices of MRI mammography was implemented under IDL environment. The breast and glandular tissue rendering, slicing and animation were displayed.

  5. Radiation coloration resistant glass

    DOEpatents

    Tomozawa, M.; Watson, E.B.; Acocella, J.

    1986-11-04

    A radiation coloration resistant glass is disclosed which is used in a radiation environment sufficient to cause coloration in most forms of glass. The coloration resistant glass includes higher proportions by weight of water and has been found to be extremely resistant to color change when exposed to such radiation levels. The coloration resistant glass is free of cerium oxide and has more than about 0.5% by weight water content. Even when exposed to gamma radiation of more than 10[sup 7] rad, the coloration resistant glass does not lose transparency. 3 figs.

  6. Radiation coloration resistant glass

    DOEpatents

    Tomozawa, Minoru; Watson, E. Bruce; Acocella, John

    1986-01-01

    A radiation coloration resistant glass is disclosed which is used in a radiation environment sufficient to cause coloration in most forms of glass. The coloration resistant glass includes higher proportions by weight of water and has been found to be extremely resistant to color change when exposed to such radiation levels. The coloration resistant glass is free of cerium oxide and has more than about 0.5% by weight water content. Even when exposed to gamma radiation of more than 10.sup.7 rad, the coloration resistant glass does not lose transparency.

  7. Preferred skin color enhancement for photographic color reproduction

    NASA Astrophysics Data System (ADS)

    Zeng, Huanzhao; Luo, Ronnier

    2011-01-01

    Skin tones are the most important colors among the memory color category. Reproducing skin colors pleasingly is an important factor in photographic color reproduction. Moving skin colors toward their preferred skin color center improves the color preference of skin color reproduction. Several methods to morph skin colors to a smaller preferred skin color region has been reported in the past. In this paper, a new approach is proposed to further improve the result of skin color enhancement. An ellipsoid skin color model is applied to compute skin color probabilities for skin color detection and to determine a weight for skin color adjustment. Preferred skin color centers determined through psychophysical experiments were applied for color adjustment. Preferred skin color centers for dark, medium, and light skin colors are applied to adjust skin colors differently. Skin colors are morphed toward their preferred color centers. A special processing is applied to avoid contrast loss in highlight. A 3-D interpolation method is applied to fix a potential contouring problem and to improve color processing efficiency. An psychophysical experiment validates that the method of preferred skin color enhancement effectively identifies skin colors, improves the skin color preference, and does not objectionably affect preferred skin colors in original images.

  8. Color transfer between high-dynamic-range images

    NASA Astrophysics Data System (ADS)

    Hristova, Hristina; Cozot, Rémi; Le Meur, Olivier; Bouatouch, Kadi

    2015-09-01

    Color transfer methods alter the look of a source image with regards to a reference image. So far, the proposed color transfer methods have been limited to low-dynamic-range (LDR) images. Unlike LDR images, which are display-dependent, high-dynamic-range (HDR) images contain real physical values of the world luminance and are able to capture high luminance variations and finest details of real world scenes. Therefore, there exists a strong discrepancy between the two types of images. In this paper, we bridge the gap between the color transfer domain and the HDR imagery by introducing HDR extensions to LDR color transfer methods. We tackle the main issues of applying a color transfer between two HDR images. First, to address the nature of light and color distributions in the context of HDR imagery, we carry out modifications of traditional color spaces. Furthermore, we ensure high precision in the quantization of the dynamic range for histogram computations. As image clustering (based on light and colors) proved to be an important aspect of color transfer, we analyze it and adapt it to the HDR domain. Our framework has been applied to several state-of-the-art color transfer methods. Qualitative experiments have shown that results obtained with the proposed adaptation approach exhibit less artifacts and are visually more pleasing than results obtained when straightforwardly applying existing color transfer methods to HDR images.

  9. Color contrast enhancement method of infrared polarization fused image

    NASA Astrophysics Data System (ADS)

    Yang, Fan; Xie, Chen

    2015-10-01

    As the traditional color fusion method based on color transfer algorithm has an issue that the color of target and background is similar. A kind of infrared polarization image color fusion method based on color contrast enhancement was proposed. Firstly the infrared radiation intensity image and the polarization image were color fused, and then color transfer technology was used between color reference image and initial fused image in the YCbCr color space. Secondly Otsu segmentation method was used to extract the target area image from infrared polarization image. Lastly the H,S,I component of the color fusion image which obtained by color transfer was adjusted to obtain the final fused image by using target area in the HSI space. Experimental results show that, the fused result which obtained by the proposed method is rich in detail and makes the contrast of target and background more outstanding. And then the ability of target detection and identification can be improved by the method.

  10. Color and Streptomycetes1

    PubMed Central

    Pridham, Thomas G.

    1965-01-01

    A report summarizing the results of an international workshop on determination of color of streptomycetes is presented. The results suggest that the color systems which seem most practically appealing and effective to specialists on actinomycetes are those embracing a limited number of color names and groups. The broad groupings allow placement of isolates into reasonably well-defined categories based on color of aerial mycelium. Attempts to expand such systems (more color groups) lead to difficulties. It is common knowledge that many, if not all, of the individual groups would in these broad systems contain strains that differ in many other respects, e.g., spore-wall ornamentation, color of vegetative (substratal) mycelium, morphology of chains of spores, and numerous physiological criteria. Also, cultures of intermediate color can be found, which makes placement difficult. As it now stands, color as a criterion for characterization of streptomycetes and streptoverticillia is in questionable status. Although much useful color information can be obtained by an individual, the application of this information to that in the literature or its use in communication with other individuals leaves much to be desired. More objective methods of color determination are needed. At present, the most effective method that could be used internationally is the color-wheel system of Tresner and Backus. Furthermore, the significance of color in speciation of these organisms is an open question. Obviously, more critical work on the color problem is needed. PMID:14264847

  11. Why color synesthesia involves more than color.

    PubMed

    Eagleman, David M; Goodale, Melvyn A

    2009-07-01

    Synesthesia is a perceptual phenomenon in which stimuli can trigger experiences in non-stimulated sensory dimensions. The literature has focused on forms of synesthesia in which stimuli (e.g. music, touch or numbers) trigger experiences of color. Generally missing, however, is the observation that synesthetic colors are often accompanied by the experience of other surface properties such as texture (e.g. a visual experience of linen, metal, marble, velvet, etc). Current frameworks for synesthesia focus only upon the involvement of brain regions such as the V4 color complex. Here, we propose an expanded framework that includes brain regions involved in the encoding of material properties - specifically, larger regions of the medial ventral stream. The overlap of visual texture and color processing within ventral regions might explain why many experiences of synesthesia extend beyond color to other material properties.

  12. Pancreas and cyst segmentation

    NASA Astrophysics Data System (ADS)

    Dmitriev, Konstantin; Gutenko, Ievgeniia; Nadeem, Saad; Kaufman, Arie

    2016-03-01

    Accurate segmentation of abdominal organs from medical images is an essential part of surgical planning and computer-aided disease diagnosis. Many existing algorithms are specialized for the segmentation of healthy organs. Cystic pancreas segmentation is especially challenging due to its low contrast boundaries, variability in shape, location and the stage of the pancreatic cancer. We present a semi-automatic segmentation algorithm for pancreata with cysts. In contrast to existing automatic segmentation approaches for healthy pancreas segmentation which are amenable to atlas/statistical shape approaches, a pancreas with cysts can have even higher variability with respect to the shape of the pancreas due to the size and shape of the cyst(s). Hence, fine results are better attained with semi-automatic steerable approaches. We use a novel combination of random walker and region growing approaches to delineate the boundaries of the pancreas and cysts with respective best Dice coefficients of 85.1% and 86.7%, and respective best volumetric overlap errors of 26.0% and 23.5%. Results show that the proposed algorithm for pancreas and pancreatic cyst segmentation is accurate and stable.

  13. Keypoint Transfer Segmentation

    PubMed Central

    Toews, M.; Langs, G.; Wells, W.; Golland, P.

    2015-01-01

    We present an image segmentation method that transfers label maps of entire organs from the training images to the novel image to be segmented. The transfer is based on sparse correspondences between keypoints that represent automatically identified distinctive image locations. Our segmentation algorithm consists of three steps: (i) keypoint matching, (ii) voting-based keypoint labeling, and (iii) keypoint-based probabilistic transfer of organ label maps. We introduce generative models for the inference of keypoint labels and for image segmentation, where keypoint matches are treated as a latent random variable and are marginalized out as part of the algorithm. We report segmentation results for abdominal organs in whole-body CT and in contrast-enhanced CT images. The accuracy of our method compares favorably to common multi-atlas segmentation while offering a speed-up of about three orders of magnitude. Furthermore, keypoint transfer requires no training phase or registration to an atlas. The algorithm’s robustness enables the segmentation of scans with highly variable field-of-view. PMID:26221677

  14. Automatic and Quantitative Measurement of Collagen Gel Contraction Using Model-Guided Segmentation.

    PubMed

    Chen, Hsin-Chen; Yang, Tai-Hua; Thoreson, Andrew R; Zhao, Chunfeng; Amadio, Peter C; Sun, Yung-Nien; Su, Fong-Chin; An, Kai-Nan

    2013-08-01

    Quantitative measurement of collagen gel contraction plays a critical role in the field of tissue engineering because it provides spatial-temporal assessment (e.g., changes of gel area and diameter during the contraction process) reflecting the cell behaviors and tissue material properties. So far the assessment of collagen gels relies on manual segmentation, which is time-consuming and suffers from serious intra- and inter-observer variability. In this study, we propose an automatic method combining various image processing techniques to resolve these problems. The proposed method first detects the maximal feasible contraction range of circular references (e.g., culture dish) and avoids the interference of irrelevant objects in the given image. Then, a three-step color conversion strategy is applied to normalize and enhance the contrast between the gel and background. We subsequently introduce a deformable circular model (DCM) which utilizes regional intensity contrast and circular shape constraint to locate the gel boundary. An adaptive weighting scheme was employed to coordinate the model behavior, so that the proposed system can overcome variations of gel boundary appearances at different contraction stages. Two measurements of collagen gels (i.e., area and diameter) can readily be obtained based on the segmentation results. Experimental results, including 120 gel images for accuracy validation, showed high agreement between the proposed method and manual segmentation with an average dice similarity coefficient larger than 0.95. The results also demonstrated obvious improvement in gel contours obtained by the proposed method over two popular, generic segmentation methods. PMID:24092954

  15. Background Subtraction Based on Color and Depth Using Active Sensors

    PubMed Central

    Fernandez-Sanchez, Enrique J.; Diaz, Javier; Ros, Eduardo

    2013-01-01

    Depth information has been used in computer vision for a wide variety of tasks. Since active range sensors are currently available at low cost, high-quality depth maps can be used as relevant input for many applications. Background subtraction and video segmentation algorithms can be improved by fusing depth and color inputs, which are complementary and allow one to solve many classic color segmentation issues. In this paper, we describe one fusion method to combine color and depth based on an advanced color-based algorithm. This technique has been evaluated by means of a complete dataset recorded with Microsoft Kinect, which enables comparison with the original method. The proposed method outperforms the others in almost every test, showing more robustness to illumination changes, shadows, reflections and camouflage. PMID:23857259

  16. Combined blazed grating and microlens array for color image sensing

    NASA Astrophysics Data System (ADS)

    Hirano, Tadayuki; Shimatani, Naoko; Kintaka, Kenji; Nishio, Kenzo; Awatsuji, Yasuhiro; Ura, Shogo

    2014-03-01

    A combination of a blazed grating and a microlens array is discussed for high-efficiency color image sensing. Each image segment includes a microlens with blazed grating and three photodiodes assigned to red, green, and blue colors. Color-splitting performances of design examples were simulated by the two-dimensional finite-difference time-domain method. It was found that the spectral characteristics were similar to the ideal NTSC specifications for a segment size of 10 µm with a polymer microlens and a TiO2 blazed grating. A prototype consisting of a honeycomb array of microlenses of 15 µm cell diameter and a TiO2 blaze grating of 1.22 µm period and 0.35 µm height was fabricated and characterized. Power utilization efficiency of about 60% was predicted theoretically and estimated experimentally, which is much higher in comparison to a conventional image sensor utilizing color filters.

