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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. Segmentation of the optic disk in color eye fundus images using an adaptive morphological approach.

    PubMed

    Welfer, Daniel; Scharcanski, Jacob; Kitamura, Cleyson M; Dal Pizzol, Melissa M; Ludwig, Laura W B; Marinho, Diane Ruschel

    2010-02-01

    The identification of some important retinal anatomical regions is a prerequisite for the computer aided diagnosis of several retinal diseases. In this paper, we propose a new adaptive method for the automatic segmentation of the optic disk in digital color fundus images, using mathematical morphology. The proposed method has been designed to be robust under varying illumination and image acquisition conditions, common in eye fundus imaging. Our experimental results based on two publicly available eye fundus image databases are encouraging, and indicate that our approach potentially can achieve a better performance than other known methods proposed in the literature. Using the DRIVE database (which consists of 40 retinal images), our method achieves a success rate of 100% in the correct location of the optic disk, with 41.47% of mean overlap. In the DIARETDB1 database (which consists of 89 retinal images), the optic disk is correctly located in 97.75% of the images, with a mean overlap of 43.65%.

  3. Color Adaptation for Color Deficient Learners.

    ERIC Educational Resources Information Center

    Johnson, Donald D.

    1995-01-01

    Describes a corrective method of color adaptation designed to allow most, if not all, individuals to participate in the learning process as well as social and work-related environments. Provides a concise summation of facts and theories concerning color deficiency. Includes anatomical drawings, graphs, and statistical data. (MJP)

  4. 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.)

  5. New color segmentation method and its applications

    NASA Astrophysics Data System (ADS)

    Wang, Jian

    1999-01-01

    Segmentation is an important step in the early stage of image analysis. Color or multi-spectral image segmentation usually involves search and clustering techniques in a three or higher dimensional spectral space - an exercise which is considered computationally expensive. This paper presents a new color segmentation method for color image analysis with its application to plant leaf area measurement. A 3D histogram for an RGB color image is established basing on an octree data structure. The histogram represents the color distribution of the image in the RGB color space on which a 3D Gaussian filter is applied to smooth out small maxima of this distribution. The color space is then searched to find out al the major maxima. Around each maxima, a covering cube with a controlled side width is established. These maxima and covering cubes are considered to be potential color classes. Each cube may expand according to the value of surrounding neighbors. Once enough modes and their cover cubes have been found, a k-means clustering algorithm is used to classify these maxima into a predetermined number of classes. Then, the classified modes and the color covered by the cubes are used as training samples for a Bayes classifier which can be used to classify all the pixels in the image. A statistical relaxation method is then sued as a find segmentation. This method can either be supervised or unsupervised, depending on the different requirements of specific applications. The octree data structure significantly reduces the color space to be searched and consequently reduces computational cost. An extension of this method can also be applied to multi-spectral image analysis.

  6. 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

  7. Color image diffusion using adaptive bilateral filter.

    PubMed

    Xie, Jun; Ann Heng, Pheng

    2005-01-01

    In this paper, we propose an approach to diffuse color images based on the bilateral filter. Real image data has a level of uncertainty that is manifested in the variability of measures assigned to pixels. This uncertainty is usually interpreted as noise and considered an undesirable component of the image data. Image diffusion can smooth away small-scale structures and noise while retaining important features, thus improving the performances for many image processing algorithms such as image compression, segmentation and recognition. The bilateral filter is noniterative, simple and fast. It has been shown to give similar and possibly better filtering results than iterative approaches. However, the performance of this filter is greatly affected by the choose of the parameters of filtering kernels. In order to remove noise and maintain the significant features on images, we extend the bilateral filter by introducing an adaptive domain spread into the nonlinear diffusion scheme. For color images, we employ the CIE-Lab color system to describe input images and the filtering process is operated using three channels together. Our analysis shows that the proposed method is more suitable for preserving strong edges on noisy images than the original bilateral filter. Empirical results on both nature images and color medical images confirm the novel method's advantages, and show it can diffuse various kinds of color images correctly and efficiently.

  8. Segmentation and Classification of Burn Color Images

    DTIC Science & Technology

    2007-11-02

    SEGMENTATION AND CLASSIFICATION OF BURN COLOR IMAGES Begoña Acha1, Carmen Serrano1, Laura Roa2 1Área de Teoría de la Señal y Comunicaciones ...2Grupo de Ingeniería Biomédica. Escuela Superior de Ingenieros. Universidad de Sevilla. Spain. e -mail: bacha@viento.us.es, cserrano@viento.us.es...IEEE Trans. on Biomedical Engineering, vol. 43, no. 10, pp. 1011-1020, Oct. 1996. [10] G. A. Hance, S. E . Umbaugh, R. H. Moss, W. V. Stoecker

  9. Digital item adaptation for color vision variations

    NASA Astrophysics Data System (ADS)

    Song, Jaeil; Yang, Seungji; Kim, Cheonseog; Nam, Jaeho; Hong, Jin-Woo; Ro, Yong Man

    2003-06-01

    As color is more widely used to carry visual information in the multimedia content, ability to perceive color plays a crucial role in getting visual information. Regardless of color vision variations, one should have visual information equally. This paper proposes the adaptation technique for color vision variations in the MPEG-21 Digital Item Adaptation (DIA). DIA is performed respectively for severe color vision deficiency (dichromats) and for mild color vision deficiency (anomalous trichromats), according to the description of user characteristics about color vision variations. Adapted images are tested by simulation program for color vision variations so as to recognize the appearance of the adapted images in the color deficient vision. Experimental result shows that proposed adaptation technique works well in the MPEG-21 framework.

  10. 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

  11. 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.

  12. Underwater color image segmentation method via RGB channel fusion

    NASA Astrophysics Data System (ADS)

    Xuan, Li; Mingjun, Zhang

    2017-02-01

    Aiming at the problem of low segmentation accuracy and high computation time by applying existing segmentation methods for underwater color images, this paper has proposed an underwater color image segmentation method via RGB color channel fusion. Based on thresholding segmentation methods to conduct fast segmentation, the proposed method relies on dynamic estimation of the optimal weights for RGB channel fusion to obtain the grayscale image with high foreground-background contrast and reaches high segmentation accuracy. To verify the segmentation accuracy of the proposed method, the authors have conducted various underwater comparative experiments. The experimental results demonstrate that the proposed method is robust to illumination, and it is superior to existing methods in terms of both segmentation accuracy and computation time. Moreover, a segmentation technique is proposed for image sequences for real-time autonomous underwater vehicle operations.

  13. Color adaptation induced from linguistic description of color

    PubMed Central

    Zheng, Liling; Huang, Ping; Zhong, Xiao; Li, Tianfeng; Mo, Lei

    2017-01-01

    Recent theories propose that language comprehension can influence perception at the low level of perceptual system. Here, we used an adaptation paradigm to test whether processing language caused color adaptation in the visual system. After prolonged exposure to a color linguistic context, which depicted red, green, or non-specific color scenes, participants immediately performed a color detection task, indicating whether they saw a green color square in the middle of a white screen or not. We found that participants were more likely to perceive the green color square after listening to discourses denoting red compared to discourses denoting green or conveying non-specific color information, revealing that language comprehension caused an adaptation aftereffect at the perceptual level. Therefore, semantic representation of color may have a common neural substrate with color perception. These results are in line with the simulation view of embodied language comprehension theory, which predicts that processing language reactivates the sensorimotor systems that are engaged during real experience. PMID:28358807

  14. A dendritic lattice neural network for color image segmentation

    NASA Astrophysics Data System (ADS)

    Urcid, Gonzalo; Lara-Rodríguez, Luis David; López-Meléndez, Elizabeth

    2015-09-01

    A two-layer dendritic lattice neural network is proposed to segment color images in the Red-Green-Blue (RGB) color space. The two layer neural network is a fully interconnected feed forward net consisting of an input layer that receives color pixel values, an intermediate layer that computes pixel interdistances, and an output layer used to classify colors by hetero-association. The two-layer net is first initialized with a finite small subset of the colors present in the input image. These colors are obtained by means of an automatic clustering procedure such as k-means or fuzzy c-means. In the second stage, the color image is scanned on a pixel by pixel basis where each picture element is treated as a vector and feeded into the network. For illustration purposes we use public domain color images to show the performance of our proposed image segmentation technique.

  15. Automatic face segmentation using color cues for coding typical videophone scenes

    NASA Astrophysics Data System (ADS)

    Zhang, Yujin; Yao, Yu R.; He, Yun

    1997-01-01

    This paper presents a simple color segmentation technique which could be used in the model-based very low bit-rate coding approaches for videophone applications, in which the delimitation of the face of speaker is request. This work attempts to segment the face of speaker using color cues. To better take the advantage of the color contents of images, the color segmentation is carried out in HSI (hue, saturation, intensity) space with the three components used in two steps. The original image is first splitted into two groups of regions, one has higher saturation values and other has lower saturation values,b y using an adaptive threshold value applied to the histogram of saturation. In the high saturation regions, the hue component can furnish useful references for further segmentation, while in the low saturation regions the intensity component can play the similar role. For each group of regions, a multi- thresholding technique based on either hue or intensity component is then proposed for the subsequent segmentation. After both groups of regions are segmented, a combination of these two segmentation results will provide the finally segmented image. Some experiments with images taken from typical 'head-and-shoulders' videophone sequences are carried out and some results are presented.

  16. Comparison of perceptual color spaces for natural image segmentation tasks

    NASA Astrophysics Data System (ADS)

    Correa-Tome, Fernando E.; Sanchez-Yanez, Raul E.; Ayala-Ramirez, Victor

    2011-11-01

    Color image segmentation largely depends on the color space chosen. Furthermore, spaces that show perceptual uniformity seem to outperform others due to their emulation of the human perception of color. We evaluate three perceptual color spaces, CIELAB, CIELUV, and RLAB, in order to determine their contribution to natural image segmentation and to identify the space that obtains the best results over a test set of images. The nonperceptual color space RGB is also included for reference purposes. In order to quantify the quality of resulting segmentations, an empirical discrepancy evaluation methodology is discussed. The Berkeley Segmentation Dataset and Benchmark is used in test series, and two approaches are taken to perform the experiments: supervised pixelwise classification using reference colors, and unsupervised clustering using k-means. A majority filter is used as a postprocessing stage, in order to determine its contribution to the result. Furthermore, a comparison of elapsed times taken by the required transformations is included. The main finding of our study is that the CIELUV color space outperforms the other color spaces in both discriminatory performance and computational speed, for the average case.

  17. Segment adaptive gradient angle interpolation.

    PubMed

    Zwart, Christine M; Frakes, David H

    2013-08-01

    We introduce a new edge-directed interpolator based on locally defined, straight line approximations of image isophotes. Spatial derivatives of image intensity are used to describe the principal behavior of pixel-intersecting isophotes in terms of their slopes. The slopes are determined by inverting a tridiagonal matrix and are forced to vary linearly from pixel-to-pixel within segments. Image resizing is performed by interpolating along the approximated isophotes. The proposed method can accommodate arbitrary scaling factors, provides state-of-the-art results in terms of PSNR as well as other quantitative visual quality metrics, and has the advantage of reduced computational complexity that is directly proportional to the number of pixels.

  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. Fast spectral color image segmentation based on filtering and clustering

    NASA Astrophysics Data System (ADS)

    Xing, Min; Li, Hongyu; Jia, Jinyuan; Parkkinen, Jussi

    2009-10-01

    This paper proposes a fast approach to spectral image segmentation. In the algorithm, two popular techniques are extended and applied to spectral color images: the mean-shift filtering and the kernel-based clustering. We claim that segmentation should be completed under illuminant F11 rather than directly using the original spectral reflectance, because such illumination can reduce data variability and expedite the following filtering. The modes obtained in the mean-shift filtering represent the local features of spectral images, and will be applied to segmentation in place of pixels. Since the modes are generally small in number, the eigendecomposition of kernel matrices, the crucial step in the kernelbased clustering, becomes much easier. The combination of these two techniques can efficiently enhance the performance of segmentation. Experiments show that the proposed segmentation method is feasible and very promising for spectral color images.

  20. 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

  1. Local adaptive contrast enhancement for color images

    NASA Astrophysics Data System (ADS)

    Dijk, Judith; den Hollander, Richard J. M.; Schavemaker, John G. M.; Schutte, Klamer

    2007-04-01

    A camera or display usually has a smaller dynamic range than the human eye. For this reason, objects that can be detected by the naked eye may not be visible in recorded images. Lighting is here an important factor; improper local lighting impairs visibility of details or even entire objects. When a human is observing a scene with different kinds of lighting, such as shadows, he will need to see details in both the dark and light parts of the scene. For grey value images such as IR imagery, algorithms have been developed in which the local contrast of the image is enhanced using local adaptive techniques. In this paper, we present how such algorithms can be adapted so that details in color images are enhanced while color information is retained. We propose to apply the contrast enhancement on color images by applying a grey value contrast enhancement algorithm to the luminance channel of the color signal. The color coordinates of the signal will remain the same. Care is taken that the saturation change is not too high. Gamut mapping is performed so that the output can be displayed on a monitor. The proposed technique can for instance be used by operators monitoring movements of people in order to detect suspicious behavior. To do this effectively, specific individuals should both be easy to recognize and track. This requires optimal local contrast, and is sometimes much helped by color when tracking a person with colored clothes. In such applications, enhanced local contrast in color images leads to more effective monitoring.

  2. Spatially varying color distributions for interactive multilabel segmentation.

    PubMed

    Nieuwenhuis, Claudia; Cremers, Daniel

    2013-05-01

    We propose a method for interactive multilabel segmentation which explicitly takes into account the spatial variation of color distributions. To this end, we estimate a joint distribution over color and spatial location using a generalized Parzen density estimator applied to each user scribble. In this way, we obtain a likelihood for observing certain color values at a spatial coordinate. This likelihood is then incorporated in a Bayesian MAP estimation approach to multiregion segmentation which in turn is optimized using recently developed convex relaxation techniques. These guarantee global optimality for the two-region case (foreground/background) and solutions of bounded optimality for the multiregion case. We show results on the GrabCut benchmark, the recently published Graz benchmark, and on the Berkeley segmentation database which exceed previous approaches such as GrabCut, the Random Walker, Santner's approach, TV-Seg, and interactive graph cuts in accuracy. Our results demonstrate that taking into account the spatial variation of color models leads to drastic improvements for interactive image segmentation.

  3. Adaptive image segmentation applied to plant reproduction by tissue culture

    NASA Astrophysics Data System (ADS)

    Vazquez Rueda, Martin G.; Hahn, Federico; Zapata, Jose L.

    1997-04-01

    This paper presents that experimental results obtained on indoor tissue culture using the adaptive image segmentation system. The performance of the adaptive technique is contrasted with different non-adaptive techniques commonly used in the computer vision field to demonstrate the improvement provided by the adaptive image segmentation system.

  4. 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

  5. Adaptive fuzzy segmentation of magnetic resonance images.

    PubMed

    Pham, D L; Prince, J L

    1999-09-01

    An algorithm is presented for the fuzzy segmentation of two-dimensional (2-D) and three-dimensional (3-D) multispectral magnetic resonance (MR) images that have been corrupted by intensity inhomogeneities, also known as shading artifacts. The algorithm is an extension of the 2-D adaptive fuzzy C-means algorithm (2-D AFCM) presented in previous work by the authors. This algorithm models the intensity inhomogeneities as a gain field that causes image intensities to smoothly and slowly vary through the image space. It iteratively adapts to the intensity inhomogeneities and is completely automated. In this paper, we fully generalize 2-D AFCM to three-dimensional (3-D) multispectral images. Because of the potential size of 3-D image data, we also describe a new faster multigrid-based algorithm for its implementation. We show, using simulated MR data, that 3-D AFCM yields lower error rates than both the standard fuzzy C-means (FCM) algorithm and two other competing methods, when segmenting corrupted images. Its efficacy is further demonstrated using real 3-D scalar and multispectral MR brain images.

  6. Using Kernel Principal Components for Color Image Segmentation

    NASA Astrophysics Data System (ADS)

    Wesolkowski, Slawo

    2002-11-01

    Distinguishing objects on the basis of color is fundamental to humans. In this paper, a clustering approach is used to segment color images. Clustering is usually done using a single point or vector as a cluster prototype. The data can be clustered in the input or feature space where the feature space is some nonlinear transformation of the input space. The idea of kernel principal component analysis (KPCA) was introduced to align data along principal components in the kernel or feature space. KPCA is a nonlinear transformation of the input data that finds the eigenvectors along which this data has maximum information content (or variation). The principal components resulting from KPCA are nonlinear in the input space and represent principal curves. This is a necessary step as colors in RGB are not linearly correlated especially considering illumination effects such as shading or highlights. The performance of the k-means (Euclidean distance-based) and Mixture of Principal Components (vector angle-based) algorithms are analyzed in the context of the input space and the feature space obtained using KPCA. Results are presented on a color image segmentation task. The results are discussed and further extensions are suggested.

  7. Segmentation of color images based on the gravitational clustering concept

    NASA Astrophysics Data System (ADS)

    Lai, Andrew H.; Yung, H. C.

    1998-03-01

    A new clustering algorithm derived from the Markovian model of the gravitational clustering concept is proposed that works in the RGB measurement space for color image. To enable the model to be applicable in image segmentation, the new algorithm imposes a clustering constraint at each clustering iteration to control and determine the formation of multiple clusters. Using such constraint to limit the attraction between clusters, a termination condition can be easily defined. The new clustering algorithm is evaluated objectively and subjectively on three different images against the K-means clustering algorithm, the recursive histogram clustering algorithm for color, the Hedley-Yan algorithm, and the widely used seed-based region growing algorithm. From the evaluation, it is observed that the new algorithm exhibits the following characteristics: (1) its objective measurement figures are comparable with the best in this group of segmentation algorithms; (2) it generates smoother region boundaries; (3) the segmented boundaries align closely with the original boundaries; and (4) it forms a meaningful number of segmented regions.

  8. Color image segmentation using watershed and Nyström method based spectral clustering

    NASA Astrophysics Data System (ADS)

    Bai, Xiaodong; Cao, Zhiguo; Yu, Zhenghong; Zhu, Hu

    2011-11-01

    Color image segmentation draws a lot of attention recently. In order to improve efficiency of spectral clustering in color image segmentation, a novel two-stage color image segmentation method is proposed. In the first stage, we use vector gradient approach to detect color image gradient information, and watershed transformation to get the pre-segmentation result. In the second stage, Nyström extension based spectral clustering is used to get the final result. To verify the proposed algorithm, it is applied to color images from the Berkeley Segmentation Dataset. Experiments show our method can bring promising results and reduce the runtime significantly.

  9. Development of a novel 2D color map for interactive segmentation of histological images

    PubMed Central

    Chaudry, Qaiser; Sharma, Yachna; Raza, Syed H.; Wang, May D.

    2016-01-01

    We present a color segmentation approach based on a two-dimensional color map derived from the input image. Pathologists stain tissue biopsies with various colored dyes to see the expression of biomarkers. In these images, because of color variation due to inconsistencies in experimental procedures and lighting conditions, the segmentation used to analyze biological features is usually ad-hoc. Many algorithms like K-means use a single metric to segment the image into different color classes and rarely provide users with powerful color control. Our 2D color map interactive segmentation technique based on human color perception information and the color distribution of the input image, enables user control without noticeable delay. Our methodology works for different staining types and different types of cancer tissue images. Our proposed method’s results show good accuracy with low response and computational time making it a feasible method for user interactive applications involving segmentation of histological images.

  10. The PCNN adaptive segmentation algorithm based on visual perception

    NASA Astrophysics Data System (ADS)

    Zhao, Yanming

    To solve network adaptive parameter determination problem of the pulse coupled neural network (PCNN), and improve the image segmentation results in image segmentation. The PCNN adaptive segmentation algorithm based on visual perception of information is proposed. Based on the image information of visual perception and Gabor mathematical model of Optic nerve cells receptive field, the algorithm determines adaptively the receptive field of each pixel of the image. And determines adaptively the network parameters W, M, and β of PCNN by the Gabor mathematical model, which can overcome the problem of traditional PCNN parameter determination in the field of image segmentation. Experimental results show that the proposed algorithm can improve the region connectivity and edge regularity of segmentation image. And also show the PCNN of visual perception information for segmentation image of advantage.

  11. 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.

  12. 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.

  13. 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.

  14. Adaptive textural segmentation of medical images

    NASA Astrophysics Data System (ADS)

    Kuklinski, Walter S.; Frost, Gordon S.; MacLaughlin, Thomas

    1992-06-01

    A number of important problems in medical imaging can be described as segmentation problems. Previous fractal-based image segmentation algorithms have used either the local fractal dimension alone or the local fractal dimension and the corresponding image intensity as features for subsequent pattern recognition algorithms. An image segmentation algorithm that utilized the local fractal dimension, image intensity, and the correlation coefficient of the local fractal dimension regression analysis computation, to produce a three-dimension feature space that was partitioned to identify specific pixels of dental radiographs as being either bone, teeth, or a boundary between bone and teeth also has been reported. In this work we formulated the segmentation process as a configurational optimization problem and discuss the application of simulated annealing optimization methods to the solution of this specific optimization problem. The configurational optimization method allows information about both, the degree of correspondence between a candidate segment and an assumed textural model, and morphological information about the candidate segment to be used in the segmentation process. To apply this configurational optimization technique with a fractal textural model however, requires the estimation of the fractal dimension of an irregularly shaped candidate segment. The potential utility of a discrete Gerchberg-Papoulis bandlimited extrapolation algorithm to the estimation of the fractal dimension of an irregularly shaped candidate segment is also discussed.

  15. Region-Based Object Recognition by Color Segmentation Using a Simplified PCNN.

    PubMed

    Chen, Yuli; Ma, Yide; Kim, Dong Hwan; Park, Sung-Kee

    2015-08-01

    In this paper, we propose a region-based object recognition (RBOR) method to identify objects from complex real-world scenes. First, the proposed method performs color image segmentation by a simplified pulse-coupled neural network (SPCNN) for the object model image and test image, and then conducts a region-based matching between them. Hence, we name it as RBOR with SPCNN (SPCNN-RBOR). Hereinto, the values of SPCNN parameters are automatically set by our previously proposed method in terms of each object model. In order to reduce various light intensity effects and take advantage of SPCNN high resolution on low intensities for achieving optimized color segmentation, a transformation integrating normalized Red Green Blue (RGB) with opponent color spaces is introduced. A novel image segmentation strategy is suggested to group the pixels firing synchronously throughout all the transformed channels of an image. Based on the segmentation results, a series of adaptive thresholds, which is adjustable according to the specific object model is employed to remove outlier region blobs, form potential clusters, and refine the clusters in test images. The proposed SPCNN-RBOR method overcomes the drawback of feature-based methods that inevitably includes background information into local invariant feature descriptors when keypoints locate near object boundaries. A large number of experiments have proved that the proposed SPCNN-RBOR method is robust for diverse complex variations, even under partial occlusion and highly cluttered environments. In addition, the SPCNN-RBOR method works well in not only identifying textured objects, but also in less-textured ones, which significantly outperforms the current feature-based methods.

  16. 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.

  17. Adaptive color visualization for dichromats using a customized hierarchical palette

    NASA Astrophysics Data System (ADS)

    Rodríguez-Pardo, Carlos E.; Sharma, Gaurav

    2011-01-01

    We propose a user-centric methodology for displaying digital color documents, that optimizes color representations in an observer specific and adaptive fashion. We apply our framework to situations involving viewers with common dichromatic color vision deficiencies, who face challenges in perceiving information presented in color images and graphics designed for color normal individuals. For situations involving qualitative data visualization, we present a computationally efficient solution that combines a customized observer-specific hierarchical palette with "display time" selection of the number of colors to generate renderings with colors that are easily discriminated by the intended viewer. The palette design is accomplished via a clustering algorithm, that arranges colors in a hierarchical tree based on their perceived differences for the intended viewer. A desired number of highly discriminable colors are readily obtained from the hierarchical palette via a simple truncation. As an illustration, we demonstrate the application of the methodology to Ishihara style images.

  18. 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.

  19. 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

  20. Monochrome Image Presentation and Segmentation Based on the Pseudo-Color and PCT Transformations

    DTIC Science & Technology

    2001-10-25

    image classification and pattern recognition, and has received extensive attention in medical image such as MRI brain image segmentation [6]. FCM is...in pseudo color image segmentation, and comparisons were made using mammograph and MRI brain images. Finally, an image edge detection has also been...methods. (a) MRI T1 image; (b) MRI T2 image; (c) PCT- guided segmentation; (d) FCM -based segmentation (NK=4, NC=2). D. Edge detection in MRI image It

  1. 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.

  2. Image segmentation on adaptive edge-preserving smoothing

    NASA Astrophysics Data System (ADS)

    He, Kun; Wang, Dan; Zheng, Xiuqing

    2016-09-01

    Nowadays, typical active contour models are widely applied in image segmentation. However, they perform badly on real images with inhomogeneous subregions. In order to overcome the drawback, this paper proposes an edge-preserving smoothing image segmentation algorithm. At first, this paper analyzes the edge-preserving smoothing conditions for image segmentation and constructs an edge-preserving smoothing model inspired by total variation. The proposed model has the ability to smooth inhomogeneous subregions and preserve edges. Then, a kind of clustering algorithm, which reasonably trades off edge-preserving and subregion-smoothing according to the local information, is employed to learn the edge-preserving parameter adaptively. At last, according to the confidence level of segmentation subregions, this paper constructs a smoothing convergence condition to avoid oversmoothing. Experiments indicate that the proposed algorithm has superior performance in precision, recall, and F-measure compared with other segmentation algorithms, and it is insensitive to noise and inhomogeneous-regions.

  3. 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.

  4. Adaptive and accurate color edge extraction method for one-shot shape acquisition

    NASA Astrophysics Data System (ADS)

    Yin, Wei; Cheng, Xiaosheng; Cui, Haihua; Li, Dawei; Zhou, Lei

    2016-09-01

    This paper presents an approach to extract accurate color edge information using encoded patterns in hue, saturation, and intensity (HSI) color space. This method is applied to one-shot shape acquisition. Theoretical analysis shows that the hue transition between primary and secondary colors in a color edge is based on light interference and diffraction. We set up a color transition model to illustrate the hue transition on an edge and then define the segmenting position of two stripes. By setting up an adaptive HSI color space, the colors of the stripes and subpixel edges are obtained precisely without a dark laboratory environment, in a low-cost processing algorithm. Since this method does not have any constraints for colors of neighboring stripes, the encoding is an easy procedure. The experimental results show that the edges of dense modulation patterns can be obtained under a complicated environment illumination, and the precision can ensure that the three-dimensional shape of the object is obtained reliably with only one image.

  5. 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

  6. An adaptive multi-feature segmentation model for infrared image

    NASA Astrophysics Data System (ADS)

    Zhang, Tingting; Han, Jin; Zhang, Yi; Bai, Lianfa

    2016-04-01

    Active contour models (ACM) have been extensively applied to image segmentation, conventional region-based active contour models only utilize global or local single feature information to minimize the energy functional to drive the contour evolution. Considering the limitations of original ACMs, an adaptive multi-feature segmentation model is proposed to handle infrared images with blurred boundaries and low contrast. In the proposed model, several essential local statistic features are introduced to construct a multi-feature signed pressure function (MFSPF). In addition, we draw upon the adaptive weight coefficient to modify the level set formulation, which is formed by integrating MFSPF with local statistic features and signed pressure function with global information. Experimental results demonstrate that the proposed method can make up for the inadequacy of the original method and get desirable results in segmenting infrared images.

  7. 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.

  8. 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%.

  9. A quaternion-based spectral clustering method for color image segmentation

    NASA Astrophysics Data System (ADS)

    Li, Xiang; Jin, Lianghai; Liu, Hong; He, Zeng

    2011-11-01

    Spectral clustering method has been widely used in image segmentation. A key issue in spectral clustering is how to build the affinity matrix. When it is applied to color image segmentation, most of the existing methods either use Euclidean metric to define the affinity matrix, or first converting color-images into gray-level images and then use the gray-level images to construct the affinity matrix (component-wise method). However, it is known that Euclidean distances can not represent the color differences well and the component-wise method does not consider the correlation between color channels. In this paper, we propose a new method to produce the affinity matrix, in which the color images are first represented in quaternion form and then the similarities between color pixels are measured by quaternion rotation (QR) mechanism. The experimental results show the superiority of the new method.

  10. [Automatic houses detection with color aerial images based on image segmentation].

    PubMed

    He, Pei-Pei; Wan, You-Chuan; Jiang, Peng-Rui; Gao, Xian-Jun; Qin, Jia-Xin

    2014-07-01

    In order to achieve housing automatic detection from high-resolution aerial imagery, the present paper utilized the color information and spectral characteristics of the roofing material, with the image segmentation theory, to study the housing automatic detection method. Firstly, This method proposed in this paper converts the RGB color space to HIS color space, uses the characteristics of each component of the HIS color space and the spectral characteristics of the roofing material for image segmentation to isolate red tiled roofs and gray cement roof areas, and gets the initial segmentation housing areas by using the marked watershed algorithm. Then, region growing is conducted in the hue component with the seed segment sample by calculating the average hue in the marked region. Finally through the elimination of small spots and rectangular fitting process to obtain a clear outline of the housing area. Compared with the traditional pixel-based region segmentation algorithm, the improved method proposed in this paper based on segment growing is in a one-dimensional color space to reduce the computation without human intervention, and can cater to the geometry information of the neighborhood pixels so that the speed and accuracy of the algorithm has been significantly improved. A case study was conducted to apply the method proposed in this paper to high resolution aerial images, and the experimental results demonstrate that this method has a high precision and rational robustness.

  11. A pixel-based color image segmentation using support vector machine and fuzzy C-means.

    PubMed

    Wang, Xiang-Yang; Zhang, Xian-Jin; Yang, Hong-Ying; Bu, Juan

    2012-09-01

    Image segmentation is an important tool in image processing and can serve as an efficient front end to sophisticated algorithms and thereby simplify subsequent processing. In this paper, we present a pixel-based color image segmentation using Support Vector Machine (SVM) and Fuzzy C-Means (FCM). Firstly, the pixel-level color feature and texture feature of the image, which is used as input of the SVM model (classifier), are extracted via the local spatial similarity measure model and Steerable filter. Then, the SVM model (classifier) is trained by using FCM with the extracted pixel-level features. Finally, the color image is segmented with the trained SVM model (classifier). This image segmentation can not only take full advantage of the local information of the color image but also the ability of the SVM classifier. Experimental evidence shows that the proposed method has a very effective computational behavior and effectiveness, and decreases the time and increases the quality of color image segmentation in comparison with the state-of-the-art segmentation methods recently proposed in the literature.

  12. 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.

  13. 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.

  14. 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.

  15. Indexing Flowers by Color Names Using Domain Knowledge-Driven Segmentation.

    DTIC Science & Technology

    1997-01-01

    We describe a solution to the problem of indexing image of flowers for searching a flower patents database by ers iii t color. We use a natural...segmentation algorithm with knowledge natnral driven feedback to isolate a flower region from the background. The color of the flower is defined by the...color names present in the flower region and their relative proportions. The database can be queried by example and by color names. We demonstrate the effectiveness of the strategy on a test database.

