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

    NASA Astrophysics Data System (ADS)

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

    2005-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

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

  4. Color image segmentation

    NASA Astrophysics Data System (ADS)

    McCrae, Kimberley A.; Ruck, Dennis W.; Rogers, Steven K.; Oxley, Mark E.

    1994-03-01

    The most difficult stage of automated target recognition is segmentation. Current segmentation problems include faces and tactical targets; previous efforts to segment these objects have used intensity and motion cues. This paper develops a color preprocessing scheme to be used with the other segmentation techniques. A neural network is trained to identify the color of a desired object, eliminating all but that color from the scene. Gabor correlations and 2D wavelet transformations will be performed on stationary images; and 3D wavelet transforms on multispectral data will incorporate color and motion detection into the machine visual system. The paper will demonstrate that color and motion cues can enhance a computer segmentation system. Results from segmenting faces both from the AFIT data base and from video taped television are presented; results from tactical targets such as tanks and airplanes are also given. Color preprocessing is shown to greatly improve the segmentation in most cases.

  5. Color image segmentation considering human sensitivity for color pattern variations

    NASA Astrophysics Data System (ADS)

    Yoon, Kuk-Jin; Kweon, In-So

    2001-10-01

    Color image segmentation plays an important role in the computer vision and image processing area. In this paper, we propose a novel color image segmentation algorithm in consideration of human visual sensitivity for color pattern variations by generalizing K-means clustering. Human visual system has different color perception sensitivity according to the spatial color pattern variation. To reflect this effect, we define the CCM (Color Complexity Measure) by calculating the absolute deviation with Gaussian weighting within the local mask and assign weight value to each color vector using the CCM values.

  6. 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.)

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

    NASA Astrophysics Data System (ADS)

    Hayasaka, Rina; Zhao, Jiying; Matsushita, Yutaka

    1997-10-01

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

  8. Adaptive Color Constancy Using Faces.

    PubMed

    Bianco, Simone; Schettini, Raimondo

    2014-08-01

    In this work we design an adaptive color constancy algorithm that, exploiting the skin regions found in faces, is able to estimate and correct the scene illumination. The algorithm automatically switches from global to spatially varying color correction on the basis of the illuminant estimations on the different faces detected in the image. An extensive comparison with both global and local color constancy algorithms is carried out to validate the effectiveness of the proposed algorithm in terms of both statistical and perceptual significance on a large heterogeneous data set of RAW images containing faces. PMID:26353334

  9. Adaptive color image watermarking algorithm

    NASA Astrophysics Data System (ADS)

    Feng, Gui; Lin, Qiwei

    2008-03-01

    As a major method for intellectual property right protecting, digital watermarking techniques have been widely studied and used. But due to the problems of data amount and color shifted, watermarking techniques on color image was not so widespread studied, although the color image is the principal part for multi-medium usages. Considering the characteristic of Human Visual System (HVS), an adaptive color image watermarking algorithm is proposed in this paper. In this algorithm, HSI color model was adopted both for host and watermark image, the DCT coefficient of intensity component (I) of the host color image was used for watermark date embedding, and while embedding watermark the amount of embedding bit was adaptively changed with the complex degree of the host image. As to the watermark image, preprocessing is applied first, in which the watermark image is decomposed by two layer wavelet transformations. At the same time, for enhancing anti-attack ability and security of the watermarking algorithm, the watermark image was scrambled. According to its significance, some watermark bits were selected and some watermark bits were deleted as to form the actual embedding data. The experimental results show that the proposed watermarking algorithm is robust to several common attacks, and has good perceptual quality at the same time.

  10. Adaptive image segmentation by quantization

    NASA Astrophysics Data System (ADS)

    Liu, Hui; Yun, David Y.

    1992-12-01

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

  11. Giant segmented adaptive mirrors: progress report

    NASA Astrophysics Data System (ADS)

    Riccardi, Armando; Biasi, Roberto; Brusa, Guido; Del Vecchio, Ciro; Esposito, Simone; Gallieni, Daniele; Salinari, Piero

    2003-01-01

    We show that the same technology developed for MMT and LBT Adaptive Secondary mirrors can be used for building segmented adaptive mirrors of essentially any size. This seems to be at the moment the most promising approach to provide the enormous number of degrees of freedom necessary for adaptive correction at visual wavelengths in giant telescopes. In this paper we recall the analytical formulation of the problem and we report recent numerical studies and initial experimental results obtained with prototype actuators for large adaptive segments.

  12. 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.

  13. An adaptive algorithm for motion compensated color image coding

    NASA Technical Reports Server (NTRS)

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

    1987-01-01

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

  14. Unsupervised color image segmentation using a lattice algebra clustering technique

    NASA Astrophysics Data System (ADS)

    Urcid, Gonzalo; Ritter, Gerhard X.

    2011-08-01

    In this paper we introduce a lattice algebra clustering technique for segmenting digital images in the Red-Green- Blue (RGB) color space. The proposed technique is a two step procedure. Given an input color image, the first step determines the finite set of its extreme pixel vectors within the color cube by means of the scaled min-W and max-M lattice auto-associative memory matrices, including the minimum and maximum vector bounds. In the second step, maximal rectangular boxes enclosing each extreme color pixel are found using the Chebychev distance between color pixels; afterwards, clustering is performed by assigning each image pixel to its corresponding maximal box. The two steps in our proposed method are completely unsupervised or autonomous. Illustrative examples are provided to demonstrate the color segmentation results including a brief numerical comparison with two other non-maximal variations of the same clustering technique.

  15. 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.

  16. Optimized mean shift algorithm for color segmentation in image sequences

    NASA Astrophysics Data System (ADS)

    Bailer, Werner; Schallauer, Peter; Haraldsson, Harald B.; Rehatschek, Herwig

    2005-03-01

    The application of the mean shift algorithm to color image segmentation has been proposed in 1997 by Comaniciu and Meer. We apply the mean shift color segmentation to image sequences, as the first step of a moving object segmentation algorithm. Previous work has shown that it is well suited for this task, because it provides better temporal stability of the segmentation result than other approaches. The drawback is higher computational cost. For speed up of processing on image sequences we exploit the fact that subsequent frames are similar and use the cluster centers of previous frames as initial estimates, which also enhances spatial segmentation continuity. In contrast to other implementations we use the originally proposed CIE LUV color space to ensure high quality segmentation results. We show that moderate quantization of the input data before conversion to CIE LUV has little influence on the segmentation quality but results in significant speed up. We also propose changes in the post-processing step to increase the temporal stability of border pixels. We perform objective evaluation of the segmentation results to compare the original algorithm with our modified version. We show that our optimized algorithm reduces processing time and increases the temporal stability of the segmentation.