  17. Light, Color, and Mirrors.

    ERIC Educational Resources Information Center

    Tiburzi, Brian; Tamborino, Laurie; Parker, Gordon A.

    2000-01-01

    Describes an exercise in which students can use flashlights, mirrors, and colored paper to discover scientific principles regarding optics. Addresses the concepts of angles of incidence and reflection, colored vs. white light, and mirror images. (WRM)

  18. Developments in Color Micrographics.

    ERIC Educational Resources Information Center

    Hourdajian, Ara

    1983-01-01

    Summarizes recent progress in color micrographics, which has centered about the corporate development of new microfilms whose capacities for reproducing and sustaining color image far exceed those of their predecessors. (Author/EJS)

  19. Color vision: retinal blues.

    PubMed

    Johnston, Jamie; Esposti, Federico; Lagnado, Leon

    2012-08-21

    Two complementary studies have resolved the circuitry underlying green-blue color discrimination in the retina. A blue-sensitive interneuron provides the inhibitory signal required for computing green-blue color opponency.

  20. Color photography of Jupiter

    NASA Technical Reports Server (NTRS)

    Larson, S. M.; Fountain, J. W.; Mintor, R. B.

    1973-01-01

    Selected color photographs of Jupiter taken with the 154-cm Catalina reflector from October 1965 to September 1973 are presented. Eight oppositions are covered showing the developments in cloud belt structure and color distribution of the Jovian atmosphere.

  1. The Trouble with Color.

    ERIC Educational Resources Information Center

    Merchant, David

    1999-01-01

    Discusses problems with color quality in Web sites. Topics include differences in monitor settings, including contrast; amount of video RAM; user preference settings; browser-safe colors; cross-platform readability; and gamma values. (LRW)

  2. Using multimodal information for the segmentation of fluorescent micrographs with application to virology and microbiology.

    PubMed

    Held, Christian; Wenzel, Jens; Webel, Rike; Marschall, Manfred; Lang, Roland; Palmisano, Ralf; Wittenberg, Thomas

    2011-01-01

    In order to improve reproducibility and objectivity of fluorescence microscopy based experiments and to enable the evaluation of large datasets, flexible segmentation methods are required which are able to adapt to different stainings and cell types. This adaption is usually achieved by the manual adjustment of the segmentation methods parameters, which is time consuming and challenging for biologists with no knowledge on image processing. To avoid this, parameters of the presented methods automatically adapt to user generated ground truth to determine the best method and the optimal parameter setup. These settings can then be used for segmentation of the remaining images. As robust segmentation methods form the core of such a system, the currently used watershed transform based segmentation routine is replaced by a fast marching level set based segmentation routine which incorporates knowledge on the cell nuclei. Our evaluations reveal that incorporation of multimodal information improves segmentation quality for the presented fluorescent datasets.

  3. A new piston control strategy for segmented mirrors

    NASA Technical Reports Server (NTRS)

    Olivier, Philip D.

    1994-01-01

    One approach to the adaptive control of large segmented mirrors involves sending tilt commands to each segment and allowing each segment to minimize the distance between its edges and those of (all or some of) its neighbors. This approach has been adopted in the Phased Array Mirror, Extendible Large Aperture (PAMELA) testbed now located at NASA's Marshall Space Flight Center, Huntsville, AL. This approach minimizes (1) the communication between the sensors and the segment actuators and (2) computations required by the central controlling computer. This report discusses issues that large segmented mirrors built around the PAMELA concept (such as SELENE) will face when they migrate to integrated, and presumably to digital, on-segment computational ability and high bandwidth response.

  4. Biology of Skin Color.

    ERIC Educational Resources Information Center

    Corcos, Alain

    1983-01-01

    Information from scientific journals on the biology of skin color is discussed. Major areas addressed include: (1) biology of melanin, melanocytes, and melanosomes; (2) melanosome and human diversity; (3) genetics of skin color; and (4) skin color, geography, and natural selection. (JN)

  5. Sweetpotato Color Analyses

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Color is an important attribute that contributes to the appearance of a sweetpotato genotype. A consumer uses color, along with geometric attributes (e.g., gloss, luster, sheen, texture, opaqueness, shape), to subjectively evaluate the appearance of a sweetpotato root. Color can be quantified by t...

  6. Reimagining the Color Wheel

    ERIC Educational Resources Information Center

    Snyder, Jennifer

    2011-01-01

    Color wheels are a traditional project for many teachers. The author has used them in art appreciation classes for many years, but one problem she found when her pre-service art education students created colored wheels was that they were boring: simple circles, with pie-shaped pieces, which students either painted or colored in. This article…

  7. Low-level motion analysis of color and luminance for perception of 2D and 3D motion.

    PubMed

    Shioiri, Satoshi; Yoshizawa, Masanori; Ogiya, Mistuharu; Matsumiya, Kazumichi; Yaguchi, Hirohisa

    2012-01-01

    We investigated the low-level motion mechanisms for color and luminance and their integration process using 2D and 3D motion aftereffects (MAEs). The 2D and 3D MAEs obtained in equiluminant color gratings showed that the visual system has the low-level motion mechanism for color motion as well as for luminance motion. The 3D MAE is an MAE for motion in depth after monocular motion adaptation. Apparent 3D motion can be perceived after prolonged exposure of one eye to lateral motion because the difference in motion signal between the adapted and unadapted eyes generates interocular velocity differences (IOVDs). Since IOVDs cannot be analyzed by the high-level motion mechanism of feature tracking, we conclude that a low-level motion mechanism is responsible for the 3D MAE. Since we found different temporal frequency characteristics between the color and luminance stimuli, MAEs in the equiluminant color stimuli cannot be attributed to a residual luminance component in the color stimulus. Although a similar MAE was found with a luminance and a color test both for 2D and 3D motion judgments after adapting to either color or luminance motion, temporal frequency characteristics were different between the color and luminance adaptation. The visual system must have a low-level motion mechanism for color signals as for luminance ones. We also found that color and luminance motion signals are integrated monocularly before IOVD analysis, showing a cross adaptation effect between color and luminance stimuli. This was supported by an experiment with dichoptic presentations of color and luminance tests. In the experiment, color and luminance tests were presented in the different eyes dichoptically with four different combinations of test and adaptation: color or luminance test in the adapted eye after color or luminance adaptation. Findings of little or no influence of the adaptation/test combinations indicate the integration of color and luminance motion signals prior to the

  8. The evolution of color vision in insects.

    PubMed

    Briscoe, A D; Chittka, L

    2001-01-01

    We review the physiological, molecular, and neural mechanisms of insect color vision. Phylogenetic and molecular analyses reveal that the basic bauplan, UV-blue-green-trichromacy, appears to date back to the Devonian ancestor of all pterygote insects. There are variations on this theme, however. These concern the number of color receptor types, their differential expression across the retina, and their fine tuning along the wavelength scale. In a few cases (but not in many others), these differences can be linked to visual ecology. Other insects have virtually identical sets of color receptors despite strong differences in lifestyle. Instead of the adaptionism that has dominated visual ecology in the past, we propose that chance evolutionary processes, history, and constraints should be considered. In addition to phylogenetic analyses designed to explore these factors, we suggest quantifying variance between individuals and populations and using fitness measurements to test the adaptive value of traits identified in insect color vision systems.

  9. Image segmentation survey

    NASA Technical Reports Server (NTRS)

    Haralick, R. M.

    1982-01-01

    The methodologies and capabilities of image segmentation techniques are reviewed. Single linkage schemes, hybrid linkage schemes, centroid linkage schemes, histogram mode seeking, spatial clustering, and split and merge schemes are addressed.

  10. Adjacent segment disease.

    PubMed

    Virk, Sohrab S; Niedermeier, Steven; Yu, Elizabeth; Khan, Safdar N

    2014-08-01

    EDUCATIONAL OBJECTIVES As a result of reading this article, physicians should be able to: 1. Understand the forces that predispose adjacent cervical segments to degeneration. 2. Understand the challenges of radiographic evaluation in the diagnosis of cervical and lumbar adjacent segment disease. 3. Describe the changes in biomechanical forces applied to adjacent segments of lumbar vertebrae with fusion. 4. Know the risk factors for adjacent segment disease in spinal fusion. Adjacent segment disease (ASD) is a broad term encompassing many complications of spinal fusion, including listhesis, instability, herniated nucleus pulposus, stenosis, hypertrophic facet arthritis, scoliosis, and vertebral compression fracture. The area of the cervical spine where most fusions occur (C3-C7) is adjacent to a highly mobile upper cervical region, and this contributes to the biomechanical stress put on the adjacent cervical segments postfusion. Studies have shown that after fusion surgery, there is increased load on adjacent segments. Definitive treatment of ASD is a topic of continuing research, but in general, treatment choices are dictated by patient age and degree of debilitation. Investigators have also studied the risk factors associated with spinal fusion that may predispose certain patients to ASD postfusion, and these data are invaluable for properly counseling patients considering spinal fusion surgery. Biomechanical studies have confirmed the added stress on adjacent segments in the cervical and lumbar spine. The diagnosis of cervical ASD is complicated given the imprecise correlation of radiographic and clinical findings. Although radiological and clinical diagnoses do not always correlate, radiographs and clinical examination dictate how a patient with prolonged pain is treated. Options for both cervical and lumbar spine ASD include fusion and/or decompression. Current studies are encouraging regarding the adoption of arthroplasty in spinal surgery, but more long

  11. Squaring a Circular Segment

    ERIC Educational Resources Information Center

    Gordon, Russell

    2008-01-01

    Consider a circular segment (the smaller portion of a circle cut off by one of its chords) with chord length c and height h (the greatest distance from a point on the arc of the circle to the chord). Is there a simple formula involving c and h that can be used to closely approximate the area of this circular segment? Ancient Chinese and Egyptian…

  12. Segmented pyroelector detector

    DOEpatents

    Stotlar, S.C.; McLellan, E.J.

    1981-01-21

    A pyroelectric detector is described which has increased voltage output and improved responsivity over equivalent size detectors. The device comprises a plurality of edge-type pyroelectric detectors which have a length which is much greater than the width of the segments between the edge-type electrodes. External circuitry connects the pyroelectric detector segments in parallel to provide a single output which maintains 50 ohm impedance characteristics.