  16. 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

  17. [Study of color blood image segmentation based on two-stage-improved FCM algorithm].

    PubMed

    Wang, Bin; Chen, Huaiqing; Huang, Hua; Rao, Jie

    2006-04-01

    This paper introduces a new method for color blood cell image segmentation based on FCM algorithm. By transforming the original blood microscopic image to indexed image, and by doing the colormap, a fuzzy apparoach to obviating the direct clustering of image pixel values, the quantity of data processing and analysis is enormously compressed. In accordance to the inherent features of color blood cell image, the segmentation process is divided into two stages. (1)confirming the number of clusters and initial cluster centers; (2) altering the distance measuring method by the distance weighting matrix in order to improve the clustering veracity. In this way, the problem of difficult convergence of FCM algorithm is solved, the iteration time of iterative convergence is reduced, the execution time of algarithm is decreased, and the correct segmentation of the components of color blood cell image is implemented.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. The new adaptive enhancement algorithm on the degraded color images

    NASA Astrophysics Data System (ADS)

    Xue, Rong Kun; He, Wei; Li, Yufeng

    2016-10-01

    Based on the scene characteristics of frequency distribution in the degraded color images, the MSRCR method and wavelet transform in the paper are introduced respectively to enhance color images and the advantages and disadvantages of them are analyzed combining with the experiment, then the combination of improved MSRCR method and wavelet transform are proposed to enhance color images, it uses wavelet to decompose color images in order to increase the coefficient of low-level details and reduce top-level details to highlight the scene information, meanwhile, the method of improved MSRCR is used to enhance the low-frequency components of degraded images processed by wavelet, then the adaptive equalization is carried on to further enhance images, finally, the enhanced color images are acquired with the reconstruction of all the coefficients brought by the wavelet transform. Through the evaluation of the experimental results and data analysis, it shows that the method proposed in the paper is better than the separate use of wavelet transform and MSRCR method.

  3. 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.

  4. Fast unsupervised Bayesian image segmentation with adaptive spatial regularisation.

    PubMed

    Pereyra, Marcelo; McLaughlin, Stephen

    2017-03-15

    This paper presents a new Bayesian estimation technique for hidden Potts-Markov random fields with unknown regularisation parameters, with application to fast unsupervised K-class image segmentation. The technique is derived by first removing the regularisation parameter from the Bayesian model by marginalisation, followed by a small-variance-asymptotic (SVA) analysis in which the spatial regularisation and the integer-constrained terms of the Potts model are decoupled. The evaluation of this SVA Bayesian estimator is then relaxed into a problem that can be computed efficiently by iteratively solving a convex total-variation denoising problem and a least-squares clustering (K-means) problem, both of which can be solved straightforwardly, even in high-dimensions, and with parallel computing techniques. This leads to a fast fully unsupervised Bayesian image segmentation methodology in which the strength of the spatial regularisation is adapted automatically to the observed image during the inference procedure, and that can be easily applied in large 2D and 3D scenarios or in applications requiring low computing times. Experimental results on synthetic and real images, as well as extensive comparisons with state-ofthe- art algorithms, confirm that the proposed methodology offer extremely fast convergence and produces accurate segmentation results, with the important additional advantage of self-adjusting regularisation parameters.

  5. 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

  6. Adaptive clutter rejection for ultrasound color Doppler imaging

    NASA Astrophysics Data System (ADS)

    Yoo, Yang Mo; Managuli, Ravi; Kim, Yongmin

    2005-04-01

    We have developed a new adaptive clutter rejection technique where an optimum clutter filter is dynamically selected according to the varying clutter characteristics in ultrasound color Doppler imaging. The selection criteria have been established based on the underlying clutter characteristics (i.e., the maximum instantaneous clutter velocity and the clutter power) and the properties of various candidate clutter filters (e.g., projection-initialized infinite impulse response and polynomial regression). We obtained an average improvement of 3.97 dB and 3.27 dB in flow signal-to-clutter-ratio (SCR) compared to the conventional and down-mixing methods, respectively. These preliminary results indicate that the proposed adaptive clutter rejection method could improve the sensitivity and accuracy in flow velocity estimation for ultrasound color Doppler imaging. For a 192 x 256 color Doppler image with an ensemble size of 10, the proposed method takes only 57.2 ms, which is less than the acquisition time. Thus, the proposed method could be implemented in modern ultrasound systems, while providing improved clutter rejection and more accurate velocity estimation in real time.

  7. Color diffusion model for active contours - an application to skin lesion segmentation.

    PubMed

    Ivanovici, Mihai; Stoica, Diana

    2012-01-01

    Most of the existing diffusion models are defined for gray-scale images. We propose a diffusion model for color images to be used as external energy for active contours. Our diffusion model is based on the first-order moment of the correlation integral expressed using ΔE distances in the CIE Lab color space. We use a multi-scale approach for active contours, the diffusion being independently computed at various scales. We validate the model on synthetic images, including multi-fractal color textures, as well as medical images representing melanoma. We conclude that the proposed diffusion model is valid for use in skin lesion segmentation in color images using active contours.

  8. Image segmentation by EM-based adaptive pulse coupled neural networks in brain magnetic resonance imaging.

    PubMed

    Fu, J C; Chen, C C; Chai, J W; Wong, S T C; Li, I C

    2010-06-01

    We propose an automatic hybrid image segmentation model that integrates the statistical expectation maximization (EM) model and the spatial pulse coupled neural network (PCNN) for brain magnetic resonance imaging (MRI) segmentation. In addition, an adaptive mechanism is developed to fine tune the PCNN parameters. The EM model serves two functions: evaluation of the PCNN image segmentation and adaptive adjustment of the PCNN parameters for optimal segmentation. To evaluate the performance of the adaptive EM-PCNN, we use it to segment MR brain image into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). The performance of the adaptive EM-PCNN is compared with that of the non-adaptive EM-PCNN, EM, and Bias Corrected Fuzzy C-Means (BCFCM) algorithms. The result is four sets of boundaries for the GM and the brain parenchyma (GM+WM), the two regions of most interest in medical research and clinical applications. Each set of boundaries is compared with the golden standard to evaluate the segmentation performance. The adaptive EM-PCNN significantly outperforms the non-adaptive EM-PCNN, EM, and BCFCM algorithms in gray mater segmentation. In brain parenchyma segmentation, the adaptive EM-PCNN significantly outperforms the BCFCM only. However, the adaptive EM-PCNN is better than the non-adaptive EM-PCNN and EM on average. We conclude that of the three approaches, the adaptive EM-PCNN yields the best results for gray matter and brain parenchyma segmentation.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. MEMS segmented-based adaptive optics scanning laser ophthalmoscope

    PubMed Central

    Manzanera, Silvestre; Helmbrecht, Michael A.; Kempf, Carl J.; Roorda, Austin

    2011-01-01

    The performance of a MEMS (micro-electro-mechanical-system) segmented deformable mirror was evaluated in an adaptive optics (AO) scanning laser ophthalmoscope. The tested AO mirror (Iris AO, Inc, Berkeley, CA) is composed of 37 hexagonal segments that allow piston/tip/tilt motion up to 5 μm stroke and ±5 mrad angle over a 3.5 mm optical aperture. The control system that implements the closed-loop operation employs a 1:1 matched 37-lenslet Shack-Hartmann wavefront sensor whose measurements are used to apply modal corrections to the deformable mirror. After a preliminary evaluation of the AO mirror optical performance, retinal images from 4 normal subjects over a 0.9°x0.9° field size were acquired through a 6.4 mm ocular pupil, showing resolved retinal features at the cellular level. Cone photoreceptors were observed as close as 0.25 degrees from the foveal center. In general, the quality of these images is comparable to that obtained using deformable mirrors based on different technologies. PMID:21559132

  14. 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)%.

  15. Adaptive Optics Educational Outreach and the Giant Segmented Mirror Telescope

    NASA Astrophysics Data System (ADS)

    Sparks, R. T.; Pompea, S. M.; Walker, C. E.

    2008-06-01

    One of the limiting factors in telescope performance is atmospheric seeing. Atmospheric seeing limits the resolution of ground based optical telescopes. Even telescopes in good locations on top of mountains cannot achieve diffraction-limited resolution. Until recently, the only way to overcome this limitation was to use space-based telescopes. Adaptive Optics (AO) is a collection of technologies that measure the turbulence of Earth's atmosphere and compensate for the turbulence, resulting in high-resolution images without the expense and complexity of space based telescopes. Our Hands-On Optics program has developed activities that teach students how telescopes form images and make observations about the resolution of a telescope. We are developing materials for high school students to use in the study of adaptive optics. These activities include various ways to illustrate atmospheric distortion by using everyday materials such as bubble wrap and mineral oil. We will also illustrate how to demonstrate the workings of a Shack-Hartman sensor to measure atmospheric distortion through the use of a unique model. We will also show activities illustrating two techniques astronomers use to improve the image: tip-tilt mirrors and deformable mirrors. We are developing an activity where students learn how to use a tip-tilt mirror to keep an image focused at one point on a screen. The culminating activity has students learn to use a deformable mirror to correct a distorted wavefront. These activities are being developed in conjunction with the Education program for the Giant Segmented Mirror Telescope (GSMT).

  16. Segmentally variable genes: a new perspective on adaptation.

    PubMed

    Zheng, Yu; Roberts, Richard J; Kasif, Simon

    2004-04-01

    Genomic sequence variation is the hallmark of life and is key to understanding diversity and adaptation among the numerous microorganisms on earth. Analysis of the sequenced microbial genomes suggests that genes are evolving at many different rates. We have attempted to derive a new classification of genes into three broad categories: lineage-specific genes that evolve rapidly and appear unique to individual species or strains; highly conserved genes that frequently perform housekeeping functions; and partially variable genes that contain highly variable regions, at least 70 amino acids long, interspersed among well-conserved regions. The latter we term segmentally variable genes (SVGs), and we suggest that they are especially interesting targets for biochemical studies. Among these genes are ones necessary to deal with the environment, including genes involved in host-pathogen interactions, defense mechanisms, and intracellular responses to internal and environmental changes. For the most part, the detailed function of these variable regions remains unknown. We propose that they are likely to perform important binding functions responsible for protein-protein, protein-nucleic acid, or protein-small molecule interactions. Discerning their function and identifying their binding partners may offer biologists new insights into the basic mechanisms of adaptation, context-dependent evolution, and the interaction between microbes and their environment.

  17. 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.

  18. 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

  19. Adaptive skin segmentation via feature-based face detection

    NASA Astrophysics Data System (ADS)

    Taylor, Michael J.; Morris, Tim

    2014-05-01

    Variations in illumination can have significant effects on the apparent colour of skin, which can be damaging to the efficacy of any colour-based segmentation approach. We attempt to overcome this issue by presenting a new adaptive approach, capable of generating skin colour models at run-time. Our approach adopts a Viola-Jones feature-based face detector, in a moderate-recall, high-precision configuration, to sample faces within an image, with an emphasis on avoiding potentially detrimental false positives. From these samples, we extract a set of pixels that are likely to be from skin regions, filter them according to their relative luma values in an attempt to eliminate typical non-skin facial features (eyes, mouths, nostrils, etc.), and hence establish a set of pixels that we can be confident represent skin. Using this representative set, we train a unimodal Gaussian function to model the skin colour in the given image in the normalised rg colour space - a combination of modelling approach and colour space that benefits us in a number of ways. A generated function can subsequently be applied to every pixel in the given image, and, hence, the probability that any given pixel represents skin can be determined. Segmentation of the skin, therefore, can be as simple as applying a binary threshold to the calculated probabilities. In this paper, we touch upon a number of existing approaches, describe the methods behind our new system, present the results of its application to arbitrary images of people with detectable faces, which we have found to be extremely encouraging, and investigate its potential to be used as part of real-time systems.

  20. Adaptive local linear regression with application to printer color management.

    PubMed

    Gupta, Maya R; Garcia, Eric K; Chin, Erika

    2008-06-01

    Local learning methods, such as local linear regression and nearest neighbor classifiers, base estimates on nearby training samples, neighbors. Usually, the number of neighbors used in estimation is fixed to be a global "optimal" value, chosen by cross validation. This paper proposes adapting the number of neighbors used for estimation to the local geometry of the data, without need for cross validation. The term enclosing neighborhood is introduced to describe a set of neighbors whose convex hull contains the test point when possible. It is proven that enclosing neighborhoods yield bounded estimation variance under some assumptions. Three such enclosing neighborhood definitions are presented: natural neighbors, natural neighbors inclusive, and enclosing k-NN. The effectiveness of these neighborhood definitions with local linear regression is tested for estimating lookup tables for color management. Significant improvements in error metrics are shown, indicating that enclosing neighborhoods may be a promising adaptive neighborhood definition for other local learning tasks as well, depending on the density of training samples.

  1. Adaptive Local Linear Regression with Application to Printer Color Management

    DTIC Science & Technology

    2008-01-01

    values formed the test samples. This process guaranteed that the CIELAB test samples were in the gamut for each printer, but each printer had a...digital images has recently led to increased consumer demand for accurate color reproduction. Given a CIELAB color one would like to reproduce, the color...management problem is to determine what RGB color one must send the printer to minimize the error between the desired CIELAB color and the CIELAB

  2. Pattern matching and adaptive image segmentation applied to plant reproduction by tissue culture

    NASA Astrophysics Data System (ADS)

    Vazquez Rueda, Martin G.; Hahn, Federico

    1999-03-01

    This paper shows the results obtained in a system vision applied to plant reproduction by tissue culture using adaptive image segmentation and pattern matching algorithms, this analysis improves the number of tissue obtained and minimize errors, the image features of tissue are considered join to statistical analysis to determine the best match and results. Tests make on potato plants are used to present comparative results with original images processed with adaptive segmentation algorithm and non adaptive algorithms and pattern matching.

  3. Optic disc and cup segmentation from color fundus photograph using graph cut with priors.

    PubMed

    Zheng, Yuanjie; Stambolian, Dwight; O'Brien, Joan; Gee, James C

    2013-01-01

    For automatic segmentation of optic disc and cup from color fundus photograph, we describe a fairly general energy function that can naturally fit into a global optimization framework with graph cut. Distinguished from most previous work, our energy function includes priors on the shape & location of disc & cup, the rim thickness and the geometric interaction of "disc contains cup". These priors together with the effective optimization of graph cut enable our algorithm to generate reliable and robust solutions. Our approach is able to outperform several state-of-the-art segmentation methods, as shown by a set of experimental comparisons with manual delineations and a series of results of correlations with the assessments of a merchant-provided software from Optical Coherence Tomography (OCT) regarding several cup and disc parameters.

  4. Color-based tumor tissue segmentation for the automated estimation of oral cancer parameters.

    PubMed

    Sun, Yung-Nien; Wang, Yi-Ying; Chang, Shao-Chien; Wu, Li-Wha; Tsai, Sen-Tien

    2010-01-01

    This article presents an automatic color-based feature extraction system for parameter estimation of oral cancer from optical microscopic images. The system first reduces image-to-image variations by means of color normalization. We then construct a database which consists of typical cancer images. The color parameters extracted from this database are then used in automated online sampling from oral cancer images. Principal component analysis is subsequently used to divide the color features into four tissue types. Each pixel in the cancer image is then classified into the corresponding tissue types based on the Mahalanobis distance. The aforementioned procedures are all fully automated; in particular, the automated sampling step greatly reduces the need for intensive labor in manual sampling and training. Experiments reveal high levels of consistency among the results achieved using the manual, semiautomatic, and fully automatic methods. Parameter comparisons between the four cancer stages are conducted, and only the mean parameters between early and late cancer stages are statistically different. In summary, the proposed system provides a useful and convenient tool for automatic segmentation and evaluation for stained biopsy samples of oral cancer. This tool can also be modified and applied to other tissue images with similar staining conditions.

  5. Image segmentation on adaptive sub-region smoothing

    NASA Astrophysics Data System (ADS)

    Gao, Junruo; Liu, Xin; He, Kun

    2017-01-01

    To improve the performance of the active contour segmentation on real images, a new segmentation method is proposed. In this model, we construct a function about Gaussian variance according to sub-regions intensity. Further, to avoid the curve vanishing, we design the convergence condition based on the confidence level of segmentation sub-regions. Experimental results show that the proposed method is less sensitive to noise and can suppress inhomogeneous intensity regions efficiently.

  6. 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.

  7. 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.

  8. 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

  9. Adaptive optics control system for segmented MEMS deformable mirrors

    NASA Astrophysics Data System (ADS)

    Kempf, Carl J.; Helmbrecht, Michael A.; Besse, Marc

    2010-02-01

    Iris AO has developed a full closed-loop control system for control of segmented MEMS deformable mirrors. It is based on a combination of matched wavefront sensing, modal wavefront estimation, and well-calibrated open-loop characteristics. This assures closed-loop operation free of problems related to co-phasing segments or undetectable waffle patterns. This controller strategy results in relatively simple on-line computations which are suitable for implementation on low cost digital signal processors. It has been successfully implemented on Iris AO's 111 actuator (37 segment) deformable mirrors used in test-beds and research systems.

  10. LoAd: A locally adaptive cortical segmentation algorithm

    PubMed Central

    Cardoso, M. Jorge; Clarkson, Matthew J.; Ridgway, Gerard R.; Modat, Marc; Fox, Nick C.; Ourselin, Sebastien

    2012-01-01

    Thickness measurements of the cerebral cortex can aid diagnosis and provide valuable information about the temporal evolution of diseases such as Alzheimer's, Huntington's, and schizophrenia. Methods that measure the thickness of the cerebral cortex from in-vivo magnetic resonance (MR) images rely on an accurate segmentation of the MR data. However, segmenting the cortex in a robust and accurate way still poses a challenge due to the presence of noise, intensity non-uniformity, partial volume effects, the limited resolution of MRI and the highly convoluted shape of the cortical folds. Beginning with a well-established probabilistic segmentation model with anatomical tissue priors, we propose three post-processing refinements: a novel modification of the prior information to reduce segmentation bias; introduction of explicit partial volume classes; and a locally varying MRF-based model for enhancement of sulci and gyri. Experiments performed on a new digital phantom, on BrainWeb data and on data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) show statistically significant improvements in Dice scores and PV estimation (p<10−3) and also increased thickness estimation accuracy when compared to three well established techniques. PMID:21316470

  11. 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.

  12. Pupil-segmentation-based adaptive optical microscopy with full-pupil illumination.

    PubMed

    Milkie, Daniel E; Betzig, Eric; Ji, Na

    2011-11-01

    Optical aberrations deteriorate the performance of microscopes. Adaptive optics can be used to improve imaging performance via wavefront shaping. Here, we demonstrate a pupil-segmentation based adaptive optical approach with full-pupil illumination. When implemented in a two-photon fluorescence microscope, it recovers diffraction-limited performance and improves imaging signal and resolution.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Thermal adaptiveness of plumage color in screech owls

    USGS Publications Warehouse

    Mosher, J.A.; Henny, C.J.

    1976-01-01

    We measured oxygen consumption rates of 8 Screech? Owls (4 red and 4 gray phase) at 4 environmental temperatures, -10?, -5?, 5?, and 15?C. These data demonstrated a significant difference in oxygen uptake between color phases at -10? and -5?C. This supports our hypothesis that red phase Screech Owls are restricted in their northern distribution by color-related metabolic differences from the gray phase birds. The problems of low red phase occurrence in the Gulf Coast states and their absence from the Western states remain to be studied.

  18. Adaptation of spherical harmonic transform for color shape reconstruction and retrieval using quaternion algebra

    NASA Astrophysics Data System (ADS)

    Dad, Nisrine; En-Nahnahi, Noureddine; Ouatik, Said El Alaoui; Oumsis, Mohammed

    2016-09-01

    A set of invariant quaternion moments based on an adaptation of the three-dimensional (3-D) spherical harmonic transform (SHT) for describing two-dimensional color shapes is proposed. The use of quaternions to deal with the color part is beneficial in the way the three color components are integrated in a single feature. An adequate mapping from the 3-D SHT to the unit disc allows a fast and accurate computation of the proposed moments. Experiments are conducted to evaluate the performance of the obtained moments in terms of color image reconstruction, robustness to geometric and photometric transformations, content-based color shape retrieval, and computation time. For this purpose, two image databases (COIL-100 and ALOI) are used. Results illustrate the effectiveness of the proposed moments in dealing with the color information.

  19. 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)

  20. Adaptive thresholding technique for retinal vessel segmentation based on GLCM-energy information.

    PubMed

    Mapayi, Temitope; Viriri, Serestina; Tapamo, Jules-Raymond

    2015-01-01

    Although retinal vessel segmentation has been extensively researched, a robust and time efficient segmentation method is highly needed. This paper presents a local adaptive thresholding technique based on gray level cooccurrence matrix- (GLCM-) energy information for retinal vessel segmentation. Different thresholds were computed using GLCM-energy information. An experimental evaluation on DRIVE database using the grayscale intensity and Green Channel of the retinal image demonstrates the high performance of the proposed local adaptive thresholding technique. The maximum average accuracy rates of 0.9511 and 0.9510 with maximum average sensitivity rates of 0.7650 and 0.7641 were achieved on DRIVE and STARE databases, respectively. When compared to the widely previously used techniques on the databases, the proposed adaptive thresholding technique is time efficient with a higher average sensitivity and average accuracy rates in the same range of very good specificity.

  1. 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.

  2. Adaptable active contour model with applications to infrared ship target segmentation

    NASA Astrophysics Data System (ADS)

    Fang, Lingling; Wang, Xianghai; Wan, Yu

    2016-07-01

    Active contour model is widely and popularly used in the field of image segmentation because of its superior theoretical properties and efficient numerical methods. An algorithm to segment a ship target in infrared (IR) images using Chan-Vese (C-V) active contour model is proposed here. The method effectively integrates both image regional and boundary information by an adaptable weight function. The method can segment IR ship images, which usually contain noises, blurry boundaries, and heterogeneous regions. In addition, compared with the state-of-the-art methods, experiment results demonstrate the performance and effectiveness of this method.

  3. 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

  4. Indexing Flowers by Color Names using Domain Knowledge-driven Segmentation,

    DTIC Science & Technology

    1998-01-01

    We describe a solution to the problem of indexing images of flowers for searching a flower patents database by color. We use a natural language color...feedback to isolate a flower region from the background. The color of the flower is defined by the color names present in the flower region and their

  5. Interactive high-quality visualization of color volume datasets using GPU-based refinements of segmentation data.

    PubMed

    Lee, Byeonghun; Kwon, Koojoo; Shin, Byeong-Seok

    2016-04-24

    Data sets containing colored anatomical images of the human body, such as Visible Human or Visible Korean, show realistic internal organ structures. However, imperfect segmentations of these color images, which are typically generated manually or semi-automatically, produces poor-quality rendering results. We propose an interactive high-quality visualization method using GPU-based refinements to aid in the study of anatomical structures. In order to represent the boundaries of a region-of-interest (ROI) smoothly, we apply Gaussian filtering to the opacity values of the color volume. Morphological grayscale erosion operations are performed to reduce the region size, which is expanded by Gaussian filtering. Pseudo-coloring and color blending are also applied to the color volume in order to give more informative rendering results. We implement these operations on GPUs to speed up the refinements. As a result, our method delivered high-quality result images with smooth boundaries and provided considerably faster refinements. The speed of these refinements is sufficient to be used with interactive renderings as the ROI changes, especially compared to CPU-based methods. Moreover, the pseudo-coloring methods used presented anatomical structures clearly.

  6. 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.

  7. MRI Brain Tumor Segmentation and Necrosis Detection Using Adaptive Sobolev Snakes

    PubMed Central

    Nakhmani, Arie; Kikinis, Ron; Tannenbaum, Allen

    2014-01-01

    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 different 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 diffusion 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. PMID:25302005

  8. 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).

  9. 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.

  10. 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.

  11. 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.

  12. Fabricating a better mouthguard. Part II: the effect of color on adaptation and fit.

    PubMed

    Del Rossi, Gianluca; Lisman, Peter; Signorile, Joseph

    2008-04-01

    The thermoforming process involves the heating of plastic sheets to a critical temperature followed by the shaping of the heated material into a three-dimensional structure. Given that custom-fabricated mouthguards are produced using the thermoforming process, the adaptation of plastic sheets to a stone model of the dentition is likely to be affected by the ability of the mouthguard material to be heated. The purpose of this study was to establish if material color affected the adaptation and fit of custom-made mouthguards. Twelve stone models were used in this investigation. Five mouthguards were produced using each model. These mouthguards were made using clear-, white-, black-, blue- and green-colored ethyl vinyl acetate. The force required to remove the various colored mouthguards from the corresponding stone models was determined using a strain gauge housed within a specially designed apparatus. Each of the mouthguards were tested three times at two different angles of pull -45 degrees and 90 degrees . Statistical tests performed using the average amount of force required for mouthguard removal revealed an angle by color interaction. Post hoc analyses revealed that the mean force required to remove the clear-colored mouthguards from their respective stone models was significantly less than the force required to pull away blue-, black- and green-colored mouthguards. This difference between clear- and dark-colored mouthguards was observed at both angles tested with the exception of the black mouthguard which differed from the clear-colored mouthguard only when removed at an angle of 90 degrees . The results of the present study indicate that by using dark-colored mouthguard material, one can achieve superior adaptation and thus produce a more firmly fitting mouthguard.

  13. The new image segmentation algorithm using adaptive evolutionary programming and fuzzy c-means clustering

    NASA Astrophysics Data System (ADS)

    Liu, Fang

    2011-06-01

    Image segmentation remains one of the major challenges in image analysis and computer vision. Fuzzy clustering, as a soft segmentation method, has been widely studied and successfully applied in mage clustering and segmentation. The fuzzy c-means (FCM) algorithm is the most popular method used in mage segmentation. However, most clustering algorithms such as the k-means and the FCM clustering algorithms search for the final clusters values based on the predetermined initial centers. The FCM clustering algorithms does not consider the space information of pixels and is sensitive to noise. In the paper, presents a new fuzzy c-means (FCM) algorithm with adaptive evolutionary programming that provides image clustering. The features of this algorithm are: 1) firstly, it need not predetermined initial centers. Evolutionary programming will help FCM search for better center and escape bad centers at local minima. Secondly, the spatial distance and the Euclidean distance is also considered in the FCM clustering. So this algorithm is more robust to the noises. Thirdly, the adaptive evolutionary programming is proposed. The mutation rule is adaptively changed with learning the useful knowledge in the evolving process. Experiment results shows that the new image segmentation algorithm is effective. It is providing robustness to noisy images.

  14. Learning self-adaptive color harmony model for aesthetic quality classification

    NASA Astrophysics Data System (ADS)

    Kuang, Zhijie; Lu, Peng; Wang, Xiaojie; Lu, Xiaofeng

    2015-03-01

    Color harmony is one of the key aspects in aesthetic quality classification for photos. The existing color harmony models either are in lack of quantization schemes or can assess simple color patterns only. Therefore, these models cannot be applied to assess color harmony of photos directly. To address this problem, we proposed a simple data-based self-adaptive color harmony model. In this model, the hue distribution of a photo is fitted by mean shift based method, then features are extracted according to this distribution and finally the Gaussian mixture model is applied for learning features extracted from all the photos. The experimental results on eight categories datasets show that the proposed method outperforms the classic rule-based methods and the state-of-the-art data-based model.

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification

    PubMed Central

    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. PMID:25945120

  20. The evolution of wing color: male mate choice opposes adaptive wing color divergence in Colias butterflies.

    PubMed

    Ellers, Jacintha; Boggs, Carol L

    2003-05-01

    Correlated evolution of mate signals and mate preference may be constrained if selection pressures acting on mate preference differ from those acting on mate signals. In particular, opposing selection pressures may act on mate preference and signals when traits have sexual as well as nonsexual functions. In the butterfly Colias philodice eriphyle, divergent selection on wing color across an elevational gradient in response to the thermal environment has led to increasing wing melanization at higher elevations. Wing color is also a long-range signal used by males in mate searching. We conducted experiments to test whether sexual selection on wing melanization via male mate choice acts in the same direction as natural selection on mate signals due to the thermal environment. We performed controlled mate choice experiments in the field over an elevational range of 1500 meters using decoy butterflies with different melanization levels. Also, we obtained a more direct estimate of the relation between wing color and sexual selection by measuring mating success in wild-caught females. Both our experiments showed that wing melanization is an important determinant of female mating success in C. p. eriphyle. However, a lack of elevational variation in male mate preference prevents coevolution of mate signals and mate preference, as males at all elevations prefer less-melanized females. We suggest that this apparently maladaptive mate choice may be maintained by differences in detectability between the morphs or by preservation of species recognition.

  1. [CT image segmentation based on automatic adaptive minimal fuzzy entropy measure].

    PubMed

    Gong, Guifang; Feng, Chengde; Zhang, Hui; Zhu, Yanfang

    2008-04-01

    In order to extract the anatomical feature of several tissues from CT image and solve the contradiction between the improvement of searching speed and the instability of results,we propose a method for image segmentation using auto adaptive minimal fuzzy entropy measure. Firstly, to find the optimal threshoding for segmenting image, the values of the exponent parameters of membership function of fuzzy subsets and the range of the searching thresholding values can be determined by using the iterative approach and the image histogram, and then the thresholding of minimizing the fuzzy entropy is implemented by searching all possible combinations of every thresholding in determinate searching range. The experiment results show that our proposed method facilitates good performance for CT image segmentation. The searching speed is quick, the segmented images show more details, and the results of many runs are steadier than those obtained by using genetic algorithm or simulated annealing algorithm.

  2. A class-adaptive spatially variant mixture model for image segmentation.

    PubMed

    Nikou, Christophoros; Galatsanos, Nikolaos P; Likas, Aristidis C

    2007-04-01

    We propose a new approach for image segmentation based on a hierarchical and spatially variant mixture model. According to this model, the pixel labels are random variables and a smoothness prior is imposed on them. The main novelty of this work is a new family of smoothness priors for the label probabilities in spatially variant mixture models. These Gauss-Markov random field-based priors allow all their parameters to be estimated in closed form via the maximum a posteriori (MAP) estimation using the expectation-maximization methodology. Thus, it is possible to introduce priors with multiple parameters that adapt to different aspects of the data. Numerical experiments are presented where the proposed MAP algorithms were tested in various image segmentation scenarios. These experiments demonstrate that the proposed segmentation scheme compares favorably to both standard and previous spatially constrained mixture model-based segmentation.

  3. Optical granulometric analysis of sedimentary deposits by color segmentation-based software: OPTGRAN-CS

    NASA Astrophysics Data System (ADS)

    Chávez, G. Moreno; Sarocchi, D.; Santana, E. Arce; Borselli, L.