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

    PubMed

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

    2016-02-01

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

  18. Color demosaicking via robust adaptive sparse representation

    NASA Astrophysics Data System (ADS)

    Huang, Lili; Xiao, Liang; Chen, Qinghua; Wang, Kai

    2015-09-01

    A single sensor camera can capture scenes by means of a color filter array. Each pixel samples only one of the three primary colors. We use a color demosaicking (CDM) technique to produce full color images and propose a robust adaptive sparse representation model for high quality CDM. The data fidelity term is characterized by l1 norm to suppress the heavy-tailed visual artifacts with an adaptively learned dictionary, while the regularization term is encouraged to seek sparsity by forcing sparse coding close to its nonlocal means to reduce coding errors. Based on the classical quadratic penalty function technique in optimization and an operator splitting method in convex analysis, we further present an effective iterative algorithm to solve the variational problem. The efficiency of the proposed method is demonstrated by experimental results with simulated and real camera data.

  19. Semi-Automated Segmentation of Microbes in Color Images

    NASA Astrophysics Data System (ADS)

    Reddy, Chandankumar K.; Liu, Feng-I.; Dazzo, Frank B.

    2003-01-01

    The goal of this work is to develop a system that can semi-automate the detection of multicolored foreground objects in digitized color images that also contain complex and very noisy backgrounds. Although considered a general problem of color image segmentation, our application is microbiology where various colored stains are used to reveal information on the microbes without cultivation. Instead of providing a simple threshold, the proposed system offers an interactive environment whereby the user chooses multiple sample points to define the range of color pixels comprising the foreground microbes of interest. The system then uses the color and spatial distances of these target points to segment the microbes from the confusing background of pixels whose RGB values lie outside the newly defined range and finally finds each cell's boundary using region-growing and mathematical morphology. Some other image processing methods are also applied to enhance the resultant image containing the colored microbes against a noise-free background. The prototype performs with 98% accuracy on a test set compared to ground truth data. The system described here will have many applications in image processing and analysis where one needs to segment typical pixel regions of similar but non-identical colors.

  20. Video rate color region segmentation for mobile robotic applications

    NASA Astrophysics Data System (ADS)

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

    2005-08-01

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

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

    PubMed

    Liu, Guoying; Zhang, Yun; Wang, Aimin

    2015-11-01

    Fuzzy c-means (FCM) clustering with spatial constraints has attracted great attention in the field of image segmentation. However, most of the popular techniques fail to resolve misclassification problems due to the inaccuracy of their spatial models. This paper presents a new unsupervised FCM-based image segmentation method by paying closer attention to the selection of local information. In this method, region-level local information is incorporated into the fuzzy clustering procedure to adaptively control the range and strength of interactive pixels. First, a novel dissimilarity function is established by combining region-based and pixel-based distance functions together, in order to enhance the relationship between pixels which have similar local characteristics. Second, a novel prior probability function is developed by integrating the differences between neighboring regions into the mean template of the fuzzy membership function, which adaptively selects local spatial constraints by a tradeoff weight depending upon whether a pixel belongs to a homogeneous region or not. Through incorporating region-based information into the spatial constraints, the proposed method strengthens the interactions between pixels within the same region and prevents over smoothing across region boundaries. Experimental results over synthetic noise images, natural color images, and synthetic aperture radar images show that the proposed method achieves more accurate segmentation results, compared with five state-of-the-art image segmentation methods. PMID:26186787

  2. Adaptive characterization method for desktop color printers

    NASA Astrophysics Data System (ADS)

    Shen, Hui-Liang; Zheng, Zhi-Huan; Jin, Chong-Chao; Du, Xin; Shao, Si-Jie; Xin, John H.

    2013-04-01

    With the rapid development of multispectral imaging technique, it is desired that the spectral color can be accurately reproduced using desktop color printers. However, due to the specific spectral gamuts determined by printer inks, it is almost impossible to exactly replicate the reflectance spectra in other media. In addition, as ink densities can not be individually controlled, desktop printers can only be regarded as red-green-blue devices, making physical models unfeasible. We propose a locally adaptive method, which consists of both forward and inverse models, for desktop printer characterization. In the forward model, we establish the adaptive transform between control values and reflectance spectrum on individual cellular subsets by using weighted polynomial regression. In the inverse model, we first determine the candidate space of the control values based on global inverse regression and then compute the optimal control values by minimizing the color difference between the actual spectrum and the predicted spectrum via forward transform. Experimental results show that the proposed method can reproduce colors accurately for different media under multiple illuminants.

  3. Automatic sputum color image segmentation for tuberculosis diagnosis

    NASA Astrophysics Data System (ADS)

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

    2001-11-01

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

  4. Color Video Segmentation by Dissimilarity Based on Edges

    NASA Astrophysics Data System (ADS)

    Ramos, Lucía; Novo, Jorge; Rouco, José; Mosquera, Antonio; Penedo, Manuel G.

    In this work new approaches are proposed to the extension to color-space of different shot change detection methods. These techniques are those ones that use the dissimilarity based on edges, in particular on space and frequency domains. They were previously defined to deal with grayscale videos, so the methods are redesigned to provide the best possible results in color-space videos. Moreover, some improvements are performed to obtain better results, as the use of an adaptative threshold instead of the fixed one previously used. Some experiments are presented to show the better behaviour of the new developed approaches.

  5. Epistatic Adaptive Evolution of Human Color Vision

    PubMed Central

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Hsiao, Yu-Zhe; Pei, Soo-Chang

    2014-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-10-01

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

  8. Adaptive synchronization and pinning control of colored networks

    NASA Astrophysics Data System (ADS)

    Wu, Zhaoyan; Xu, Xin-Jian; Chen, Guanrong; Fu, Xinchu

    2012-12-01

    A colored network model, corresponding to a colored graph in mathematics, is used for describing the complexity of some inter-connected physical systems. A colored network is consisted of colored nodes and edges. Colored nodes may have identical or nonidentical local dynamics. Colored edges between any pair of nodes denote not only the outer coupling topology but also the inner interactions. In this paper, first, synchronization of edge-colored networks is studied from adaptive control and pinning control approaches. Then, synchronization of general colored networks is considered. To achieve synchronization of a colored network to an arbitrarily given orbit, open-loop control, pinning control and adaptive coupling strength methods are proposed and tested, with some synchronization criteria derived. Finally, numerical examples are given to illustrate theoretical results.

  9. 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.

  10. 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.

  11. Color image segmentation using vector angle-based region growing

    NASA Astrophysics Data System (ADS)

    Wesolkowski, Slawo; Fieguth, Paul W.