  13. Geometry Guided Segmentation

    NASA Astrophysics Data System (ADS)

    Dunn, Stanley M.; Liang, Tajen

    1989-03-01

    Our overall goal is to develop an image understanding system for automatically interpreting dental radiographs. This paper describes the module that integrates the intrinsic image data to form the region adjacency graph that represents the image. The specific problem is to develop a robust method for segmenting the image into small regions that do not overlap anatomical boundaries. Classical algorithms for finding homogeneous regions (i.e., 2 class segmentation or connected components) will not always yield correct results since blurred edges can cause adjacent anatomical regions to be labeled as one region. This defect is a problem in this and other applications where an object count is necessary. Our solution to the problem is to guide the segmentation by intrinsic properties of the constituent objects. The module takes a set of intrinsic images as arguments. A connected components-like algorithm is performed, but the connectivity relation is not 4- or 8-neighbor connectivity in binary images; the connectivity is defined in terms of the intrinsic image data. We shall describe both the classical method and the modified segmentation procedures, and present experiments using both algorithms. Our experiments show that for the dental radiographs a segmentation using gray level data in conjunction with edges of the surfaces of teeth give a robust and reliable segmentation.

  14. Segmenting patients and physicians using preferences from discrete choice experiments.

    PubMed

    Deal, Ken

    2014-01-01

    students. Those segments were very different-where one wanted substantial penalties against cyberbullies and were willing to devote time to a prevention program, while the other felt no need to be involved in prevention and wanted only minor penalties. Segmentation recognizes key differences in why patients and physicians prefer different health programs and treatments. A viable segmentation solution may lead to adapting prevention programs and treatments for each targeted segment and/or to educating and communicating to better inform those in each segment of the program/treatment benefits. Segment members' revealed preferences showing behavioral changes provide the ultimate basis for evaluating the segmentation benefits to the health organization. PMID:24327338

  15. [Segmentation, grouping and accentuation during stimuli perception].

    PubMed

    Sokolov, E N; Nezlina, N I

    2009-01-01

    The paper is concerned with grouping, segmentation and accentuation occurring in the processes of stimuli perception. An universal model of these events is based on vector coding in neuronal networks. Grouping is unification of objects or events into collections according to their similarity. Segmentation is separation of such groups up to small ensembles of units. In neuroscience grouping and segmentation are regarded as referred to neural mechanisms underlying perceptual and semantic processes resulting in a phenomenal attachment or separation. It is assumed that stimuli in neuronal nets are encoded by combinations of excitations of cardinal neurons constituting excitation vectors. Differences among stimuli are formed as absolute values of their excitation vector differences. The more different are stimuli the separate are their perceptual and semantic representations. The more similar are respective stimuli, the less is their separation. It suggests that stimuli having similar excitation vectors would be grouped together. On the contrary stimuli with opposed excitation vectors would be segmented and pushed to different ensembles. The vector encoding is expressed also for location in space. Thus spatial separation of objects is increasing with the increasing of their spatial excitation vector differences. The universal principle of vector encoding of differences can be illustrated by color contrast: differences of contrast colors rise with increase of their excitation vector differences. Objects having similar excitation vectors constitute a group accentuated due to summation of their excitation vectors. Groups of objects characterized by different excitation vectors are mutually accentuated by a contrast mechanism. A plastic accentuation depends on novelty of stimulation being habituated during repeated stimulus presentations.

  16. Comparison of Color Model in Cotton Image Under Conditions of Natural Light

    NASA Astrophysics Data System (ADS)

    Zhang, J. H.; Kong, F. T.; Wu, J. Z.; Wang, S. W.; Liu, J. J.; Zhao, P.

    Although the color images contain a large amount of information reflecting the species characteristics, different color models also get different information. The selection of color models is the key to separating crops from background effectively and rapidly. Taking the cotton images collected under natural light as the object, we convert the color components of RGB color model, HSL color model and YIQ color model respectively. Then, we use subjective evaluation and objective evaluation methods, evaluating the 9 color components of conversion. It is concluded that the Q component of the soil, straw and plastic film region gray values remain the same without larger fluctuation when using subjective evaluation method. In the objective evaluation, we use the variance method, average gradient method, gray prediction objective evaluation error statistics method and information entropy method respectively to find the minimum numerical of Q color component suitable for background segmentation.

  17. Industrial Color Inspection

    NASA Astrophysics Data System (ADS)

    McCamy, C. S.

    1986-10-01

    Color is a very important property of many products and an essential feature of some. The commercial value of color is evident in the fact that customers reject product that is satisfactory in every other way, but is not the right color. Color isrumerically specified, measured, and controlled just as length or weight are. It has three dimensions: Hue, Value, and Chroma, and may be represented in a three-dimensional space. Colors of objects depend on the illumination and pairs of colors may match in one light but not in another. Controlled illumination is required for color matching. Illuminants were standardized by the International Commission on Illumination (CIE). As a basis for color measurement, the CIE adopted three spectral sensitivity functions representing a standard observer. Color may be measured by instruments using standard illumination and simulating the standard observer. It is better to measure spectral reflectance or transmittance and compute colorimetric quantities. Color may be inspected on a production line and the data obtained can be used to control the process. When production cannot be controlled as precisely as required, product may be sorted by color.

  18. Watermarking spot colors

    NASA Astrophysics Data System (ADS)

    Alattar, Osama M.; Reed, Alastair M.

    2003-06-01

    Watermarking of printed materials has usually focused on process inks of cyan, magenta, yellow and black (CMYK). In packaging, almost three out of four printed materials include spot colors. Spot colors are special premixed inks, which can be produced in a vibrant range of colors, often outside the CMYK color gamut. In embedding a watermark into printed material, a common approach is to modify the luminance value of each pixel in the image. In the case of process color work pieces, the luminance change can be scaled to the C, M, Y and K channels using a weighting function, to produce the desired change in luminance. In the case of spot color art designs, there is only one channel available and the luminance change is applied to this channel. In this paper we develop a weighting function to embed the watermark signal across the range of different spot colors. This weighting function normalizes visibility effect and signal robustness across a wide range of different spot colors. It normalizes the signal robustness level over the range of an individual spot color"s intensity levels. Further, it takes into account the sensitivity of the capturing device to the different spot colors.

  19. Acquired color vision deficiency.

    PubMed

    Simunovic, Matthew P

    2016-01-01

    Acquired color vision deficiency occurs as the result of ocular, neurologic, or systemic disease. A wide array of conditions may affect color vision, ranging from diseases of the ocular media through to pathology of the visual cortex. Traditionally, acquired color vision deficiency is considered a separate entity from congenital color vision deficiency, although emerging clinical and molecular genetic data would suggest a degree of overlap. We review the pathophysiology of acquired color vision deficiency, the data on its prevalence, theories for the preponderance of acquired S-mechanism (or tritan) deficiency, and discuss tests of color vision. We also briefly review the types of color vision deficiencies encountered in ocular disease, with an emphasis placed on larger or more detailed clinical investigations.

  20. True Colors Shining Through

    NASA Technical Reports Server (NTRS)

    2004-01-01

    This image mosaic illustrates how scientists use the color calibration targets (upper left) located on both Mars Exploration Rovers to fine-tune the rovers' sense of color. In the center, spectra, or light signatures, acquired in the laboratory of the colored chips on the targets are shown as lines. Actual data from Mars Exploration Rover Spirit's panoramic camera is mapped on top of these lines as dots. The plot demonstrates that the observed colors of Mars match the colors of the chips, and thus approximate the red planet's true colors. This finding is further corroborated by the picture taken on Mars of the calibration target, which shows the colored chips as they would appear on Earth.

  1. Organization And Knowledge Representation In An Expert System For Scene Segmentation In Histologic Sections

    NASA Astrophysics Data System (ADS)

    Thompson, Deborah B.; Griswold, W. G.; Kuhn, William P.; Bartels, H. G.; Shoemaker, Richard L.; Bartels, Peter H.

    1989-06-01

    An expert system to guide scene segmentation in histologic sections is described. The system uses a semantic net for knowledge representation. At each node of the net, frames are associated to allow the staging of additional information. Scene segmentation is the result of model-based reasoning, supported by a digital image processing library and adaptive selection of segmentation procedures to resolve local segmentation difficulties.

  2. Segmented Versus Traditional Crisis Intervention Team Training.

    PubMed

    Cuddeback, Gary S; Kurtz, Robert A; Wilson, Amy Blank; VanDeinse, Tonya; Burgin, Stacey E

    2016-09-01

    There are more than 2,500 Crisis Intervention Teams (CIT) in operation across the country. Results of research on the effectiveness and impact of CIT are mixed. One aspect of CIT training that has yet to be examined is the expert-derived suggestion that 40 consecutive hours of training is an essential element of CIT for law enforcement officers. That is, CIT training is delivered in one 40-hour week, but it is unclear whether the training could be delivered in segments and still achieve its desired outcomes. Segmented training could make CIT more accessible to smaller, particularly rural, law enforcement agencies. Can segmented CIT achieve outcomes similar to those of traditional CIT training? We compared the knowledge and attitudes of 47 police officers who received traditional CIT training and 32 officers who received segmented CIT training. Our findings suggest that segmented CIT training and traditional CIT training produce comparable results regarding officers' knowledge of mental illness and attitudes toward persons with mental illness, providing preliminary support for this adaptation to the delivery of CIT training. PMID:27644867

  3. Spontaneous Regeneration of Human Photoreceptor Outer Segments.

    PubMed

    Horton, Jonathan C; Parker, Alicia B; Botelho, James V; Duncan, Jacque L

    2015-01-01

    Photoreceptors are damaged in many common eye diseases, such as macular degeneration, retinal detachment, and retinitis pigmentosa. The development of methods to promote the repair or replacement of affected photoreceptors is a major goal of vision research. In this context, it would be useful to know whether photoreceptors are capable of undergoing some degree of spontaneous regeneration after injury. We report a subject who lost retinal function in a wide zone around the optic disc, giving rise to massive enlargement of the physiological blind spot. Imaging with an adaptive optics scanning laser ophthalmoscope (AOSLO) showed depletion of cone outer segments in the affected retina. A year later visual function had improved, with shrinkage of the enlarged blind spot. AOSLO imaging showed repopulation of cone outer segments, although their density remained below normal. There was a one-to-one match between sites of formerly missing outer segments and new outer segments that had appeared over the course of the year's recovery. This correspondence provided direct morphological evidence that damaged cones are capable, under some circumstances, of generating new outer segments. PMID:26213154

  4. Segmented Versus Traditional Crisis Intervention Team Training.

    PubMed

    Cuddeback, Gary S; Kurtz, Robert A; Wilson, Amy Blank; VanDeinse, Tonya; Burgin, Stacey E

    2016-09-01

    There are more than 2,500 Crisis Intervention Teams (CIT) in operation across the country. Results of research on the effectiveness and impact of CIT are mixed. One aspect of CIT training that has yet to be examined is the expert-derived suggestion that 40 consecutive hours of training is an essential element of CIT for law enforcement officers. That is, CIT training is delivered in one 40-hour week, but it is unclear whether the training could be delivered in segments and still achieve its desired outcomes. Segmented training could make CIT more accessible to smaller, particularly rural, law enforcement agencies. Can segmented CIT achieve outcomes similar to those of traditional CIT training? We compared the knowledge and attitudes of 47 police officers who received traditional CIT training and 32 officers who received segmented CIT training. Our findings suggest that segmented CIT training and traditional CIT training produce comparable results regarding officers' knowledge of mental illness and attitudes toward persons with mental illness, providing preliminary support for this adaptation to the delivery of CIT training.