    2015-12-01

    The study of grain size distribution is fundamental for understanding sedimentological environments. Through these analyses, clast erosion, transport and deposition processes can be interpreted and modeled. However, grain size distribution analysis can be difficult in some outcrops due to the number and complexity of the arrangement of clasts and matrix and their physical size. Despite various technological advances, it is almost impossible to get the full grain size distribution (blocks to sand grain size) with a single method or instrument of analysis. For this reason development in this area continues to be fundamental. In recent years, various methods of particle size analysis by automatic image processing have been developed, due to their potential advantages with respect to classical ones; speed and final detailed content of information (virtually for each analyzed particle). In this framework, we have developed a novel algorithm and software for grain size distribution analysis, based on color image segmentation using an entropy-controlled quadratic Markov measure field algorithm and the Rosiwal method for counting intersections between clast and linear transects in the images. We test the novel algorithm in different sedimentary deposit types from 14 varieties of sedimentological environments. The results of the new algorithm were compared with grain counts performed manually by the same Rosiwal methods applied by experts. The new algorithm has the same accuracy as a classical manual count process, but the application of this innovative methodology is much easier and dramatically less time-consuming. The final productivity of the new software for analysis of clasts deposits after recording field outcrop images can be increased significantly.

  4. Segmentation and tracking of the electro-encephalogram signal using an adaptive recursive bandpass filter.

    PubMed

    Gharieb, R R; Cichocki, A

    2001-03-01

    An adaptive filtering approach for the segmentation and tracking of electro-encephalogram (EEG) signal waves is described. In this approach, an adaptive recursive bandpass filter is employed for estimating and tracking the centre frequency associated with each EEG wave. The main advantage inherent in the approach is that the employed adaptive filter has only one unknown coefficient to be updated. This coefficient, having an absolute value less than 1, represents an efficient distinct feature for each EEG specific wave, and its time function reflects the non-stationarity behaviour of the EEG signal. Therefore the proposed approach is simple and accurate in comparison with existing multivariate adaptive approaches. The approach is examined using extensive computer simulations. It is applied to computer-generated EEG signals composed of different waves. The adaptive filter coefficient (i.e. the segmentation parameter) is -0.492 for the delta wave, -0.360 for the theta wave, -0.191 for the alpha wave, -0.027 for the sigma wave, 0.138 for the beta wave and 0.605 for the gamma wave. This implies that the segmentation parameter increases with the increase in the centre frequency of the EEG waves, which provides fast on-line information about the behaviour of the EEG signal. The approach is also applied to real-world EEG data for the detection of sleep spindles.

  5. Automatic cytoplasm and nuclei segmentation for color cervical smear image using an efficient gap-search MRF.

    PubMed

    Zhao, Lili; Li, Kuan; Wang, Mao; Yin, Jianping; Zhu, En; Wu, Chengkun; Wang, Siqi; Zhu, Chengzhang

    2016-04-01

    Accurate and effective cervical smear image segmentation is required for automated cervical cell analysis systems. Thus, we proposed a novel superpixel-based Markov random field (MRF) segmentation framework to acquire the nucleus, cytoplasm and image background of cell images. We seek to classify color non-overlapping superpixel-patches on one image for image segmentation. This model describes the whole image as an undirected probabilistic graphical model and was developed using an automatic label-map mechanism for determining nuclear, cytoplasmic and background regions. A gap-search algorithm was designed to enhance the model efficiency. Data show that the algorithms of our framework provide better accuracy for both real-world and the public Herlev datasets. Furthermore, the proposed gap-search algorithm of this model is much more faster than pixel-based and superpixel-based algorithms.

  6. 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

  7. Study of adaptive LLL/infrared image color fusion algorithm based on the environment illumination

    NASA Astrophysics Data System (ADS)

    Hu, Qing-ping; Zhang, Xiao-hui; Liu, Chao

    2016-10-01

    LLL (Low-light-level) / infrared image fusion can integrate both bands information of the target, it is beneficial for target detection and scene perception in the low visibility weather such as night, haze, rain, and snow. The quality of fused image is declined, when any channel image quality drops. There will be great changes in the brightness, contrast and noise on LLL images when environment illumination has obvious changes, but the current color fusion methods is not adapted to the environment illumination change in larger dynamic range. In this paper, LLL image characteristics are analyzed under different environment illumination, and a kind of adaptive color fusion method is proposed based on the RGB color space. The fused image can get better brightness and signal-to-noise ratio under the different intensity of illumination.

  8. SAR image segmentation with entropy ranking based adaptive semi-supervised spectral clustering

    NASA Astrophysics Data System (ADS)

    Zhang, Xiangrong; Yang, Jie; Hou, Biao; Jiao, Licheng

    2010-10-01

    Spectral clustering has become one of the most popular modern clustering algorithms in recent years. In this paper, a new algorithm named entropy ranking based adaptive semi-supervised spectral clustering for SAR image segmentation is proposed. We focus not only on finding a suitable scaling parameter but also determining automatically the cluster number with the entropy ranking theory. Also, two kinds of constrains must-link and cannot-link based semi-supervised spectral clustering is applied to gain better segmentation results. Experimental results on SAR images show that the proposed method outperforms other spectral clustering algorithms.

  9. Biological versus Electronic Adaptive Coloration: How Can One Inform the Other?

    DTIC Science & Technology

    2012-01-01

    which typically require batteries. However, a few displays have had solar - cells integrated into them to harvest energy [60,61]. Speed. Ideally, speed...the mechanisms of their adaptive coloration. This review includes detailed subsections on the chro- matophore organs, iridophores and leucophore cells ...mitochondria muscle cellnerve axon glial cell chromatophore structure nucleus cytoelastic sacculus capsules with charged pigment black state

  10. Cellular pulse-coupled neural network with adaptive weights for image segmentation and its VLSI implementation

    NASA Astrophysics Data System (ADS)

    Schreiter, Juerg; Ramacher, Ulrich; Heittmann, Arne; Matolin, Daniel; Schuffny, Rene

    2004-05-01

    We present a cellular pulse coupled neural network with adaptive weights and its analog VLSI implementation. The neural network operates on a scalar image feature, such as grey scale or the output of a spatial filter. It detects segments and marks them with synchronous pulses of the corresponding neurons. The network consists of integrate-and-fire neurons, which are coupled to their nearest neighbors via adaptive synaptic weights. Adaptation follows either one of two empirical rules. Both rules lead to spike grouping in wave like patterns. This synchronous activity binds groups of neurons and labels the corresponding image segments. Applications of the network also include feature preserving noise removal, image smoothing, and detection of bright and dark spots. The adaptation rules are insensitive for parameter deviations, mismatch and non-ideal approximation of the implied functions. That makes an analog VLSI implementation feasible. Simulations showed no significant differences in the synchronization properties between networks using the ideal adaptation rules and networks resembling implementation properties such as randomly distributed parameters and roughly implemented adaptation functions. A prototype is currently being designed and fabricated using an Infineon 130nm technology. It comprises a 128 × 128 neuron array, analog image memory, and an address event representation pulse output.

  11. 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

  12. 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.

  13. Automatic white matter lesion segmentation using an adaptive outlier detection method.

    PubMed

    Ong, Kok Haur; Ramachandram, Dhanesh; Mandava, Rajeswari; Shuaib, Ibrahim Lutfi

    2012-07-01

    White matter (WM) lesions are diffuse WM abnormalities that appear as hyperintense (bright) regions in cranial magnetic resonance imaging (MRI). WM lesions are often observed in older populations and are important indicators of stroke, multiple sclerosis, dementia and other brain-related disorders. In this paper, a new automated method for WM lesions segmentation is presented. In the proposed method, the presence of WM lesions is detected as outliers in the intensity distribution of the fluid-attenuated inversion recovery (FLAIR) MR images using an adaptive outlier detection approach. Outliers are detected using a novel adaptive trimmed mean algorithm and box-whisker plot. In addition, pre- and postprocessing steps are implemented to reduce false positives attributed to MRI artifacts commonly observed in FLAIR sequences. The approach is validated using the cranial MRI sequences of 38 subjects. A significant correlation (R=0.9641, P value=3.12×10(-3)) is observed between the automated approach and manual segmentation by radiologist. The accuracy of the proposed approach was further validated by comparing the lesion volumes computed using the automated approach and lesions manually segmented by an expert radiologist. Finally, the proposed approach is compared against leading lesion segmentation algorithms using a benchmark dataset.

  14. 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.

  15. 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.

  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. PMID:27773959

  17. 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.

  18. 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.

  19. An adaptive window-setting scheme for segmentation of bladder tumor surface via MR cystography.

    PubMed

    Duan, Chaijie; Yuan, Kehong; Liu, Fanghua; Xiao, Ping; Lv, Guoqing; Liang, Zhengrong

    2012-07-01

    This paper proposes an adaptive window-setting scheme for noninvasive detection and segmentation of bladder tumor surface in T(1)-weighted magnetic resonance (MR) images. The inner border of the bladder wall is first covered by a group of ball-shaped detecting windows with different radii. By extracting the candidate tumor windows and excluding the false positive (FP) candidates, the entire bladder tumor surface is detected and segmented by the remaining windows. Different from previous bladder tumor detection methods that are mostly focusing on the existence of a tumor, this paper emphasizes segmenting the entire tumor surface in addition to detecting the presence of the tumor. The presented scheme was validated by ten clinical T(1)-weighted MR image datasets (five volunteers and five patients). The bladder tumor surfaces and the normal bladder wall inner borders in the ten datasets were covered by 223 and 10,491 windows, respectively. Such a large number of the detecting windows makes the validation statistically meaningful. In the FP reduction step, the best feature combination was obtained by using receiver operating characteristics or ROC analysis. The validation results demonstrated the potential of this presented scheme in segmenting the entire tumor surface with high sensitivity and low FP rate. This study inherits our previous results of automatic segmentation of the bladder wall and will be an important element in our MR-based virtual cystoscopy or MR cystography system.

  20. Adaptive Wiener filter super-resolution of color filter array images.

    PubMed

    Karch, Barry K; Hardie, Russell C

    2013-08-12

    Digital color cameras using a single detector array with a Bayer color filter array (CFA) require interpolation or demosaicing to estimate missing color information and provide full-color images. However, demosaicing does not specifically address fundamental undersampling and aliasing inherent in typical camera designs. Fast non-uniform interpolation based super-resolution (SR) is an attractive approach to reduce or eliminate aliasing and its relatively low computational load is amenable to real-time applications. The adaptive Wiener filter (AWF) SR algorithm was initially developed for grayscale imaging and has not previously been applied to color SR demosaicing. Here, we develop a novel fast SR method for CFA cameras that is based on the AWF SR algorithm and uses global channel-to-channel statistical models. We apply this new method as a stand-alone algorithm and also as an initialization image for a variational SR algorithm. This paper presents the theoretical development of the color AWF SR approach and applies it in performance comparisons to other SR techniques for both simulated and real data.

  1. 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.

  2. Segments.

    ERIC Educational Resources Information Center

    Zemsky, Robert; Shaman, Susan; Shapiro, Daniel B.

    2001-01-01

    Presents a market taxonomy for higher education, including what it reveals about the structure of the market, the model's technical attributes, and its capacity to explain pricing behavior. Details the identification of the principle seams separating one market segment from another and how student aspirations help to organize the market, making…

  3. Skin Color-Based Video Segmentation under Time-Varying Illumination

    DTIC Science & Technology

    2003-03-25

    Face and Gesture Recognition , pp. 379–384, 1996. [15] R. Kjeldsen and J. Kender. Finding skin in color images. Proc. International Conf. on Automatic...Face and Gesture Recognition , pp. 312–317, 1996. [16] M. Storring, H.J. Andersen, and E. Granum. Skin colour detection under changing lighting...Object oriented face detection using range and color information. Proc. International Conf. on Automatic Face and Gesture Recognition , pp. 76–81, 1998

  4. 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.

  5. 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.

  6. Nonlinearities and adaptation of color vision from sequential principal curves analysis.

    PubMed

    Laparra, Valero; Jiménez, Sandra; Camps-Valls, Gustavo; Malo, Jesús

    2012-10-01

    Mechanisms of human color vision are characterized by two phenomenological aspects: the system is nonlinear and adaptive to changing environments. Conventional attempts to derive these features from statistics use separate arguments for each aspect. The few statistical explanations that do consider both phenomena simultaneously follow parametric formulations based on empirical models. Therefore, it may be argued that the behavior does not come directly from the color statistics but from the convenient functional form adopted. In addition, many times the whole statistical analysis is based on simplified databases that disregard relevant physical effects in the input signal, as, for instance, by assuming flat Lambertian surfaces. In this work, we address the simultaneous statistical explanation of the nonlinear behavior of achromatic and chromatic mechanisms in a fixed adaptation state and the change of such behavior (i.e., adaptation) under the change of observation conditions. Both phenomena emerge directly from the samples through a single data-driven method: the sequential principal curves analysis (SPCA) with local metric. SPCA is a new manifold learning technique to derive a set of sensors adapted to the manifold using different optimality criteria. Here sequential refers to the fact that sensors (curvilinear dimensions) are designed one after the other, and not to the particular (eventually iterative) method to draw a single principal curve. Moreover, in order to reproduce the empirical adaptation reported under D65 and A illuminations, a new database of colorimetrically calibrated images of natural objects under these illuminants was gathered, thus overcoming the limitations of available databases. The results obtained by applying SPCA show that the psychophysical behavior on color discrimination thresholds, discount of the illuminant, and corresponding pairs in asymmetric color matching emerge directly from realistic data regularities, assuming no a priori

  7. Examining the Pathologic Adaptation Model of Community Violence Exposure in Male Adolescents of Color

    PubMed Central

    Gaylord-Harden, Noni K.; So, Suzanna; Bai, Grace J.; Henry, David B.; Tolan, Patrick H.

    2017-01-01

    The current study examined a model of desensitization to community violence exposure—the pathologic adaptation model—in male adolescents of color. The current study included 285 African American (61%) and Latino (39%) male adolescents (W1 M age = 12.41) from the Chicago Youth Development Study to examine the longitudinal associations between community violence exposure, depressive symptoms, and violent behavior. Consistent with the pathologic adaptation model, results indicated a linear, positive association between community violence exposure in middle adolescence and violent behavior in late adolescence, as well as a curvilinear association between community violence exposure in middle adolescence and depressive symptoms in late adolescence, suggesting emotional desensitization. Further, these effects were specific to cognitive-affective symptoms of depression and not somatic symptoms. Emotional desensitization outcomes, as assessed by depressive symptoms, can occur in male adolescents of color exposed to community violence and these effects extend from middle adolescence to late adolescence. PMID:27653968

  8. Automatic nevi segmentation using adaptive mean shift filters and feature analysis

    NASA Astrophysics Data System (ADS)

    King, Michael A.; Lee, Tim K.; Atkins, M. Stella; McLean, David I.

    2004-05-01

    A novel automatic method of segmenting nevi is explained and analyzed in this paper. The first step in nevi segmentation is to iteratively apply an adaptive mean shift filter to form clusters in the image and to remove noise. The goal of this step is to remove differences in skin intensity and hairs from the image, while still preserving the shape of nevi present on the skin. Each iteration of the mean shift filter changes pixel values to be a weighted average of pixels in its neighborhood. Some new extensions to the mean shift filter are proposed to allow for better segmentation of nevi from the skin. The kernel, that describes how the pixels in its neighborhood will be averaged, is adaptive; the shape of the kernel is a function of the local histogram. After initial clustering, a simple merging of clusters is done. Finally, clusters that are local minima are found and analyzed to determine which clusters are nevi. When this algorithm was compared to an assessment by an expert dermatologist, it showed a sensitivity rate and diagnostic accuracy of over 95% on the test set, for nevi larger than 1.5mm.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. New adaptive clutter rejection for ultrasound color Doppler imaging: in vivo study.

    PubMed

    Yoo, Yang Mo; Kim, Yongmin

    2010-03-01

    Clutter rejection is essential for accurate flow estimation in ultrasound color Doppler imaging. In this article, we present a new adaptive clutter rejection (ACR) technique where an optimum filter is dynamically selected depending upon the underlying clutter characteristics (e.g., tissue acceleration and power). We compared the performance of the ACR method with other adaptive methods, i.e., down-mixing (DM) and adaptive clutter filtering (ACF), using in vivo data acquired from the kidney, liver and common carotid artery. With the kidney data, the ACR method provided an average improvement of 3.05 dB and 1.7 dB in flow signal-to-clutter ratio (SCR) compared with DM and ACF, respectively. With the liver data, SCR was improved by 2.75 dB and 1.8 dB over DM and ACF while no significant improvement with ACR was found in the common carotid artery data. Thus, the proposed adaptive method could provide more accurate flow estimation by improving clutter rejection in abdominal ultrasound color Doppler imaging pending validation.

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

    PubMed

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

    2013-01-06

    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 signaling.

  16. 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

  17. Applying innovative stripes adaptive detection to three-dimensional measurement of color fringe profilometry

    NASA Astrophysics Data System (ADS)

    Jeffrey Kuo, Chung-Feng; Chang, Alvin; Joseph Kuo, Ping-Chen; Lee, Chi-Lung; Wu, Han-Cheng

    2016-12-01

    This study developed a 3D software and hardware measurement system, and proposes an innovative stripes adaptive detection algorithm. The fringe intensity is regulated automatically according to the reflection coefficient of different analytes, in order to avoid overexposure. For the measurement of the object in discontinuously changing height, a novel intensity difference coding unwrapping phase technology is used, thus overcoming the technological bottleneck of traditional phase unwrapping. In order to increase the measurement efficiency, the stripe pattern is combined with intensity coding pattern by three-channel color information, in order to generate an adaptive compound color stripe pattern. The measurement efficiency is increased by approximately two times compared with traditional gray stripe pattern. In order to increase the measurement accuracy, the uneven brightness is corrected by using brightness gain function. The three-channel intensity nonlinear response is corrected by cubic spline interpolation system response inverse function. The three-channel image is corrected by color cross-talk correction technology. The experiment proved that the system repeatability is 20 μm. The traditional phase-shifting profilometry is improved successfully, overcoming the technical measurement bottleneck of discontinuous change in the analyte height, so as to attain low cost, high measurement accuracy, efficiency and measurement reliability.

  18. 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.

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

    NASA Astrophysics Data System (ADS)

    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.

  20. Region-based retrieval of remote sensing image patches with adaptive image segmentation

    NASA Astrophysics Data System (ADS)

    Li, Shijin; Zhu, Jiali; Zhu, Yuelong; Feng, Jun

    2012-06-01

    Over the past four decades, the satellite imaging sensors have acquired huge quantities of Earth- observation data. Content-based image retrieval allows for fast and effective queries of remote sensing images. Here, we take the following two issues into consideration. Firstly, different features and their combination should be chosen for different land covers. Secondly, for the block dividing strategy and the complexities of the remote sensing images, it can not effectively retrieve some small target areas scattered in multiple nontarget blocks. Aiming at the above two issues, a new region-based retrieval method with adaptive image segmentation is proposed. In order to improve the accuracy of remote sensing image segmentation, feature selection and weighing is performed by two-stage clustering, and image segmentation is accomplished based on the chosen features and mean shift procedure. Meanwhile, for the homogeneous characteristics of remote sensing land covers, a new regional representation and matching scheme are adopted to perform image retrieval. Experimental results on retrieving various land covers show that the method can avoid the impact of traditional blocking strategies, and can achieve an average percentage of 19% higher precision with the same level of recall rate, than the relevance feedback method for small target areas.

  1. Adaptive Mesh Expansion Model (AMEM) for Liver Segmentation from CT Image

    PubMed Central

    Wang, Xuehu; Yang, Jian; Ai, Danni; Zheng, Yongchang; Tang, Songyuan; Wang, Yongtian

    2015-01-01

    This study proposes a novel adaptive mesh expansion model (AMEM) for liver segmentation from computed tomography images. The virtual deformable simplex model (DSM) is introduced to represent the mesh, in which the motion of each vertex can be easily manipulated. The balloon, edge, and gradient forces are combined with the binary image to construct the external force of the deformable model, which can rapidly drive the DSM to approach the target liver boundaries. Moreover, tangential and normal forces are combined with the gradient image to control the internal force, such that the DSM degree of smoothness can be precisely controlled. The triangular facet of the DSM is adaptively decomposed into smaller triangular components, which can significantly improve the segmentation accuracy of the irregularly sharp corners of the liver. The proposed method is evaluated on the basis of different criteria applied to 10 clinical data sets. Experiments demonstrate that the proposed AMEM algorithm is effective and robust and thus outperforms six other up-to-date algorithms. Moreover, AMEM can achieve a mean overlap error of 6.8% and a mean volume difference of 2.7%, whereas the average symmetric surface distance and the root mean square symmetric surface distance can reach 1.3 mm and 2.7 mm, respectively. PMID:25769030

  2. Different colors of light lead to different adaptation and activation as determined by high-density EEG.

    PubMed

    Münch, M; Plomp, G; Thunell, E; Kawasaki, A; Scartezzini, J L; Herzog, M H

    2014-11-01

    Light adaptation is crucial for coping with the varying levels of ambient light. Using high-density electroencephalography (EEG), we investigated how adaptation to light of different colors affects brain responsiveness. In a within-subject design, sixteen young participants were adapted first to dim white light and then to blue, green, red, or white bright light (one color per session in a randomized order). Immediately after both dim and bright light adaptation, we presented brief light pulses and recorded event-related potentials (ERPs). We analyzed ERP response strengths and brain topographies and determined the underlying sources using electrical source imaging. Between 150 and 261 ms after stimulus onset, the global field power (GFP) was higher after dim than bright light adaptation. This effect was most pronounced with red light and localized in the frontal lobe, the fusiform gyrus, the occipital lobe and the cerebellum. After bright light adaptation, within the first 100 ms after light onset, stronger responses were found than after dim light adaptation for all colors except for red light. Differences between conditions were localized in the frontal lobe, the cingulate gyrus, and the cerebellum. These results indicate that very short-term EEG brain responses are influenced by prior light adaptation and the spectral quality of the light stimulus. We show that the early EEG responses are differently affected by adaptation to different colors of light which may contribute to known differences in performance and reaction times in cognitive tests.

  3. Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores.

    PubMed

    Zhang, Jiong; Dashtbozorg, Behdad; Bekkers, Erik; Pluim, Josien P W; Duits, Remco; Ter Haar Romeny, Bart M

    2016-12-01

    This paper presents a robust and fully automatic filter-based approach for retinal vessel segmentation. We propose new filters based on 3D rotating frames in so-called orientation scores, which are functions on the Lie-group domain of positions and orientations [Formula: see text]. By means of a wavelet-type transform, a 2D image is lifted to a 3D orientation score, where elongated structures are disentangled into their corresponding orientation planes. In the lifted domain [Formula: see text], vessels are enhanced by means of multi-scale second-order Gaussian derivatives perpendicular to the line structures. More precisely, we use a left-invariant rotating derivative (LID) frame, and a locally adaptive derivative (LAD) frame. The LAD is adaptive to the local line structures and is found by eigensystem analysis of the left-invariant Hessian matrix (computed with the LID). After multi-scale filtering via the LID or LAD in the orientation score domain, the results are projected back to the 2D image plane giving us the enhanced vessels. Then a binary segmentation is obtained through thresholding. The proposed methods are validated on six retinal image datasets with different image types, on which competitive segmentation performances are achieved. In particular, the proposed algorithm of applying the LAD filter on orientation scores (LAD-OS) outperforms most of the state-of-the-art methods. The LAD-OS is capable of dealing with typically difficult cases like crossings, central arterial reflex, closely parallel and tiny vessels. The high computational speed of the proposed methods allows processing of large datasets in a screening setting.

  4. Detection of Single Standing Dead Trees from Aerial Color Infrared Imagery by Segmentation with Shape and Intensity Priors

    NASA Astrophysics Data System (ADS)

    Polewski, P.; Yao, W.; Heurich, M.; Krzystek, P.; Stilla, U.

    2015-03-01

    Standing dead trees, known as snags, are an essential factor in maintaining biodiversity in forest ecosystems. Combined with their role as carbon sinks, this makes for a compelling reason to study their spatial distribution. This paper presents an integrated method to detect and delineate individual dead tree crowns from color infrared aerial imagery. Our approach consists of two steps which incorporate statistical information about prior distributions of both the image intensities and the shapes of the target objects. In the first step, we perform a Gaussian Mixture Model clustering in the pixel color space with priors on the cluster means, obtaining up to 3 components corresponding to dead trees, living trees, and shadows. We then refine the dead tree regions using a level set segmentation method enriched with a generative model of the dead trees' shape distribution as well as a discriminative model of their pixel intensity distribution. The iterative application of the statistical shape template yields the set of delineated dead crowns. The prior information enforces the consistency of the template's shape variation with the shape manifold defined by manually labeled training examples, which makes it possible to separate crowns located in close proximity and prevents the formation of large crown clusters. Also, the statistical information built into the segmentation gives rise to an implicit detection scheme, because the shape template evolves towards an empty contour if not enough evidence for the object is present in the image. We test our method on 3 sample plots from the Bavarian Forest National Park with reference data obtained by manually marking individual dead tree polygons in the images. Our results are scenario-dependent and range from a correctness/completeness of 0.71/0.81 up to 0.77/1, with an average center-of-gravity displacement of 3-5 pixels between the detected and reference polygons.

  5. Development of an adaptive bilateral filter for evaluating color image difference

    NASA Astrophysics Data System (ADS)

    Wang, Zhaohui; Hardeberg, Jon Yngve

    2012-04-01

    Spatial filtering, which aims to mimic the contrast sensitivity function (CSF) of the human visual system (HVS), has previously been combined with color difference formulae for measuring color image reproduction errors. These spatial filters attenuate imperceptible information in images, unfortunately including high frequency edges, which are believed to be crucial in the process of scene analysis by the HVS. The adaptive bilateral filter represents a novel approach, which avoids the undesirable loss of edge information introduced by CSF-based filtering. The bilateral filter employs two Gaussian smoothing filters in different domains, i.e., spatial domain and intensity domain. We propose a method to decide the parameters, which are designed to be adaptive to the corresponding viewing conditions, and the quantity and homogeneity of information contained in an image. Experiments and discussions are given to support the proposal. A series of perceptual experiments were conducted to evaluate the performance of our approach. The experimental sample images were reproduced with variations in six image attributes: lightness, chroma, hue, compression, noise, and sharpness/blurriness. The Pearson's correlation values between the model-predicted image difference and the observed difference were employed to evaluate the performance, and compare it with that of spatial CIELAB and image appearance model.

  6. 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.

  7. A fuzzy locally adaptive Bayesian segmentation approach for volume determination in PET.

    PubMed

    Hatt, Mathieu; Cheze le Rest, Catherine; Turzo, Alexandre; Roux, Christian; Visvikis, Dimitris

    2009-06-01

    Accurate volume estimation in positron emission tomography (PET) is crucial for different oncology applications. The objective of our study was to develop a new fuzzy locally adaptive Bayesian (FLAB) segmentation for automatic lesion volume delineation. FLAB was compared with a threshold approach as well as the previously proposed fuzzy hidden Markov chains (FHMC) and the fuzzy C-Means (FCM) algorithms. The performance of the algorithms was assessed on acquired datasets of the IEC phantom, covering a range of spherical lesion sizes (10-37 mm), contrast ratios (4:1 and 8:1), noise levels (1, 2, and 5 min acquisitions), and voxel sizes (8 and 64 mm(3)). In addition, the performance of the FLAB model was assessed on realistic nonuniform and nonspherical volumes simulated from patient lesions. Results show that FLAB performs better than the other methodologies, particularly for smaller objects. The volume error was 5%-15% for the different sphere sizes (down to 13 mm), contrast and image qualities considered, with a high reproducibility (variation < 4%). By comparison, the thresholding results were greatly dependent on image contrast and noise, whereas FCM results were less dependent on noise but consistently failed to segment lesions < 2 cm. In addition, FLAB performed consistently better for lesions < 2 cm in comparison to the FHMC algorithm. Finally the FLAB model provided errors less than 10% for nonspherical lesions with inhomogeneous activity distributions. Future developments will concentrate on an extension of FLAB in order to allow the segmentation of separate activity distribution regions within the same functional volume as well as a robustness study with respect to different scanners and reconstruction algorithms.

  8. Multichannel adaptive signal detection in space-time colored compound-gaussian autoregressive processes

    NASA Astrophysics Data System (ADS)

    Xu, Qi; Ma, Xiaochuan; Yan, Shefeng; Hao, Chengpeng; Shi, Bo

    2012-12-01

    In this article, we consider the problem of adaptive detection for a multichannel signal in the presence of spatially and temporally colored compound-Gaussian disturbance. By modeling the disturbance as a multichannel autoregressive (AR) process, we first derive a parametric generalized likelihood ratio test against compound-Gaussian disturbance (CG-PGLRT) assuming that the true multichannel AR parameters are perfectly known. For the two-step GLRT design criterion, we combine the multichannel AR parameter estimation algorithm with three covariance matrix estimation strategies for compound-Gaussian environment, then obtain three adaptive CG-PGLRT detectors by replacing the ideal multichannel AR parameters with their estimates. Owing to treating the random texture components of disturbance as deterministic unknown parameters, all of the proposed detectors require no a priori knowledge about the disturbance statistics. The performance assessments are conducted by means of Monte Carlo trials. We focus on the issues of constant false alarm rate (CFAR) behavior, detection and false alarm probabilities. Numerical results show that the proposed adaptive CG-PGLRT detectors have dramatically ease the training and computational burden compared to the generalized likelihood ratio test-linear quadratic (GLRT-LQ) which is referred to as covariance matrix based detector and relies more heavily on training.

  9. Segmentation of the heart and great vessels in CT images using a model-based adaptation framework.

    PubMed

    Ecabert, Olivier; Peters, Jochen; Walker, Matthew J; Ivanc, Thomas; Lorenz, Cristian; von Berg, Jens; Lessick, Jonathan; Vembar, Mani; Weese, Jürgen

    2011-12-01

    Recently, model-based methods for the automatic segmentation of the heart chambers have been proposed. An important application of these methods is the characterization of the heart function. Heart models are, however, increasingly used for interventional guidance making it necessary to also extract the attached great vessels. It is, for instance, important to extract the left atrium and the proximal part of the pulmonary veins to support guidance of ablation procedures for atrial fibrillation treatment. For cardiac resynchronization therapy, a heart model including the coronary sinus is needed. We present a heart model comprising the four heart chambers and the attached great vessels. By assigning individual linear transformations to the heart chambers and to short tubular segments building the great vessels, variable sizes of the heart chambers and bending of the vessels can be described in a consistent way. A configurable algorithmic framework that we call adaptation engine matches the heart model automatically to cardiac CT angiography images in a multi-stage process. First, the heart is detected using a Generalized Hough Transformation. Subsequently, the heart chambers are adapted. This stage uses parametric as well as deformable mesh adaptation techniques. In the final stage, segments of the large vascular structures are successively activated and adapted. To optimize the computational performance, the adaptation engine can vary the mesh resolution and freeze already adapted mesh parts. The data used for validation were independent from the data used for model-building. Ground truth segmentations were generated for 37 CT data sets reconstructed at several cardiac phases from 17 patients. Segmentation errors were assessed for anatomical sub-structures resulting in a mean surface-to-surface error ranging 0.50-0.82mm for the heart chambers and 0.60-1.32mm for the parts of the great vessels visible in the images.

  10. 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.

  11. 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.

  12. Image segmentation for uranium isotopic analysis by SIMS: Combined adaptive thresholding and marker controlled watershed approach

    SciTech Connect

    Willingham, David G.; Naes, Benjamin E.; Heasler, Patrick G.; Zimmer, Mindy M.; Barrett, Christopher A.; Addleman, Raymond S.