    2002-06-01

    A new region growing color image segmentation algorithm is presented in this paper. This algorithm is invariant to highlights and shading. This is accomplished in two steps. First, the average pixel intensity is removed from each RGB coordinate. This transformation mitigates the effects of highlights. Next, region seeds are obtained using the Mixture of Principal Components algorithm. Each region is characterized using two parameters. The first is the distance between the region prototype and the candidate pixel. The second is the distance between the candidate pixel and its nearest neighbor in the region. The inner vector product or vector angle is used as the similarity measure which makes both of these measures shading invariant. Results on a real image illustrate the effectiveness of the method.

  12. Comparison of color image segmentations for lane following

    NASA Astrophysics Data System (ADS)

    Sandt, Frederic; Aubert, Didier

    1993-05-01

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

  13. 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.

  14. 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. PMID:25494514

  15. Optimal wavefront control for adaptive segmented mirrors

    NASA Technical Reports Server (NTRS)

    Downie, John D.; Goodman, Joseph W.

    1989-01-01

    A ground-based astronomical telescope with a segmented primary mirror will suffer image-degrading wavefront aberrations from at least two sources: (1) atmospheric turbulence and (2) segment misalignment or figure errors of the mirror itself. This paper describes the derivation of a mirror control feedback matrix that assumes the presence of both types of aberration and is optimum in the sense that it minimizes the mean-squared residual wavefront error. Assumptions of the statistical nature of the wavefront measurement errors, atmospheric phase aberrations, and segment misalignment errors are made in the process of derivation. Examples of the degree of correlation are presented for three different types of wavefront measurement data and compared to results of simple corrections.

  16. 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

  17. Color microscopy image segmentation using competitive learning and fuzzy Kohonen networks

    NASA Astrophysics Data System (ADS)

    Gaddipatti, Ajeetkumar; Vince, David G.; Cothren, Robert M., Jr.; Cornhill, J. Fredrick

    1998-06-01

    Over the past decade, there has been increased interest in quantifying cell populations in tissue sections. Image analysis is now being used for analysis in limited pathological applications, such as PAP smear evaluation, with the dual aim of increasing for accuracy of diagnosis and reducing the review time. These applications primarily used gray scale images and dealt with cytological smears in which cells were well separated. Quantification of routinely stained tissue represented a more difficult problem in that objects could not be separated in gray scale as part of the background could also have the same intensity as the objects of interest. Many of the existing semiautomatic algorithms were specific to a particular application and were computationally expensive. Hence, this paper investigates the general adaptive automated color segmentation approaches, which alleviate these problems. In particular, competitive learning and the fuzzy-kohonen networks are studied. Four adaptive segmentation algorithms are compared using synthetic images and clinical microscopy slide images. Both qualitative and quantitative performance comparisons are performed with the clinical images. A method for finding the optimal number of clusters in the image is also validated. Finally the merits and feasibility of including contextual information in the segmentation are discussed along with future directions.

  18. Approach to nonparametric cooperative multiband segmentation with adaptive threshold.

    PubMed

    Sebari, Imane; He, Dong-Chen

    2009-07-10

    We present a new nonparametric cooperative approach to multiband image segmentation. It is based on cooperation between region-growing segmentation and edge segmentation. This approach requires no input data other than the images to be processed. It uses a spectral homogeneity criterion whose threshold is determined automatically. The threshold is adaptive and varies depending on the objects to be segmented. Applying this new approach to very high resolution satellite imagery has yielded satisfactory results. The approach demonstrated its performance on images of varied complexity and was able to detect objects of great spatial and spectral heterogeneity. PMID:19593349

  19. 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.

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

    PubMed

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

  2. 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.

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

    PubMed

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

    2016-08-01

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

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

    PubMed Central

    Hillis, James M.; Brainard, David H.

    2009-01-01

    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. PMID:17621318

  5. The influence of contrast adaptation on color appearance.

    PubMed

    Webster, M A; Mollon, J D

    1994-08-01

    Most models of color vision assume that signals from the three classes of cone receptor are recoded into only three independent post-receptoral channels: one that encodes luminance and two that encode color. Stimuli that are equated for their effects on two of the channels should be discriminable only to the remaining channel, and are thus assumed to isolate the responses of single channels. We used an asymmetric matching task to examine whether such models can account for changes in color appearance following adaptation to contrast--to temporal variations in luminance and chromaticity around a fixed mean luminance and chromaticity. The experiments extend to suprathreshold color appearance the threshold adaptation paradigm of Krauskopf, Williams and Heeley [(1982) Vision Research, 32, 1123-1131]. Adaptation changes the perceived color of chromatic test stimuli both by reducing their saturation (contrast) and by changing their hue (direction within the equiluminant plane). The saturation losses are largest for test stimuli that lie along the chromatic axis defining the adapting modulation, while the hue changes are rotations away from the adapting direction and toward an orthogonal direction within the S and L-M plane. Similar selective changes in both perceived color and perceived lightness occur following adaptation to stimuli that covary in luminance and chromaticity. The selectivity of the aftereffects for multiple directions within color-luminance space is inconsistent with sensitivity changes in only three independent channels. These aftereffects suggest instead that color appearance depends on channels that can be selectively tuned to any color-luminance direction, and that there are no directions that invariably isolate responses in only a single channel. We use the perceived color changes to examine the spectral sensitivities of the chromatic channels and to estimate the distribution of channels. We also examine how adaptation alters the contrast

  6. Adaptation and the color statistics of natural images.

    PubMed

    Webster, M A; Mollon, J D

    1997-12-01

    Color perception depends profoundly on adaptation processes that adjust sensitivity in response to the prevailing pattern of stimulation. We examined how color sensitivity and appearance might be influenced by adaptation to the color distributions characteristic of natural images. Color distributions were measured for natural scenes by sampling an array of locations within each scene with a spectroradiometer, or by recording each scene with a digital camera successively through 31 interference filters. The images were used to reconstruct the L, M and S cone excitation at each spatial location, and the contrasts along three post-receptoral axes [L + M, L - M or S - (L + M)]. Individual scenes varied substantially in their mean chromaticity and luminance, in the principal color-luminance axes of their distributions, and in the range of contrasts in their distributions. Chromatic contrasts were biased along a relatively narrow range of bluish to yellowish-green angles, lying roughly between the S - (L + M) axis (which was more characteristic of scenes with lush vegetation and little sky) and a unique blue-yellow axis (which was more typical of arid scenes). For many scenes L - M and S - (L + M) signals were highly correlated, with weaker correlations between luminance and chromaticity. We use a two-stage model (von Kries scaling followed by decorrelation) to show how the appearance of colors may be altered by light adaptation to the mean of the distributions and by contrast adaptation to the contrast range and principal axes of the distributions; and we show that such adjustments are qualitatively consistent with empirical measurements of asymmetric color matches obtained after adaptation to successive random samples drawn from natural distributions of chromaticities and lightnesses. Such adaptation effects define the natural range of operating states of the visual system. PMID:9425544

  7. 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.