  5. Spontaneous Regeneration of Human Photoreceptor Outer Segments

    PubMed Central

    Horton, Jonathan C.; Parker, Alicia B.; Botelho, James V.; Duncan, Jacque L.

    2015-01-01

    Photoreceptors are damaged in many common eye diseases, such as macular degeneration, retinal detachment, and retinitis pigmentosa. The development of methods to promote the repair or replacement of affected photoreceptors is a major goal of vision research. In this context, it would be useful to know whether photoreceptors are capable of undergoing some degree of spontaneous regeneration after injury. We report a subject who lost retinal function in a wide zone around the optic disc, giving rise to massive enlargement of the physiological blind spot. Imaging with an adaptive optics scanning laser ophthalmoscope (AOSLO) showed depletion of cone outer segments in the affected retina. A year later visual function had improved, with shrinkage of the enlarged blind spot. AOSLO imaging showed repopulation of cone outer segments, although their density remained below normal. There was a one-to-one match between sites of formerly missing outer segments and new outer segments that had appeared over the course of the year’s recovery. This correspondence provided direct morphological evidence that damaged cones are capable, under some circumstances, of generating new outer segments. PMID:26213154

  6. Rediscovering market segmentation.

    PubMed

    Yankelovich, Daniel; Meer, David

    2006-02-01

    In 1964, Daniel Yankelovich introduced in the pages of HBR the concept of nondemographic segmentation, by which he meant the classification of consumers according to criteria other than age, residence, income, and such. The predictive power of marketing studies based on demographics was no longer strong enough to serve as a basis for marketing strategy, he argued. Buying patterns had become far better guides to consumers' future purchases. In addition, properly constructed nondemographic segmentations could help companies determine which products to develop, which distribution channels to sell them in, how much to charge for them, and how to advertise them. But more than 40 years later, nondemographic segmentation has become just as unenlightening as demographic segmentation had been. Today, the technique is used almost exclusively to fulfill the needs of advertising, which it serves mainly by populating commercials with characters that viewers can identify with. It is true that psychographic types like "High-Tech Harry" and "Joe Six-Pack" may capture some truth about real people's lifestyles, attitudes, self-image, and aspirations. But they are no better than demographics at predicting purchase behavior. Thus they give corporate decision makers very little idea of how to keep customers or capture new ones. Now, Daniel Yankelovich returns to these pages, with consultant David Meer, to argue the case for a broad view of nondemographic segmentation. They describe the elements of a smart segmentation strategy, explaining how segmentations meant to strengthen brand identity differ from those capable of telling a company which markets it should enter and what goods to make. And they introduce their "gravity of decision spectrum", a tool that focuses on the form of consumer behavior that should be of the greatest interest to marketers--the importance that consumers place on a product or product category.

  7. Colors, colored overlays, and reading skills

    PubMed Central

    Uccula, Arcangelo; Enna, Mauro; Mulatti, Claudio

    2014-01-01

    In this article, we are concerned with the role of colors in reading written texts. It has been argued that colored overlays applied above written texts positively influence both reading fluency and reading speed. These effects would be particularly evident for those individuals affected by the so called Meares-Irlen syndrome, i.e., who experience eyestrain and/or visual distortions – e.g., color, shape, or movement illusions – while reading. This condition would interest the 12–14% of the general population and up to the 46% of the dyslexic population. Thus, colored overlays have been largely employed as a remedy for some aspects of the difficulties in reading experienced by dyslexic individuals, as fluency and speed. Despite the wide use of colored overlays, how they exert their effects has not been made clear yet. Also, according to some researchers, the results supporting the efficacy of colored overlays as a tool for helping readers are at least controversial. Furthermore, the very nature of the Meares-Irlen syndrome has been questioned. Here we provide a concise, critical review of the literature. PMID:25120525

  8. The number of discernible colors perceived by dichromats in natural scenes and the effects of colored lenses.

    PubMed

    Linhares, João M M; Pinto, Paulo D; Nascimento, Sérgio M C

    2008-01-01

    The number of discernible colors perceived by normal trichromats when viewing natural scenes can be estimated by analyzing idealized color volumes or hyperspectral data obtained from actual scenes. The purpose of the present work was to estimate the relative impairment in chromatic diversity experienced by dichromats when viewing natural scenes and to investigate the effects of colored lenses. The estimates were obtained computationally from the analysis of hyperspectral images of natural scenes and using a quantitative model of dichromats' vision. The color volume corresponding to each scene was represented in CIELAB color space and segmented into cubes of unitary side. For normal trichromats, the number of discernible colors was estimated by counting the number of non-empty cubes. For dichromats, an algorithm simulating for normal observers the appearance of the scenes for dichromats was used, and the number of discernible colors was then counted as for normal trichromats. The effects of colored lenses were estimated by prior filtering the spectral radiance from the scenes with the spectral transmittance function of the lenses. It was found that in dichromatic vision the number of discernible colors was about 7% of normal trichromatic vision. With some colored lenses considerable improvements in chromatic diversity were obtained for trichromats; for dichromats, however, only modest improvements could be obtained with efficiency levels dependent on the combination of scene, lens and type of deficiency.

  9. The number of discernible colors perceived by dichromats in natural scenes and the effects of colored lenses.

    PubMed

    Linhares, João M M; Pinto, Paulo D; Nascimento, Sérgio M C

    2008-01-01

    The number of discernible colors perceived by normal trichromats when viewing natural scenes can be estimated by analyzing idealized color volumes or hyperspectral data obtained from actual scenes. The purpose of the present work was to estimate the relative impairment in chromatic diversity experienced by dichromats when viewing natural scenes and to investigate the effects of colored lenses. The estimates were obtained computationally from the analysis of hyperspectral images of natural scenes and using a quantitative model of dichromats' vision. The color volume corresponding to each scene was represented in CIELAB color space and segmented into cubes of unitary side. For normal trichromats, the number of discernible colors was estimated by counting the number of non-empty cubes. For dichromats, an algorithm simulating for normal observers the appearance of the scenes for dichromats was used, and the number of discernible colors was then counted as for normal trichromats. The effects of colored lenses were estimated by prior filtering the spectral radiance from the scenes with the spectral transmittance function of the lenses. It was found that in dichromatic vision the number of discernible colors was about 7% of normal trichromatic vision. With some colored lenses considerable improvements in chromatic diversity were obtained for trichromats; for dichromats, however, only modest improvements could be obtained with efficiency levels dependent on the combination of scene, lens and type of deficiency. PMID:18598424

  10. Automatic segmentation of cell nuclei in Feulgen-stained histological sections of prostate cancer and quantitative evaluation of segmentation results.

    PubMed

    Nielsen, Birgitte; Albregtsen, Fritz; Danielsen, Håvard E

    2012-07-01

    Digital image analysis of cell nuclei is useful to obtain quantitative information for the diagnosis and prognosis of cancer. However, the lack of a reliable automatic nuclear segmentation is a limiting factor for high-throughput nuclear image analysis. We have developed a method for automatic segmentation of nuclei in Feulgen-stained histological sections of prostate cancer. A local adaptive thresholding with an object perimeter gradient verification step detected the nuclei and was combined with an active contour model that featured an optimized initialization and worked within a restricted region to improve convergence of the segmentation of each nucleus. The method was tested on 30 randomly selected image frames from three cases, comparing the results from the automatic algorithm to a manual delineation of 924 nuclei. The automatic method segmented a few more nuclei compared to the manual method, and about 73% of the manually segmented nuclei were also segmented by the automatic method. For each nucleus segmented both manually and automatically, the accuracy (i.e., agreement with manual delineation) was estimated. The mean segmentation sensitivity/specificity were 95%/96%. The results from the automatic method were not significantly different from the ground truth provided by manual segmentation. This opens the possibility for large-scale nuclear analysis based on automatic segmentation of nuclei in Feulgen-stained histological sections.

  11. Color Reproduction with a Smartphone

    ERIC Educational Resources Information Center

    Thoms, Lars-Jochen; Colicchia, Giuseppe; Girwidz, Raimund

    2013-01-01

    The world is full of colors. Most of the colors we see around us can be created on common digital displays simply by superposing light with three different wavelengths. However, no mixture of colors can produce a fully pure color identical to a spectral color. Using a smartphone, students can investigate the main features of primary color addition…

  12. A combined spatial-spectral method for automated white blood cells segmentation

    NASA Astrophysics Data System (ADS)

    Li, Qingli; Wang, Yiting; Liu, Hongying; Wang, Jianbiao; Guo, Fangmin

    2013-12-01

    To overcome the shortcomings in the traditional white blood cells (WBCs) identification methods based on the color or gray images captured by light microscopy, a microscopy hyperspectral imaging system was used to analyze the blood smears. The system was developed by coupling an acousto-optic tunable filter (AOTF) adapter to a microscopy and driven by a SPF Model AOTF controller, which can capture hyperspectral images from 550 nm to 1000 nm with the spectral resolution 2-5 nm. Moreover, a combined spatial-spectral algorithm is proposed to segment the nuclei and cytoplasm of WBCs from the microscopy hyperspectral images. The proposed algorithm is based on the pixel-wise improved spectral angle mapper (ISAM) segmentation, followed by the majority voting within the active contour model regions. Experimental results show that the accuracy of the proposed algorithm is 91.06% (nuclei) and 85.59% (cytoplasm), respectively, which is higher than that of the spectral information divergence (SID) algorithm because the new method can jointly use both the spectral and spatial information of blood cells.

  13. Scorpion image segmentation system

    NASA Astrophysics Data System (ADS)

    Joseph, E.; Aibinu, A. M.; Sadiq, B. A.; Bello Salau, H.; Salami, M. J. E.

    2013-12-01

    Death as a result of scorpion sting has been a major public health problem in developing countries. Despite the high rate of death as a result of scorpion sting, little report exists in literature of intelligent device and system for automatic detection of scorpion. This paper proposed a digital image processing approach based on the floresencing characteristics of Scorpion under Ultra-violet (UV) light for automatic detection and identification of scorpion. The acquired UV-based images undergo pre-processing to equalize uneven illumination and colour space channel separation. The extracted channels are then segmented into two non-overlapping classes. It has been observed that simple thresholding of the green channel of the acquired RGB UV-based image is sufficient for segmenting Scorpion from other background components in the acquired image. Two approaches to image segmentation have also been proposed in this work, namely, the simple average segmentation technique and K-means image segmentation. The proposed algorithm has been tested on over 40 UV scorpion images obtained from different part of the world and results obtained show an average accuracy of 97.7% in correctly classifying the pixel into two non-overlapping clusters. The proposed 1system will eliminate the problem associated with some of the existing manual approaches presently in use for scorpion detection.