    2016-05-31

    A novel approach to particle identification and particle isotope ratio determination has been developed for nuclear safeguard applications. This particle search approach combines an adaptive thresholding algorithm and marker-controlled watershed segmentation (MCWS) transform, which improves the secondary ion mass spectrometry (SIMS) isotopic analysis of uranium containing particle populations for nuclear safeguards applications. The Niblack assisted MCWS approach (a.k.a. SEEKER) developed for this work has improved the identification of isotopically unique uranium particles under conditions that have historically presented significant challenges for SIMS image data processing techniques. Particles obtained from five NIST uranium certified reference materials (CRM U129A, U015, U150, U500 and U850) were successfully identified in regions of SIMS image data 1) where a high variability in image intensity existed, 2) where particles were touching or were in close proximity to one another and/or 3) where the magnitude of ion signal for a given region was count limited. Analysis of the isotopic distributions of uranium containing particles identified by SEEKER showed four distinct, accurately identified 235U enrichment distributions, corresponding to the NIST certified 235U/238U isotope ratios for CRM U129A/U015 (not statistically differentiated), U150, U500 and U850. Additionally, comparison of the minor uranium isotope (234U, 235U and 236U) atom percent values verified that, even in the absence of high precision isotope ratio measurements, SEEKER could be used to segment isotopically unique uranium particles from SIMS image data. Although demonstrated specifically for SIMS analysis of uranium containing particles for nuclear safeguards, SEEKER has application in addressing a broad set of image processing challenges.

  13. 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.

  14. 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

  15. Unsupervised boundary delineation of spinal neural foramina using a multi-feature and adaptive spectral segmentation.

    PubMed

    He, Xiaoxu; Zhang, Heye; Landis, Mark; Sharma, Manas; Warrington, James; Li, Shuo

    2017-02-01

    As a common disease in the elderly, neural foramina stenosis (NFS) brings a significantly negative impact on the quality of life due to its symptoms including pain, disability, fall risk and depression. Accurate boundary delineation is essential to the clinical diagnosis and treatment of NFS. However, existing clinical routine is extremely tedious and inefficient due to the requirement of physicians' intensively manual delineation. Automated delineation is highly needed but faces big challenges from the complexity and variability in neural foramina images. In this paper, we propose a pure image-driven unsupervised boundary delineation framework for the automated neural foramina boundary delineation. This framework is based on a novel multi-feature and adaptive spectral segmentation (MFASS) algorithm. MFASS firstly utilizes the combination of region and edge features to generate reliable spectral features with a good separation between neural foramina and its surroundings, then estimates an optimal separation threshold for each individual image to separate neural foramina from its surroundings. This self-adjusted optimal separation threshold, estimated from spectral features, successfully overcome the diverse appearance and shape variations. With the robustness from the multi-feature fusion and the flexibility from the adaptively optimal separation threshold estimation, the proposed framework, based on MFASS, provides an automated and accurate boundary delineation. Validation was performed in 280 neural foramina MR images from 56 clinical subjects. Our method was benchmarked with manual boundary obtained by experienced physicians. Results demonstrate that the proposed method enjoys a high and stable consistency with experienced physicians (Dice: 90.58% ± 2.79%; SMAD: 0.5657 ± 0.1544 mm). Therefore, the proposed framework enables an efficient and accurate clinical tool in the diagnosis of neural foramina stenosis.

  16. Adaptive clutter filter in 2-D color flow imaging based on in vivo I/Q signal.

    PubMed

    Zhou, Xiaoming; Zhang, Congyao; Liu, Dong C

    2014-01-01

    Color flow imaging has been well applied in clinical diagnosis. For the high quality color flow images, clutter filter is important to separate the Doppler signals from blood and tissue. Traditional clutter filters, such as finite impulse response, infinite impulse response and regression filters, were applied, which are based on the hypothesis that the clutter signal is stationary or tissue moves slowly. However, in realistic clinic color flow imaging, the signals are non-stationary signals because of accelerated moving tissue. For most related papers, simulated RF signals are widely used without in vivo I/Q signal. Hence, in this paper, adaptive polynomial regression filter, which is down mixing with instantaneous clutter frequency, was proposed based on in vivo carotid I/Q signal in realistic color flow imaging. To get the best performance, the optimal polynomial order of polynomial regression filter and the optimal polynomial order for estimation of instantaneous clutter frequency respectively were confirmed. Finally, compared with the mean blood velocity and quality of 2-D color flow image, the experiment results show that adaptive polynomial regression filter, which is down mixing with instantaneous clutter frequency, can significantly enhance the mean blood velocity and get high quality 2-D color flow image.

  17. 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.

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

    PubMed

    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.

  19. 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

  20. Heritability of Chip Color and Specific Gravity in a Long-Day Adapted Solanum phureja-S. stenotomum Population

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Acceptable chip color and high specific gravity are important characteristics for chipping potatoes. High specific gravity in U.S. chipping varieties traces back to B5141-6 (‘Lenape’). In an effort to expand the germplasm base for high specific gravity, a long-day adapted diploid hybrid Solanum p...

  1. Novel and powerful 3D adaptive crisp active contour method applied in the segmentation of CT lung images.

    PubMed

    Rebouças Filho, Pedro Pedrosa; Cortez, Paulo César; da Silva Barros, Antônio C; C Albuquerque, Victor Hugo; R S Tavares, João Manuel

    2017-01-01

    The World Health Organization estimates that 300 million people have asthma, 210 million people have Chronic Obstructive Pulmonary Disease (COPD), and, according to WHO, COPD will become the third major cause of death worldwide in 2030. Computational Vision systems are commonly used in pulmonology to address the task of image segmentation, which is essential for accurate medical diagnoses. Segmentation defines the regions of the lungs in CT images of the thorax that must be further analyzed by the system or by a specialist physician. This work proposes a novel and powerful technique named 3D Adaptive Crisp Active Contour Method (3D ACACM) for the segmentation of CT lung images. The method starts with a sphere within the lung to be segmented that is deformed by forces acting on it towards the lung borders. This process is performed iteratively in order to minimize an energy function associated with the 3D deformable model used. In the experimental assessment, the 3D ACACM is compared against three approaches commonly used in this field: the automatic 3D Region Growing, the level-set algorithm based on coherent propagation and the semi-automatic segmentation by an expert using the 3D OsiriX toolbox. When applied to 40 CT scans of the chest the 3D ACACM had an average F-measure of 99.22%, revealing its superiority and competency to segment lungs in CT images.

  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.

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

    PubMed Central

    Wang, Changmiao; Jia, Fucang; Wu, Jianhuang; Li, Guanglin

    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

  4. 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.

  5. Adaptive clutter rejection for 3D color Doppler imaging: preliminary clinical study.

    PubMed

    Yoo, Yang Mo; Sikdar, Siddhartha; Karadayi, Kerem; Kolokythas, Orpheus; Kim, Yongmin

    2008-08-01

    In three-dimensional (3D) ultrasound color Doppler imaging (CDI), effective rejection of flash artifacts caused by tissue motion (clutter) is important for improving sensitivity in visualizing blood flow in vessels. Since clutter characteristics can vary significantly during volume acquisition, a clutter rejection technique that can adapt to the underlying clutter conditions is desirable for 3D CDI. We have previously developed an adaptive clutter rejection (ACR) method, in which an optimum filter is dynamically selected from a set of predesigned clutter filters based on the measured clutter characteristics. In this article, we evaluated the ACR method with 3D in vivo data acquired from 37 kidney transplant patients clinically indicated for a duplex ultrasound examination. We compared ACR against a conventional clutter rejection method, down-mixing (DM), using a commonly-used flow signal-to-clutter ratio (SCR) and a new metric called fractional residual clutter area (FRCA). The ACR method was more effective in removing the flash artifacts while providing higher sensitivity in detecting blood flow in the arcuate arteries and veins in the parenchyma of transplanted kidneys. ACR provided 3.4 dB improvement in SCR over the DM method (11.4 +/- 1.6 dB versus 8.0 +/- 2.0 dB, p < 0.001) and had lower average FRCA values compared with the DM method (0.006 +/- 0.003 versus 0.036 +/- 0.022, p < 0.001) for all study subjects. These results indicate that the new ACR method is useful for removing nonstationary tissue motion while improving the image quality for visualizing 3D vascular structure in 3D CDI.

  6. 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).

  7. 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.

  8. 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'.

  9. Image segmentation using globally optimal growth in three dimensions with an adaptive feature set

    NASA Astrophysics Data System (ADS)

    Taylor, David C.; Barrett, William A.

    1994-09-01

    A globally optimal region growing algorithm for 3D segmentation of anatomical objects is developed. The notion of simple 3D connected component labelling is extended to enable the combination of arbitrary features in the segmentation process. This algorithm uses a hybrid octree-btree structure to segment an object of interest in an ordered fashion. This tree structure overcomes the computational complexity of global optimality in three dimensions. The segmentation process is controlled by a set of active features, which work in concert to extract the object of interest. The cost function used to enforce the order is based on the combination of active features. The characteristics of the data throughout the volume dynamically influences which features are active. A foundation for applying user interaction with the object directly to the feature set is established. The result is a system which analyzes user input and neighborhood data and optimizes the tools used in the segmentation process accordingly.

  10. Assessing Hippocampal Development and Language in Early Childhood: Evidence From a New Application of the Automatic Segmentation Adapter Tool

    PubMed Central

    Lee, Joshua K.; Nordahl, Christine W.; Amaral, David G.; Lee, Aaron; Solomon, Marjorie; Ghetti, Simona

    2016-01-01

    Volumetric assessments of the hippocampus and other brain structures during childhood provide useful indices of brain development and correlates of cognitive functioning in typically and atypically developing children. Automated methods such as FreeSurfer promise efficient and replicable segmentation, but may include errors which are avoided by trained manual tracers. A recently devised automated correction tool that uses a machine learning algorithm to remove systematic errors, the Automatic Segmentation Adapter Tool (ASAT), was capable of substantially improving the accuracy of FreeSurfer segmentations in an adult sample [Wang et al., 2011], but the utility of ASAT has not been examined in pediatric samples. In Study 1, the validity of FreeSurfer and ASAT corrected hippocampal segmentations were examined in 20 typically developing children and 20 children with autism spectrum disorder aged 2 and 3 years. We showed that while neither FreeSurfer nor ASAT accuracy differed by disorder or age, the accuracy of ASAT corrected segmentations were substantially better than FreeSurfer segmentations in every case, using as few as 10 training examples. In Study 2, we applied ASAT to 89 typically developing children aged 2 to 4 years to examine relations between hippocampal volume, age, sex, and expressive language. Girls had smaller hippocampi overall, and in left hippocampus this difference was larger in older than younger girls. Expressive language ability was greater in older children, and this difference was larger in those with larger hippocampi, bilaterally. Overall, this research shows that ASAT is highly reliable and useful to examinations relating behavior to hippocampal structure. PMID:26279309

  11. Assessing hippocampal development and language in early childhood: Evidence from a new application of the Automatic Segmentation Adapter Tool.

    PubMed

    Lee, Joshua K; Nordahl, Christine W; Amaral, David G; Lee, Aaron; Solomon, Marjorie; Ghetti, Simona

    2015-11-01

    Volumetric assessments of the hippocampus and other brain structures during childhood provide useful indices of brain development and correlates of cognitive functioning in typically and atypically developing children. Automated methods such as FreeSurfer promise efficient and replicable segmentation, but may include errors which are avoided by trained manual tracers. A recently devised automated correction tool that uses a machine learning algorithm to remove systematic errors, the Automatic Segmentation Adapter Tool (ASAT), was capable of substantially improving the accuracy of FreeSurfer segmentations in an adult sample [Wang et al., 2011], but the utility of ASAT has not been examined in pediatric samples. In Study 1, the validity of FreeSurfer and ASAT corrected hippocampal segmentations were examined in 20 typically developing children and 20 children with autism spectrum disorder aged 2 and 3 years. We showed that while neither FreeSurfer nor ASAT accuracy differed by disorder or age, the accuracy of ASAT corrected segmentations were substantially better than FreeSurfer segmentations in every case, using as few as 10 training examples. In Study 2, we applied ASAT to 89 typically developing children aged 2 to 4 years to examine relations between hippocampal volume, age, sex, and expressive language. Girls had smaller hippocampi overall, and in left hippocampus this difference was larger in older than younger girls. Expressive language ability was greater in older children, and this difference was larger in those with larger hippocampi, bilaterally. Overall, this research shows that ASAT is highly reliable and useful to examinations relating behavior to hippocampal structure.

  12. 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.

  13. 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

  14. 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.

  15. A fully-automatic locally adaptive thresholding algorithm for blood vessel segmentation in 3D digital subtraction angiography.

    PubMed

    Boegel, Marco; Hoelter, Philip; Redel, Thomas; Maier, Andreas; Hornegger, Joachim; Doerfler, Arnd

    2015-01-01

    Subarachnoid hemorrhage due to a ruptured cerebral aneurysm is still a devastating disease. Planning of endovascular aneurysm therapy is increasingly based on hemodynamic simulations necessitating reliable vessel segmentation and accurate assessment of vessel diameters. In this work, we propose a fully-automatic, locally adaptive, gradient-based thresholding algorithm. Our approach consists of two steps. First, we estimate the parameters of a global thresholding algorithm using an iterative process. Then, a locally adaptive version of the approach is applied using the estimated parameters. We evaluated both methods on 8 clinical 3D DSA cases. Additionally, we propose a way to select a reference segmentation based on 2D DSA measurements. For large vessels such as the internal carotid artery, our results show very high sensitivity (97.4%), precision (98.7%) and Dice-coefficient (98.0%) with our reference segmentation. Similar results (sensitivity: 95.7%, precision: 88.9% and Dice-coefficient: 90.7%) are achieved for smaller vessels of approximately 1mm diameter.

  16. Adaptive energy selective active contour with shape priors for nuclear segmentation and gleason grading of prostate cancer.

    PubMed

    Ali, Sahirzeeshan; Veltri, Robert; Epstein, Jonathan I; Christudass, Christhunesa; Madabhushi, Anant

    2011-01-01

    Shape based active contours have emerged as a natural solution to overlap resolution. However, most of these shape-based methods are computationally expensive. There are instances in an image where no overlapping objects are present and applying these schemes results in significant computational overhead without any accompanying, additional benefit. In this paper we present a novel adaptive active contour scheme (AdACM) that combines boundary and region based energy terms with a shape prior in a multi level set formulation. To reduce the computational overhead, the shape prior term in the variational formulation is only invoked for those instances in the image where overlaps between objects are identified; these overlaps being identified via a contour concavity detection scheme. By not having to invoke all 3 terms (shape, boundary, region) for segmenting every object in the scene, the computational expense of the integrated active contour model is dramatically reduced, a particularly relevant consideration when multiple objects have to be segmented on very large histopathological images. The AdACM was employed for the task of segmenting nuclei on 80 prostate cancer tissue microarray images. Morphological features extracted from these segmentations were found to able to discriminate different Gleason grade patterns with a classification accuracy of 84% via a Support Vector Machine classifier. On average the AdACM model provided 100% savings in computational times compared to a non-optimized hybrid AC model involving a shape prior.

  17. Surgical wound segmentation based on adaptive threshold edge detection and genetic algorithm

    NASA Astrophysics Data System (ADS)

    Shih, Hsueh-Fu; Ho, Te-Wei; Hsu, Jui-Tse; Chang, Chun-Che; Lai, Feipei; Wu, Jin-Ming

    2017-02-01

    Postsurgical wound care has a great impact on patients' prognosis. It often takes few days, even few weeks, for the wound to stabilize, which incurs a great cost of health care and nursing resources. To assess the wound condition and diagnosis, it is important to segment out the wound region for further analysis. However, the scenario of this strategy often consists of complicated background and noise. In this study, we propose a wound segmentation algorithm based on Canny edge detector and genetic algorithm with an unsupervised evaluation function. The results were evaluated by the 112 clinical images, and 94.3% of images were correctly segmented. The judgment was based on the evaluation of experimented medical doctors. This capability to extract complete wound regions, makes it possible to conduct further image analysis such as intelligent recovery evaluation and automatic infection requirements.

  18. 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

  19. Underwater color constancy: enhancement of automatic live fish recognition

    NASA Astrophysics Data System (ADS)

    Chambah, Majed; Semani, Dahbia; Renouf, Arnaud; Courtellemont, Pierre; Rizzi, Alessandro

    2003-12-01

    We present in this paper some advances in color restoration of underwater images, especially with regard to the strong and non uniform color cast which is typical of underwater images. The proposed color correction method is based on ACE model, an unsupervised color equalization algorithm. ACE is a perceptual approach inspired by some adaptation mechanisms of the human visual system, in particular lightness constancy and color constancy. A perceptual approach presents a lot of advantages: it is unsupervised, robust and has local filtering properties, that lead to more effective results. The restored images give better results when displayed or processed (fish segmentation and feature extraction). The presented preliminary results are satisfying and promising.

  20. A new type of color-coded light structures for an adapted and rapid determination of point correspondences for 3D reconstruction

    NASA Astrophysics Data System (ADS)

    Caulier, Yannick; Bernhard, Luc; Spinnler, Klaus

    2011-05-01

    This paper proposes a new type of color coded light structures for the inspection of complex moving objects. The novelty of the methods relies on the generation of free-form color patterns permitting the projection of color structures adapted to the geometry of the surfaces to be characterized. The point correspondence determination algorithm consists of a stepwise procedure involving simple and computationally fast methods. The algorithm is therefore robust against varying recording conditions typically arising in real-time quality control environments and can be further integrated for industrial inspection purposes. The proposed approach is validated and compared on the basis of different experimentations concerning the 3D surface reconstruction by projecting adapted spatial color coded patterns. It is demonstrated that in case of certain inspection requirements, the method permits to code more reference points that similar color coded matrix methods.

  1. Pointwise shape-adaptive DCT for high-quality denoising and deblocking of grayscale and color images.

    PubMed

    Foi, Alessandro; Katkovnik, Vladimir; Egiazarian, Karen

    2007-05-01

    The shape-adaptive discrete cosine transform ISA-DCT) transform can be computed on a support of arbitrary shape, but retains a computational complexity comparable to that of the usual separable block-DCT (B-DCT). Despite the near-optimal decorrelation and energy compaction properties, application of the SA-DCT has been rather limited, targeted nearly exclusively to video compression. In this paper, we present a novel approach to image filtering based on the SA-DCT. We use the SA-DCT in conjunction with the Anisotropic Local Polynomial Approximation-Intersection of Confidence Intervals technique, which defines the shape of the transform's support in a pointwise adaptive manner. The thresholded or attenuated SA-DCT coefficients are used to reconstruct a local estimate of the signal within the adaptive-shape support. Since supports corresponding to different points are in general overlapping, the local estimates are averaged together using adaptive weights that depend on the region's statistics. This approach can be used for various image-processing tasks. In this paper, we consider, in particular, image denoising and image deblocking and deringing from block-DCT compression. A special structural constraint in luminance-chrominance space is also proposed to enable an accurate filtering of color images. Simulation experiments show a state-of-the-art quality of the final estimate, both in terms of objective criteria and visual appearance. Thanks to the adaptive support, reconstructed edges are clean, and no unpleasant ringing artifacts are introduced by the fitted transform.

  2. 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.

  3. 30 Mbit/s codec for the NTSC color TV signal using an interfield-intrafield adaptive prediction

    NASA Astrophysics Data System (ADS)

    Yamamoto, H.; Hatori, Y.; Murakami, H.

    1981-12-01

    This paper proposes a new approach to the composite coding of the NTSC color TV signal, i.e., an interfield-intrafield adaptive prediction. First, concerning prediction efficiency for various moving pictures, an advantage of this coding scheme over interframe coding is clarified theoretically and experimentally. This adaptive prediction gives very good and stable performance for still to violently moving pictures. A 30 Mbit/s codec, based on this idea, and its performance are presented. Field transmission testing through an Intelsat satellite using this codec is also described. The picture quality is satisfactory for practically all the pictures expected in broadcast TV programs, and it is subjectively estimated to be a little better than that of the half-transponder FM transmission now employed in the Intelsat system.

  4. 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

  5. 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.

  6. Video object segmentation via adaptive threshold based on background model diversity

    NASA Astrophysics Data System (ADS)

    Boubekeur, Mohamed Bachir; Luo, SenLin; Labidi, Hocine; Benlefki, Tarek

    2015-03-01

    The background subtraction could be presented as classification process when investigating the upcoming frames in a video stream, taking in consideration in some cases: a temporal information, in other cases the spatial consistency, and these past years both of the considerations above. The classification often relied in most of the cases on a fixed threshold value. In this paper, a framework for background subtraction and moving object detection based on adaptive threshold measure and short/long frame differencing procedure is proposed. The presented framework explored the case of adaptive threshold using mean squared differences for a sampled background model. In addition, an intuitive update policy which is neither conservative nor blind is presented. The algorithm succeeded on extracting the moving foreground and isolating an accurate background.

  7. Adaptive extraction of emotion-related EEG segments using multidimensional directed information in time-frequency domain.

    PubMed

    Petrantonakis, Panagiotis C; Hadjileontiadis, Leontios J

    2010-01-01

    Emotion discrimination from electroencephalogram (EEG) has gained attention the last decade as a user-friendly and effective approach to EEG-based emotion recognition (EEG-ER) systems. Nevertheless, challenging issues regarding the emotion elicitation procedure, especially its effectiveness, raise. In this work, a novel method, which not only evaluates the degree of emotion elicitation but localizes the emotion information in the time-frequency domain, as well, is proposed. The latter, incorporates multidimensional directed information at the time-frequency EEG representation, extracted using empirical mode decomposition, and introduces an asymmetry index for adaptive emotion-related EEG segment selection. Experimental results derived from 16 subjects visually stimulated with pictures from the valence/arousal space drawn from the International Affective Picture System database, justify the effectiveness of the proposed approach and its potential contribution to the enhancement of EEG-ER systems.

  8. Adaptive reshaper for high dynamic range and wide color gamut video compression

    NASA Astrophysics Data System (ADS)

    Lu, Taoran; Pu, Fangjun; Yin, Peng; Pytlarz, Jaclyn; Chen, Tao; Husak, Walt

    2016-09-01

    High Dynamic Range (HDR) and Wider Color Gamut (WCG) content represents a greater range of luminance levels and a more complete reproduction of colors found in real-world scenes. The characteristics of HDR/WCG content are very different from the SDR content. It poses a challenge to the compression system which is originally designed for SDR content. Recently in MPEG/VCEG, two directions have been taken to improve compression performances for HDR/WCG video using HEVC Main10 codec. The first direction is to improve HDR-10 using encoder optimization. The second direction is to modify the video signal in pre/post processing to better fit compression system. The process therefore is out of coding loop and does not involve changes to the HEVC specification. Among many proposals in the second direction, reshaper is identified to be the key component. In this paper, a novel luma reshaper is presented which re-allocates the codewords to help codec improve subjective quality. In addition, encoder optimization can be performed jointly with reshaping. Experiments are conducted with ICtCp color difference signal. Simulation results show that if both joint optimization of reshaper and encoder are carried out, there is evidence that improvement over the HDR-10 anchor can be achieved.

  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 multi-objective archive-based hybrid scatter search for segmentation in lung computed tomography imaging

    NASA Astrophysics Data System (ADS)

    Bong, Chin Wei; Yoong Lam, Hong; Tajudin Khader, Ahamad; Kamarulzaman, Hamzah

    2012-03-01

    This article proposes a multi-objective clustering ensemble method for medical image segmentation. The proposed method is called adaptive multi-objective archive-based hybrid scatter search (AMAHSS). It utilizes fuzzy clustering with optimization of three fitness functions: global fuzzy compactness of the clusters, fuzzy separation and symmetry distance-based cluster validity index. The AMAHSS enables the search strategy to explore intensively the search space with high-quality solutions and to move to unexplored search space when necessary. The best single solution is processed using the metaclustering algorithm. The proposed framework is designed to segment lung computed tomography images for candidate nodule detection. This candidate nodule will then be classified as cancerous or non-cancerous. The authors validate the method with standard k-means, fuzzy c-means and the multi-objective genetic algorithm with different postprocessing methods for the final solution. The results obtained from the benchmark experiment indicate that the method achieves up to 90% of the positive predictive rate.

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. A spectral element method with adaptive segmentation for accurately simulating extracellular electrical stimulation of neurons.

    PubMed

    Eiber, Calvin D; Dokos, Socrates; Lovell, Nigel H; Suaning, Gregg J

    2016-08-19

    The capacity to quickly and accurately simulate extracellular stimulation of neurons is essential to the design of next-generation neural prostheses. Existing platforms for simulating neurons are largely based on finite-difference techniques; due to the complex geometries involved, the more powerful spectral or differential quadrature techniques cannot be applied directly. This paper presents a mathematical basis for the application of a spectral element method to the problem of simulating the extracellular stimulation of retinal neurons, which is readily extensible to neural fibers of any kind. The activating function formalism is extended to arbitrary neuron geometries, and a segmentation method to guarantee an appropriate choice of collocation points is presented. Differential quadrature may then be applied to efficiently solve the resulting cable equations. The capacity for this model to simulate action potentials propagating through branching structures and to predict minimum extracellular stimulation thresholds for individual neurons is demonstrated. The presented model is validated against published values for extracellular stimulation threshold and conduction velocity for realistic physiological parameter values. This model suggests that convoluted axon geometries are more readily activated by extracellular stimulation than linear axon geometries, which may have ramifications for the design of neural prostheses.

  16. The adaptive function of melanin-based plumage coloration to trace metals

    PubMed Central

    Chatelain, M.; Gasparini, J.; Jacquin, L.; Frantz, A.

    2014-01-01

    Trace metals produced by anthropogenic activities are of major importance in urban areas and might constitute a new evolutionary force selecting for the ability to cope with their deleterious effects. Interestingly, melanin pigments are known to bind metal ions, thereby potentially sequestering them in inert body parts such as coat and feathers, and facilitating body detoxification. Thus, a more melanic plumage or coat coloration could bring a selective advantage for animals living in polluted areas. We tested this hypothesis by investigating the link between melanin-based coloration and zinc and lead concentrations in feathers of urban feral pigeons, both at capture time and after one year of captivity in standardized conditions. Results show that differently coloured pigeons had similar metal concentrations at capture time. Metal concentrations strongly decreased after one year in standardized conditions, and more melanic pigeons had higher concentrations of zinc (but not lead) in their feathers. This suggests that more melanic pigeons have a higher ability to store some metals in their feathers compared with their paler counterparts, which could explain their higher success in urbanized areas. Overall, this work suggests that trace metal pollution may exert new selective forces favouring more melanic phenotypes in polluted environments. PMID:24671830

  17. 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, ...

  18. 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.

  19. An adaptive switching filter based on approximated variance for detection of impulse noise from color images.

    PubMed

    Pritamdas, K; Singh, Kh Manglem; Singh, L Lolitkumar

    2016-01-01

    A new adaptive switching algorithm is presented where two adaptive filters are switched correspondingly for lower and higher noise ratio of the image. An adaptive center weighted vector median filter is used for the lower noise ratio whereas for higher noise ratio the noisy pixels are detected based on the comparison of the difference between the mean of the vector pixels in the window and the approximated variance of the vector pixels in the window. Then the window comprising the detected noisy pixel is further considered where the pixels are given exponential weights according to their similarity to the other neighboring pixels, spatially and radio metrically. The noisy pixels are then replaced by the weighted average of the pixels within the window. The filter is able to preserve higher signal content in the higher noise ratio as compared to other robust filters in comparison. With a little high in computational complexity, this technique performs well both in lower and higher noise ratios. Simulation results on various RGB images show that the proposed algorithm outperforms many other existing nonlinear filters in terms of preservation of edges and fine details.

  20. 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

  1. Adaptive clutter rejection for ultrasound color flow imaging based on recursive eigendecomposition.

    PubMed

    You, Wei; Wang, Yuanyuan

    2009-10-01

    In the conventional eigenfilter used to reject clutter components of ultrasound color flow imaging, input samples are required to be statistically stationary. However, clutter movements may vary over the depth of the imaged area, which makes the eigenfilter less efficient. In the current study, a novel clutter rejection method is proposed based on the recursive eigendecomposition algorithm. In this method, the current eigenvector matrix of the ultrasound echo correlation matrix, which will be used to construct the clutter subspace, is determined by previous eigenvector matrices and the current input. After the estimated clutter signal is obtained by projecting the original input into the clutter space, each filtered output is eventually obtained by subtracting the estimated clutter signal from the original input. This procedure is iterated for each sample volume along the depth. During the updating process, a forgetting factor is introduced to determine proper weights for different inputs. Simulated data in 3 situations and in vivo data collected from human carotid arteries are used to compare the proposed method with other popular clutter filters. Results show that the proposed method can achieve the most accurate velocity profiles in all simulation situations and introduces the fewest velocity artifacts in the tissue region in the in vivo experiment.

  2. 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.

  3. Mono-component feature extraction for mechanical fault diagnosis using modified empirical wavelet transform via data-driven adaptive Fourier spectrum segment

    NASA Astrophysics Data System (ADS)

    Pan, Jun; Chen, Jinglong; Zi, Yanyang; Li, Yueming; He, Zhengjia

    2016-05-01

    Due to the multi-modulation feature in most of the vibration signals, the extraction of embedded fault information from condition monitoring data for mechanical fault diagnosis still is not a relaxed task. Despite the reported achievements, Wavelet transform follows the dyadic partition scheme and would not allow a data-driven frequency partition. And then Empirical Wavelet Transform (EWT) is used to extract inherent modulation information by decomposing signal into mono-components under an orthogonal basis and non-dyadic partition scheme. However, the pre-defined segment way of Fourier spectrum without dependence on analyzed signals may result in inaccurate mono-component identification. In this paper, the modified EWT (MEWT) method via data-driven adaptive Fourier spectrum segment is proposed for mechanical fault identification. First, inner product is calculated between the Fourier spectrum of analyzed signal and Gaussian function for scale representation. Then, adaptive spectrum segment is achieved by detecting local minima of the scale representation. Finally, empirical modes can be obtained by adaptively merging mono-components based on their envelope spectrum similarity. The adaptively extracted empirical modes are analyzed for mechanical fault identification. A simulation experiment and two application cases are used to verify the effectiveness of the proposed method and the results show its outstanding performance.

  4. Adaptive Segmentation Evaluation.

    DTIC Science & Technology

    1987-09-24

    NAME OF PERFORMING ORGANIZATION b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Martin Marietta Corporation If aplicable ) Orlando Aerospace...w I a S DC 3 o IJ 0) 6 44, in in Wor Vr Nr-s t V-9 -* 9- 6 000000000a00a00000000 - ~J S 000 041G O ’tpf 00, got- 33 00 0 0 0 1 0C.0. Ol (P 000. O0ok...0 0 0 a c c 0 u - v000 - coo r- aow~ ca C .soL w0~on 1 _j _j r 1 1 -C 0M1 N of a (~V-. C 1 P-0 Mn 0 -~ vr M 1 1 (r1 W-TL/5 q W - ’a-i - aI 0 W 0 I r

  5. Luminance contours can gate afterimage colors and "real" colors.

    PubMed

    Anstis, Stuart; Vergeer, Mark; Van Lier, Rob

    2012-09-06

    It has long been known that colored images may elicit afterimages in complementary colors. We have already shown (Van Lier, Vergeer, & Anstis, 2009) that one and the same adapting image may result in different afterimage colors, depending on the test contours presented after the colored image. The color of the afterimage depends on two adapting colors, those both inside and outside the test. Here, we further explore this phenomenon and show that the color-contour interactions shown for afterimage colors also occur for "real" colors. We argue that similar mechanisms apply for both types of stimulation.