  8. 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

  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. Patterns of transfer of adaptation among body segments

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  11. 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.

  12. Video segmentation using spatial proximity, color, and motion information for region-based coding

    NASA Astrophysics Data System (ADS)

    Hong, Won H.; Kim, Nam Chul; Lee, Sang-Mi

    1994-09-01

    An efficient video segmentation algorithm with homogeneity measure to incorporate spatial proximity, color, and motion information simultaneously is presented for region-based coding. The procedure toward complete segmentation consists of two steps: primary segmentation, and secondary segmentation. In the primary segmentation, an input image is finely segmented by FSCL. In the secondary segmentation, a lot of small regions and similar regions generated in the preceding step are eliminated or merged by a fast RSST. Through some experiments, it is found that the proposed algorithm produces efficient segmentation results and the video coding system with this algorithm yields visually acceptable quality and PSNR equals 36 - 37 dB at a very low bitrate of about 13.2 kbits/s.

  13. Colored adaptive compressed imaging with a single photodiode.

    PubMed

    Yan, Yiyun; Dai, Huidong; Liu, Xingjiong; He, Weiji; Chen, Qian; Gu, Guohua

    2016-05-10

    Computational ghost imaging is commonly used to reconstruct grayscale images. Currently, however, there is little research aimed at reconstructing color images. In this paper, we theoretically and experimentally demonstrate a colored adaptive compressed imaging method. Benefiting from imaging in YUV color space, the proposed method adequately exploits the sparsity of the U, V components in the wavelet domain, the interdependence between luminance and chrominance, and human visual characteristics. The simulation and experimental results show that our method greatly reduces the measurements required and offers better image quality compared to recovering the red (R), green (G), and blue (B) components separately in RGB color space. As the application of a single photodiode increases, our method shows great potential in many fields. PMID:27168280

  14. Color Enhancement in Endoscopic Images Using Adaptive Sigmoid Function and Space Variant Color Reproduction.

    PubMed

    Imtiaz, Mohammad S; Wahid, Khan A

    2015-01-01

    Modern endoscopes play an important role in diagnosing various gastrointestinal (GI) tract related diseases. The improved visual quality of endoscopic images can provide better diagnosis. This paper presents an efficient color image enhancement method for endoscopic images. It is achieved in two stages: image enhancement at gray level followed by space variant chrominance mapping color reproduction. Image enhancement is achieved by performing adaptive sigmoid function and uniform distribution of sigmoid pixels. Secondly, a space variant chrominance mapping color reproduction is used to generate new chrominance components. The proposed method is used on low contrast color white light images (WLI) to enhance and highlight the vascular and mucosa structures of the GI tract. The method is also used to colorize grayscale narrow band images (NBI) and video frames. The focus value and color enhancement factor show that the enhancement level in the processed image is greatly increased compared to the original endoscopic image. The overall contrast level of the processed image is higher than the original image. The color similarity test has proved that the proposed method does not add any additional color which is not present in the original image. The algorithm has low complexity with an execution speed faster than other related methods. PMID:26089969

  15. 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

  16. Partitioning histopathological images: an integrated framework for supervised color-texture segmentation and cell splitting.

    PubMed

    Kong, Hui; Gurcan, Metin; Belkacem-Boussaid, Kamel

    2011-09-01

    For quantitative analysis of histopathological images, such as the lymphoma grading systems, quantification of features is usually carried out on single cells before categorizing them by classification algorithms. To this end, we propose an integrated framework consisting of a novel supervised cell-image segmentation algorithm and a new touching-cell splitting method. For the segmentation part, we segment the cell regions from the other areas by classifying the image pixels into either cell or extra-cellular category. Instead of using pixel color intensities, the color-texture extracted at the local neighborhood of each pixel is utilized as the input to our classification algorithm. The color-texture at each pixel is extracted by local Fourier transform (LFT) from a new color space, the most discriminant color space (MDC). The MDC color space is optimized to be a linear combination of the original RGB color space so that the extracted LFT texture features in the MDC color space can achieve most discrimination in terms of classification (segmentation) performance. To speed up the texture feature extraction process, we develop an efficient LFT extraction algorithm based on image shifting and image integral. For the splitting part, given a connected component of the segmentation map, we initially differentiate whether it is a touching-cell clump or a single nontouching cell. The differentiation is mainly based on the distance between the most likely radial-symmetry center and the geometrical center of the connected component. The boundaries of touching-cell clumps are smoothed out by Fourier shape descriptor before carrying out an iterative, concave-point and radial-symmetry based splitting algorithm. To test the validity, effectiveness and efficiency of the framework, it is applied to follicular lymphoma pathological images, which exhibit complex background and extracellular texture with nonuniform illumination condition. For comparison purposes, the results of the

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

    NASA Astrophysics Data System (ADS)

    Cooper, Ted J.

    2000-12-01

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

  18. Fire flame detection using color segmentation and space-time analysis

    NASA Astrophysics Data System (ADS)

    Ruchanurucks, Miti; Saengngoen, Praphin; Sajjawiso, Theeraphat

    2011-10-01

    This paper presents a fire flame detection using CCTV cameras based on image processing. The scheme relies on color segmentation and space-time analysis. The segmentation is performed to extract fire-like-color regions in an image. Many methods are benchmarked against each other to find the best for practical CCTV camera. After that, the space-time analysis is used to recognized fire behavior. A space-time window is generated from contour of the threshold image. Feature extraction is done in Fourier domain of the window. Neural network is used for behavior recognition. The system will be shown to be practical and robust.

  19. 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.

  20. Weld Spot Detection by Color Segmentation and Template Convolution

    SciTech Connect

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

    2007-12-26

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

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

  2. 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.

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

    NASA Astrophysics Data System (ADS)

    Nam, Hyoungsik; Song, Eun-Ji

    2013-06-01

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

  4. 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.

  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 segmentation of wavelet transform coefficients for video compression

    NASA Astrophysics Data System (ADS)

    Wasilewski, Piotr

    2000-04-01

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

  7. Nonlinear color space and spatiotemporal MRF for hierarchical segmentation of face features in video.

    PubMed

    Liévin, Marc; Luthon, Franck

    2004-01-01

    This paper deals with the low-level joint processing of color and motion for robust face analysis within a feature-based approach. To gain robustness and contrast under unsupervised viewing conditions, a nonlinear color transform relevant for hue segmentation is derived from a logarithmic model. A hierarchical segmentation scheme is based on Markov random field modeling, that combines hue and motion detection within a spatiotemporal neighborhood. Relevant face regions are segmented without parameter tuning. The accuracy of the label fields enables not only face detection and tracking but also geometrical measurements on facial feature edges, such as lips or eyes. Results are shown both on typical test sequences and on various sequences acquired from micro- or mobile cameras. The efficiency of the method makes it suitable for real-time applications aiming at audiovisual communication in unsupervised environments. PMID:15376958

  8. Component-based handprint segmentation using adaptive writing style model

    NASA Astrophysics Data System (ADS)

    Garris, Michael D.