  14. On the purposes of color for living beings: toward a theory of color organization.

    PubMed

    Pinna, Baingio; Reeves, Adam

    2015-01-01

    Phylogenetic and paleontological evidence indicates that in the animal kingdom the ability to perceive colors evolved independently several times over the course of millennia. This implies a high evolutionary neural investment and suggests that color vision provides some fundamental biological benefits. What are these benefits? Why are some animals so colorful? What are the adaptive and perceptual meanings of polychromatism? We suggest that in addition to the discrimination of light and surface chromaticity, sensitivity to color contributes to the whole, the parts and the fragments of perceptual organization. New versions of neon color spreading and the watercolor illusion indicate that the visual purpose of color in humans is threefold: to inter-relate each chromatic component of an object, thus favoring the emergence of the whole; to support a part-whole organization in which components reciprocally enhance each other by amodal completion; and, paradoxically, to reveal fragments and hide the whole-that is, there is a chromatic parceling-out process of separation, division, and fragmentation of the whole. The evolution of these contributions of color to organization needs to be established, but traces of it can be found in Harlequin camouflage by animals and in the coloration of flowers.

  15. The nature of colors

    NASA Astrophysics Data System (ADS)

    da Pos, Osvaldo

    2002-06-01

    Color is a visible aspect of objects and lights, and as such is an objective characteristic of our phenomenal world. Correspondingly also objects and lights are objective, although their subjectivity cannot be disregarded since they belong to our phenomenal world. The distinction between perception and sensation deals with colors seen either in complex displays or in isolation. Reality of colors is apparently challenged by virtual reality, while virtual reality is a good example of what colors are. It seems difficult to combine that aspect of reality colors have in our experience and the concept that colors represent something in the external environment: the distinction between stimulation and perceived object is crucial for understanding the relationships between phenomenal world and physical reality. A modern concept of isomorphism seems useful in interpreting the role of colors. The relationship between the psychological structure of colors and the physical stimulation is enlightened by the analysis of pseudocolors. The perceptual, subjective characteristics of colors go along with the subjectivity of scientific concepts. Colors, emotions, and concepts are all in some people's mind: none of them is independent of the subject mind. Nevertheless they can be communicated from person to person by an appropriate scientific terminology.

  16. Information through color imagery

    USGS Publications Warehouse

    Colvocoresses, Alden P.

    1975-01-01

    The color-sensing capability of the human eye is a powerful tool. In remote sensing we should use color to display data more meaningfully, not to re-create the scene. Color disappears with distance, and features change color with viewing angle. Color infrared film lets us apply color with additional meaning even though we introduce a false color response. Although the marginal gray scale on an ERTS (Earth Resources Technology Satellite) image may indicate balance between the green, red, and infrared bands, and although each band may be printed in a primary color, tests show that we are not fully applying the three primary colors. Therefore, contrast in the green band should be raised. For true three-color remote sensing of the Earth, we must find two generally meaningful signatures in the visible spectrum, or perhaps extend our spectral range. Before turning to costly digital processing we should explore analog processing. Most ERTS users deal with relative spectral radiance; the few concerned with absolute radiance could use the computer-compatible tapes or special annotations. NASA (National Aeronautics and Space Administration), which assigns the range and contrast to the ERTS image, controls processing and could adjust the density range for maximum contrast in any ERTS scene. NASA cannot alter processing for local changes in reflective characteristics of the Earth but could adjust for Sun elevation and optimize the contrast in a given band.

  17. Cooperative processes in image segmentation

    NASA Technical Reports Server (NTRS)

    Davis, L. S.

    1982-01-01

    Research into the role of cooperative, or relaxation, processes in image segmentation is surveyed. Cooperative processes can be employed at several levels of the segmentation process as a preprocessing enhancement step, during supervised or unsupervised pixel classification and, finally, for the interpretation of image segments based on segment properties and relations.

  18. Head segmentation in vertebrates

    PubMed Central

    Kuratani, Shigeru; Schilling, Thomas

    2008-01-01

    Classic theories of vertebrate head segmentation clearly exemplify the idealistic nature of comparative embryology prior to the 20th century. Comparative embryology aimed at recognizing the basic, primary structure that is shared by all vertebrates, either as an archetype or an ancestral developmental pattern. Modern evolutionary developmental (Evo-Devo) studies are also based on comparison, and therefore have a tendency to reduce complex embryonic anatomy into overly simplified patterns. Here again, a basic segmental plan for the head has been sought among chordates. We convened a symposium that brought together leading researchers dealing with this problem, in a number of different evolutionary and developmental contexts. Here we give an overview of the outcome and the status of the field in this modern era of Evo-Devo. We emphasize the fact that the head segmentation problem is not fully resolved, and we discuss new directions in the search for hints for a way out of this maze. PMID:20607135

  19. Phasing a segmented telescope

    NASA Astrophysics Data System (ADS)

    Paykin, Irina; Yacobi, Lee; Adler, Joan; Ribak, Erez N.

    2015-02-01

    A crucial part of segmented or multiple-aperture systems is control of the optical path difference between the segments or subapertures. In order to achieve optimal performance we have to phase subapertures to within a fraction of the wavelength, and this requires high accuracy of positioning for each subaperture. We present simulations and hardware realization of a simulated annealing algorithm in an active optical system with sparse segments. In order to align the optical system we applied the optimization algorithm to the image itself. The main advantage of this method over traditional correction methods is that wave-front-sensing hardware and software are no longer required, making the optical and mechanical system much simpler. The results of simulations and laboratory experiments demonstrate the ability of this optimization algorithm to correct both piston and tip-tilt errors.

  20. Segmented annular combustor

    DOEpatents

    Reider, Samuel B.

    1979-01-01

    An industrial gas turbine engine includes an inclined annular combustor made up of a plurality of support segments each including inner and outer walls of trapezoidally configured planar configuration extents and including side flanges thereon interconnected by means of air cooled connector bolt assemblies to form a continuous annular combustion chamber therebetween and wherein an air fuel mixing chamber is formed at one end of the support segments including means for directing and mixing fuel within a plenum and a perforated header plate for directing streams of air and fuel mixture into the combustion chamber; each of the outer and inner walls of each of the support segments having a ribbed lattice with tracks slidably supporting porous laminated replaceable panels and including pores therein for distributing combustion air into the combustion chamber while cooling the inner surface of each of the panels by transpiration cooling thereof.

  1. Poly-Pattern Compressive Segmentation of ASTER Data for GIS

    NASA Technical Reports Server (NTRS)

    Myers, Wayne; Warner, Eric; Tutwiler, Richard

    2007-01-01

    Pattern-based segmentation of multi-band image data, such as ASTER, produces one-byte and two-byte approximate compressions. This is a dual segmentation consisting of nested coarser and finer level pattern mappings called poly-patterns. The coarser A-level version is structured for direct incorporation into geographic information systems in the manner of a raster map. GIs renderings of this A-level approximation are called pattern pictures which have the appearance of color enhanced images. The two-byte version consisting of thousands of B-level segments provides a capability for approximate restoration of the multi-band data in selected areas or entire scenes. Poly-patterns are especially useful for purposes of change detection and landscape analysis at multiple scales. The primary author has implemented the segmentation methodology in a public domain software suite.

  2. Skin lesion image segmentation using Delaunay Triangulation for melanoma detection.

    PubMed

    Pennisi, Andrea; Bloisi, Domenico D; Nardi, Daniele; Giampetruzzi, Anna Rita; Mondino, Chiara; Facchiano, Antonio

    2016-09-01

    Developing automatic diagnostic tools for the early detection of skin cancer lesions in dermoscopic images can help to reduce melanoma-induced mortality. Image segmentation is a key step in the automated skin lesion diagnosis pipeline. In this paper, a fast and fully-automatic algorithm for skin lesion segmentation in dermoscopic images is presented. Delaunay Triangulation is used to extract a binary mask of the lesion region, without the need of any training stage. A quantitative experimental evaluation has been conducted on a publicly available database, by taking into account six well-known state-of-the-art segmentation methods for comparison. The results of the experimental analysis demonstrate that the proposed approach is highly accurate when dealing with benign lesions, while the segmentation accuracy significantly decreases when melanoma images are processed. This behavior led us to consider geometrical and color features extracted from the binary masks generated by our algorithm for classification, achieving promising results for melanoma detection.

  3. Skin lesion image segmentation using Delaunay Triangulation for melanoma detection.

    PubMed

    Pennisi, Andrea; Bloisi, Domenico D; Nardi, Daniele; Giampetruzzi, Anna Rita; Mondino, Chiara; Facchiano, Antonio

    2016-09-01

    Developing automatic diagnostic tools for the early detection of skin cancer lesions in dermoscopic images can help to reduce melanoma-induced mortality. Image segmentation is a key step in the automated skin lesion diagnosis pipeline. In this paper, a fast and fully-automatic algorithm for skin lesion segmentation in dermoscopic images is presented. Delaunay Triangulation is used to extract a binary mask of the lesion region, without the need of any training stage. A quantitative experimental evaluation has been conducted on a publicly available database, by taking into account six well-known state-of-the-art segmentation methods for comparison. The results of the experimental analysis demonstrate that the proposed approach is highly accurate when dealing with benign lesions, while the segmentation accuracy significantly decreases when melanoma images are processed. This behavior led us to consider geometrical and color features extracted from the binary masks generated by our algorithm for classification, achieving promising results for melanoma detection. PMID:27215953

  4. Colored Diffraction Catastrophes

    NASA Astrophysics Data System (ADS)

    Berry, M. V.; Klein, S.

    1996-03-01

    On fine scales, caustics produced with white light show vividly colored diffraction fringes. For caustics described by the elementary catastrophes of singularity theory, the colors are characteristic of the type of singularity. We study the diffraction colors of the fold and cusp catastrophes. The colors can be simulated computationally as the superposition of monochromatic patterns for different wavelengths. Far from the caustic, where the luminosity contrast is negligible, the fringe colors persist; an asymptotic theory explains why. Experiments with caustics produced by refraction through irregular bathroom-window glass show good agreement with theory. Colored fringes near the cusp reveal fine lines that are not present in any of the monochromatic components; these lines are explained in terms of partial decoherence between rays with widely differing path differences.

  5. Laser color recording unit

    NASA Astrophysics Data System (ADS)

    Jung, E.

    1984-05-01

    A color recording unit was designed for output and control of digitized picture data within computer controlled reproduction and picture processing systems. In order to get a color proof picture of high quality similar to a color print, together with reduced time and material consumption, a photographic color film material was exposed pixelwise by modulated laser beams of three wavelengths for red, green and blue light. Components of different manufacturers for lasers, acousto-optic modulators and polygon mirrors were tested, also different recording methods as (continuous tone mode or screened mode and with a drum or flatbed recording principle). Besides the application for the graphic arts - the proof recorder CPR 403 with continuous tone color recording with a drum scanner - such a color hardcopy peripheral unit with large picture formats and high resolution can be used in medicine, communication, and satellite picture processing.

  6. Digital color representation

    DOEpatents

    White, James M.; Faber, Vance; Saltzman, Jeffrey S.