  6. 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…

  7. A fast algorithm for adaptive clutter rejection in ultrasound color flow imaging based on the first-order perturbation: a simulation study.

    PubMed

    You, Wei; Wang, Yuanyuan

    2010-08-01

    A fast clutter rejection method for ultrasound color flow imaging is proposed based on the first-order perturbation as an efficient implementation of eigen-decomposition. The proposed method is verified by simulated data. Results show that the proposed method can be adaptive to non-stationary clutter movements and its computational complexity is lower than that of the conventional eigen-based clutter rejection methods.

  8. New adaptive clutter rejection based on spectral analysis for ultrasound color Doppler imaging: phantom and in vivo abdominal study.

    PubMed

    Geunyong Park; Sunmi Yeo; Jae Jin Lee; Changhan Yoon; Hyun-Woo Koh; Hyungjoon Lim; Youngtae Kim; Hwan Shim; Yangmo Yoo

    2014-01-01

    Effective rejection of time-varying clutter originating from slowly moving vessels and surrounding tissues is important for depicting hemodynamics in ultrasound color Doppler imaging (CDI). In this paper, a new adaptive clutter rejection method based on spectral analysis (ACR-SA) is presented for suppressing nonstationary clutter. In ACR-SA, tissue and flow characteristics are analyzed by singular value decomposition and tissue acceleration of backscattered Doppler signals to determine an appropriate clutter filter from a set of clutter filters. To evaluate the ACR-SA method, 20 frames of complex baseband data were acquired by a commercial ultrasound system equipped with a research package (Accuvix V10, Samsung Medison, Seoul, Korea) using a 3.5-MHz convex array probe by introducing tissue movements to the flow phantom (Gammex 1425 A LE, Gammex, Middleton, WI, USA). In addition, 20 frames of in vivo abdominal data from five volunteers were captured. From the phantom experiment, the ACR-SA method provided 2.43 dB (p <; 0.001) and 1.09 dB ( ) improvements in flow signal-to-clutter ratio (SCR) compared to static (STA) and down-mixing (ACR-DM) methods. Similarly, it showed smaller values in fractional residual clutter area (FRCA) compared to the STA and ACR-DM methods (i.e., 2.3% versus 5.4% and 3.7%, respectively, ). The consistent improvements in SCR from the proposed ACR-SA method were obtained with the in vivo abdominal data (i.e., 4.97 dB and 3.39 dB over STA and ACR-DM, respectively). The ACR-SA method showed less than 1% FRCA values for all in vivo abdominal data. These results indicate that the proposed ACR-SA method can improve image quality in CDI by providing enhanced rejection of nonstationary clutter.

  9. An adaptive 3D region growing algorithm to automatically segment and identify thoracic aorta and its centerline using computed tomography angiography scans

    NASA Astrophysics Data System (ADS)

    Ferreira, F.; Dehmeshki, J.; Amin, H.; Dehkordi, M. E.; Belli, A.; Jouannic, A.; Qanadli, S.

    2010-03-01

    Thoracic Aortic Aneurysm (TAA) is a localized swelling of the thoracic aorta. The progressive growth of an aneurysm may eventually cause a rupture if not diagnosed or treated. This necessitates the need for an accurate measurement which in turn calls for the accurate segmentation of the aneurysm regions. Computer Aided Detection (CAD) is a tool to automatically detect and segment the TAA in the Computer tomography angiography (CTA) images. The fundamental major step of developing such a system is to develop a robust method for the detection of main vessel and measuring its diameters. In this paper we propose a novel adaptive method to simultaneously segment the thoracic aorta and to indentify its center line. For this purpose, an adaptive parametric 3D region growing is proposed in which its seed will be automatically selected through the detection of the celiac artery and the parameters of the method will be re-estimated while the region is growing thorough the aorta. At each phase of region growing the initial center line of aorta will also be identified and modified through the process. Thus the proposed method simultaneously detect aorta and identify its centerline. The method has been applied on CT images from 20 patients with good agreement with the visual assessment by two radiologists.

  10. Modeling of display color parameters and algorithmic color selection

    NASA Astrophysics Data System (ADS)

    Silverstein, Louis D.; Lepkowski, James S.; Carter, Robert C.; Carter, Ellen C.

    1986-01-01

    An algorithmic approach to color selection, which is based on psychophysical models of color processing, is described. The factors that affect color differentiation, such as wavelength separation, color stimulus size, and brightness adaptation level, are discussed. The use of the CIE system of colorimetry and the CIELUV color difference metric for display color modeling is examined. The computer program combines the selection algorithm with internally derived correction factors for color image field size, ambient lighting characteristics, and anomalous red-green color vision deficiencies of display operators. The performance of the program is evaluated and uniform chromaticity scale diagrams for six-color and seven-color selection problems are provided.

  11. 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.

  12. 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

  13. An approach for visibility improvement of dark color images using adaptive gamma correction and DCT-SVD

    NASA Astrophysics Data System (ADS)

    Tiwari, Mayank; Lamba, Subir Singh; Gupta, Bhupendra

    2016-07-01

    This paper proposes an efficient method to improve visibility of dark color images and video sequences. Visibility improvement of dark color images play a significant role in computer vision, digital image processing and pattern recognition. In the proposed method we have worked in hue-saturation-value (HSV) color model. The proposed method initially decomposes the V-plane of the input image into low and high frequency components using DCT; it then estimates the singular value matrix of the low-frequency component. After applying certain processing to improve visibility of the dark color image, it reconstructs the processed image by applying inverse DCT. Experimental results show that the proposed method produces enhanced images of comparable or higher quality than those produced using previous state-of-the-art methods.

  14. 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.

  15. A fast and efficient segmentation scheme for cell microscopic image.

    PubMed

    Lebrun, G; Charrier, C; Lezoray, O; Meurie, C; Cardot, H

    2007-04-27

    Microscopic cellular image segmentation schemes must be efficient for reliable analysis and fast to process huge quantity of images. Recent studies have focused on improving segmentation quality. Several segmentation schemes have good quality but processing time is too expensive to deal with a great number of images per day. For segmentation schemes based on pixel classification, the classifier design is crucial since it is the one which requires most of the processing time necessary to segment an image. The main contribution of this work is focused on how to reduce the complexity of decision functions produced by support vector machines (SVM) while preserving recognition rate. Vector quantization is used in order to reduce the inherent redundancy present in huge pixel databases (i.e. images with expert pixel segmentation). Hybrid color space design is also used in order to improve data set size reduction rate and recognition rate. A new decision function quality criterion is defined to select good trade-off between recognition rate and processing time of pixel decision function. The first results of this study show that fast and efficient pixel classification with SVM is possible. Moreover posterior class pixel probability estimation is easy to compute with Platt method. Then a new segmentation scheme using probabilistic pixel classification has been developed. This one has several free parameters and an automatic selection must dealt with, but criteria for evaluate segmentation quality are not well adapted for cell segmentation, especially when comparison with expert pixel segmentation must be achieved. Another important contribution in this paper is the definition of a new quality criterion for evaluation of cell segmentation. The results presented here show that the selection of free parameters of the segmentation scheme by optimisation of the new quality cell segmentation criterion produces efficient cell segmentation.

  16. 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

  17. Diffeomorphic registration with self-adaptive spatial regularization for the segmentation of non-human primate brains.

    PubMed

    Risser, Laurent; Dolius, Lionel; Fonta, Caroline; Mescam, Muriel

    2014-01-01

    Cerebral aging has been linked to structural and functional changes in the brain throughout life. Here, we study the marmoset, a small non-human primate, in order to get insights into the mechanisms of brain aging in normal and pathological conditions. Imaging the brain of small animals with techniques such as MRI, quickly becomes a challenging task when compared with human brain imaging. Very often, a simple pre-processing step such as brain extraction cannot be achieved with classical tools. In this paper, we propose a diffeomorphic registration algorithm, which makes use of learned constraints to propagate the manual segmentation of a marmoset brain template to other MR images of marmoset brains. The main methological contribution of our paper is to explore a new strategy to automatically tune the spatial regularization of the deformations. Results show that we obtain a robust segmentation of the brain, even for images with a low contrast.

  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. Motion Alters Color Appearance

    PubMed Central

    Hong, Sang-Wook; Kang, Min-Suk

    2016-01-01

    Chromatic induction compellingly demonstrates that chromatic context as well as spectral lights reflected from an object determines its color appearance. Here, we show that when one colored object moves around an identical stationary object, the perceived saturation of the stationary object decreases dramatically whereas the saturation of the moving object increases. These color appearance shifts in the opposite directions suggest that normalization induced by the object’s motion may mediate the shift in color appearance. We ruled out other plausible alternatives such as local adaptation, attention, and transient neural responses that could explain the color shift without assuming interaction between color and motion processing. These results demonstrate that the motion of an object affects both its own color appearance and the color appearance of a nearby object, suggesting a tight coupling between color and motion processing. PMID:27824098

  20. 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.

  1. Evaluation of atlas based auto-segmentation for head and neck target volume delineation in adaptive/replan IMRT

    NASA Astrophysics Data System (ADS)

    Speight, R.; Karakaya, E.; Prestwich, R.; Sen, M.; Lindsay, R.; Harding, R.; Sykes, J.

    2014-03-01

    IMRT for head and neck patients requires clinicians to delineate clinical target volumes (CTV) on a planning-CT (>2hrs/patient). When patients require a replan-CT, CTVs must be re-delineated. This work assesses the performance of atlas-based autosegmentation (ABAS), which uses deformable image registration between planning and replan-CTs to auto-segment CTVs on the replan-CT, based on the planning contours. Fifteen patients with planning-CT and replan-CTs were selected. One clinician delineated CTVs on the planning-CTs and up to three clinicians delineated CTVs on the replan-CTs. Replan-CT volumes were auto-segmented using ABAS using the manual CTVs from the planning-CT as an atlas. ABAS CTVs were edited manually to make them clinically acceptable. Clinicians were timed to estimate savings using ABAS. CTVs were compared using dice similarity coefficient (DSC) and mean distance to agreement (MDA). Mean inter-observer variability (DSC>0.79 and MDA<2.1mm) was found to be greater than intra-observer variability (DSC>0.91 and MDA<1.5mm). Comparing ABAS to manual CTVs gave DSC=0.86 and MDA=2.07mm. Once edited, ABAS volumes agreed more closely with the manual CTVs (DSC=0.87 and MDA=1.87mm). The mean clinician time required to produce CTVs reduced from 169min to 57min when using ABAS. ABAS segments volumes with accuracy close to inter-observer variability however the volumes require some editing before clinical use. Using ABAS reduces contouring time by a factor of three.

  2. Adaptation.

    PubMed

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  3. Kidney-specific chloride channel, OmClC-K, predominantly expressed in the diluting segment of freshwater-adapted tilapia kidney

    PubMed Central

    Miyazaki, Hiroaki; Kaneko, Toyoji; Uchida, Shinichi; Sasaki, Sei; Takei, Yoshio

    2002-01-01

    The kidney plays an important role in osmoregulation in freshwater teleosts, which are exposed to the danger of osmotic loss of Na+ and Cl−. However, ion-transport mechanisms in the kidney are poorly understood, and ion transporters of the fish nephron have not been identified thus far. From Mozambique tilapia, Oreochromis mossambicus, we have cloned a chloride channel, which is a homologue of the mammalian kidney-specific chloride channel, ClC-K. The cDNA of the channel, named OmClC-K, encodes a protein whose amino acid sequence has high homology to Xenopus and mammalian ClC-K (Xenopus ClC-K, 41.8%; rat ClC-K2, 40.9%; rat ClC-K1, 40.1%). The mRNA of OmClC-K was expressed exclusively in the kidney, and the expression level of mRNA was increased more in freshwater-adapted fish than seawater-adapted fish. The immunohistochemical study using a specific antibody showed that OmClC-K-positive cells were specifically located in the distal nephron segments. Immunoelectron microscopy further showed that immunoreaction of OmClC-K was recognizable on the structure of basolateral membrane infoldings in the distal tubule cells. The localization of OmClC-K and its induction in hypoosmotic media suggest that OmClC-K is involved in Cl− reabsorption in the distal tubule of freshwater-adapted tilapia. PMID:12427972

  4. 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

  5. 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…

  6. Dealing with missing data in the MICROSCOPE space mission: An adaptation of inpainting to handle colored-noise data

    NASA Astrophysics Data System (ADS)

    Pires, Sandrine; Bergé, Joel; Baghi, Quentin; Touboul, Pierre; Métris, Gilles

    2016-12-01

    The MICROSCOPE space mission, launched on April 25, 2016, aims to test the weak equivalence principle (WEP) with a 10-15 precision. Reaching this performance requires an accurate and robust data analysis method, especially since the possible WEP violation signal will be dominated by a strongly colored noise. An important complication is brought by the fact that some values will be missing—therefore, the measured time series will not be strictly regularly sampled. Those missing values induce a spectral leakage that significantly increases the noise in Fourier space, where the WEP violation signal is looked for, thereby complicating scientific returns. Recently, we developed an inpainting algorithm to correct the MICROSCOPE data for missing values. This code has been integrated in the official MICROSCOPE data processing and analysis pipeline because it enables us to significantly measure an equivalence principle violation (EPV) signal in a model-independent way, in the inertial satellite configuration. In this work, we present several improvements to the method that may allow us now to reach the MICROSCOPE requirements for both inertial and spin satellite configurations. The main improvement has been obtained using a prior on the power spectrum of the colored noise that can be directly derived from the incomplete data. We show that after reconstructing missing values with this new algorithm, a least-squares fit may allow us to significantly measure an EPV signal with a 0.96 ×10-15 precision in the inertial mode and 1.20 ×10-15 precision in the spin mode. Although, the inpainting method presented in this paper has been optimized to the MICROSCOPE data, it remains sufficiently general to be used in the general context of missing data in time series dominated by an unknown colored noise. The improved inpainting software, called inpainting for colored-noise dominated signals, is freely available at http://www.cosmostat.org/software/icon.

  7. Evaluation of color categorization for representing vehicle colors

    NASA Astrophysics Data System (ADS)

    Zeng, Nan; Crisman, Jill D.

    1997-02-01

    This paper evaluates the accuracy of three color categorization techniques in describing vehicles colors for a system, AutoColor, which we are developing for Intelligent Transportation Systems. Color categorization is used to efficiently represent 24-bit color images with up to 8 bits of color information. Our inspiration for color categorization is based on the fact that humans typically use only a few color names to describe the numerous colors they perceive. Our Crayon color categorization technique uses a naming scheme for digitized colors which is roughly based on human names for colors. The fastest and most straight forward method for compacting a 24-bit representation into an 8-bit representation is to use the most significant bits (MSB) to represent the colors. In addition, we have developed an Adaptive color categorization technique which can derive a set of color categories for the current imaging conditions. In this paper, we detail the three color categorization techniques, Crayon, MSB, and Adaptive, and we evaluate their performance on representing vehicle colors in our AutoColor system.

  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. Influence of reconstruction settings on the performance of adaptive thresholding algorithms for FDG-PET image segmentation in radiotherapy planning.

    PubMed

    Matheoud, Roberta; Della Monica, Patrizia; Loi, Gianfranco; Vigna, Luca; Krengli, Marco; Inglese, Eugenio; Brambilla, Marco

    2011-01-30

    The purpose of this study was to analyze the behavior of a contouring algorithm for PET images based on adaptive thresholding depending on lesions size and target-to-background (TB) ratio under different conditions of image reconstruction parameters. Based on this analysis, the image reconstruction scheme able to maximize the goodness of fit of the thresholding algorithm has been selected. A phantom study employing spherical targets was designed to determine slice-specific threshold (TS) levels which produce accurate cross-sectional areas. A wide range of TB ratio was investigated. Multiple regression methods were used to fit the data and to construct algorithms depending both on target cross-sectional area and TB ratio, using various reconstruction schemes employing a wide range of iteration number and amount of postfiltering Gaussian smoothing. Analysis of covariance was used to test the influence of iteration number and smoothing on threshold determination. The degree of convergence of ordered-subset expectation maximization (OSEM) algorithms does not influence TS determination. Among these approaches, the OSEM at two iterations and eight subsets with a 6-8 mm post-reconstruction Gaussian three-dimensional filter provided the best fit with a coefficient of determination R² = 0.90 for cross-sectional areas ≤ 133 mm² and R² = 0.95 for cross-sectional areas > 133 mm². The amount of post-reconstruction smoothing has been directly incorporated in the adaptive thresholding algorithms. The feasibility of the method was tested in two patients with lymph node FDG accumulation and in five patients using the bladder to mimic an anatomical structure of large size and uniform uptake, with satisfactory results. Slice-specific adaptive thresholding algorithms look promising as a reproducible method for delineating PET target volumes with good accuracy.

  10. 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

  11. 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.

  12. 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

  13. Designing an Algorithm for Cancerous Tissue Segmentation Using Adaptive K-means Cluttering and Discrete Wavelet Transform

    PubMed Central

    Rezaee, Kh.; Haddadnia, J.

    2013-01-01

    Background: Breast cancer is currently one of the leading causes of death among women worldwide. The diagnosis and separation of cancerous tumors in mammographic images require accuracy, experience and time, and it has always posed itself as a major challenge to the radiologists and physicians. Objective: This paper proposes a new algorithm which draws on discrete wavelet transform and adaptive K-means techniques to transmute the medical images implement the tumor estimation and detect breast cancer tumors in mammograms in early stages. It also allows the rapid processing of the input data. Method: In the first step, after designing a filter, the discrete wavelet transform is applied to the input images and the approximate coefficients of scaling components are constructed. Then, the different parts of image are classified in continuous spectrum. In the next step, by using adaptive K-means algorithm for initializing and smart choice of clusters’ number, the appropriate threshold is selected. Finally, the suspicious cancerous mass is separated by implementing the image processing techniques. Results: We Received 120 mammographic images in LJPEG format, which had been scanned in Gray-Scale with 50 microns size, 3% noise and 20% INU from clinical data taken from two medical databases (mini-MIAS and DDSM). The proposed algorithm detected tumors at an acceptable level with an average accuracy of 92.32% and sensitivity of 90.24%. Also, the Kappa coefficient was approximately 0.85, which proved the suitable reliability of the system performance. Conclusion: The exact positioning of the cancerous tumors allows the radiologist to determine the stage of disease progression and suggest an appropriate treatment in accordance with the tumor growth. The low PPV and high NPV of the system is a warranty of the system and both clinical specialists and patients can trust its output. PMID:25505753

  14. 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

  15. 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.

  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 most ...

  17. 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…

  18. 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

  19. 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.

  20. 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.

  1. LSM: perceptually accurate line segment merging

    NASA Astrophysics Data System (ADS)

    Hamid, Naila; Khan, Nazar

    2016-11-01

    Existing line segment detectors tend to break up perceptually distinct line segments into multiple segments. We propose an algorithm for merging such broken segments to recover the original perceptually accurate line segments. The algorithm proceeds by grouping line segments on the basis of angular and spatial proximity. Then those line segment pairs within each group that satisfy unique, adaptive mergeability criteria are successively merged to form a single line segment. This process is repeated until no more line segments can be merged. We also propose a method for quantitative comparison of line segment detection algorithms. Results on the York Urban dataset show that our merged line segments are closer to human-marked ground-truth line segments compared to state-of-the-art line segment detection algorithms.

  2. Color blindness

    MedlinePlus

    ... have trouble telling the difference between red and green. This is the most common type of color ... color blindness often have problems seeing reds and greens, too. The most severe form of color blindness ...

  3. 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.

  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. 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

  6. Color quality scale

    NASA Astrophysics Data System (ADS)

    Davis, Wendy; Ohno, Yoshi

    2010-03-01

    The color rendering index (CRI) has been shown to have deficiencies when applied to white light-emitting-diode-based sources. Furthermore, evidence suggests that the restricted scope of the CRI unnecessarily penalizes some light sources with desirable color qualities. To solve the problems of the CRI and include other dimensions of color quality, the color quality scale (CQS) has been developed. Although the CQS uses many of elements of the CRI, there are a number of fundamental differences. Like the CRI, the CQS is a test-samples method that compares the appearance of a set of reflective samples when illuminated by the test lamp to their appearance under a reference illuminant. The CQS uses a larger set of reflective samples, all of high chroma, and combines the color differences of the samples with a root mean square. Additionally, the CQS does not penalize light sources for causing increases in the chroma of object colors but does penalize sources with smaller rendered color gamut areas. The scale of the CQS is converted to span 0-100, and the uniform object color space and chromatic adaptation transform used in the calculations are updated. Supplementary scales have also been developed for expert users.

  7. 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.

  8. 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.

  9. 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.

  10. Chromostereopsis in "virtual reality" adapters with electrically tuneable liquid lens oculars

    NASA Astrophysics Data System (ADS)

    Ozolinsh, Maris; Muizniece, Kristine; Berzinsh, Janis

    2016-10-01

    Chromostereopsis can be sight and feel in "Virtual Reality" adapters, that induces the appearance of color dependant depth sense and, finally, combines this sense with the source conceived depth scenario. Present studies are devoted to investigation the induced chromastereopsis when using adapted "Virtual Reality" frame together with mobile devices as smartphones. We did observation of composite visual stimuli presented on the high spatial resolution screen of the mobile phone placed inside a portable "Virtual Reality" adapter. Separated for the left and right eyes stimuli consisted of two areas: a) identical for both eyes color chromostereopsis part, and b) additional conventional color neutral random-dot stereopsis part with a stereodisparity based on the horizontal shift of a random-dot segment in images for the left and right eyes, correspondingly. The observer task was to equalize the depth sense for neutral and colored stimuli areas. Such scheme allows to determine actual observed chromostereopsis disparity value versus eye stimuli color difference. At standard observation conditions for adapter with +2D ocular lenses for mobile red-blue stimuli, the perceptual chromostereopsis depth sensitivity on color difference was linearly approximated with a slope SChS ≈ 2.1[arcmin/(Labcolor difference)] for red-blue pairs. Additional to standard application in adapter the tuneable "Varioptic" liquid lens oculars were incorporated, that allowed stimuli eye magnification, vergence and disparity values control electrically.

  11. 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.

  12. Color Algebras

    NASA Technical Reports Server (NTRS)

    Mulligan, Jeffrey B.

    2017-01-01

    A color algebra refers to a system for computing sums and products of colors, analogous to additive and subtractive color mixtures. We would like it to match the well-defined algebra of spectral functions describing lights and surface reflectances, but an exact correspondence is impossible after the spectra have been projected to a three-dimensional color space, because of metamerism physically different spectra can produce the same color sensation. Metameric spectra are interchangeable for the purposes of addition, but not multiplication, so any color algebra is necessarily an approximation to physical reality. Nevertheless, because the majority of naturally-occurring spectra are well-behaved (e.g., continuous and slowly-varying), color algebras can be formulated that are largely accurate and agree well with human intuition. Here we explore the family of algebras that result from associating each color with a member of a three-dimensional manifold of spectra. This association can be used to construct a color product, defined as the color of the spectrum of the wavelength-wise product of the spectra associated with the two input colors. The choice of the spectral manifold determines the behavior of the resulting system, and certain special subspaces allow computational efficiencies. The resulting systems can be used to improve computer graphic rendering techniques, and to model various perceptual phenomena such as color constancy.

  13. Color Facsimile.

    DTIC Science & Technology

    1995-02-01

    modification of existing JPEG compression and decompression software available from Independent JPEG Users Group to process CIELAB color images and to use...externally specificed Huffman tables. In addition a conversion program was written to convert CIELAB color space images to red, green, blue color space

  14. 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…

  15. EVENT SEGMENTATION

    PubMed Central

    Zacks, Jeffrey M.; Swallow, Khena M.

    2012-01-01

    One way to understand something is to break it up into parts. New research indicates that segmenting ongoing activity into meaningful events is a core component of ongoing perception, with consequences for memory and learning. Behavioral and neuroimaging data suggest that event segmentation is automatic and that people spontaneously segment activity into hierarchically organized parts and sub-parts. This segmentation depends on the bottom-up processing of sensory features such as movement, and on the top-down processing of conceptual features such as actors’ goals. How people segment activity affects what they remember later; as a result, those who identify appropriate event boundaries during perception tend to remember more and learn more proficiently. PMID:22468032

  16. 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.

  17. Cats: Optical to Near-Infrared Colors of the Bulge and Disk of Two z = 0.7 Galaxies Using Hubble Space Telescope and Keck Laser Adaptive Optics Imaging

    NASA Astrophysics Data System (ADS)

    Steinbring, E.; Melbourne, J.; Metevier, A. J.; Koo, D. C.; Chun, M. R.; Simard, L.; Larkin, J. E.; Max, C. E.

    2008-10-01

    We have employed laser guide star (LGS) adaptive optics (AO) on the Keck II telescope to obtain near-infrared (NIR) images in the Extended Groth Strip deep galaxy survey field. This is a continuation of our Center for Adaptive Optics Treasury Survey program of targeting 0.5 < z < 1 galaxies where existing images with the Hubble Space Telescope (HST) are already in hand. Our AO field has already been imaged by the Advanced Camera for Surveys and the Near Infrared Camera and Multiobject Spectrograph (NICMOS). Our AO images at 2.2 μm (K') are comparable in depth to those from the HST, have Strehl ratios up to 0.4, and full width at half-maximum resolutions superior to that from NICMOS. By sampling the field with the LGS at different positions, we obtain better quality AO images than with an immovable natural guide star. As examples of the power of adding LGS AO to HST data, we study the optical to NIR colors and color gradients of the bulge and disk of two galaxies in the field with z = 0.7. All authors except L.S. are affiliated with the Center for Adaptive Optics.

  18. 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…

  19. 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…

  20. Color terms and color concepts.

    PubMed

    Davidoff, Jules

    2006-08-01

    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 are taken up in the current commentary, especially with regard to the neuropsychological evidence. Data from aphasic patients also argue for a priority for abstract thought, but nevertheless it may still be that the use of color terms is the only way in which to form color categories even if both linguistic and attentional factors play an important role.

  1. 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.

  2. 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…

  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. Image segmentation using common techniques and illumination applied to tissue culture

    NASA Astrophysics Data System (ADS)

    Vazquez Rueda, Martin G.; Hahn, Federico

    1998-03-01

    This paper present the comparation and performance on no adaptive image segmentation techniques using illumination and adaptive image segmentation techniques. Results obtained on indoor plant reproduction by tissue culture, show the improve in time process, simplify the image segmentation process, experimental results are presented using common techniques in image processing and illumination, contrasted with adaptive image segmentation.

  5. 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.

  6. 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

  7. Design Considerations for a Highly Segmented Mirror

    NASA Astrophysics Data System (ADS)

    Padin, Stephen

    2003-06-01

    Design issues for a 30-m highly segmented mirror are explored, with emphasis on parametric models of simple, inexpensive segments. A mirror with many small segments offers cost savings through quantity production and permits high-order active and adaptive wave-front corrections. For a 30-m f/1 .5 paraboloidal mirror made of spherical, hexagonal glass segments, with simple warping harnesses and three-point supports, the maximum segment diameter is ~100 mm, and the minimum segment thickness is ~5 mm. Large-amplitude, low-order gravitational deformations in the mirror cell can be compensated if the segments are mounted on a plate floating on astatic supports. Because gravitational deformations in the plate are small, the segment actuators require a stroke of only a few tens of micrometers, and the segment positions can be measured by a wave-front sensor.

  8. Color Metric.

    ERIC Educational Resources Information Center

    Illinois State Office of Education, Springfield.

    This booklet was designed to convey metric information in pictoral form. The use of pictures in the coloring book enables the more mature person to grasp the metric message instantly, whereas the younger person, while coloring the picture, will be exposed to the metric information long enough to make the proper associations. Sheets of the booklet…

  9. Quantum Color

    SciTech Connect

    Lincoln, Don

    2016-07-05

    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.

  10. 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.

  11. Simple color conversion method to perceptible images for color vision deficiencies

    NASA Astrophysics Data System (ADS)

    Meguro, Mitsuhiko; Takahashi, Chihiro; Koga, Toshio

    2006-02-01

    In this paper, we propose a color conversion method for realizing barrier free systems for color-defective vision. Human beings are perceiving colors by a ratio of reaction values by three kinds of cones on the retina. The three cones have different sensitivity to a wavelength of light. Nevertheless, dichromats, who are lacking of one of the three cones, tends to be diffcult for discriminating colors of a certain combination. The proposed techniques make new images by converting color for creating perceptible combination of color. The proposed method has three parts of processes. Firstly, we do image segmentation based on the color space L*a*b*. Secondly, we judge whether mean colors of divided regions of the segmented image tend to be confusion or not by using confusion color loci and color vision models of the persons with color-defective vision. Finally, the proposed technique realizes the perceptible images for dichromats by changing the confusion color in several regions of images. We show how effectiveness of the method by some application results.

  12. 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.

  13. 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.

  14. Adaptation of a support vector machine algorithm for segmentation and visualization of retinal structures in volumetric optical coherence tomography data sets

    PubMed Central

    Zawadzki, Robert J.; Fuller, Alfred R.; Wiley, David F.; Hamann, Bernd; Choi, Stacey S.; Werner, John S.

    2008-01-01

    Recent developments in Fourier domain—optical coherence tomography (Fd-OCT) have increased the acquisition speed of current ophthalmic Fd-OCT instruments sufficiently to allow the acquisition of volumetric data sets of human retinas in a clinical setting. The large size and three-dimensional (3D) nature of these data sets require that intelligent data processing, visualization, and analysis tools are used to take full advantage of the available information. Therefore, we have combined methods from volume visualization, and data analysis in support of better visualization and diagnosis of Fd-OCT retinal volumes. Custom-designed 3D visualization and analysis software is used to view retinal volumes reconstructed from registered B-scans. We use a support vector machine (SVM) to perform semiautomatic segmentation of retinal layers and structures for subsequent analysis including a comparison of measured layer thicknesses. We have modified the SVM to gracefully handle OCT speckle noise by treating it as a characteristic of the volumetric data. Our software has been tested successfully in clinical settings for its efficacy in assessing 3D retinal structures in healthy as well as diseased cases. Our tool facilitates diagnosis and treatment monitoring of retinal diseases. PMID:17867795

  15. 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.

  16. Color vision test

    MedlinePlus

    ... from birth) color vision problems: Achromatopsia -- complete color blindness , seeing only shades of gray Deuteranopia -- difficulty telling ... test - color; Ishihara color vision test Images Color blindness tests References Adams AJ, Verdon WA, Spivey BE. ...

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Color transparency

    SciTech Connect

    Jennings, B.K.; Miller, G.A.

    1993-11-01

    The anomously large transmission of nucleons through a nucleus following a hard collision is explored. This effect, known as color transparency, is believed to be a prediction of QCD. The necessary conditions for its occurrence and the effects that must be included a realistic calculation are discussed.

  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 Central

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

    2014-01-01

    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. PMID:24591602

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. Colorful drying.