    1997-04-01

    Building upon the utility of connected components, NIST has designed a new character segmentor based on statistically modeling the style of a person's handwriting. Simple spatial features capture the characteristics of a particular writer's style of handprint, enabling the new method to maintain a traditional character-level segmentation philosophy without the integration of recognition or the use of oversegmentation and linguistic postprocessing. Estimates for stroke width and character height are used to compute aspect ratio and standard stroke count features that adapt to the writer's style at the field level. The new method has been developed with a predetermined set of fuzzy rules making the segmentor much less fragile and much more adaptive, and the new method successfully reconstructs fragmented characters as well as splits touching characters. The new segmentor was integrated into the NIST public domain form-based handprint recognition systems and then tested on a set of 490 handwriting sample forms found in NIST special database 19. When compared to a simple component-based segmentor, the new adaptable method improved the overall recognition of handprinted digits by 3.4 percent and field level recognition by 6.9 percent, while effectively reducing deletion errors by 82 percent. The same program code and set of parameters successfully segments sequences of uppercase and lowercase characters without any context-based tuning. While not as dramatic as digits, the recognition of uppercase and lowercase characters improved by 1.7 percent and 1.3 percent respectively. The segmentor maintains a relatively straight-forward and logical process flow avoiding convolutions of encoded exceptions as is common in expert systems. As a result, the new segmentor operates very efficiently, and throughput as high as 362 characters per second can be achieved. Letters and numbers are constructed from a predetermined configuration of a relatively small number of strokes. Results

  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. Hierarchical data clustering approach for segmenting colored three-dimensional point clouds of building interiors

    NASA Astrophysics Data System (ADS)

    Sareen, Kuldeep K.; Knopf, George K.; Canas, Roberto

    2011-07-01

    A range scan of a building's interior typically produces an immense cloud of colorized three-dimensional data that represents diverse surfaces ranging from simple planes to complex objects. To create a virtual reality model of the preexisting room, it is necessary to segment the data into meaningful clusters. Unfortunately, segmentation algorithms based solely on surface curvature have difficulty in handling such diverse interior geometries, occluded boundaries, and closely placed objects with similar curvature properties. The proposed two stage hierarchical clustering algorithm overcomes many of these challenges by exploiting the registered color and spatial information simultaneously. Large planar regions are initially identified using constraints that combine color (hue) and a measure of local planarity called planar alignment factor. This stage assigns 72 to 84% of the sampled points to clusters representing flat surfaces such as walls, ceilings, or floors. The significantly reduced data points are clustered further using local surface normal and hue deviation information. A local density driven investigation distance (fixed density distance) is used for normal computation and cluster expansion. The methodology is tested on colorized range data of a typical room interior. The combined approach enabled the successful segmentation of planar and complex geometries in both dense and sparse data regions.

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

    PubMed

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

    2016-09-01

    The present study focuses on automatically to segment the blood flow pattern of color Doppler ultrasound in hand region of rheumatoid arthritis patients and to correlate the extracted the statistical features and color Doppler parameters with standard parameters. Thirty patients with rheumatoid arthritis (RA) and their total of 300 joints of both the hands, i.e., 240 MCP and 60 wrists were examined in this study. Ultrasound color Doppler of both the hands of all the patients was obtained. Automated segmentation of color Doppler image was performed using color enhancement scaling based segmentation algorithm. The region of interest is fixed in the MCP joints and wrist of the hand. Features were extracted from the defined ROI of the segmented output image. The color fraction was measured using Mimics software. The standard parameters such as HAQ score, DAS 28 score, and ESR was obtained for all the patients. The color fraction tends to be increased in wrist and MCP3 joints which indicate the increased blood flow pattern and color Doppler activity as part of inflammation in hand joints of RA. The ESR correlated significantly with the feature extracted parameters such as mean, standard deviation and entropy in MCP3, MCP4 joint and the wrist region. The developed automated color image segmentation algorithm provides a quantitative analysis for diagnosis and assessment of RA. The correlation study between the color Doppler parameters with the standard parameters provides moral significance in quantitative analysis of RA in MCP3 joint and the wrist region. PMID:27449351

  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. Real-Time Adaptive Foreground/Background Segmentation

    NASA Astrophysics Data System (ADS)

    Butler, Darren E.; Bove, V. Michael; Sridharan, Sridha

    2005-12-01

    The automatic analysis of digital video scenes often requires the segmentation of moving objects from a static background. Historically, algorithms developed for this purpose have been restricted to small frame sizes, low frame rates, or offline processing. The simplest approach involves subtracting the current frame from the known background. However, as the background is rarely known beforehand, the key is how to learn and model it. This paper proposes a new algorithm that represents each pixel in the frame by a group of clusters. The clusters are sorted in order of the likelihood that they model the background and are adapted to deal with background and lighting variations. Incoming pixels are matched against the corresponding cluster group and are classified according to whether the matching cluster is considered part of the background. The algorithm has been qualitatively and quantitatively evaluated against three other well-known techniques. It demonstrated equal or better segmentation and proved capable of processing [InlineEquation not available: see fulltext.] PAL video at full frame rate using only 35%-40% of a [InlineEquation not available: see fulltext.] GHz Pentium 4 computer.

  15. 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.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

    Wang, Aimin; Shen, Lansun; Zhao, Zhongxu

    2000-04-01

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

  18. 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)%.

  19. 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

  20. 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.

  1. 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.