    1992-01-01

    An image population having a large number of attributes is processed to form a display population with a predetermined smaller number of attributes which represent the larger number of attributes. In a particular application, the color values in an image are compressed for storage in a discrete lookup table (LUT) where an 8-bit data signal is enabled to form a display of 24-bit color values. The LUT is formed in a sampling and averaging process from the image color values with no requirement to define discrete Voronoi regions for color compression. Image color values are assigned 8-bit pointers to their closest LUT value whereby data processing requires only the 8-bit pointer value to provide 24-bit color values from the LUT.

  7. Colored diffraction catastrophes.

    PubMed Central

    Berry, M V; Klein, S

    1996-01-01

    On fine scales, caustics produced with white light show vividly colored diffraction fringes. For caustics described by the elementary catastrophes of singularity theory, the colors are characteristic of the type of singularity. We study the diffraction colors of the fold and cusp catastrophes. The colors can be simulated computationally as the superposition of monochromatic patterns for different wavelengths. Far from the caustic, where the luminosity contrast is negligible, the fringe colors persist; an asymptotic theory explains why. Experiments with caustics produced by refraction through irregular bathroom-window glass show good agreement with theory. Colored fringes near the cusp reveal fine lines that are not present in any of the monochromatic components; these lines are explained in terms of partial decoherence between rays with widely differing path differences. Images Fig. 1 Fig. 2 Fig. 3 Fig. 6 Fig. 8 Fig. 9 Fig. 10 PMID:11607642

  8. Estimating secondary color.

    PubMed

    Walker, B H

    1993-12-01

    Image quality of a refracting lens system often will be limited by residual secondary color. Information in this paper permits rapid determination of blur spot size, and resulting image quality degradation, due to secondary color for a refracting lens system that has been designed with normal optical glasses and is free of primary color (achromatic). Included here is a brief description of the basic theory involved and an example of how the plotted data are used. PMID:20856581

  9. Measurements of ocean color

    NASA Technical Reports Server (NTRS)

    Hovis, W. A.

    1972-01-01

    An airborne instrument for determining ocean color and measurements made with the instrument are discussed. It was concluded that a clear relationship exists between the chlorophyll concentration and the color of the water. High altitude measurements from 50,000 feet are described and the effects of atmospheric scattering on the energy reaching the sensor are examined. The measured spectrum of ocean color at high and low altitudes is plotted.

  10. Albert H. Munsell: A sense of color at the interface of art and science

    USGS Publications Warehouse

    Landa, E.R.

    2004-01-01

    The color theory conceived and commercialized by Albert H. Munsell (1858-1918) has become a universal part of the lexicon of soil science. An American painter noted for his seascapes and portraits, he had a long-standing interest in the description of color. Munsell began studies aimed at standardizing color description, using hue, value, and chroma scales, around 1898. His landmark treatise, "A Color Notation," was published in 1905. Munsell died about 30 years before his color charts came into wide-spread use in soil survey programs in the United States. Dorothy Nickerson, who began her career as secretary and laboratory assistant to Munsell's son, and later spent 37 years at USDA as a color-science specialist, did much to adapt the Munsell Color System to soil-color usage. The legacy of color research pioneered by A.H. Munsell is honored today by the Munsell Color Science Laboratory established in 1983 at the Rochester Institute of Technology.

  11. Adaptive evolutionary paths from UV reception to sensing violet light by epistatic interactions

    PubMed Central

    Yokoyama, Shozo; Altun, Ahmet; Jia, Huiyong; Yang, Hui; Koyama, Takashi; Faggionato, Davide; Liu, Yang; Starmer, William T.

    2015-01-01

    Ultraviolet (UV) reception is useful for such basic behaviors as mate choice, foraging, predator avoidance, communication, and navigation, whereas violet reception improves visual resolution and subtle contrast detection. UV and violet reception are mediated by the short wavelength–sensitive (SWS1) pigments that absorb light maximally (λmax) at ~360 nm and ~395 to 440 nm, respectively. Because of strong nonadditive (epistatic) interactions among amino acid changes in the pigments, the adaptive evolutionary mechanisms of these phenotypes are not well understood. Evolution of the violet pigment of the African clawed frog (Xenopus laevis, λmax = 423 nm) from the UV pigment in the amphibian ancestor (λmax = 359 nm) can be fully explained by eight mutations in transmembrane (TM) I–III segments. We show that epistatic interactions involving the remaining TM IV–VII segments provided evolutionary potential for the frog pigment to gradually achieve its violet-light reception by tuning its color sensitivity in small steps. Mutants in these segments also impair pigments that would cause drastic spectral shifts and thus eliminate them from viable evolutionary pathways. The overall effects of epistatic interactions involving TM IV–VII segments have disappeared at the last evolutionary step and thus are not detectable by studying present-day pigments. Therefore, characterizing the genotype-phenotype relationship during each evolutionary step is the key to uncover the true nature of epistasis. PMID:26601250

  12. Robust system for human airway-tree segmentation

    NASA Astrophysics Data System (ADS)

    Graham, Michael W.; Gibbs, Jason D.; Higgins, William E.

    2008-03-01

    Robust and accurate segmentation of the human airway tree from multi-detector computed-tomography (MDCT) chest scans is vital for many pulmonary-imaging applications. As modern MDCT scanners can detect hundreds of airway tree branches, manual segmentation and semi-automatic segmentation requiring significant user intervention are impractical for producing a full global segmentation. Fully-automated methods, however, may fail to extract small peripheral airways. We propose an automatic algorithm that searches the entire lung volume for airway branches and poses segmentation as a global graph-theoretic optimization problem. The algorithm has shown strong performance on 23 human MDCT chest scans acquired by a variety of scanners and reconstruction kernels. Visual comparisons with adaptive region-growing results and quantitative comparisons with manually-defined trees indicate a high sensitivity to peripheral airways and a low false-positive rate. In addition, we propose a suite of interactive segmentation tools for cleaning and extending critical areas of the automatically segmented result. These interactive tools have potential application for image-based guidance of bronchoscopy to the periphery, where small, terminal branches can be important visual landmarks. Together, the automatic segmentation algorithm and interactive tool suite comprise a robust system for human airway-tree segmentation.

  13. Polarization encoded color camera.

    PubMed

    Schonbrun, Ethan; Möller, Guðfríður; Di Caprio, Giuseppe

    2014-03-15

    Digital cameras would be colorblind if they did not have pixelated color filters integrated into their image sensors. Integration of conventional fixed filters, however, comes at the expense of an inability to modify the camera's spectral properties. Instead, we demonstrate a micropolarizer-based camera that can reconfigure its spectral response. Color is encoded into a linear polarization state by a chiral dispersive element and then read out in a single exposure. The polarization encoded color camera is capable of capturing three-color images at wavelengths spanning the visible to the near infrared. PMID:24690806

  14. Crater Floor in Color

    NASA Technical Reports Server (NTRS)

    2004-01-01

    [figure removed for brevity, see original site]

    Released 5 May 2004 This daytime visible color image was collected on November 18, 2003 during the Southern Summer season in Terra Cimmeria.

    This daytime visible color image was collected on September 4, 2002 during the Northern Spring season in Vastitas Borealis. The THEMIS VIS camera is capable of capturing color images of the martian surface using its five different color filters. In this mode of operation, the spatial resolution and coverage of the image must be reduced to accommodate the additional data volume produced from the use of multiple filters. To make a color image, three of the five filter images (each in grayscale) are selected. Each is contrast enhanced and then converted to a red, green, or blue intensity image. These three images are then combined to produce a full color, single image. Because the THEMIS color filters don't span the full range of colors seen by the human eye, a color THEMIS image does not represent true color. Also, because each single-filter image is contrast enhanced before inclusion in the three-color image, the apparent color variation of the scene is exaggerated. Nevertheless, the color variation that does appear is representative of some change in color, however subtle, in the actual scene. Note that the long edges of THEMIS color images typically contain color artifacts that do not represent surface variation.

    Image information: VIS instrument. Latitude -23.7, Longitude 135.6 East (224.4 West). 19 meter/pixel resolution.

    Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with

  15. Fingers that change color

    MedlinePlus

    ... conditions can cause fingers or toes to change color: Buerger disease Chilblains. Painful inflammation of small blood vessels. Cryoglobulinemia Frostbite Necrotizing vasculitis Peripheral artery disease ...

  16. Color reproduction with a smartphone

    NASA Astrophysics Data System (ADS)

    Thoms, Lars-Jochen; Colicchia, Giuseppe; Girwidz, Raimund

    2013-10-01

    The world is full of colors. Most of the colors we see around us can be created on common digital displays simply by superposing light with three different wavelengths. However, no mixture of colors can produce a fully pure color identical to a spectral color. Using a smartphone, students can investigate the main features of primary color addition and understand how colors are made on digital displays.

  17. Segmentation of touching cell nuclei using gradient flow tracking.

    PubMed

    Li, G; Liu, T; Nie, J; Guo, L; Chen, J; Zhu, J; Xia, W; Mara, A; Holley, S; Wong, S T C

    2008-07-01

    Reliable cell nuclei segmentation is an important yet unresolved problem in biological imaging studies. This paper presents a novel computerized method for robust cell nuclei segmentation based on gradient flow tracking. This method is composed of three key steps: (1) generate a diffused gradient vector flow field; (2) perform a gradient flow tracking procedure to attract points to the basin of a sink; and (3) separate the image into small regions, each containing one nucleus and nearby peripheral background, and perform local adaptive thresholding in each small region to extract the cell nucleus from the background. To show the generality of the proposed method, we report the validation and experimental results using microscopic image data sets from three research labs, with both over-segmentation and under-segmentation rates below 3%. In particular, this method is able to segment closely juxtaposed or clustered cell nuclei, with high sensitivity and specificity in different situations.

  18. Segments of van Gogh.

    ERIC Educational Resources Information Center

    Mannlein, Sally

    2002-01-01

    Describes an art project that was used with first grade students in which they learn about Vincent van Gogh's style of painting. Explains that the children learn to create circles and straight lines and how to fill in with color. (CMK)

  19. Sample training based wildfire segmentation by 2D histogram θ-division with minimum error.

    PubMed

    Zhao, Jianhui; Dong, Erqian; Sun, Mingui; Jia, Wenyan; Zhang, Dengyi; Yuan, Zhiyong

    2013-01-01

    A novel wildfire segmentation algorithm is proposed with the help of sample training based 2D histogram θ-division and minimum error. Based on minimum error principle and 2D color histogram, the θ-division methods were presented recently, but application of prior knowledge on them has not been explored. For the specific problem of wildfire segmentation, we collect sample images with manually labeled fire pixels. Then we define the probability function of error division to evaluate θ-division segmentations, and the optimal angle θ is determined by sample training. Performances in different color channels are compared, and the suitable channel is selected. To further improve the accuracy, the combination approach is presented with both θ-division and other segmentation methods such as GMM. Our approach is tested on real images, and the experiments prove its efficiency for wildfire segmentation.

  20. Hyperspectral imagery and segmentation

    NASA Astrophysics Data System (ADS)

    Wellman, Mark C.; Nasrabadi, Nasser M.