    PubMed

    Lakio, Satu; Heinämäki, Jyrki; Yliruusi, Jouko

    2010-03-01

    Drying is one of the standard unit operations in the pharmaceutical industry and it is important to become aware of the circumstances that dominate during the process. The purpose of this study was to test microcapsulated thermochromic pigments as heat indicators in a fluid bed drying process. The indicator powders were manually granulated with alpha-lactose monohydrate resulting in three particle-size groups. Also, pellets were coated with the indicator powders. The granules and pellets were fluidized in fluid bed dryer to observe the progress of the heat flow in the material and to study the heat indicator properties of the indicator materials. A tristimulus colorimeter was used to measure CIELAB color values. Color indicator for heat detection can be utilized to test if the heat-sensitive API would go through physical changes during the pharmaceutical drying process. Both the prepared granules and pellets can be used as heat indicator in fluid bed drying process. The colored heat indicators give an opportunity to learn new aspects of the process at real time and could be exploded, for example, for scaling-up studies.

  11. 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.

  12. 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.

  13. Color Range and Color Distribution of Healthy Human Gingiva: a Prospective Clinical Study.

    PubMed

    Ho, Daniel K; Ghinea, Razvan; Herrera, Luis J; Angelov, Nikola; Paravina, Rade D

    2015-12-22

    The aim of this study is to compile a comprehensive database on color range and color distribution of healthy human gingiva by age, gender and ethnicity. Spectral reflection of keratinized gingiva at upper central incisors was measured by spectroradiometer and converted into CIELAB values. Lightness range (ΔL*) for all groups together was 26.8. Corresponding a* (green-red) and b* (blue-yellow) ranges (Δa* and Δb*) were 18.3 and 13.0. Significant differences (p < 0.05) were recorded by age for L* and a* coordinates, by gender for b* coordinate, and by ethnicity for L*, a* and b* coordinates. R(2)-values between color coordinates were 0.01 (L*/a*), 0.03 (L*/b*), and 0.12 (a*/b*). The smallest color differences were recorded between age groups 46-60 and 60 + (ΔE* = 0.9), and between Caucasians and Hispanics (ΔE* = 1.1). Color difference by gender was 1.3. When total L*a*b* ranges were divided into four equal segments, 51.7% of subjects had L* value within the third segment (from lightest to darkest), 47.1% had a* value within the third segment (from less red to redder), and 59.3% had b* value within the second segment (from less yellow to yellower). It was found that ethnicity and age had statistically significant influence on the color of human gingiva.

  14. Hierarchical layered and semantic-based image segmentation using ergodicity map

    NASA Astrophysics Data System (ADS)

    Yadegar, Jacob; Liu, Xiaoqing

    2010-04-01

    Image segmentation plays a foundational role in image understanding and computer vision. Although great strides have been made and progress achieved on automatic/semi-automatic image segmentation algorithms, designing a generic, robust, and efficient image segmentation algorithm is still challenging. Human vision is still far superior compared to computer vision, especially in interpreting semantic meanings/objects in images. We present a hierarchical/layered semantic image segmentation algorithm that can automatically and efficiently segment images into hierarchical layered/multi-scaled semantic regions/objects with contextual topological relationships. The proposed algorithm bridges the gap between high-level semantics and low-level visual features/cues (such as color, intensity, edge, etc.) through utilizing a layered/hierarchical ergodicity map, where ergodicity is computed based on a space filling fractal concept and used as a region dissimilarity measurement. The algorithm applies a highly scalable, efficient, and adaptive Peano- Cesaro triangulation/tiling technique to decompose the given image into a set of similar/homogenous regions based on low-level visual cues in a top-down manner. The layered/hierarchical ergodicity map is built through a bottom-up region dissimilarity analysis. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level of detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanisms for contextual topological object/region relationship generation. Experiments have been conducted within the maritime image environment where the segmented layered semantic objects include the basic level objects (i.e. sky/land/water) and deeper level objects in the sky/land/water surfaces. Experimental results demonstrate the proposed algorithm has the capability to robustly and efficiently segment images into layered semantic objects

  15. A Color Image Edge Detection Algorithm Based on Color Difference

    NASA Astrophysics Data System (ADS)

    Zhuo, Li; Hu, Xiaochen; Jiang, Liying; Zhang, Jing

    2016-12-01

    Although image edge detection algorithms have been widely applied in image processing, the existing algorithms still face two important problems. On one hand, to restrain the interference of noise, smoothing filters are generally exploited in the existing algorithms, resulting in loss of significant edges. On the other hand, since the existing algorithms are sensitive to noise, many noisy edges are usually detected, which will disturb the subsequent processing. Therefore, a color image edge detection algorithm based on color difference is proposed in this paper. Firstly, a new operation called color separation is defined in this paper, which can reflect the information of color difference. Then, for the neighborhood of each pixel, color separations are calculated in four different directions to detect the edges. Experimental results on natural and synthetic images show that the proposed algorithm can remove a large number of noisy edges and be robust to the smoothing filters. Furthermore, the proposed edge detection algorithm is applied in road foreground segmentation and shadow removal, which achieves good performances.

  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. Neural locus of color afterimages.

    PubMed

    Zaidi, Qasim; Ennis, Robert; Cao, Dingcai; Lee, Barry

    2012-02-07

    After fixating on a colored pattern, observers see a similar pattern in complementary colors when the stimulus is removed [1-6]. Afterimages were important in disproving the theory that visual rays emanate from the eye, in demonstrating interocular interactions, and in revealing the independence of binocular vision from eye movements. Afterimages also prove invaluable in exploring selective attention, filling in, and consciousness. Proposed physiological mechanisms for color afterimages range from bleaching of cone photopigments to cortical adaptation [4-9], but direct neural measurements have not been reported. We introduce a time-varying method for evoking afterimages, which provides precise measurements of adaptation and a direct link between visual percepts and neural responses [10]. We then use in vivo electrophysiological recordings to show that all three classes of primate retinal ganglion cells exhibit subtractive adaptation to prolonged stimuli, with much slower time constants than those expected of photoreceptors. At the cessation of the stimulus, ganglion cells generate rebound responses that can provide afterimage signals for later neurons. Our results indicate that afterimage signals are generated in the retina but may be modified like other retinal signals by cortical processes, so that evidence presented for cortical generation of color afterimages is explainable by spatiotemporal factors that modify all signals.

  18. [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

  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. Color Functionality Used in Visual Display for Occupational and Environmental Safety and Managing Color Vision Deficiency.

    PubMed

    Ochiai, Nobuhisa; Kondo, Hiroyuki

    2017-01-01

    The effects of color perception are utilized in visual displays for the purpose of safety in the workplace and in daily life. These effects, generally known as color functionality, are divided into four classifications: visibility, legibility, conspicuity and discriminability. This article focuses on the relationship between the color functionality of color schemes used in visual displays for occupational and environmental safety and color vision deficiency (particularly congenital red-green color deficiency), a critical issue in ophthalmology, and examines the effects of color functionality on the perception of the color red in individuals with protan defects. Due to abrupt system reforms, current Japanese clinical ophthalmology finds itself in a situation where it is insufficiently prepared to handle congenital red-green color deficiencies. Indeed, occupational problems caused by color vision deficiencies have been almost completely neglected, and are an occupational safety and health concern that will need to be solved in the future. This report will present the guidelines for the color vision testing established by the British Health and Safety Executive (HSE), a pioneering example of a model meant to solve these problems. Issues relating to the creation of guidelines adapted to Japanese clinical ophthalmology will also be examined, and we will discuss ways to utilize color functionality used in visual displays for occupational and environmental safety to help manage color vision deficiency.

  1. 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.

  2. 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.

  3. 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.

  4. Segmentation and segment connection of obstructed colon

    NASA Astrophysics Data System (ADS)

    Medved, Mario; Truyen, Roel; Likar, Bostjan; Pernus, Franjo

    2004-05-01

    Segmentation of colon CT images is the main factor that inhibits automation of virtual colonoscopy. There are two main reasons that make efficient colon segmentation difficult. First, besides the colon, the small bowel, lungs, and stomach are also gas-filled organs in the abdomen. Second, peristalsis or residual feces often obstruct the colon, so that it consists of multiple gas-filled segments. In virtual colonoscopy, it is very useful to automatically connect the centerlines of these segments into a single colon centerline. Unfortunately, in some cases this is a difficult task. In this study a novel method for automated colon segmentation and connection of colon segments' centerlines is proposed. The method successfully combines features of segments, such as centerline and thickness, with information on main colon segments. The results on twenty colon cases show that the method performs well in cases of small obstructions of the colon. Larger obstructions are mostly also resolved properly, especially if they do not appear in the sigmoid part of the colon. Obstructions in the sigmoid part of the colon sometimes cause improper classification of the small bowel segments. If a segment is too small, it is classified as the small bowel segment. However, such misclassifications have little impact on colon analysis.

  5. 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.

  6. 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.

  7. Robust Atlas-Based Segmentation of Highly Variable Anatomy: Left Atrium Segmentation.

    PubMed

    Depa, Michal; Sabuncu, Mert R; Holmvang, Godtfred; Nezafat, Reza; Schmidt, Ehud J; Golland, Polina

    Automatic segmentation of the heart's left atrium offers great benefits for planning and outcome evaluation of atrial ablation procedures. However, the high anatomical variability of the left atrium presents significant challenges for atlas-guided segmentation. In this paper, we demonstrate an automatic method for left atrium segmentation using weighted voting label fusion and a variant of the demons registration algorithm adapted to handle images with different intensity distributions. We achieve accurate automatic segmentation that is robust to the high anatomical variations in the shape of the left atrium in a clinical dataset of MRA images.

  8. Strehl ratio and modulation transfer function for segmented mirror telescopes as functions of segment phase error.

    PubMed

    Chanan, G; Troy, M

    1999-11-01

    We derive the Strehl ratio for a segmented mirror telescope as a function of the rms segment phase error and the observing wavelength, with and without the effects of the atmosphere. A simple analytical expression is given for the atmosphere-free case. Although our specific results are in the context of the Keck telescope, they are presented in a way that should be readily adaptable to other segmented geometries. We also derive the corresponding modulation transfer functions. These results are useful in determining how accurately a segmented mirror telescope needs to be phased for a variety of observing applications.

  9. Color Relationalism and Relativism.

    PubMed

    Byrne, Alex; Hilbert, David R

    2017-01-01

    This paper critically examines color relationalism and color relativism, two theories of color that are allegedly supported by variation in normal human color vision. We mostly discuss color relationalism, defended at length in Jonathan Cohen's The Red and the Real, and argue that the theory has insuperable problems.

  10. Primary Theme Club. Colors.

    ERIC Educational Resources Information Center

    Walmsley, Bonnie Brown; Camp, Anne-Marie

    1997-01-01

    Presents a cross-curricular theme unit on colors that includes a pullout poster and a resource list. Social studies activities highlight flags of the world. Science activities teach about colors of animals and the science of color. Language arts activities describe colorful language. Mathematics activities involve sorting and graphing colors. (SM)

  11. Activities: Some Colorful Mathematics.

    ERIC Educational Resources Information Center

    DeTemple, Duane W.; Walker, Dean A.

    1996-01-01

    Describes three activities in discrete mathematics that involve coloring geometric objects: counting colored regions of overlapping simple closed curves, counting colored triangulations of polygons, and determining the number of colors required to paint the plane so that no two points one inch apart are the same color. (MKR)

  12. 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...

  13. Early visual mechanisms do not contribute to synesthetic color experience.

    PubMed

    Hong, Sang Wook; Blake, Randolph

    2008-03-01

    Color-graphemic synesthetes perceive colors when viewing alphanumeric characters. Theories of color-graphemic synesthesia posit that synesthetic color experience arises from activation of neural mechanisms also involved in ordinary color vision. To learn how early in visual processing those mechanisms exist, we performed several experiments. In one experiment, real colors were altered in appearance by the lightness of their backgrounds, but the appearance of synesthetic colors was immune to surrounding light levels. In the second experiment using a hue cancellation technique, adaptation to synesthetic color had no subsequent effect on the amount of cancelling light to achieve equilibrium yellow, whereas adaptation to real colors did. In the third experiment, vivid synesthetic color had no influence on equilibrium yellow settings of the actual color of the characters evoking synesthesia. Because brightness contrast and chromatic adaptation are putatively mediated by neural mechanisms early in visual processing including retina and primary visual cortex, our results imply that neural events responsible for synesthetic color emerge subsequent to these early visual stages.

  14. 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.

  15. 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.

  16. Multiquadric Spline-Based Interactive Segmentation of Vascular Networks

    PubMed Central

    Meena, Sachin; Surya Prasath, V. B.; Kassim, Yasmin M.; Maude, Richard J.; Glinskii, Olga V.; Glinsky, Vladislav V.; Huxley, Virginia H.; Palaniappan, Kannappan

    2016-01-01

    Commonly used drawing tools for interactive image segmentation and labeling include active contours or boundaries, scribbles, rectangles and other shapes. Thin vessel shapes in images of vascular networks are difficult to segment using automatic or interactive methods. This paper introduces the novel use of a sparse set of user-defined seed points (supervised labels) for precisely, quickly and robustly segmenting complex biomedical images. A multiquadric spline-based binary classifier is proposed as a unique approach for interactive segmentation using as features color values and the location of seed points. Epifluorescence imagery of the dura mater microvasculature are difficult to segment for quantitative applications due to challenging tissue preparation, imaging conditions, and thin, faint structures. Experimental results based on twenty epifluorescence images is used to illustrate the benefits of using a set of seed points to obtain fast and accurate interactive segmentation compared to four interactive and automatic segmentation approaches. PMID:28227856

  17. Multiquadric Spline-Based Interactive Segmentation of Vascular Networks.

    PubMed

    Meena, Sachin; Surya Prasath, V B; Kassim, Yasmin M; Maude, Richard J; Glinskii, Olga V; Glinsky, Vladislav V; Huxley, Virginia H; Palaniappan, Kannappan

    2016-08-01

    Commonly used drawing tools for interactive image segmentation and labeling include active contours or boundaries, scribbles, rectangles and other shapes. Thin vessel shapes in images of vascular networks are difficult to segment using automatic or interactive methods. This paper introduces the novel use of a sparse set of user-defined seed points (supervised labels) for precisely, quickly and robustly segmenting complex biomedical images. A multiquadric spline-based binary classifier is proposed as a unique approach for interactive segmentation using as features color values and the location of seed points. Epifluorescence imagery of the dura mater microvasculature are difficult to segment for quantitative applications due to challenging tissue preparation, imaging conditions, and thin, faint structures. Experimental results based on twenty epifluorescence images is used to illustrate the benefits of using a set of seed points to obtain fast and accurate interactive segmentation compared to four interactive and automatic segmentation approaches.

  18. Color vision and color formation in dragonflies.

    PubMed

    Futahashi, Ryo

    2016-10-01

    Dragonflies including damselflies are colorful and large-eyed insects, which show remarkable sexual dimorphism, color transition, and color polymorphism. Recent comprehensive visual transcriptomics has unveiled an extraordinary diversity of opsin genes within the lineage of dragonflies. These opsin genes are differentially expressed between aquatic larvae and terrestrial adults, as well as between dorsal and ventral regions of adult compound eyes. Recent topics of color formation in dragonflies are also outlined. Non-iridescent blue color is caused by coherent light scattering from the quasiordered nanostructures, whereas iridescent color is produced by multilayer structures. Wrinkles or wax crystals sometimes enhances multilayer structural colors. Sex-specific and stage-specific color differences in red dragonflies is attributed to redox states of ommochrome pigments.

  19. Urine - abnormal color

    MedlinePlus

    ... medlineplus.gov/ency/article/003139.htm Urine - abnormal color To use the sharing features on this page, please enable JavaScript. The usual color of urine is straw-yellow. Abnormally colored urine ...

  20. Tooth - abnormal colors

    MedlinePlus

    ... medlineplus.gov/ency/article/003065.htm Tooth - abnormal colors To use the sharing features on this page, please enable JavaScript. Abnormal tooth color is any color other than white to yellowish- ...

  1. 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.

  2. Color Blindness Simulations

    MedlinePlus

    ... Coordinator Color blindness Simulations Normal Color Vision Deuteranopia Color blindness marked by confusion of purplish red and green Tritanopia A dichromatism in which the spectrum is seen in tones of red and green. ...

  3. Segmentation Assisted Food Classification for Dietary Assessment.

    PubMed

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

    2011-01-24

    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.

  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. 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

  6. Nonlinear two-stage model for color discrimination.

    PubMed

    Inamura, Taisuke; Shioiri, Satoshi; Tsujimura, Sei-ichi; Yaguchi, Hirohisa

    2011-04-01

    We modified a two-stage model for color discrimination proposed in a previous study [Color Res. Appl.25, 105 (2000)]; in order to extend the model to wider conditions, we considered the conditions with luminance modulations in addition to color modulations. Using the modified model, we successfully predicted color discrimination data with test color changes along both the chromatic and luminance axes under a variety of background colors. Both qualitative and quantitative assessments in modeling showed that nonlinearity is required in both the cone and the cone-opponent stages to interpret adaptation effects of both color and luminance on color discrimination. This fact suggests that the nonlinear properties at each stage have different roles in color perception.

  7. An efficient iris segmentation approach

    NASA Astrophysics Data System (ADS)

    Gomai, Abdu; El-Zaart, A.; Mathkour, H.

    2011-10-01

    Iris recognition system became a reliable system for authentication and verification tasks. It consists of five stages: image acquisition, iris segmentation, iris normalization, feature encoding, and feature matching. Iris segmentation stage is one of the most important stages. It plays an essential role to locate the iris efficiently and accurately. In this paper, we present a new approach for iris segmentation using image processing technique. This approach is composed of four main parts. (1) Eliminating reflections of light on the eye image based on inverting the color of the grayscale image, filling holes in the intensity image, and inverting the color of the intensity image to get the original grayscale image without any reflections. (2) Pupil boundary detection based on dividing an eye image to nine sub-images and finding the minimum value of the mean intensity for each sub-image to get a suitable threshold value of pupil. (3) Enhancing the contrast of outer iris boundary using exponential operator to have sharp variation. (4) Outer iris boundary localization based on applying a gray threshold and morphological operations on the rectangular part of an eye image including the pupil and the outer boundaries of iris to find the small radius of outer iris boundary from the center of pupil. The proposed approach has been tested on CASIA v1.0 iris image database and other collected iris image database. The experimental results show that the approach is able to detect pupil and outer iris boundary with high accuracy results approximately 100% and reduce time consuming.

  8. 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

  9. 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.

  10. 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.

  11. XRA image segmentation using regression

    NASA Astrophysics Data System (ADS)

    Jin, Jesse S.

    1996-04-01

    Segmentation is an important step in image analysis. Thresholding is one of the most important approaches. There are several difficulties in segmentation, such as automatic selecting threshold, dealing with intensity distortion and noise removal. We have developed an adaptive segmentation scheme by applying the Central Limit Theorem in regression. A Gaussian regression is used to separate the distribution of background from foreground in a single peak histogram. The separation will help to automatically determine the threshold. A small 3 by 3 widow is applied and the modal of the local histogram is used to overcome noise. Thresholding is based on local weighting, where regression is used again for parameter estimation. A connectivity test is applied to the final results to remove impulse noise. We have applied the algorithm to x-ray angiogram images to extract brain arteries. The algorithm works well for single peak distribution where there is no valley in the histogram. The regression provides a method to apply knowledge in clustering. Extending regression for multiple-level segmentation needs further investigation.

  12. Diffractive parameric colors.

    PubMed

    Orava, Joni; Heikkila, Noora; Jaaskelainen, Timo; Parkkinen, Jussi

    2008-12-01

    A method of producing inkless parameric color pairs is studied. In this method, colors are formed additively using diffraction gratings with differing grating periods as primary colors. Gratings with different grating periods reflect different spectral radiance peaks of a fluorescent lamp to the desired viewing angle, according to the grating equation. Four spectral peaks of a 4000 K fluorescent lamp--red, green, cyan, and blue-are used as the primary colors. The colors are mixed additively by fixing the relative areas of different grating periods inside a pixel. With four primary colors it is possible to mix certain colors with different triplets of primary colors. Thus, it is theoretically possible to produce metameric colors. In this study, three parameric color pairs are fabricated using electron beam lithography, electroplating, and hot embossing. The radiance spectra of the color pairs are measured by spectroradiometer from hot-embossed plastic samples. The CIELAB DeltaE(ab) and CIEDE2000 color differences between radiance spectra of the color pairs are calculated. The CIEDE2000 color differences of color pairs are between 2.6 and 7.2 units in reference viewing conditions. The effects of viewing angle and different light sources are also evaluated. It is found that both the viewing angle and the light source have very strong influences on the color differences of the color pairs.

  13. Toward an improved color rendering metric

    NASA Astrophysics Data System (ADS)

    Davis, Wendy; Ohno, Yoshi

    2005-09-01

    Several aspects of the Color Rendering Index (CRI) are flawed, limiting its usefulness in assessing the color rendering capabilities of LEDs for general illumination. At NIST, we are developing recommendations to modify the CRI that would overcome these problems. The current CRI is based on only eight reflective samples, all of which are low to medium chromatic saturation. These colors do not adequately span the range of normal object colors. Some lights that are able to accurately render colors of low saturation perform poorly with highly saturated colors. This is particularly prominent with light sources with peaked spectral distributions as realized by solid-state lighting. We have assembled 15 Munsell samples that overcome these problems and have performed analysis to show the improvement. Additionally, the CRI penalizes lamps for showing increases in object chromatic saturation compared to reference lights, which is actually desirable for most applications. We suggest a new computation scheme for determining the color rendering score that differentiates between hue and saturation shifts and takes their directions into account. The uniform color space used in the CRI is outdated and a replacement will be recommended. The CRI matches the CCT of the reference to that of the test light. This can be problematic when lights are substantially bluish or reddish. Lights of extreme CCTs are frequently poor color renderers, though they can score very high on the current CRI. An improved chromatic adaptation correction calculation would eliminate the need to match CCT and an updated correction is being considered.

  14. 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

  15. Uniform color space based on color matching

    NASA Astrophysics Data System (ADS)

    Liao, Shih-Fang; Yang, Tsung-Hsun; Lee, Cheng-Chung

    2007-09-01

    This research intends to explore with a uniform color space based on the CIE 1931 x-y chromatic coordinate system. The goal is to improve the non-uniformity of the CIE 1931 x-y chromaticity diagram such as to approach the human color sensation as possible; however, its simple methodology still can be kept. In spite of the existence of various kinds of the uniform color coordinate systems built up early (CIE u'-v', CIE Lab, CIE LUV, etc.), the establishment of a genuine uniform color space is actually still an important work both for the basic research in color science and the practical applications of colorimetry, especially for recent growing request in illumination engineering and in display technology. In this study, the MacAdam ellipses and the Munsell color chips are utilized for the comparison with the human color sensation. One specific linear transformation matrix is found for the CIE 1931 color matching functions (see manuscript) to become the novel uniform ones. With the aid of the optimization method, the transformation matrix can be easily discovered and makes the 25 MacAdam ellipses are similar to each other in the novel uniform color space. On the other hand, the perfectiveness of the equal-hue curves and the equal-chroma contours from the Mnusell color chips evaluates for the best optimization conditions among several different definitions for the similarity of all the MacAdam ellipses. Finally, the color difference between any two colors can be simply measured by the Euclidean distance in the novel uniform color space and is still fitted to the human color sensation.

  16. Fast Color Change with Photochromic Fused Naphthopyrans.

    PubMed

    Sousa, Céu M; Berthet, Jerome; Delbaere, Stephanie; Polónia, André; Coelho, Paulo J

    2015-12-18

    Photochromic molecules can reversibly develop color upon irradiation with UV light. These smart molecules, mainly in the naphthopyran family, have been applied with success to ophthalmic lenses that darken quickly under sunlight and revert to the uncolored state after several minutes in the dark. This slow adaptation to the absence of light is one of the limitations and is due to the formation of an unwanted photoisomer. We have designed a new naphthopyran with a bridged structure which prohibits the formation of the undesirable, persistent photoisomer and thus shows a very fast switching between the uncolored and colored states. UV irradiation of a hybrid siloxane matrix doped with the new fused naphthopyran leads to the formation of a pink coloration bleaching in a few milliseconds, in the absence of light, at room temperature. This new fused naphthopyran is easily prepared in three steps from readily accessible precursors and is amenable to structural modifications to tailor color and lifetime of the colored photoisomer.

  17. 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...

  18. 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.

  19. 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…

  20. Digital Color Image Restoration

    DTIC Science & Technology

    1975-08-01

    color image recording system is derived and the equations representing the model and the equations of colorimetry are expressed in matrix form. Computer ... algorithms are derived which correct color errors introduced by imperfections in the color recording system. The sources of color error which are

  1. 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)

  2. Color spaces in digital video

    SciTech Connect

    Gaunt, R.

    1997-05-01

    Whether it`s photography, computer graphics, publishing, or video; each medium has a defined color space, or gamut, which defines the extent that a given set of RGB colors can be mixed. When converting from one medium to another, an image must go through some form of conversion which maps colors into the destination color space. The conversion process isn`t always straight forward, easy, or reversible. In video, two common analog composite color spaces are Y`tjv (used in PAL) and Y`IQ (used in NTSC). These two color spaces have been around since the beginning of color television, and are primarily used in video transmission. Another analog scheme used in broadcast studios is Y`, R`-Y`, B`-Y` (used in Betacam and Mll) which is a component format. Y`, R`-Y`,B`-Y` maintains the color information of RGB but in less space. From this, the digital component video specification, ITU-Rec. 601-4 (formerly CCIR Rec. 601) was based. The color space for Rec. 601 is symbolized as Y`CbCr. Digital video formats such as DV, Dl, Digital-S, etc., use Rec. 601 to define their color gamut. Digital composite video (for D2 tape) is digitized analog Y`UV and is seeing decreased use. Because so much information is contained in video, segments of any significant length usually require some form of data compression. All of the above mentioned analog video formats are a means of reducing the bandwidth of RGB video. Video bulk storage devices, such as digital disk recorders, usually store frames in Y`CbCr format, even if no other compression method is used. Computer graphics and computer animations originate in RGB format because RGB must be used to calculate lighting and shadows. But storage of long animations in RGB format is usually cost prohibitive and a 30 frame-per-second data rate of uncompressed RGB is beyond most computers. By taking advantage of certain aspects of the human visual system, true color 24-bit RGB video images can be compressed with minimal loss of visual information

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. An entropy-based approach to automatic image segmentation of satellite images

    NASA Astrophysics Data System (ADS)

    Barbieri, Andre L.; de Arruda, G. F.; Rodrigues, Francisco A.; Bruno, Odemir M.; Costa, Luciano da Fontoura

    2011-02-01

    An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation.

  9. 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.

  10. 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.

  11. Vane segment support and alignment device

    SciTech Connect

    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.

  12. 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

  13. Iterative Vessel Segmentation of Fundus Images.

    PubMed

    Roychowdhury, Sohini; Koozekanani, Dara D; Parhi, Keshab K

    2015-07-01

    This paper presents a novel unsupervised iterative blood vessel segmentation algorithm using fundus images. First, a vessel enhanced image is generated by tophat reconstruction of the negative green plane image. An initial estimate of the segmented vasculature is extracted by global thresholding the vessel enhanced image. Next, new vessel pixels are identified iteratively by adaptive thresholding of the residual image generated by masking out the existing segmented vessel estimate from the vessel enhanced image. The new vessel pixels are, then, region grown into the existing vessel, thereby resulting in an iterative enhancement of the segmented vessel structure. As the iterations progress, the number of false edge pixels identified as new vessel pixels increases compared to the number of actual vessel pixels. A key contribution of this paper is a novel stopping criterion that terminates the iterative process leading to higher vessel segmentation accuracy. This iterative algorithm is robust to the rate of new vessel pixel addition since it achieves 93.2-95.35% vessel segmentation accuracy with 0.9577-0.9638 area under ROC curve (AUC) on abnormal retinal images from the STARE dataset. The proposed algorithm is computationally efficient and consistent in vessel segmentation performance for retinal images with variations due to pathology, uneven illumination, pigmentation, and fields of view since it achieves a vessel segmentation accuracy of about 95% in an average time of 2.45, 3.95, and 8 s on images from three public datasets DRIVE, STARE, and CHASE_DB1, respectively. Additionally, the proposed algorithm has more than 90% segmentation accuracy for segmenting peripapillary blood vessels in the images from the DRIVE and CHASE_DB1 datasets.

  14. Resolution for color photography

    NASA Astrophysics Data System (ADS)

    Hubel, Paul M.; Bautsch, Markus

    2006-02-01

    Although it is well known that luminance resolution is most important, the ability to accurately render colored details, color textures, and colored fabrics cannot be overlooked. This includes the ability to accurately render single-pixel color details as well as avoiding color aliasing. All consumer digital cameras on the market today record in color and the scenes people are photographing are usually color. Yet almost all resolution measurements made on color cameras are done using a black and white target. In this paper we present several methods for measuring and quantifying color resolution. The first method, detailed in a previous publication, uses a slanted-edge target of two colored surfaces in place of the standard black and white edge pattern. The second method employs the standard black and white targets recommended in the ISO standard, but records these onto the camera through colored filters thus giving modulation between black and one particular color component; red, green, and blue color separation filters are used in this study. The third method, conducted at Stiftung Warentest, an independent consumer organization of Germany, uses a whitelight interferometer to generate fringe pattern targets of varying color and spatial frequency.

  15. 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)

  16. 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.

  17. 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.

  18. Color Image Segmentation Approach to Monitor Flowering in Lesquerella

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Lesquerella (Lesquerella fendleri) seed soil has been proposed as a petroleum alternative in the production of many industrial products, but several crop management and breeding challenges must be addressed before the crop will be grown commercially. Lesquerella canopies characteristically exhibit ...

  19. Color image segmentation approach to monitor flowering in lesquerella

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Lesquerella (Lesquerella fendleri) seed soil has been proposed as a petroleum alternative in the production of many industrial products, but several crop management and breeding challenges must be addressed before the crop will be grown commercially. Lesquerella canopies characteristically exhibit ...

  20. A wrapper-based approach to image segmentation and classification.

    PubMed

    Farmer, Michael E; Jain, Anil K

    2005-12-01

    The traditional processing flow of segmentation followed by classification in computer vision assumes that the segmentation is able to successfully extract the object of interest from the background image. It is extremely difficult to obtain a reliable segmentation without any prior knowledge about the object that is being extracted from the scene. This is further complicated by the lack of any clearly defined metrics for evaluating the quality of segmentation or for comparing segmentation algorithms. We propose a method of segmentation that addresses both of these issues, by using the object classification subsystem as an integral part of the segmentation. This will provide contextual information regarding the objects to be segmented, as well as allow us to use the probability of correct classification as a metric to determine the quality of the segmentation. We view traditional segmentation as a filter operating on the image that is independent of the classifier, much like the filter methods for feature selection. We propose a new paradigm for segmentation and classification that follows the wrapper methods of feature selection. Our method wraps the segmentation and classification together, and uses the classification accuracy as the metric to determine the best segmentation. By using shape as the classification feature, we are able to develop a segmentation algorithm that relaxes the requirement that the object of interest to be segmented must be homogeneous in some low-level image parameter, such as texture, color, or grayscale. This represents an improvement over other segmentation methods that have used classification information only to modify the segmenter parameters, since these algorithms still require an underlying homogeneity in some parameter space. Rather than considering our method as, yet, another segmentation algorithm, we propose that our wrapper method can be considered as an image segmentation framework, within which existing image segmentation

  1. The influence of color on emotional perception of natural scenes.

    PubMed

    Codispoti, Maurizio; De Cesarei, Andrea; Ferrari, Vera

    2012-01-01

    Is color a critical factor when processing the emotional content of natural scenes? Under challenging perceptual conditions, such as when pictures are briefly presented, color might facilitate scene segmentation and/or function as a semantic cue via association with scene-relevant concepts (e.g., red and blood/injury). To clarify the influence of color on affective picture perception, we compared the late positive potentials (LPP) to color versus grayscale pictures, presented for very brief (24 ms) and longer (6 s) exposure durations. Results indicated that removing color information had no effect on the affective modulation of the LPP, regardless of exposure duration. These findings imply that the recognition of the emotional content of scenes, even when presented very briefly, does not critically rely on color information.