  2. Fully automated glottis segmentation in endoscopic videos using local color and shape features of glottal regions.

    PubMed

    Gloger, Oliver; Lehnert, Bernhard; Schrade, Andreas; Völzke, Henry

    2015-03-01

    Exact analysis of glottal vibration patterns is indispensable for the assessment of laryngeal pathologies. Increasing demand of voice related examination and large amount of data provided by high-speed laryngoscopy and stroboscopy call for automatic assistance in research and patient care. Automatic glottis segmentation is necessary to assist glottal vibration pattern analysis, but unfortunately proves to be very challenging. Previous glottis segmentation approaches hardly consider characteristic glottis features as well as inhomogeneity of glottal regions and show serious drawbacks in their application for diagnostic purposes. We developed a fully automated glottis segmentation framework that extracts a set of glottal regions in endoscopic videos by using a flexible thresholding technique combined with a refining level set method that incorporates prior glottis shape knowledge. A novel descriptor for glottal regions is presented to remove potential nonglottal fake regions that show glottis-like shape properties. Knowledge of local color distributions is incorporated into Bayesian probability image generation. Glottal regions are then tracked frame-by-frame in probability images with a region-based level set segmentation strategy. Principal component analysis of pixel coordinates is applied to determine glottal orientation in each frame and to remove nonglottal regions if erroneous regions are included. The framework shows very promising results concerning segmentation accuracy and processing times and is applicable for both stroboscopic and high-speed videos. PMID:25350912

  3. Optic Disc and Cup Segmentation from Color Fundus Photograph Using Graph Cut with Priors

    PubMed Central

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

    2014-01-01

    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. PMID:24579126

  4. Excitation of two-colored temporal solitons in a segmented quasi-phase-matching structure.

    PubMed

    Zeng, Xianglong; Ashihara, Satoshi; Wang, Zijie; Wang, Tingyun; Chen, Yuping; Cha, Myoungsik

    2009-09-14

    We conducted a numerical study on the excitation of a two-colored temporal soliton in a segmented quasi-phase-matching (QPM) structure. The device has three parts: a periodic QPM grating for second-harmonic generation, a single domain for phase shift, and a periodic QPM grating for soliton evolution. The second harmonic pulse generated in the first grating works as a seed in the cascaded up-and-down conversions in the second grating. The numerical results showed that the second harmonic seeding enables the excitation of soliton pulses with an improved spatio-temporal intensity profile in a broad bandwidth of the wave-vector mismatch. PMID:19770904

  5. 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.

  6. 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.

  7. 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

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

    NASA Astrophysics Data System (ADS)

    Liu, Zongyi; Zhou, Hanning

    2011-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

  10. Color responses and their adaptation in human superior colliculus and lateral geniculate nucleus.

    PubMed

    Chang, Dorita H F; Hess, Robert F; Mullen, Kathy T

    2016-09-01

    We use an fMRI adaptation paradigm to explore the selectivity of human responses in the lateral geniculate nucleus (LGN) and superior colliculus (SC) to red-green color and achromatic contrast. We measured responses to red-green (RG) and achromatic (ACH) high contrast sinewave counter-phasing rings with and without adaptation, within a block design. The signal for the RG test stimulus was reduced following both RG and ACH adaptation, whereas the signal for the ACH test was unaffected by either adaptor. These results provide compelling evidence that the human LGN and SC have significant capacity for color adaptation. Since in the LGN red-green responses are mediated by P cells, these findings are in contrast to earlier neurophysiological data from non-human primates that have shown weak or no contrast adaptation in the P pathway. Cross-adaptation of the red-green color response by achromatic contrast suggests unselective response adaptation and points to a dual role for P cells in responding to both color and achromatic contrast. We further show that subcortical adaptation is not restricted to the geniculostriate system, but is also present in the superior colliculus (SC), an oculomotor region that until recently, has been thought to be color-blind. Our data show that the human SC not only responds to red-green color contrast, but like the LGN, shows reliable but unselective adaptation. PMID:27150230

  11. Segmentation and thematic classification of color orthophotos over non-compressed and JPEG 2000 compressed images

    NASA Astrophysics Data System (ADS)

    Zabala, A.; Cea, C.; Pons, X.

    2012-04-01

    Lossy compression is now increasingly used due to the enormous amount of images gathered by airborne and satellite sensors. Nevertheless, the implications of these compression procedures have been scarcely assessed. Segmentation before digital image classification is also a technique increasingly used in GEOBIA (GEOgraphic Object-Based Image Analysis). This paper presents an object-oriented application for image analysis using color orthophotos (RGB bands) and a Quickbird image (RGB and a near infrared band). We use different compression levels in order to study the effects of the data loss on the segmentation-based classification results. A set of 4 color orthophotos with 1 m spatial resolution and a 4-band Quickbird satellite image with 0.7 m spatial resolution each covering an area of about 1200 × 1200 m 2 (144 ha) was chosen for the experiment. Those scenes were compressed at 8 compression ratios (between 5:1 and 1000:1) using the JPEG 2000 standard. There were 7 thematic categories: dense vegetation, herbaceous, bare lands, road and asphalt areas, building areas, swimming pools and rivers (if necessary). The best category classification was obtained using a hierarchical classification algorithm over the second segmentation level. The same segmentation and classification methods were applied in order to establish a semi-automatic technique for all 40 images. To estimate the overall accuracy, a confusion matrix was calculated using a photointerpreted ground-truth map (fully covering 25% of each orthophoto). The mean accuracy over non-compressed images was 66% for the orthophotos and 72% for the Quickbird image. It is interesting to obtain this medium overall accuracy to be able to properly assess the compression effects (if the initial overall accuracy is very high, the possible positive effects of compression would not be noticeable). The first and second compression levels (up to 10:1) obtain results similar to the reference ones. Differences in the third to

  12. LoAd: a locally adaptive cortical segmentation algorithm.

    PubMed

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

    2011-06-01

    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

  13. 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

  14. Adaptive epithelial cytoplasm segmentation and epithelial unit separation in immunoflurorescent images

    NASA Astrophysics Data System (ADS)

    Ramachandran, Janakiramanan; Scott, Richard; Ajemba, Peter; Karvir, Hrishikesh; Khan, Faisal; Zeineh, Jack; Donovan, Michael; Fernandez, Gerardo

    2012-02-01

    Tissue segmentation is one of the key preliminary steps in the morphometric analysis of tissue architecture. In multi-channel immunoflurorescent biomarker images, the primary segmentation steps consist of segmenting the nuclei (epithelial and stromal) and epithelial cytoplasm from 4',6-diamidino-2-phenylindole (DAPI) and cytokeratin 18 (CK18) biomarker images respectively. The epithelial cytoplasm segmentation can be very challenging due to variability in cytoplasm morphology and image staining. A robust and adaptive segmentation algorithm was developed for the purpose of both delineating the boundaries and separating thin gaps that separate the epithelial unit structures. This paper discusses novel methods that were developed for adaptive segmentation of epithelial cytoplasm and separation of epithelial units. The adaptive segmentation was performed by computing the non-epithelial background texture of every CK18 biomarker image. The epithelial unit separation was performed using two complementary techniques: a marker based, center-initialized watershed transform and a boundary initialized fast marching-watershed segmentation. The adaptive segmentation algorithm was tested on 926 CK18 biomarker biopsy images (326 patients) with limited background noise and 1030 prostatectomy images (374 patients) with noisy to very noisy background. The segmentation performance was measured using two different methods, namely; stability and background textural metrics. It was observed that the database of 1030 noisy prostatectomy images had a lower mean value (using stability and three background texture performance metrics) compared to the biopsy dataset of 926 images that had limited background noise. The average of all four performance metrics yielded 94.32% accuracy for prostatectomy images compared to 99.40% accuracy for biopsy images.