    2002-07-01

    Hyperspectral imagery (HSI), a passive infrared imaging technique which creates images of fine resolution across the spectrum is currently being considered for Army tactical applications. An important tactical application of infra-red (IR) hyperspectral imagery is the detection of low contrast targets, including those targets that may employ camouflage, concealment and deception (CCD) techniques [1,2]. Spectral reflectivity characteristics were used for efficient segmentation between different materials such as painted metal, vegetation and soil for visible to near IR bands in the range of 0.46-1.0 microns as shown previously by Kwon et al [3]. We are currently investigating the HSI where the wavelength spans from 7.5-13.7 microns. The energy in this range of wavelengths is almost entirely emitted rather than reflected, therefore, the gray level of a pixel is a function of the temperature and emissivity of the object. This is beneficial since light level and reflection will not need to be considered in the segmentation. We will present results of a step-wise segmentation analysis on the long-wave infrared (LWIR) hyperspectrum utilizing various classifier architectures applied to both the full-band, broad-band and narrow-band features derived from the Spatially Enhanced Broadband Array Spectrograph System (SEBASS) data base. Stepwise segmentation demonstrates some of the difficulties in the multi-class case. These results give an indication of the added capability the hyperspectral imagery and associated algorithms will bring to bear on the target acquisition problem.

  1. Clarifying color category border according to color vision

    NASA Astrophysics Data System (ADS)

    Ichihara, Takumi; Ichihara, Yasuyo G.

    2015-01-01

    We usually recognize color by two kinds of processes. In the first, the color is recognized continually and a small difference in color is recognized. In the second, the color is recognized discretely. This process recognizes a similar color of a certain range as being in the same color category. The small difference in color is ignored. Recognition by using the color category is important for communication using color. It is known that a color vision defect confuses colors on the confusion locus of color. However, the color category of a color vision defect has not been thoroughly researched. If the color category of the color vision defect is clarified, it will become an important key for color universal design. In this research, we classified color stimuli into four categories to check the shape and the border of the color categories of varied color vision. The experimental result was as follows. The border of protanopia is the following three on the CIE 1931 (x, y) chromaticity diagram: y = -0.3068x + 0.4795, y = -0.1906x + 0.4021, y = -0.2624x + 0.3896. The border of deuteranopia is the following three on the CIE 1931 (x, y) chromaticity diagram: y = -0.7931x + 0.7036, y = -0.718x + 0.5966, y = -0.6667x + 0.5061.

  2. Ocean color imagery: Coastal zone color scanner

    NASA Technical Reports Server (NTRS)

    Hovis, W. A.

    1975-01-01

    Investigations into the feasibility of sensing ocean color from high altitude for determination of chlorophyll and sediment distributions were carried out using sensors on NASA aircraft, coordinated with surface measurements carried out by oceanographic vessels. Spectrometer measurements in 1971 and 1972 led to development of an imaging sensor now flying on a NASA U-2 and the Coastal Zone Color Scanner to fly on Nimbus G in 1978. Results of the U-2 effort show the imaging sensor to be of great value in sensing pollutants in the ocean.

  3. Improving color correction across camera and illumination changes by contextual sample selection

    NASA Astrophysics Data System (ADS)

    Wannous, Hazem; Lucas, Yves; Treuillet, Sylvie; Mansouri, Alamin; Voisin, Yvon

    2012-04-01

    In many tasks of machine vision applications, it is important that recorded colors remain constant, in the real world scene, even under changes of the illuminants and the cameras. Contrary to the human vision system, a machine vision system exhibits inadequate adaptability to the variation of lighting conditions. Automatic white balance control available in commercial cameras is not sufficient to provide reproducible color classification. We address this problem of color constancy on a large image database acquired with varying digital cameras and lighting conditions. A device-independent color representation may be obtained by applying a chromatic adaptation transform, from a calibrated color checker pattern included in the field of view. Instead of using the standard Macbeth color checker, we suggest selecting judicious colors to design a customized pattern from contextual information. A comparative study demonstrates that this approach ensures a stronger constancy of the colors-of-interest before vision control thus enabling a wide variety of applications.

  4. Automatic brain segmentation in rhesus monkeys

    NASA Astrophysics Data System (ADS)

    Styner, Martin; Knickmeyer, Rebecca; Joshi, Sarang; Coe, Christopher; Short, Sarah J.; Gilmore, John

    2007-03-01

    Many neuroimaging studies are applied to primates as pathologies and environmental exposures can be studied in well-controlled settings and environment. In this work, we present a framework for both the semi-automatic creation of a rhesus monkey atlas and a fully automatic segmentation of brain tissue and lobar parcellation. We determine the atlas from training images by iterative, joint deformable registration into an unbiased average image. On this atlas, probabilistic tissue maps and a lobar parcellation. The atlas is then applied via affine, followed by deformable registration. The affinely transformed atlas is employed for a joint T1/T2 based tissue classification. The deformed atlas parcellation masks the tissue segmentations to define the parcellation. Other regional definitions on the atlas can also straightforwardly be used as segmentation. We successfully built average atlas images for the T1 and T2 datasets using a developmental training datasets of 18 cases aged 16-34 months. The atlas clearly exhibits an enhanced signal-to-noise ratio compared to the original images. The results further show that the cortical folding variability in our data is highly limited. Our segmentation and parcellation procedure was successfully re-applied to all training images, as well as applied to over 100 additional images. The deformable registration was able to identify corresponding cortical sulcal borders accurately. Even though the individual methods used in this segmentation framework have been applied before on human data, their combination is novel, as is their adaptation and application to rhesus monkey MRI data. The reduced variability present in the primate data results in a segmentation pipeline that exhibits high stability and anatomical accuracy.

  5. Polar Cap Colors

    NASA Technical Reports Server (NTRS)

    2004-01-01

    [figure removed for brevity, see original site]

    Released 12 May 2004 This daytime visible color image was collected on June 6, 2003 during the Southern Spring season near the South Polar Cap Edge.

    The THEMIS VIS camera is capable of capturing color images of the martian surface using its five different color filters. In this mode of operation, the spatial resolution and coverage of the image must be reduced to accommodate the additional data volume produced from the use of multiple filters. To make a color image, three of the five filter images (each in grayscale) are selected. Each is contrast enhanced and then converted to a red, green, or blue intensity image. These three images are then combined to produce a full color, single image. Because the THEMIS color filters don't span the full range of colors seen by the human eye, a color THEMIS image does not represent true color. Also, because each single-filter image is contrast enhanced before inclusion in the three-color image, the apparent color variation of the scene is exaggerated. Nevertheless, the color variation that does appear is representative of some change in color, however subtle, in the actual scene. Note that the long edges of THEMIS color images typically contain color artifacts that do not represent surface variation.

    Image information: VIS instrument. Latitude -77.8, Longitude 195 East (165 West). 38 meter/pixel resolution.

    Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

    NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA

  6. Navigation lights color study

    NASA Astrophysics Data System (ADS)

    Barbosa, Jose G.; Alberg, Matthew T.

    2015-05-01

    The chromaticity of navigation lights are defined by areas on the International Commission on Illumination (CIE) 1931 chromaticity diagram. The corner coordinates for these areas are specified in the International Regulations for Prevention of Collisions at Sea, 1972 (72 COLREGS). The navigation light's color of white, red, green, and yellow are bounded by these areas. The chromaticity values specified by the COLREGS for navigation lights were intended for the human visual system (HVS). The HVS can determine the colors of these lights easily under various conditions. For digital color camera imaging systems the colors of these lights are dependent on the camera's color spectral sensitivity, settings, and color correction. At night the color of these lights are used to quickly determine the relative course of vessels. If these lights are incorrectly identified or there is a delay in identifying them this could be a potential safety of ship concern. Vessels that use camera imaging systems exclusively for sight, at night, need to detect, identify, and discriminate navigation lights for navigation and collision avoidance. The introduction of light emitting diode (LED) lights and lights with different spectral signatures have the potential to be imaged very differently with an RGB color filter array (CFA) color camera than with the human eye. It has been found that some green navigation lights' images appear blue verse green. This has an impact on vessels that use camera imaging systems exclusively for navigation. This paper will characterize color cameras ability to properly reproducing navigation lights' color and survey a set of navigation light to determine if they conform to the COLREGS.

  7. Convex-relaxed kernel mapping for image segmentation.

    PubMed

    Ben Salah, Mohamed; Ben Ayed, Ismail; Jing Yuan; Hong Zhang

    2014-03-01

    This paper investigates a convex-relaxed kernel mapping formulation of image segmentation. We optimize, under some partition constraints, a functional containing two characteristic terms: 1) a data term, which maps the observation space to a higher (possibly infinite) dimensional feature space via a kernel function, thereby evaluating nonlinear distances between the observations and segments parameters and 2) a total-variation term, which favors smooth segment surfaces (or boundaries). The algorithm iterates two steps: 1) a convex-relaxation optimization with respect to the segments by solving an equivalent constrained problem via the augmented Lagrange multiplier method and 2) a convergent fixed-point optimization with respect to the segments parameters. The proposed algorithm can bear with a variety of image types without the need for complex and application-specific statistical modeling, while having the computational benefits of convex relaxation. Our solution is amenable to parallelized implementations on graphics processing units (GPUs) and extends easily to high dimensions. We evaluated the proposed algorithm with several sets of comprehensive experiments and comparisons, including: 1) computational evaluations over 3D medical-imaging examples and high-resolution large-size color photographs, which demonstrate that a parallelized implementation of the proposed method run on a GPU can bring a significant speed-up and 2) accuracy evaluations against five state-of-the-art methods over the Berkeley color-image database and a multimodel synthetic data set, which demonstrates competitive performances of the algorithm. PMID:24723519

  8. Image segmentation by hierarchial agglomeration of polygons using ecological statistics

    DOEpatents

    Prasad, Lakshman; Swaminarayan, Sriram

    2013-04-23

    A method for rapid hierarchical image segmentation based on perceptually driven contour completion and scene statistics is disclosed. The method begins with an initial fine-scale segmentation of an image, such as obtained by perceptual completion of partial contours into polygonal regions using region-contour correspondences established by Delaunay triangulation of edge pixels as implemented in VISTA. The resulting polygons are analyzed with respect to their size and color/intensity distributions and the structural properties of their boundaries. Statistical estimates of granularity of size, similarity of color, texture, and saliency of intervening boundaries are computed and formulated into logical (Boolean) predicates. The combined satisfiability of these Boolean predicates by a pair of adjacent polygons at a given segmentation level qualifies them for merging into a larger polygon representing a coarser, larger-scale feature of the pixel image and collectively obtains the next level of polygonal segments in a hierarchy of fine-to-coarse segmentations. The iterative application of this process precipitates textured regions as polygons with highly convolved boundaries and helps distinguish them from objects which typically have more regular boundaries. The method yields a multiscale decomposition of an image into constituent features that enjoy a hierarchical relationship with features at finer and coarser scales. This provides a traversable graph structure from which feature content and context in terms of other features can be derived, aiding in automated image understanding tasks. The method disclosed is highly efficient and can be used to decompose and analyze large images.