  2. 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

  3. 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.

  4. 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)

  5. Focus on Color Photography

    ERIC Educational Resources Information Center

    Galindez, Peter

    1978-01-01

    Photographs and text describe techniques by which color negative film can be developed and printed. An equipment list, by which black and white printing facilities can be converted to make color prints, is provided. (CP)

  6. 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

  7. Color rendition engine.

    PubMed

    Zukauskas, Artūras; Vaicekauskas, Rimantas; Vitta, Pranciškus; Tuzikas, Arūnas; Petrulis, Andrius; Shur, Michael

    2012-02-27

    A source of white light with continuously tuned color rendition properties, such as color fidelity, as well as color saturating and color dulling ability has been developed. The source, which is composed of red (R), amber (A), green (G), and blue (B) light-emitting diodes, has a spectral power distribution varied as a weighted sum of "white" RGB and AGB blends. At the RGB and AGB end-points, the source has a highest color saturating and color dulling ability, respectively, as follows from the statistical analysis of the color-shift vectors for 1269 Munsell samples. The variation of the weight parameter allows for continuously traversing all possible metameric RAGB blends, including that with the highest color fidelity. The source was used in a psychophysical experiment on the estimation of the color appearance of familiar objects, such as vegetables, fruits, and soft-drink cans of common brands, at correlated color temperatures of 3000 K, 4500 K, and 6500 K. By continuously tuning the weight parameter, each of 100 subjects selected RAGB blends that, to their opinion, matched lighting characterized as "most saturating," "most dulling," "most natural," and "preferential". The end-point RGB and AGB blends have been almost unambiguously attributed to "most saturating" and "most dulling" lighting, respectively. RAGB blends that render a highest number of colors with high fidelity have, on average, been attributed to "most natural" lighting. The "preferential" color quality of lighting has, on average, been matched to RAGB blends that provide color rendition with fidelity somewhat reduced in favor of a higher saturation. Our results infer that tunable "color rendition engines" can validate color rendition metrics and provide lighting meeting specific needs and preferences to color quality.

  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. 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

  10. Automatic knee cartilage delineation using inheritable segmentation

    NASA Astrophysics Data System (ADS)

    Dries, Sebastian P. M.; Pekar, Vladimir; Bystrov, Daniel; Heese, Harald S.; Blaffert, Thomas; Bos, Clemens; van Muiswinkel, Arianne M. C.

    2008-03-01

    We present a fully automatic method for segmentation of knee joint cartilage from fat suppressed MRI. The method first applies 3-D model-based segmentation technology, which allows to reliably segment the femur, patella, and tibia by iterative adaptation of the model according to image gradients. Thin plate spline interpolation is used in the next step to position deformable cartilage models for each of the three bones with reference to the segmented bone models. After initialization, the cartilage models are fine adjusted by automatic iterative adaptation to image data based on gray value gradients. The method has been validated on a collection of 8 (3 left, 5 right) fat suppressed datasets and demonstrated the sensitivity of 83+/-6% compared to manual segmentation on a per voxel basis as primary endpoint. Gross cartilage volume measurement yielded an average error of 9+/-7% as secondary endpoint. For cartilage being a thin structure, already small deviations in distance result in large errors on a per voxel basis, rendering the primary endpoint a hard criterion.

  11. Colored 3D surface reconstruction using Kinect sensor

    NASA Astrophysics Data System (ADS)

    Guo, Lian-peng; Chen, Xiang-ning; Chen, Ying; Liu, Bin

    2015-03-01

    A colored 3D surface reconstruction method which effectively fuses the information of both depth and color image using Microsoft Kinect is proposed and demonstrated by experiment. Kinect depth images are processed with the improved joint-bilateral filter based on region segmentation which efficiently combines the depth and color data to improve its quality. The registered depth data are integrated to achieve a surface reconstruction through the colored truncated signed distance fields presented in this paper. Finally, the improved ray casting for rendering full colored surface is implemented to estimate color texture of the reconstruction object. Capturing the depth and color images of a toy car, the improved joint-bilateral filter based on region segmentation is used to improve the quality of depth images and the peak signal-to-noise ratio (PSNR) is approximately 4.57 dB, which is better than 1.16 dB of the joint-bilateral filter. The colored construction results of toy car demonstrate the suitability and ability of the proposed method.

  12. 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…

  13. Color: Implications in dentistry

    PubMed Central

    Sikri, Vimal K

    2010-01-01

    The success of restorative dentistry is determined on the basis of functional and esthetic results. To achieve esthetics, four basic determinants are required in sequence; viz., position, contour, texture and color. The knowledge of the concept of color is essential for achieving good esthetics. This review compiles the various aspects of color, its measurements and shade matching in dentistry. PMID:21217954

  14. 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)

  15. Color vision deficiencies

    NASA Astrophysics Data System (ADS)

    Vannorren, D.

    1982-04-01

    Congenital and acquired color vision defects are described in the context of physiological data. Light sources, photometry, color systems and test methods are described. A list of medicines is also presented. The practical social consequences of color vision deficiencies are discussed.

  16. Color Television in Instruction.

    ERIC Educational Resources Information Center

    Bretz, Rudy

    In spite of repeated research into the matter, no evidence has been discovered to support the claim that color television is superior to black-and-white television as an instructional aid. It is possible that there are advantages to color television which are unmeasured or unmeasurable, but the current claims for color; that it heightens realism,…

  17. Color Discrimination Work Sample.

    ERIC Educational Resources Information Center

    Shawsheen Valley Regional Vocational-Technical High School, Billerica, MA.

    This manual contains a work sample intended to assess a handicapped student's ability to see likenesses or differences in colors or shades, identifying or matching certain colors, and selecting colors that go together. Section 1 describes the assessment and lists related occupations and DOT codes. Instructions to the evaluator are provided in the…

  18. 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.

  19. Attention shift-based multiple saliency object segmentation

    NASA Astrophysics Data System (ADS)

    Wu, Chang-Wei; Zhao, Hou-Qiang; Cao, Song-Xiao; Xiang, Ke; Wang, Xuan-Yin

    2016-09-01

    Object segmentation is an important but highly challenging problem in computer vision and image processing. An attention shift-based multiple saliency object segmentation model, called ASMSO, is introduced. The proposed ASMSO could produce a pool of potential object regions for each saliency object and be applicable to multiple saliency object segmentation. The potential object regions are produced by combing the methods of gPb-owt-ucm and min-cut graph, whereas the saliency objects are detected by a visual attention model with an attention shift mechanism. In order to deal with various scenes, the model attention shift-based multiple saliency object segmentation (ASMSO) contains different features which include not only traditional features, such as color, uniform, and texture, but also a new position feature originating from proximity of Gestalt theory. Experiments on the training set of PASCAL VOC2012 segmentation dataset not only show that traditional color feature and the proposed position feature work much better than features of texture and uniformity, but also prove that ASMSO is suitable for multiple object segmentation. In addition, experiments on a traditional saliency dataset show that ASMSO could also be applied to traditional saliency object segmentation and performs much better than the state-of-the-art method.

  20. Color Classification of Coordination Compounds.

    ERIC Educational Resources Information Center

    Poncini, Laurence; Wimmer, Franz L.

    1987-01-01

    Proposes that colored compounds be classified by reference to a standard color-order system incorporating a color dictionary. Argues that the colors of new compounds could be incorporated into the characterization process and into computer storage systems. (TW)

  1. Intelligent segmentation of industrial radiographic images using neural networks

    NASA Astrophysics Data System (ADS)

    Lawson, Shaun W.; Parker, Graham A.

    1994-10-01

    An application of machine vision, incorporating neural networks, which aims to fully automate real-time radiographic inspection in welding process is described. The current methodology adopted comprises two distinct stages - the segmentation of the weld from the background content of the radiographic image, and the segmentation of suspect defect areas inside the weld region itself. In the first stage, a back propagation neural network has been employed to adaptively and accurately segment the weld region from a given image. The training of the network is achieved with a single image showing a typical weld in the run which is to be inspected, coupled with a very simple schematic weld 'template'. The second processing stage utilizes a further backpropagation network which is trained on a test set of image data previously segmented by a conventional adaptive threshold method. It is shown that the two techniques can be combined to fully segment radiographic weld images.

  2. 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.

  3. Segmentation and estimation of spatially varying illumination.

    PubMed

    Lin Gu; Huynh, Cong Phuoc; Robles-Kelly, Antonio

    2014-08-01

    In this paper, we present an unsupervised method for segmenting the illuminant regions and estimating the illumination power spectrum from a single image of a scene lit by multiple light sources. Here, illuminant region segmentation is cast as a probabilistic clustering problem in the image spectral radiance space. We formulate the problem in an optimization setting, which aims to maximize the likelihood of the image radiance with respect to a mixture model while enforcing a spatial smoothness constraint on the illuminant spectrum. We initialize the sample pixel set under each illuminant via a projection of the image radiance spectra onto a low-dimensional subspace spanned by a randomly chosen subset of spectra. Subsequently, we optimize the objective function in a coordinate-ascent manner by updating the weights of the mixture components, sample pixel set under each illuminant, and illuminant posterior probabilities. We then estimate the illuminant power spectrum per pixel making use of these posterior probabilities. We compare our method with a number of alternatives for the tasks of illumination region segmentation, illumination color estimation, and color correction. Our experiments show the effectiveness of our method as applied to one hyperspectral and three trichromatic image data sets.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Segregating animals in naturalistic surroundings: interaction of color distributions and mechanisms.

    PubMed

    Jansen, Michael; Giesel, Martin; Zaidi, Qasim

    2016-03-01

    Humans have been shown to rapidly detect animals in naturalistic scenes, but the role of color in this task is unclear. We first analyze the color information contained in a large number of images of salient and camouflaged animals in generic backgrounds. We found that color distributions of most animals and of their immediate backgrounds were oriented along other than the cardinal directions of color space. In addition, the maximum distances between animals and background distributions also tended to be along noncardinal directions, suggesting a role for higher-order cortical color mechanisms whose preferred axes are distributed widely in color space. We measured temporal thresholds for segmenting animal color distributions from background distributions in the absence of spatial cues. Combined over all observers and all images in our sample, thresholds for segmenting isoluminant projections of these distributions were lower than for segmenting the original distributions and considerably lower than for segmenting achromatic projections. Color information is thus likely to be useful in segregating animals in generic views, i.e., views not purposely chosen by the photographer to enhance the visibility of the animal. However, a comparison of thresholds with distances between distributions failed to reveal any advantage conferred by higher-order color mechanisms.

  9. Colors, colored overlays, and reading skills.

    PubMed

    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.

  10. 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

  11. Miniature Color Display Phase 4

    DTIC Science & Technology

    1993-05-01

    is used to generate full color. By spectral tuning of the xenon arc-lamp backlight and the color polarizers, a color gamut comparable to that of a...5 1.2 Phase IV Accom plishments ................................... 5 1.2.1 Subtractive Color Gamut ...Technical Achievem ents .............................................. 8 2.1 Subtractive Color Gamut 2.1.1 Sub Color LC Technology

  12. 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…

  13. Facial Skin Segmentation Using Bacterial Foraging Optimization Algorithm

    PubMed Central

    Bakhshali, Mohamad Amin; Shamsi, Mousa

    2012-01-01

    Nowadays, analyzing human facial image has gained an ever-increasing importance due to its various applications. Image segmentation is required as a very important and fundamental operation for significant analysis and interpretation of images. Among the segmentation methods, image thresholding technique is one of the most well-known methods due to its simplicity, robustness, and high precision. Thresholding based on optimization of the objective function is among the best methods. Numerous methods exist for the optimization process and bacterial foraging optimization (BFO) is among the most efficient and novel ones. Using this method, optimal threshold is extracted and then segmentation of facial skin is performed. In the proposed method, first, the color facial image is converted from RGB color space to Improved Hue-Luminance-Saturation (IHLS) color space, because IHLS has a great mapping of the skin color. To perform thresholding, the entropy-based method is applied. In order to find the optimum threshold, BFO is used. In order to analyze the proposed algorithm, color images of the database of Sahand University of Technology of Tabriz, Iran were used. Then, using Otsu and Kapur methods, thresholding was performed. In order to have a better understanding from the proposed algorithm; genetic algorithm (GA) is also used for finding the optimum threshold. The proposed method shows the better results than other thresholding methods. These results include misclassification error accuracy (88%), non-uniformity accuracy (89%), and the accuracy of region's area error (89%). PMID:23724370

  14. Facial skin segmentation using bacterial foraging optimization algorithm.

    PubMed

    Bakhshali, Mohamad Amin; Shamsi, Mousa

    2012-10-01

    Nowadays, analyzing human facial image has gained an ever-increasing importance due to its various applications. Image segmentation is required as a very important and fundamental operation for significant analysis and interpretation of images. Among the segmentation methods, image thresholding technique is one of the most well-known methods due to its simplicity, robustness, and high precision. Thresholding based on optimization of the objective function is among the best methods. Numerous methods exist for the optimization process and bacterial foraging optimization (BFO) is among the most efficient and novel ones. Using this method, optimal threshold is extracted and then segmentation of facial skin is performed. In the proposed method, first, the color facial image is converted from RGB color space to Improved Hue-Luminance-Saturation (IHLS) color space, because IHLS has a great mapping of the skin color. To perform thresholding, the entropy-based method is applied. In order to find the optimum threshold, BFO is used. In order to analyze the proposed algorithm, color images of the database of Sahand University of Technology of Tabriz, Iran were used. Then, using Otsu and Kapur methods, thresholding was performed. In order to have a better understanding from the proposed algorithm; genetic algorithm (GA) is also used for finding the optimum threshold. The proposed method shows the better results than other thresholding methods. These results include misclassification error accuracy (88%), non-uniformity accuracy (89%), and the accuracy of region's area error (89%).

  15. Support for context effects on segmentation and segments depends on the context.

    PubMed

    Heffner, Christopher C; Newman, Rochelle S; Idsardi, William J

    2017-04-01

    Listeners must adapt to differences in speech rate across talkers and situations. Speech rate adaptation effects are strong for adjacent syllables (i.e., proximal syllables). For studies that have assessed adaptation effects on speech rate information more than one syllable removed from a point of ambiguity in speech (i.e., distal syllables), the difference in strength between different types of ambiguity is stark. Studies of word segmentation have shown large shifts in perception as a result of distal rate manipulations, while studies of segmental perception have shown only weak, or even nonexistent, effects. However, no study has standardized methods and materials to study context effects for both types of ambiguity simultaneously. Here, a set of sentences was created that differed as minimally as possible except for whether the sentences were ambiguous to the voicing of a consonant or ambiguous to the location of a word boundary. The sentences were then rate-modified to slow down the distal context speech rate to various extents, dependent on three different definitions of distal context that were adapted from previous experiments, along with a manipulation of proximal context to assess whether proximal effects were comparable across ambiguity types. The results indicate that the definition of distal influenced the extent of distal rate effects strongly for both segments and segmentation. They also establish the presence of distal rate effects on word-final segments for the first time. These results were replicated, with some caveats regarding the perception of individual segments, in an Internet-based sample recruited from Mechanical Turk.

  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. 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.

  18. A Learning-Based Wrapper Method to Correct Systematic Errors in Automatic Image Segmentation: Consistently Improved Performance in Hippocampus, Cortex and Brain Segmentation

    PubMed Central

    Wang, Hongzhi; Das, Sandhitsu R.; Suh, Jung Wook; Altinay, Murat; Pluta, John; Craige, Caryne; Avants, Brian; Yushkevich, Paul A.

    2011-01-01

    We propose a simple but generally applicable approach to improving the accuracy of automatic image segmentation algorithms relative to manual segmentations. The approach is based on the hypothesis that a large fraction of the errors produced by automatic segmentation are systematic, i.e., occur consistently from subject to subject, and serves as a wrapper method around a given host segmentation method. The wrapper method attempts to learn the intensity, spatial and contextual patterns associated with systematic segmentation errors produced by the host method on training data for which manual segmentations are available. The method then attempts to correct such errors in segmentations produced by the host method on new images. One practical use of the proposed wrapper method is to adapt existing segmentation tools, without explicit modification, to imaging data and segmentation protocols that are different from those on which the tools were trained and tuned. An open-source implementation of the proposed wrapper method is provided, and can be applied to a wide range of image segmentation problems. The wrapper method is evaluated with four host brain MRI segmentation methods: hippocampus segmentation using FreeSurfer (Fischl et al., 2002); hippocampus segmentation using multi-atlas label fusion (Artaechevarria et al., 2009); brain extraction using BET (Smith, 2002); and brain tissue segmentation using FAST (Zhang et al., 2001). The wrapper method generates 72%, 14%, 29% and 21% fewer erroneously segmented voxels than the respective host segmentation methods. In the hippocampus segmentation experiment with multi-atlas label fusion as the host method, the average Dice overlap between reference segmentations and segmentations produced by the wrapper method is 0.908 for normal controls and 0.893 for patients with mild cognitive impairment. Average Dice overlaps of 0.964, 0.905 and 0.951 are obtained for brain extraction, white matter segmentation and gray matter

  19. Selection of small color palette for color image quantization

    NASA Astrophysics Data System (ADS)

    Chau, Wing K.; Wong, S. K. M.; Yang, Xuedong; Wan, Shijie J.

    1992-05-01

    Two issues are involved in color image quantization: color palette selection and color mapping. A common practice for color palette selection is to minimize the color distortion for each pixel (the median-cut, the variance-based and the k-means algorithms). After the color palette has been chosen, a quantized image may be generated by mapping the original color of each pixel onto its nearest color in the color palette. Such an approach can usually produce quantized images of high quality with 128 or more colors. For 32 - 64 colors, the quality of the quantized images is often acceptable with the aid of dithering techniques in the color mapping process. For 8 - 16 color, however, the above statistical method for color selection becomes no longer suitable because of the great reduction of color gamut. In order to preserve the color gamut of the original image, one may want to select the colors in such a way that the convex hull formed by these colors in the RGB color space encloses most colors of the original image. Quantized images generated in such a geometrical way usually preserve a lot of image details, but may contain too much high frequency noises. This paper presents an effective algorithm for the selection of very small color palette by combining the strengths of the above statistical and geometrical approaches. We demonstrate that with the new method images of high quality can be produced by using only 4 to 8 colors.

  20. 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

  1. 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.

  2. Keypoint Transfer Segmentation.

    PubMed

    Wachinger, C; 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.

  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. Active Mask Segmentation of Fluorescence Microscope Images

    PubMed Central

    Srinivasa, Gowri; Fickus, Matthew C.; Guo, Yusong; Linstedt, Adam D.; Kovačević, Jelena

    2009-01-01

    We propose a new active mask algorithm for the segmentation of fluorescence microscope images of punctate patterns. It combines the (a) flexibility offered by active-contour methods, (b) speed offered by multiresolution methods, (c) smoothing offered by multiscale methods, and (d) statistical modeling offered by region-growing methods into a fast and accurate segmentation tool. The framework moves from the idea of the “contour” to that of “inside and outside”, or, masks, allowing for easy multidimensional segmentation. It adapts to the topology of the image through the use of multiple masks. The algorithm is almost invariant under initialization, allowing for random initialization, and uses a few easily tunable parameters. Experiments show that the active mask algorithm matches the ground truth well, and outperforms the algorithm widely used in fluorescence microscopy, seeded watershed, both qualitatively as well as quantitatively. PMID:19380268

  5. Segmented ion thruster

    NASA Technical Reports Server (NTRS)

    Brophy, John R. (Inventor)

    1993-01-01

    Apparatus and methods for large-area, high-power ion engines comprise dividing a single engine into a combination of smaller discharge chambers (or segments) configured to operate as a single large-area engine. This segmented ion thruster (SIT) approach enables the development of 100-kW class argon ion engines for operation at a specific impulse of 10,000 s. A combination of six 30-cm diameter ion chambers operating as a single engine can process over 100 kW. Such a segmented ion engine can be operated from a single power processor unit.

  6. Chromatic settings and the structural color constancy index.

    PubMed

    Roca-Vila, Jordi; Parraga, C Alejandro; Vanrell, Maria

    2013-03-11

    Color constancy is usually measured by achromatic setting, asymmetric matching, or color naming paradigms, whose results are interpreted in terms of indexes and models that arguably do not capture the full complexity of the phenomenon. Here we propose a new paradigm, chromatic setting, which allows a more comprehensive characterization of color constancy through the measurement of multiple points in color space under immersive adaptation. We demonstrated its feasibility by assessing the consistency of subjects' responses over time. The paradigm was applied to two-dimensional (2-D) Mondrian stimuli under three different illuminants, and the results were used to fit a set of linear color constancy models. The use of multiple colors improved the precision of more complex linear models compared to the popular diagonal model computed from gray. Our results show that a diagonal plus translation matrix that models mechanisms other than cone gain might be best suited to explain the phenomenon. Additionally, we calculated a number of color constancy indices for several points in color space, and our results suggest that interrelations among colors are not as uniform as previously believed. To account for this variability, we developed a new structural color constancy index that takes into account the magnitude and orientation of the chromatic shift in addition to the interrelations among colors and memory effects.

  7. 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.

  8. Multi-segment coherent beam combining

    SciTech Connect

    Neal, D.R.; Tucker, S.D.; Morgan, R.; Smith, T.G.; Warren, M.E.; Gruetzner, J.K.; Rosenthal, R.R.; Bentley, A.E.

    1994-12-31

    Scaling laser systems to large sizes for power beaming and other applications can sometimes be simplified by combing a number of smaller lasers. However, to fully utilize this scaling, coherent beam combination is necessary. This requires measuring and controlling each beam`s pointing and phase relative to adjacent beams using an adaptive optical system. We have built a sub-scale brass-board to evaluate various methods for beam-combining. It includes a segmented adaptive optic and several different specialized wavefront sensors that are fabricated using diffractive optics methods. We have evaluated a number of different phasing algorithms, including hierarchical and matrix methods, and have demonstrated phasing of several elements. The system is currently extended to a large number of segments to evaluate various scaling methodologies.

  9. 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.

  10. True Colors of Mars

    NASA Technical Reports Server (NTRS)

    2004-01-01

    This image taken on Mars by the panoramic camera on the Mars Exploration Rover Spirit shows the rover's color calibration target, also known as the MarsDial. The target's mirror and the shadows cast on it by the Sun help scientists determine the degree to which dusty martian skies alter the panoramic camera's perception of color. By adjusting for this effect, Mars can be seen in all its true colors.

  11. Accurate spectral color measurements

    NASA Astrophysics Data System (ADS)

    Hiltunen, Jouni; Jaeaeskelaeinen, Timo; Parkkinen, Jussi P. S.

    1999-08-01

    Surface color measurement is of importance in a very wide range of industrial applications including paint, paper, printing, photography, textiles, plastics and so on. For a demanding color measurements spectral approach is often needed. One can measure a color spectrum with a spectrophotometer using calibrated standard samples as a reference. Because it is impossible to define absolute color values of a sample, we always work with approximations. The human eye can perceive color difference as small as 0.5 CIELAB units and thus distinguish millions of colors. This 0.5 unit difference should be a goal for the precise color measurements. This limit is not a problem if we only want to measure the color difference of two samples, but if we want to know in a same time exact color coordinate values accuracy problems arise. The values of two instruments can be astonishingly different. The accuracy of the instrument used in color measurement may depend on various errors such as photometric non-linearity, wavelength error, integrating sphere dark level error, integrating sphere error in both specular included and specular excluded modes. Thus the correction formulas should be used to get more accurate results. Another question is how many channels i.e. wavelengths we are using to measure a spectrum. It is obvious that the sampling interval should be short to get more precise results. Furthermore, the result we get is always compromise of measuring time, conditions and cost. Sometimes we have to use portable syste or the shape and the size of samples makes it impossible to use sensitive equipment. In this study a small set of calibrated color tiles measured with the Perkin Elmer Lamda 18 and the Minolta CM-2002 spectrophotometers are compared. In the paper we explain the typical error sources of spectral color measurements, and show which are the accuracy demands a good colorimeter should have.

  12. MonoColor CMOS sensor

    NASA Astrophysics Data System (ADS)

    Wang, Ynjiun P.

    2009-02-01

    A new breed of CMOS color sensor called MonoColor sensor is developed for a barcode reading application in AIDC industry. The RGBW color filter array (CFA) in a MonoColor sensor is arranged in a 8 x 8 pixels CFA with only 4 pixels of them are color (RGB) pixels and the rest of 60 pixels are transparent or monochrome. Since the majority of pixels are monochrome, MonoColor sensor maintains 98% barcode decode performance compared with a pure monochrome CMOS sensor. With the help of monochrome and color pixel fusion technique, the resulting color pictures have similar color quality in terms of Color Semantic Error (CSE) compared with a Bayer pattern (RGB) CMOS color camera. Since monochrome pixels are more sensitive than color pixels, a MonoColor sensor produces in general about 2X brighter color picture and higher luminance pixel resolution.

  13. Segmentation by depth does not always facilitate visual search.

    PubMed

    Finlayson, Nonie J; Remington, Roger W; Retell, James D; Grove, Philip M

    2013-07-11

    In visual search, target detection times are relatively insensitive to set size when targets and distractors differ on a single feature dimension. Search can be confined to only those elements sharing a single feature, such as color (Egeth, Virzi, & Garbart, 1984). These findings have been taken as evidence that elementary feature dimensions support a parallel segmentation of a scene into discrete sets of items. Here we explored if relative depth (signaled by binocular disparity) could support a similar parallel segmentation by examining the effects of distributing distracting elements across two depth planes. Three important empirical findings emerged. First, when the target was a feature singleton on the target depth plane, but a conjunction search among distractors on the nontarget plane, search efficiency increased compared to a single depth plane. Second, benefits of segmentation in depth were only observed when the target depth plane was known in advance. Third, no benefit of segmentation in depth was observed when both planes required a conjunction search, even with prior knowledge of the target depth plane. Overall, the benefit of distributing the elements of a search set across two depth planes was observed only when the two planes differed both in binocular disparity and in the elementary feature composition of individual elements. We conclude that segmentation of the search array into two depth planes can facilitate visual search, but unlike color or other elementary properties, does not provide an automatic, preattentive 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.

  15. The Colors of 'Endurance'

    NASA Technical Reports Server (NTRS)

    2004-01-01

    This false-color image shows visible mineral changes between the materials that make up the rim of the impact crater known as 'Endurance.' The image was taken by the panoramic camera on NASA's Mars Exploration Rover Opportunity using all 13 color filters. The cyan blue color denotes basalts, whereas the dark green color denotes a mixture of iron oxide and basaltic materials. Reds and yellows indicate dusty material containing sulfates. Scientists are very interested in exploring the interior and exterior material around the crater's rim for clues to the processes that formed the crater, as well as the rocks and textures that define the crater.

  16. Universality of color names.

    PubMed

    Lindsey, Delwin T; Brown, Angela M

    2006-10-31

    We analyzed the World Color Survey (WCS) color-naming data set by using k-means cluster and concordance analyses. Cluster analysis relied on a similarity metric based on pairwise Pearson correlation of the complete chromatic color-naming patterns obtained from individual WCS informants. When K, the number of k-means clusters, varied from 2 to 10, we found that (i) the average color-naming patterns of the clusters all glossed easily to single or composite English patterns, and (ii) the structures of the k-means clusters unfolded in a hierarchical way that was reminiscent of the Berlin and Kay sequence of color category evolution. Gap statistical analysis showed that 8 was the optimal number of WCS chromatic categories: RED, GREEN, YELLOW-OR-ORANGE, BLUE, PURPLE, BROWN, PINK, and GRUE (GREEN-OR-BLUE). Analysis of concordance in color naming within WCS languages revealed small regions in color space that exhibited statistically significantly high concordance across languages. These regions agreed well with five of six primary focal colors of English. Concordance analysis also revealed boundary regions of statistically significantly low concordance. These boundary regions coincided with the boundaries associated with English WARM and COOL. Our results provide compelling evidence for similarities in the mechanisms that guide the lexical partitioning of color space among WCS languages and English.

  17. 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

  18. CPCs with segmented absorbers

    SciTech Connect

    Keita, M.; Robertson, H.S. )

    1991-01-01

    One of the most promising means of improving the performance of solar thermal collectors is to reduce the energy lost by the hot absorber. One way to do this, not currently part of the technology, is to recognize that since the absorber is usually not irradiated uniformly, it is therefore possible to construct an absorber of thermally isolated segments, circulate the fluid in sequence from low to high irradiance segments, and reduce loss by improving effective concentration. This procedure works even for ideal concentrators, without violating Winston's theorem. Two equivalent CPC collectors with single and segmented absorber were constructed and compared under actual operating conditions. The results showed that the daily thermal efficiency of the collector with segmented absorber is higher (about 13%) than that of the collector with nonsegmented absorber.

  19. 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…

  20. GPS Control Segment Improvements

    DTIC Science & Technology

    2015-04-29

    Systems Center GPS Control Segment Improvements Mr. Tim McIntyre GPS Product Support Manager GPS Ops Support and Sustainment Division Peterson...hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and...DATE 29 APR 2015 2. REPORT TYPE 3. DATES COVERED 00-00-2015 to 00-00-2015 4. TITLE AND SUBTITLE GPS Control Segment Improvements 5a. CONTRACT

  1. 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.

  2. 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.

  3. 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.

  4. Saliency region selection in large aerial imagery using multiscale SLIC segmentation

    NASA Astrophysics Data System (ADS)

    Sahli, Samir; Lavigne, Daniel A.; Sheng, Yunlong

    2012-06-01

    Advents in new sensing hardwares like GigE-cameras and fast growing data transmission capability create an imbalance between the amount of large scale aerial imagery and the means at disposal for treating them. Selection of saliency regions can reduce significantly the prospecting time and computation cost for the detection of objects in large scale aerial imagery. We propose a new approach using multiscale Simple Linear Iterative Clustering (SLIC) technique to compute the saliency regions. The SLIC is fast to create compact and uniform superpixels, based on the distances in both color and geometric spaces. When a salient structure of the object is over-segmented by the SLIC, a number of superpixels will follow the edges in the structure and therefore acquires irregular shapes. Thus, the superpixels deformation betrays presence of salient structures. We quantify the non-compactness of the superpixels as a salience measure, which is computed using the distance transform and the shape factor. To treat objects or object details of various sizes in an image, or the multiscale images, we compute the SLIC segmentations and the salient measures at multiple scales with a set of predetermined sizes of the superpixels. The final saliency map is a sum of the salience measures obtained at multiple scales. The proposed approach is fast, requires no input of user-defined parameter, produces well defined salient regions at full resolution and adapted to multi-scale image processing.