  15. 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.

  16. Cell segmentation using coupled level sets and graph-vertex coloring.

    PubMed

    Nath, Sumit K; Palaniappan, Kannappan; Bunyak, Filiz

    2006-01-01

    Current level-set based approaches for segmenting a large number of objects are computationally expensive since they require a unique level set per object (the N-level set paradigm), or [log2N] level sets when using a multiphase interface tracking formulation. Incorporating energy-based coupling constraints to control the topological interactions between level sets further increases the computational cost to O(N2). We propose a new approach, with dramatic computational savings, that requires only four, or fewer, level sets for an arbitrary number of similar objects (like cells) using the Delaunay graph to capture spatial relationships. Even more significantly, the coupling constraints (energy-based and topological) are incorporated using just constant O(1) complexity. The explicit topological coupling constraint, based on predicting contour collisions between adjacent level sets, is developed to further prevent false merging or absorption of neighboring cells, and also reduce fragmentation during level set evolution. The proposed four-color level set algorithm is used to efficiently and accurately segment hundreds of individual epithelial cells within a moving monolayer sheet from time-lapse images of in vitro wound healing without any false merging of cells. PMID:17354879

  17. 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.

  18. 3D segmentation of masses in DCE-MRI images using FCM and adaptive MRF

    NASA Astrophysics Data System (ADS)

    Zhang, Chengjie; Li, Lihua

    2014-03-01

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

  19. 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.

  20. Adaptive Thresholding Technique for Retinal Vessel Segmentation Based on GLCM-Energy Information

    PubMed Central

    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. PMID:25802550

  1. Spatial-frequency-contingent color aftereffects: adaptation with one-dimensional stimuli.

    PubMed

    Day, R H; Webster, W R; Gillies, O; Crassini, B

    1992-01-01

    The McCollough effect was shown to be spatial-frequency selective by Lovegrove and Over (1972) after adaptation with vertical colored square-wave gratings separated by 1 octave. Adaptation with slide-presented red and green vertical square-wave gratings separated by 1 octave failed to produce contingent color aftereffects (CAEs). However, when each of these gratings was adapted alone, strong CAEs were produced. Adaptation with vertical colored sine-wave gratings separated by 1 octave also failed to produce CAEs, but strong effects were produced by adaptation with each grating alone. By varying the spatial frequency of the test sine wave, CAEs were found to be tuned for spatial frequency at 2.85 octaves after adaptation of 4 cycles per degree (cpd) and at 2.30 octaves after adaptation of 8 cpd. Adaptation of both vertical and horizontal sine-wave gratings produced strong CAEs, with bandwidths ranging from 1.96 to 2.90 octaves and with lower adapting contrast producing weaker CAEs. These results indicate that the McCollough effect is more broadly tuned for spatial frequency than are simple adaptation effects. PMID:1549425

  2. 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)

  3. 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.

  4. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  6. 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.

  7. 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. PMID:27127935

  8. 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.

  9. 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.

  10. 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

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

    PubMed

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

    2015-01-01

    The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms. PMID:25945120

  12. Adaptive inter color residual prediction for efficient red-green-blue intra coding

    NASA Astrophysics Data System (ADS)

    Jeong, Jinwoo; Choe, Yoonsik; Kim, Yong-Goo

    2011-07-01

    Intra coding of an RGB video is important to many high fidelity multimedia applications because video acquisition is mostly done in RGB space, and the coding of decorrelated color video loses its virtue in high quality ranges. In order to improve the compression performance of an RGB video, this paper proposes an inter color prediction using adaptive weights. For making full use of spatial, as well as inter color correlation of an RGB video, the proposed scheme is based on a residual prediction approach, and thus the incorporated prediction is performed on the transformed frequency components of spatially predicted residual data of each color plane. With the aid of efficient prediction employing frequency domain inter color residual correlation, the proposed scheme achieves up to 24.3% of bitrate reduction, compared to the common mode of H.264/AVC high 4:4:4 intra profile.

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  14. 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.

  15. 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. PMID:26874832

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. Application of new advanced CNN structure with adaptive thresholds to color edge detection

    NASA Astrophysics Data System (ADS)

    Deng, Shaojiang; Tian, Yuan; Hu, Xipeng; Wei, Pengcheng; Qin, Mingfu

    2012-04-01

    Color edge detection is much more efficient than gray scale detection when edges exist at the boundary between regions of different colors with no change in intensity. This paper presents adaptive templates, which are capable of detecting various color and intensity changes in color image. To avoid conception of multilayer proposed in literatures, modification has been done to the CNN structure. This modified structure allows a matrix C, which carries the change information of pixels, to replace the control parts in the basic CNN equation. This modification is necessary because in multilayer structure, it faces the challenge of how to represent the intrinsic relationship among each primary layer. Additionally, in order to enhance the accuracy of edge detection, adaptive detection threshold is employed. The adaptive thresholds are considered to be alterable criteria in designing matrix C. The proposed synthetic system not only avoids the problem which is engendered by multi-layers but also exploits full information of pixels themselves. Experimental results prove that the proposed method is efficient.

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

    PubMed

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

    2015-07-01

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

  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. 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. PMID:23938797

  4. Time course of adaptation to stimuli presented along cardinal lines in color space

    NASA Astrophysics Data System (ADS)

    Hughes, Alan; Demarco, Paul J.

    2003-12-01

    Visual sensitivity is a process that allows the visual system to maintain optimal response over a wide range of ambient light levels and chromaticities. Several studies have used variants of the probe-flash paradigm to show that the time course of adaptation to abrupt changes in ambient luminance depends on both receptoral and postreceptoral mechanisms. Though a few studies have explored how these processes govern adaptation to color changes, most of this effort has targeted the L-M-cone pathway. The purpose of our work was to use the probe-flash paradigm to more fully explore light adaptation in both the L-M- and the S-cone pathways. We measured sensitivity to chromatic probes presented after the onset of a 2-s chromatic flash. Test and flash stimuli were spatially coextensive 2° fields presented in Maxwellian view. Flash stimuli were presented as excursions from white and could extended in one of two directions along an equiluminant L-M-cone or S-cone line. Probes were presented as excursions from the adapting flash chromaticity and could extend either toward the spectrum locus or toward white. For both color lines, the data show a fast and slow adaptation component, although this was less evident in the S-cone data. The fast and slow components were modeled as first- and second-site adaptive processes, respectively. We find that the time course of adaptation is different for the two cardinal pathways. In addition, the time course for S-cone stimulation is polarity dependent. Our results characterize the rapid time course of adaptation in the chromatic pathways and reveal that the mechanics of adaptation within the S-cone pathway are distinct from those in the L-M-cone pathways.