  9. Easy-interactive and quick psoriasis lesion segmentation

    NASA Astrophysics Data System (ADS)

    Ma, Guoli; He, Bei; Yang, Wenming; Shu, Chang

    2013-12-01

    This paper proposes an interactive psoriasis lesion segmentation algorithm based on Gaussian Mixture Model (GMM). Psoriasis is an incurable skin disease and affects large population in the world. PASI (Psoriasis Area and Severity Index) is the gold standard utilized by dermatologists to monitor the severity of psoriasis. Computer aid methods of calculating PASI are more objective and accurate than human visual assessment. Psoriasis lesion segmentation is the basis of the whole calculating. This segmentation is different from the common foreground/background segmentation problems. Our algorithm is inspired by GrabCut and consists of three main stages. First, skin area is extracted from the background scene by transforming the RGB values into the YCbCr color space. Second, a rough segmentation of normal skin and psoriasis lesion is given. This is an initial segmentation given by thresholding a single gaussian model and the thresholds are adjustable, which enables user interaction. Third, two GMMs, one for the initial normal skin and one for psoriasis lesion, are built to refine the segmentation. Experimental results demonstrate the effectiveness of the proposed algorithm.

  10. Efficient terrestrial laser scan segmentation exploiting data structure

    NASA Astrophysics Data System (ADS)

    Mahmoudabadi, Hamid; Olsen, Michael J.; Todorovic, Sinisa

    2016-09-01

    New technologies such as lidar enable the rapid collection of massive datasets to model a 3D scene as a point cloud. However, while hardware technology continues to advance, processing 3D point clouds into informative models remains complex and time consuming. A common approach to increase processing efficiently is to segment the point cloud into smaller sections. This paper proposes a novel approach for point cloud segmentation using computer vision algorithms to analyze panoramic representations of individual laser scans. These panoramas can be quickly created using an inherent neighborhood structure that is established during the scanning process, which scans at fixed angular increments in a cylindrical or spherical coordinate system. In the proposed approach, a selected image segmentation algorithm is applied on several input layers exploiting this angular structure including laser intensity, range, normal vectors, and color information. These segments are then mapped back to the 3D point cloud so that modeling can be completed more efficiently. This approach does not depend on pre-defined mathematical models and consequently setting parameters for them. Unlike common geometrical point cloud segmentation methods, the proposed method employs the colorimetric and intensity data as another source of information. The proposed algorithm is demonstrated on several datasets encompassing variety of scenes and objects. Results show a very high perceptual (visual) level of segmentation and thereby the feasibility of the proposed algorithm. The proposed method is also more efficient compared to Random Sample Consensus (RANSAC), which is a common approach for point cloud segmentation.

  11. Color names, color categories, and color-cued visual search: sometimes, color perception is not categorical.

    PubMed

    Brown, Angela M; Lindsey, Delwin T; Guckes, Kevin M

    2011-01-01

    The relation between colors and their names is a classic case study for investigating the Sapir-Whorf hypothesis that categorical perception is imposed on perception by language. Here, we investigate the Sapir-Whorf prediction that visual search for a green target presented among blue distractors (or vice versa) should be faster than search for a green target presented among distractors of a different color of green (or for a blue target among different blue distractors). A. L. Gilbert, T. Regier, P. Kay, and R. B. Ivry (2006) reported that this Sapir-Whorf effect is restricted to the right visual field (RVF), because the major brain language centers are in the left cerebral hemisphere. We found no categorical effect at the Green-Blue color boundary and no categorical effect restricted to the RVF. Scaling of perceived color differences by Maximum Likelihood Difference Scaling (MLDS) also showed no categorical effect, including no effect specific to the RVF. Two models fit the data: a color difference model based on MLDS and a standard opponent-colors model of color discrimination based on the spectral sensitivities of the cones. Neither of these models nor any of our data suggested categorical perception of colors at the Green-Blue boundary, in either visual field.

  12. Dynamic egg color mimicry.

    PubMed

    Hanley, Daniel; Šulc, Michal; Brennan, Patricia L R; Hauber, Mark E; Grim, Tomáš; Honza, Marcel

    2016-06-01

    Evolutionary hypotheses regarding the function of eggshell phenotypes, from solar protection through mimicry, have implicitly assumed that eggshell appearance remains static throughout the laying and incubation periods. However, recent research demonstrates that egg coloration changes over relatively short, biologically relevant timescales. Here, we provide the first evidence that such changes impact brood parasite-host eggshell color mimicry during the incubation stage. First, we use long-term data to establish how rapidly the Acrocephalus arundinaceus Linnaeus (great reed warbler) responded to natural parasitic eggs laid by the Cuculus canorus Linnaeus (common cuckoo). Most hosts rejected parasitic eggs just prior to clutch completion, but the host response period extended well into incubation (~10 days after clutch completion). Using reflectance spectrometry and visual modeling, we demonstrate that eggshell coloration in the great reed warbler and its brood parasite, the common cuckoo, changes rapidly, and the extent of eggshell color mimicry shifts dynamically over the host response period. Specifically, 4 days after being laid, the host should notice achromatic color changes to both cuckoo and warbler eggs, while chromatic color changes would be noticeable after 8 days. Furthermore, we demonstrate that the perceived match between host and cuckoo eggshell color worsened over the incubation period. These findings have important implications for parasite-host coevolution dynamics, because host egg discrimination may be aided by disparate temporal color changes in host and parasite eggs. PMID:27516874

  13. Requirements for color technology

    NASA Astrophysics Data System (ADS)

    Campbell, Ronald B., Jr.

    1993-06-01

    The requirements for color technology in the general office are reviewed. The two most salient factors driving the requirements for color are the information explosion and the virtually negligible growth in white collar productivity in the recent past. Accordingly, the business requirement upon color technology is that it be utilized in an effective and efficient manner to increase office productivity. Recent research on productivity and growth has moved beyond the classical two factor productivity model of labor and capital to explicitly include knowledge as a third and vital factor. Documents are agents of knowledge in the general office. Documents articulate, express, disseminate, and communicate knowledge. The central question addressed here is how can color, in conjunction with other techniques such as graphics and document design, improve the growth of knowledge? The central thesis is that the effective use of color to convert information into knowledge is one of the most powerful ways to increase office productivity. Material on the value of color is reviewed. This material is related to the role of documents. Document services are the way in which users access and utilize color technology. The requirements for color technology are then defined against the services taxonomy.

  14. Colorful Underwater Sea Creatures

    ERIC Educational Resources Information Center

    McCutcheon, Heather

    2011-01-01

    In this article, the author describes a project wherein students created colorful underwater sea creatures. This project began with a discussion about underwater sea creatures and how they live. The first step was making the multi-colored tissue paper that would become sea creatures and seaweed. Once students had the shapes of their sea creatures…

  15. 3-D Color Wheels

    ERIC Educational Resources Information Center

    DuBois, Ann

    2010-01-01

    The blending of information from an academic class with projects from art class can do nothing but strengthen the learning power of the student. Creating three-dimensional color wheels provides the perfect opportunity to combine basic geometry knowledge with color theory. In this article, the author describes how her seventh-grade painting…

  16. Equivalent Colorings with "Maple"

    ERIC Educational Resources Information Center

    Cecil, David R.; Wang, Rongdong

    2005-01-01

    Many counting problems can be modeled as "colorings" and solved by considering symmetries and Polya's cycle index polynomial. This paper presents a "Maple 7" program link http://users.tamuk.edu/kfdrc00/ that, given Polya's cycle index polynomial, determines all possible associated colorings and their partitioning into equivalence classes. These…

  17. Drawing Color Lines.

    ERIC Educational Resources Information Center

    Gude, Olivia

    2000-01-01

    Addresses the teaching of color symbolism and asserts that racism is embodied and perpetuated through conventional notions of black and white symbolism. Discusses a project with two eighth grade classes, focusing on the discussion of color symbolism in school and popular culture. Considers the importance of analyzing contemporary languages of…

  18. Dynamic egg color mimicry.

    PubMed

    Hanley, Daniel; Šulc, Michal; Brennan, Patricia L R; Hauber, Mark E; Grim, Tomáš; Honza, Marcel

    2016-06-01

    Evolutionary hypotheses regarding the function of eggshell phenotypes, from solar protection through mimicry, have implicitly assumed that eggshell appearance remains static throughout the laying and incubation periods. However, recent research demonstrates that egg coloration changes over relatively short, biologically relevant timescales. Here, we provide the first evidence that such changes impact brood parasite-host eggshell color mimicry during the incubation stage. First, we use long-term data to establish how rapidly the Acrocephalus arundinaceus Linnaeus (great reed warbler) responded to natural parasitic eggs laid by the Cuculus canorus Linnaeus (common cuckoo). Most hosts rejected parasitic eggs just prior to clutch completion, but the host response period extended well into incubation (~10 days after clutch completion). Using reflectance spectrometry and visual modeling, we demonstrate that eggshell coloration in the great reed warbler and its brood parasite, the common cuckoo, changes rapidly, and the extent of eggshell color mimicry shifts dynamically over the host response period. Specifically, 4 days after being laid, the host should notice achromatic color changes to both cuckoo and warbler eggs, while chromatic color changes would be noticeable after 8 days. Furthermore, we demonstrate that the perceived match between host and cuckoo eggshell color worsened over the incubation period. These findings have important implications for parasite-host coevolution dynamics, because host egg discrimination may be aided by disparate temporal color changes in host and parasite eggs.

  19. Cytoplasm segmentation on cervical cell images using graph cut-based approach.

    PubMed

    Zhang, Ling; Kong, Hui; Chin, Chien Ting; Wang, Tianfu; Chen, Siping

    2014-01-01

    This paper proposes a method to segment the cytoplasm in cervical cell images using graph cut-based algorithm. First, the A* channel in CIE LAB color space is extracted for contrast enhancement. Then, in order to effectively extract cytoplasm boundaries when image histograms present non-bimodal distribution, Otsu multiple thresholding is performed on the contrast enhanced image to generate initial segments, based on which the segments are refined by the multi-way graph cut method. We use 21 cervical cell images with non-ideal imaging condition to evaluate cytoplasm segmentation performance. The proposed method achieved a 93% accuracy which outperformed state-of-the-art works.

  20. Selective Pressures Explain Differences in Flower Color among Gentiana lutea Populations.

    PubMed

    Sobral, Mar; Veiga, Tania; Domínguez, Paula; Guitián, Javier A; Guitián, Pablo; Guitián, José M

    2015-01-01

    Flower color variation among plant populations might reflect adaptation to local conditions such as the interacting animal community. In the northwest Iberian Peninsula, flower color of Gentiana lutea varies longitudinally among populations, ranging from orange to yellow. We explored whether flower color is locally adapted and the role of pollinators and seed predators as agents of selection by analyzing the influence of flower color on (i) pollinator visitation rate and (ii) escape from seed predation and (iii) by testing whether differences in pollinator communities correlate with flower color variation across populations. Finally, (iv) we investigated whether variation in selective pressures explains flower color variation among 12 G. lutea populations. Flower color influenced pollinator visits and differences in flower color among populations were related to variation in pollinator communities. Selective pressures on flower color vary among populations and explain part of flower color differences among populations of G. lutea. We conclude that flower color in G. lutea is locally adapted and that pollinators play a role in this adaptation.