  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. The diversity of male nuptial coloration leads to species diversity in Lake Victoria cichlids.

    PubMed

    Miyagi, Ryutaro; Terai, Yohey

    2013-01-01

    The amazing coloration shown by diverse cichlid fish not only fascinates aquarium keepers, but also receives great attention from biologists interested in speciation because of its recently-revealed role in their adaptive radiation in an African lake. We review the important role of coloration in the speciation and adaptive evolution of Lake Victoria cichlids, which have experienced adaptive radiation during a very short evolutionary period. Mature male cichlids display their colors during mate choice. The color of their skin reflects light, and the reflected light forms a color signal that is received by the visual system of females. The adaptive divergence of visual perceptions shapes and diverges colorations, to match the adapted visual perceptions. The divergence of visual perception and coloration indicates that the divergence of color signals causes reproductive isolation between species, and this process leads to speciation. Differences in color signals among coexisting species act to maintain reproductive isolation by preventing hybridization. Thus, the diversity of coloration has caused speciation and has maintained species diversity in Lake Victoria cichlids.

  8. 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…

  9. 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…

  10. Color: an exosomatic organ?

    NASA Astrophysics Data System (ADS)

    van Brakel, Jaap; Saunders, Barbara

    2001-12-01

    According to the dominant view in cognitive science, in particular in its more popularized versions, color sensings or perceptions are located in a 'quality space'. This space has three dimensions: hue (the chromatic aspect of color), saturation (the 'intensity' of hue), and brightness. This space is structured further via a small number of primitive hues or landmark colors, usually four (red, yellow, green, blue) or six (if white and black are included). It has also been suggested that there are eleven semantic universals - the six colors previously mentioned plus orange, pink, brown, purple, and grey. Scientific evidence for these widely accepted theories is at best minimal, based on sloppy methodology and at worst non-existent. Against the standard view, it is argued that color might better be regarded as the outcome of a social-historical developmental trajectory in which there is mutual shaping of philosophical presuppositions, scientific theories, experimental practices, technological tools, industrial products, rhetorical frameworks, and their intercalated and recursive interactions with the practices of daily life. That is: color, the domain of color, is the outcome of interactive processes of scientific, instrumental, industrial, and everyday lifeworlds. That is: color might better be called an exosomatic organ, a second nature.

  11. A Semester of Color

    ERIC Educational Resources Information Center

    Rabinovitch, Andrea

    2006-01-01

    Every Thursday evening, ten high school students meet at the Riverdale Art Project, a New York City-based art program that the author co-founded ten years ago. Students are participating in a semester-long color workshop where they learn about color theory in a structured and engaging way. Focusing on five essential characteristics of color…

  12. 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…

  13. 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.

  14. Disabled Students of Color.

    ERIC Educational Resources Information Center

    Frank, Zelma Lloyd; Ball-Brown, Brenda

    1993-01-01

    Explores why few disabled students of color use student services. Details why some of these students were unnecessarily placed in special education programs and focuses on the experiences of this group. Addresses general cultural differences that can affect responses between people of color and disability services. Provides guidelines for service…

  15. Plasmonic color tuning

    NASA Astrophysics Data System (ADS)

    Lee, Byoungho; Yun, Hansik; Lee, Seung-Yeol; Kim, Hwi

    2016-03-01

    In general, color filter is an optical component to permit the transmission of a specific color in cameras, displays, and microscopes. Each filter has its own unchangeable color because it is made by chemical materials such as dyes and pigments. Therefore, in order to express various colorful images in a display, one pixel should have three sub-pixels of red, green, and blue colors. Here, we suggest new plasmonic structure and method to change the color in a single pixel. It is comprised of a cavity and a metal nanoaperture. The optical cavity generally supports standing waves inside it, and various standing waves having different wavelength can be confined together in one cavity. On the other hand, although light cannot transmit sub-wavelength sized aperture, surface plasmons can propagate through the metal nanoaperture with high intensity due to the extraordinary transmission. If we combine the two structures, we can organize the spatial distribution of amplitudes according to wavelength of various standing waves using the cavity, and we can extract a light with specific wavelength and amplitude using the nanoaperture. Therefore, this cavity-aperture structure can simultaneously tune the color and intensity of the transmitted light through the single nanoaperture. We expect that the cavity-apertures have a potential for dynamic color pixels, micro-imaging system, and multiplexed sensors.

  16. 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…

  17. TOCM digital color photography

    NASA Astrophysics Data System (ADS)

    Zhang, Baoying; Mu, Guoguang; Fang, Zhiliang; Li, Zhengqun; Fang, Hui; Yang, Yong

    2009-11-01

    In this paper, total optical color modulator (TOCM) digital color photography is presented. TOCM has the character of multi-wave superposed in spatial domain and separated in frequency domain. If TOCM is close-contacted with the image plane of a black-and-white (B&W) CCD, the encoding B&W CCD is formed. Image from the encoding B&W CCD are digital encoded by the TOCM. The decoded color image can be obtained by computer program. The program includes four main steps. The first step is Fourier transforming of the encoded image. The second step is filtering the spectra of the first and zero order in frequency domain. The third is inverse Fourier transforming of the filtered spectra. The last is melting the image with zero order. Then the digital color image will be shown on the display of the computer. The experiment proves that this technique is feasible. The principle of encoding color information in B&W image can be applied to color-blind sensors to get digital color image. Furthermore, it can be applied to digital multi-spectra color photography.

  18. 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.

  19. Selective Pressures Explain Differences in Flower Color among Gentiana lutea Populations

    PubMed Central

    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. PMID:26172378

  20. Image color reduction method for color-defective observers using a color palette composed of 20 particular colors

    NASA Astrophysics Data System (ADS)

    Sakamoto, Takashi

    2015-01-01

    This study describes a color enhancement method that uses a color palette especially designed for protan and deutan defects, commonly known as red-green color blindness. The proposed color reduction method is based on a simple color mapping. Complicated computation and image processing are not required by using the proposed method, and the method can replace protan and deutan confusion (p/d-confusion) colors with protan and deutan safe (p/d-safe) colors. Color palettes for protan and deutan defects proposed by previous studies are composed of few p/d-safe colors. Thus, the colors contained in these palettes are insufficient for replacing colors in photographs. Recently, Ito et al. proposed a p/dsafe color palette composed of 20 particular colors. The author demonstrated that their p/d-safe color palette could be applied to image color reduction in photographs as a means to replace p/d-confusion colors. This study describes the results of the proposed color reduction in photographs that include typical p/d-confusion colors, which can be replaced. After the reduction process is completed, color-defective observers can distinguish these confusion colors.

  1. 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.

  2. Color spaces for color-gamut mapping

    NASA Astrophysics Data System (ADS)

    McCann, John J.

    1999-10-01

    Before doing extensive color gamut experiments, we wanted to test the uniformity of CIE L*a*b*. This paper shows surprisingly large discrepancies between CIE L*a*b* and isotropic observation-based color spaces, such as Munsell: (1) L*a*b* chroma exaggerate yellows and underestimate blues. (2) The average discrepancy between L*a*b* and ideal is 27%. (3) Chips with identical L*a*b* hue angles are not the same color. L*a*b* introduces errors larger than many gamut mapping corrections. We have isotropic data in the Munsell Book. Computers allow 3D lookup tables to convert instantly any measured L*a*b* to interpolated Munsell Book values. We call this space ML, Ma, and Mb in honor of Munsell. LUTs have been developed for both LabtoMLab and MLabtoLab. With this zero-error, isotropic space we can return our attention to the original problem of color-gamut image processing.

  3. Color vision and dentistry.

    PubMed

    Wasson, W; Schuman, N

    1992-05-01

    Color vision is a critical component of restorative and esthetic dentistry, but dentists, as a group, do not have their color vision tested at any time during their careers. A study was undertaken to ascertain the color-vision status of practicing dental personnel at the University of Tennessee, College of Dentistry. One hundred fifty individuals, 75 men and 75 women, were screened. The results corroborated the existing medical data for the general population. It was found that 9.3% of the men and none of the women exhibited color-vision defect. Since most dentists are male, this study demonstrates an area of potential weakness for some practitioners. Once a color-vision problem is found, it is simple to remedy by employing a team approach to shade matching or mechanical means of matching shades (by the practitioner). No ethnic or racial distinctions were detected, although these have been reported in other studies.

  4. Green tagging in displaying color Doppler aliasing: a comparison to standard color mapping in renal artery stenosis.

    PubMed

    Gao, Jing; Mennitt, Kevin; Belfi, Lily; Zheng, Yuan-Yi; Chen, Zong; Rubin, Jonathan M

    2013-11-01

    To quantitatively assess the contrast-to-noise ratio (CNR) of green tagging and standard color flow images in displaying fast flow velocity, we retrospectively reviewed 20 cases of hemodynamically significant renal artery stenosis (RAS) detected by renal color Doppler ultrasound and confirmed with digital subtraction angiography. At the site of RAS, blood flow with high velocity that appeared as aliasing on color flow images was computationally analyzed with both green tagging and standard color mapping. To assess the difference in the CNR between normal background flow and the aliased signal as a function of visualizing aliasing between the two color mappings, we used GetColorpixels (Chongqing Medical University, Chongqing, China) to count the values in the color channels after segmenting color pixels from gray-scale pixels. We then calculated the CNR in each color channel-red, green, and blue (RGB)--in the aliasing region on green tagging and standard color mapping. The CNRs in the red, green and blue channels were 0.35 ± 0.44, 1.11 ± 0.41 and 0.51 ± 0.19, respectively, on standard color mapping, and 0.97 ± 0.80, 4.01 ± 1.36 and 0.64 ± 0.29, respectively, on green tagging. We used a single-factor analysis of variance and two-tailed t-test to assess the difference in CNR in each color channel between the two color mappings at the site of RAS. With these comparisons, there was no significant difference in the CNR in the red or blue channel between green tagging and standard color mapping (p > 0.05). However, there was a statistically significant difference in the CNR in the green channel between the two color mappings (p = 0.00019). Furthermore, the CNR measured in the green channel on the green tagging image was significantly higher than the CNRs in all other color channels on both color mapping images (p = 0.000). Hence, we conclude that green tagging has significantly higher visibility as a function of high-velocity flow than standard color mapping. The

  5. 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.

  6. Outer Space Research Helps Color Habitability in Earth Interiors

    NASA Technical Reports Server (NTRS)

    Haines, Richard F.

    1977-01-01

    Color is one of the most important elements in making an environment habitable. Both color and light level combine to create comfortable and efficient work areas and satisfying leisure time environments. Indeed, without light, color cannot even be experienced. It is vitally important for the designer to understand the subject of habitability and to know how to make a positive impact upon the habitability of spaces through the application of proven principles of color-design developed by the scientific community. Consider some of these possibilities and pitfalls: A color chosen in broad daylight will not appear the same under dim lighting conditions. If a designer were creating a dimly lit cocktail lounge, for example, there is little sense in using dark colors, which also tend to be more expensive. When the eyes have dark-adapted for even five minutes, any color reflecting 20 percent or less will appear black, and the color experience will be lost. Therefore, surface reflectances should be kept at least above 20 to 25 percent to maintain color where illumination is at low levels. In effect, for lower reflectance surfaces, higher levels of illumination are required to produce the most accurate color discriminability.

  7. 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.

  8. Segmented heterochromia in scalp hair.

    PubMed

    Yoon, Kyeong Han; Kim, Daehwan; Sohn, Seonghyang; Lee, Won Soo

    2003-12-01

    Segmented heterochromia of scalp hair is characterized by the irregularly alternating segmentation of hair into dark and light bands and is known to be associated with iron deficiency anemia. The authors report the case of an 11-year-old boy with segmented heterochromia associated with iron deficiency anemia. After 11 months of iron replacement, the boy's segmented heterochromic hair recovered completely.

  9. 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.

  10. Stool Color: When to Worry

    MedlinePlus

    ... to worry Yesterday, my stool color was bright green. Should I be concerned? Answers from Michael F. ... of colors. All shades of brown and even green are considered normal. Only rarely does stool color ...

  11. Interference Colors in Thin Films.

    ERIC Educational Resources Information Center

    Armstrong, H. L.

    1979-01-01

    Explains interference colors in thin films as being due to the removal, or considerable reduction, of a certain color by destructive inteference that results in the complementary color being seen. (GA)

  12. Shifts in color discrimination during early pregnancy.

    PubMed

    Orbán, Levente L; Dastur, Farhad N

    2012-05-25

    The present study explores two hypotheses: a) women during early pregnancy should experience increased color discrimination ability, and b) women during early pregnancy should experience shifts in subjective preference away from images of foods that appear either unripe or spoiled. Both of these hypotheses derive from an adaptive view of pregnancy sickness that proposes the function of pregnancy sickness is to decrease the likelihood of ingestion of foods with toxins or teratogens. Changes to color discrimination could be part of a network of perceptual and physiological defenses (e.g., changes to olfaction, nausea, vomiting) that support such a function. Participants included 13 pregnant women and 18 non-pregnant women. Pregnant women scored significantly higher than non-pregnant controls on the Farnsworth-Munsell (FM) 100 Hue Test, an objective test of color discrimination, although no difference was found between groups in preferences for food images at different stages of ripeness or spoilage. These results are the first indication that changes to color discrimination may occur during early pregnancy, and is consistent with the view that pregnancy sickness may function as an adaptive defense mechanism.

  13. [Pulmonary segmental mediolytic arteriopathy].

    PubMed

    Müller, A M; Kullmann, H J

    2006-03-01

    Segmental mediolytic arteriopathy (SMA) is defined as non-inflammatory arteriopathy with mediolysis due to segmental loss of media and consecutive formation of vascular gaps. Up to now, less than 40 cases of visceral and cerebral SMA and, to our knowledge, only one case of pulmonary SMA have been reported. We present the history of a 21 year old female patient, admitted to hospital with hemoptysis, but without other symptoms. Apart from two lesions in the sixth and tenth pulmonary segment, documented by CT and interpreted as colliquations, there were no other clinical and laboratory findings. Repeated bronchoscopy supplied no further information. Histomorphology of the resected lesion revealed SMA without evidence of vasculitis. Wegener's disease could be excluded. The aetiology of the disease is still unknown. Acute vasospasm (due to inappropriate reactions to catecholamine or endothelial dysfunction), as well as SMA as a precursor or subtype of fibromuscular dysplasia, are two theories still under discussion.

  14. 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.

  15. 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

  16. 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.

  17. Data compression experiments with LANDSAT thematic mapper and Nimbus-7 coastal zone color scanner data

    NASA Technical Reports Server (NTRS)

    Tilton, James C.; Ramapriyan, H. K.

    1989-01-01

    A case study is presented where an image segmentation based compression technique is applied to LANDSAT Thematic Mapper (TM) and Nimbus-7 Coastal Zone Color Scanner (CZCS) data. The compression technique, called Spatially Constrained Clustering (SCC), can be regarded as an adaptive vector quantization approach. The SCC can be applied to either single or multiple spectral bands of image data. The segmented image resulting from SCC is encoded in small rectangular blocks, with the codebook varying from block to block. Lossless compression potential (LDP) of sample TM and CZCS images are evaluated. For the TM test image, the LCP is 2.79. For the CZCS test image the LCP is 1.89, even though when only a cloud-free section of the image is considered the LCP increases to 3.48. Examples of compressed images are shown at several compression ratios ranging from 4 to 15. In the case of TM data, the compressed data are classified using the Bayes' classifier. The results show an improvement in the similarity between the classification results and ground truth when compressed data are used, thus showing that compression is, in fact, a useful first step in the analysis.

  18. Efficient thermal image segmentation through integration of nonlinear enhancement with unsupervised active contour model

    NASA Astrophysics Data System (ADS)

    Albalooshi, Fatema A.; Krieger, Evan; Sidike, Paheding; Asari, Vijayan K.

    2015-03-01

    Thermal images are exploited in many areas of pattern recognition applications. Infrared thermal image segmentation can be used for object detection by extracting regions of abnormal temperatures. However, the lack of texture and color information, low signal-to-noise ratio, and blurring effect of thermal images make segmenting infrared heat patterns a challenging task. Furthermore, many segmentation methods that are used in visible imagery may not be suitable for segmenting thermal imagery mainly due to their dissimilar intensity distributions. Thus, a new method is proposed to improve the performance of image segmentation in thermal imagery. The proposed scheme efficiently utilizes nonlinear intensity enhancement technique and Unsupervised Active Contour Models (UACM). The nonlinear intensity enhancement improves visual quality by combining dynamic range compression and contrast enhancement, while the UACM incorporates active contour evolutional function and neural networks. The algorithm is tested on segmenting different objects in thermal images and it is observed that the nonlinear enhancement has significantly improved the segmentation performance.

  19. Automatic backscatter analysis of regional left ventricular systolic function using color kinesis.

    PubMed

    Schwartz, S L; Cao, Q L; Vannan, M A; Pandian, N G

    1996-06-15

    Assessment of regional wall motion by 2-dimensional echocardiography can be performed by either semiquantitative wall motion scoring or by quantitative analysis. The former is subjective and requires expertise. Quantitative methods are too time-consuming for routine use in a busy clinical laboratory. Color kinesis is a new algorithm utilizing acoustic backscatter analysis. It provides a color encoded map of endocardial motion in real time. In each frame a new color layer is added; the thickness of the color beam represents endocardial motion during that frame. The end-systolic image has multiple color layers, representing regional and temporal heterogeneity of segmental motion. The purpose of this study was to validate the use of color kinesis for semiquantitative analysis of regional left ventricular systolic function and quantitatively in measurement of endocardial excursion. Semiquantitative wall motion scoring was performed in 18 patients using both 2-dimensional echo and color kinesis. Scoring was identical in 74% of segments; there was 84% agreement in definition of normal vs. abnormal. There was less interobserver variability in wall motion scoring using color kinesis. Endocardial excursion was quantified in 21 patients. 70% of the imaged segments were suitable for analysis. Correlation between 2-dimensional echocardiographic measurements and color kinesis was excellent, r = 0.87. The mean difference in excursion as measured by the 2 methods was -0.05 +/- 2.0 mm. In conclusion, color kinesis is a useful method for assessing regional contraction by displaying a color map of systolic endocardial excursion. This algorithm may improve the confidence and accuracy of assessment of segmental ventricular function by echocardiographic methods.

  20. Color universal design: analysis of color category dependency on color vision type (3)

    NASA Astrophysics Data System (ADS)

    Kojima, Natsuki; Ichihara, Yasuyo G.; Ikeda, Tomohiro; Kamachi, Miyuki G.; Ito, Kei

    2012-01-01

    We report on the results of a study investigating the color perception characteristics of people with red-green color confusion. We believe that this is an important step towards achieving Color Universal Design. In Japan, approximately 5% of men and 0.2% of women have red-green confusion. The percentage for men is higher in Europe and the United States; up to 8% in some countries. Red-green confusion involves a perception of colors different from normal color vision. Colors are used as a means of disseminating clear information to people; however, it may be difficult to convey the correct information to people who have red-green confusion. Consequently, colors should be chosen that minimize accidents and that promote more effective communication. In a previous survey, we investigated color categories common to each color vision type, trichromat (C-type color vision), protan (P-type color vision) and deuteran (D-type color vision). In the present study, first, we conducted experiments in order to verify a previous survey of C-type color vision and P-type color vision. Next, we investigated color difference levels within "CIE 1976 L*a*b*" (the CIELAB uniform color space), where neither C-type nor P-type color vision causes accidents under certain conditions (rain maps/contour line levels and graph color legend levels). As a result, we propose a common chromaticity of colors that the two color vision types are able to categorize by means of color names common to C-type color vision. We also offer a proposal to explain perception characteristics of color differences with normal color vision and red-green confusion using the CIELAB uniform color space. This report is a follow-up to SPIE-IS & T / Vol. 7528 7528051-8 and SPIE-IS & T /vol. 7866 78660J-1-8.

  1. Stork Color Proofing Technology

    NASA Astrophysics Data System (ADS)

    Ekman, C. Frederick

    1989-04-01

    For the past few years, Stork Colorproofing B.V. has been marketing an analog color proofing system in Europe based on electrophoto-graphic technology it pioneered for the purpose of high resolution, high fidelity color imaging in the field of the Graphic Arts. Based in part on this technology, it will make available on a commercial basis a digital color proofing system in 1989. Proofs from both machines will provide an exact reference for the user and will look, feel, and behave in a reproduction sense like the printed press sheet.

  2. Colors on Jupiter

    NASA Technical Reports Server (NTRS)

    Owen, T.; Terrile, R. J.

    1981-01-01

    The colors present in the clouds of Jupiter at the time of the Voyager encounters are described as they appear in high resolution images. It is shown that latitude, altitude and dwelltime are all critical factors in determining which colors appear where, although the identities of the responsible chromophores remain unestablished. Simultaneous ground-based 5 micron observations are used to determine the relative altitudes of the cloud systems which are characterized as white clouds, tawny clouds, dark brown cloud belts, and blue-grey hot spots in equatorial regions. Correlations between cloud color and certain latitudes have been maintained for decades, which suggests the importance of the internal energy source.

  3. Colors and contact dermatitis.

    PubMed

    Bonamonte, Domenico; Foti, Caterina; Romita, Paolo; Vestita, Michelangelo; Angelini, Gianni

    2014-01-01

    The diagnosis of skin diseases relies on several clinical signs, among which color is of paramount importance. In this review, we consider certain clinical presentations of both eczematous and noneczematous contact dermatitis in which color plays a peculiar role orientating toward the right diagnosis. The conditions that will be discussed include specific clinical-morphologic subtypes of eczematous contact dermatitis, primary melanocytic, and nonmelanocytic contact hyperchromia, black dermographism, contact chemical leukoderma, and others. Based on the physical, chemical, and biologic factors underlying a healthy skin color, the various skin shades drawing a disease picture are thoroughly debated, stressing their etiopathogenic origins and histopathologic aspects.

  4. 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.

  5. Overlapping image segmentation for context-dependent anomaly detection

    NASA Astrophysics Data System (ADS)

    Theiler, James; Prasad, Lakshman

    2011-06-01

    The challenge of finding small targets in big images lies in the characterization of the background clutter. The more homogeneous the background, the more distinguishable a typical target will be from its background. One way to homogenize the background is to segment the image into distinct regions, each of which is individually homogeneous, and then to treat each region separately. In this paper we will report on experiments in which the target is unspecified (it is an anomaly), and various segmentation strategies are employed, including an adaptive hierarchical tree-based scheme. We find that segmentations that employ overlap achieve better performance in the low false alarm rate regime.

  6. 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.

  7. 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.

  8. A new method for colors characterization of colored stainless steel using CIE and Munsell color systems

    NASA Astrophysics Data System (ADS)

    Ji, Keming; Xue, Yongqiang; Cui, Zixiang

    2015-09-01

    It is important to establish an accurate and comprehensive method of characterizing colors of colored stainless steel and understand the changing mechanism and the regularity of colors for the research, production and application of colored stainless steel. In this work, the method which combines reflectance-wavelength with both CIE and Munsell color systems is studied, the changing regularity of hue, brightness and saturation with increasing coloring potential differences is investigated, and the mechanism of color changing is discussed. The results show that by using this method the colors of colored stainless steel can be accurately and comprehensively characterized; with coloring potential differences and colored film thickness increasing, the peaks and troughs of the reflectance curves in visible region move toward long wave, causing the cyclically changing of hue and brightness; the amplitude of reflectance curves increases, resulting in growing of the saturation; the CIE 1931 coordinate curve of colors counterclockwise and cyclically changes around the equal energy light spot.

  9. Shadow detection in color aerial images based on HSI space and color attenuation relationship

    NASA Astrophysics Data System (ADS)

    Shi, Wenxuan; Li, Jie

    2012-12-01

    Many problems in image processing and computer vision arise from shadows in a single color aerial image. This article presents a new algorithm by which shadows are extracted from a single color aerial image. Apart from using the ratio value of the hue over the intensity in some state-of-the-art algorithms, this article introduces another ratio map, which is obtained by applying the saturation over the intensity. Candidate shadow and nonshadow regions are separated by applying Otus's thresholding method. The color attenuation relationship that describes the relationship between the attenuation of each color channel is derived from the Planck's blackbody irradiance law. For each region, the color attenuation relationship and other determination conditions are performed iteratively to segment it into smaller sub-regions and to identify whether each sub-region is a true shadow region. Compared with previous methods, the proposed algorithm presents better shadow detection accuracy in the images that contain some dark green lawn, river, or low brightness shadow regions. The experimental results demonstrate the advantage of the proposed algorithm.

  10. Impact of Multiscale Retinex Computation on Performance of Segmentation Algorithms

    NASA Technical Reports Server (NTRS)

    Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.; Hines, Glenn D.

    2004-01-01

    Classical segmentation algorithms subdivide an image into its constituent components based upon some metric that defines commonality between pixels. Often, these metrics incorporate some measure of "activity" in the scene, e.g. the amount of detail that is in a region. The Multiscale Retinex with Color Restoration (MSRCR) is a general purpose, non-linear image enhancement algorithm that significantly affects the brightness, contrast and sharpness within an image. In this paper, we will analyze the impact the MSRCR has on segmentation results and performance.

  11. Interactive image segmentation by constrained spectral graph partitioning

    NASA Astrophysics Data System (ADS)

    Zhang, Hao; He, Jin; Zhang, Hong; Huang, Zhanhua

    2010-11-01

    This paper proposed an interactive image segmentation algorithm that can tolerate slightly incorrect user constraints. Interactive image segmentation was formulated as a constrained spectral graph partitioning problem. Furthermore, it was proven to equal to a supervised classification problem, where the feature space was formed by rows of the eigenvector matrix that was computed by spectral graph analysis. ν-SVM (support vector machine) was preferred as the classifier. Some incorrect labels in user constraints were tolerated by being identified as margin errors in ν-SVM. Comparison with other algorithms on real color images was reported.

  12. 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.

  13. Image segmentation using trainable fuzzy set classifiers

    NASA Astrophysics Data System (ADS)

    Schalkoff, Robert J.; Carver, Albrecht E.; Gurbuz, Sabri

    1999-07-01

    A general image analysis and segmentation method using fuzzy set classification and learning is described. The method uses a learned fuzzy representation of pixel region characteristics, based upon the conjunction and disjunction of extracted and derived fuzzy color and texture features. Both positive and negative exemplars of some visually apparent characteristic which forms the basis of the inspection, input by a human operator, are used together with a clustering algorithm to construct positive similarity membership functions and negative similarity membership functions. Using these composite fuzzified images, P and N, are produced using fuzzy union. Classification is accomplished via image defuzzification, whereby linguistic meaning is assigned to each pixel in the fuzzy set using a fuzzy inference operation. The technique permits: (1) strict color and texture discrimination, (2) machine learning of color and texture characteristics of regions, (3) and judicious labeling of each pixel based upon leaned fuzzy representation and fuzzy classification. This approach appears ideal for applications involving visual inspection and allows the development of image-based inspection systems which may be trained and used by relatively unskilled workers. We show three different examples involving the visual inspection of mixed waste drums, lumber and woven fabric.

  14. Demosaicking algorithm for the Kodak-RGBW color filter array

    NASA Astrophysics Data System (ADS)

    Rafinazari, M.; Dubois, E.

    2015-01-01

    Digital cameras capture images through different Color Filter Arrays and then reconstruct the full color image. Each CFA pixel only captures one primary color component; the other primary components will be estimated using information from neighboring pixels. During the demosaicking algorithm, the two unknown color components will be estimated at each pixel location. Most of the demosaicking algorithms use the RGB Bayer CFA pattern with Red, Green and Blue filters. The least-Squares Luma-Chroma demultiplexing method is a state of the art demosaicking method for the Bayer CFA. In this paper we develop a new demosaicking algorithm using the Kodak-RGBW CFA. This particular CFA reduces noise and improves the quality of the reconstructed images by adding white pixels. We have applied non-adaptive and adaptive demosaicking method using the Kodak-RGBW CFA on the standard Kodak image dataset and the results have been compared with previous work.

  15. Cast segment evaluation

    NASA Technical Reports Server (NTRS)

    Diem, H. G.; Studhalter, W. R.

    1971-01-01

    Evaluation program to determine feasibility of fabricating segmented rocket engine thrust chambers using low cost, lightweight castings extends state of the art in areas of casting size and complexity, and in ability to provide thin sections and narrow, deep, cooling channels. Related developments are discussed.

  16. [Segmental testicular infarction].

    PubMed

    Ripa Saldías, L; Guarch Troyas, R; Hualde Alfaro, A; de Pablo Cárdenas, A; Ruiz Ramo, M; Pinós Paul, M

    2006-02-01

    We report the case of a 47 years old man previously diagnosed of left hidrocele. After having a recent mild left testicular pain, an ultrasonografic study revealed a solid hipoecoic testicular lesion rounded by a big hidrocele, suggesting a testicular neoplasm. Radical inguinal orchiectomy was made and pathologic study showed segmental testicular infarction. No malignancy was found. We review the literature of the topic.

  17. Segmentation and Impoverished Youth.

    ERIC Educational Resources Information Center

    Friedman, Judith J.; Friedman, Samuel R.

    1986-01-01

    The following characteristics of jobs held by impoverished youth who applied for a job training program were examined: (1) benefits; (2) skills; (3) career ladders; and (4) unionization. Results imply that segmentation models are not fruitful as guides to labor market experiences of youth at the bottom of wage scale. Other studies were also…

  18. Iterative color constancy with temporal filtering for an image sequence with no relative motion between the camera and the scene.

    PubMed

    Simão, Josemar; Jörg Andreas Schneebeli, Hans; Vassallo, Raquel Frizera

    2015-11-01

    Color constancy is the ability to perceive the color of a surface as invariant even under changing illumination. In outdoor applications, such as mobile robot navigation or surveillance, the lack of this ability harms the segmentation, tracking, and object recognition tasks. The main approaches for color constancy are generally targeted to static images and intend to estimate the scene illuminant color from the images. We present an iterative color constancy method with temporal filtering applied to image sequences in which reference colors are estimated from previous corrected images. Furthermore, two strategies to sample colors from the images are tested. The proposed method has been tested using image sequences with no relative movement between the scene and the camera. It also has been compared with known color constancy algorithms such as gray-world, max-RGB, and gray-edge. In most cases, the iterative color constancy method achieved better results than the other approaches.

  19. Color Video Petrography.

    ERIC Educational Resources Information Center

    Nagle, Frederick

    1981-01-01

    Describes the production and use of color videocassettes with an inexpensive, conventional TV camera and an ordinary petrographic microscope. The videocassettes are used in optical mineralogy and petrology courses. (Author/WB)

  20. Copying and Coloring

    ERIC Educational Resources Information Center

    Kohl, Herb

    1977-01-01

    Investigates what appeals to students in using coloring books and whether they use them in imaginative ways. The intent was to use the information to develop creative book activities that interest and challenge students. (Author/RK)