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

    SciTech Connect

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

    2010-07-01

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

  6. Optic disc segmentation by balloon snake with texture from color fundus image.

    PubMed

    Sun, Jinyang; Luan, Fangjun; Wu, Hanhui

    2015-01-01

    A well-established method for diagnosis of glaucoma is the examination of the optic nerve head based on fundus image as glaucomatous patients tend to have larger cup-to-disc ratios. The difficulty of optic segmentation is due to the fuzzy boundaries and peripapillary atrophy (PPA). In this paper a novel method for optic nerve head segmentation is proposed. It uses template matching to find the region of interest (ROI). The method of vessel erasing in the ROI is based on PDE inpainting which will make the boundary smoother. A novel optic disc segmentation approach using image texture is explored in this paper. A cluster method based on image texture is employed before the optic disc segmentation step to remove the edge noise such as cup boundary and vessels. We replace image force in the snake with image texture and the initial contour of the balloon snake is inside the optic disc to avoid the PPA. The experimental results show the superior performance of the proposed method when compared to some traditional segmentation approaches. An average segmentation dice coefficient of 94% has been obtained. PMID:25861249

  7. Optic Disc Segmentation by Balloon Snake with Texture from Color Fundus Image

    PubMed Central

    Sun, Jinyang; Luan, Fangjun; Wu, Hanhui

    2015-01-01

    A well-established method for diagnosis of glaucoma is the examination of the optic nerve head based on fundus image as glaucomatous patients tend to have larger cup-to-disc ratios. The difficulty of optic segmentation is due to the fuzzy boundaries and peripapillary atrophy (PPA). In this paper a novel method for optic nerve head segmentation is proposed. It uses template matching to find the region of interest (ROI). The method of vessel erasing in the ROI is based on PDE inpainting which will make the boundary smoother. A novel optic disc segmentation approach using image texture is explored in this paper. A cluster method based on image texture is employed before the optic disc segmentation step to remove the edge noise such as cup boundary and vessels. We replace image force in the snake with image texture and the initial contour of the balloon snake is inside the optic disc to avoid the PPA. The experimental results show the superior performance of the proposed method when compared to some traditional segmentation approaches. An average segmentation dice coefficient of 94% has been obtained. PMID:25861249

  8. Segmented adaptive optic mirrors for laser power beaming and other space applications

    SciTech Connect

    Bennett, H.E.

    1996-12-31

    In order to effectively beam laser power into space to power satellites or to remove space debris in mid or high earth orbit very large mirrors (perhaps 12 m in diameter or more) and an adaptive optic system to penetrate the atmosphere are required. Mirrors with adaptive optic segment sizes less than the equivalent Fried coefficient for atmospheric turbulence (typically 3 - 5 cm at zenith in the visible region of the spectrum) are optimum for atmospheric penetration. These new mirrors may have hundreds of thousands of segments. The behavior of such mirrors under high powered laser irradiation is not clear, although for a large mirror both average and peak irradiation levels will be very low. Attention must be paid to penetration of laser energy into the gaps between segments and to the cumulative effect of edge diffraction. These problems do not appear to be severe and this new class of optics appears to offer new possibilities for use in space. It may change the way in which one looks at telescopes for space applications.

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

    NASA Astrophysics Data System (ADS)

    Corej, Thomas A.; Schmidt, Jason D.

    2009-08-01

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

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

    SciTech Connect

    Yao Jianhua; Summers, Ronald M.

    2007-05-15

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

  11. Adaptive model based pulmonary artery segmentation in 3D chest CT

    NASA Astrophysics Data System (ADS)

    Feuerstein, Marco; Kitasaka, Takayuki; Mori, Kensaku

    2010-03-01

    The extraction and analysis of the pulmonary artery in computed tomography (CT) of the chest can be an important, but time-consuming step for the diagnosis and treatment of lung disease, in particular in non-contrast data, where the pulmonary artery has low contrast and frequently merges with adjacent tissue of similar intensity. We here present a new method for the automatic segmentation of the pulmonary artery based on an adaptive model, Hough and Euclidean distance transforms, and spline fitting, which works equally well on non-contrast and contrast enhanced data. An evaluation on 40 patient data sets and a comparison to manual segmentations in terms of Jaccard index, sensitivity, specificity, and minimum mean distance shows its overall robustness.

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

    NASA Astrophysics Data System (ADS)

    Huang, Jian; Liu, Gui-xiong

    2016-04-01

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

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

    PubMed

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

    2013-08-01

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

  14. 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.

  15. Spatial-frequency-contingent color aftereffects: adaptation with two-dimensional stimulus patterns.

    PubMed

    Webster, W R; Day, R H; Gillies, O; Crassini, B

    1992-01-01

    The spatial-frequency theory of vision has been supported by adaptation studies using checkerboards in which contingent color aftereffects (CAEs) were produced at fundamental frequencies oriented at 45 degrees to the edges. A replication of this study failed to produce CAEs at the orientation of either the edges or the fundamentals. Using a computer-generated display, no CAEs were produced by adaptation of a square or an oblique checkerboard. But when one type of checkerboard (4 cpd) was adapted alone, CAEs were produced on the adapted checkerboard and on sine-wave gratings aligned with the fundamental and third harmonics of the checkerboard spectrum. Adaptation of a coarser checkerboard (0.80 cpd) produced CAEs aligned with both the edges and the harmonic frequencies. With checkerboards of both frequencies, CAEs were also found on the other type of checkerboard that had not been adapted. This observation raises problems for any edge-detector theory of vision, because there was no adaptation to edges. It was concluded that spatial-frequency mechanisms are operating at both low- and high-spatial frequencies and that an edge mechanism is operative at lower frequencies. The implications of these results are assessed for other theories of spatial vision. PMID:1549426

  16. A self-adaptive mean-shift segmentation approach based on graph theory for high-resolution remote sensing images

    NASA Astrophysics Data System (ADS)

    Chen, Luwan; Han, Ling; Ning, Xiaohong

    2015-12-01

    An auto new segmentation approach based on graph theory which named self-adaptive mean-shift for high-resolution remote sensing images was proposed in this paper. This approach could overcome some defects that classic Mean-Shift must determine the fixed bandwidth through trial many times, and could effectively distinguish the difference between different features in the texture rich region. Segmentation experiments were processed with WorldView satellite image. The results show that the presented method is adaptive, and its speed and precision can satisfy application, so it is a robust automatic segmentation algorithm.

  17. 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

  18. 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

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

    PubMed Central

    Hillis, James M.; Brainard, David H.

    2007-01-01

    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. PMID:16277280

  20. 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.

  1. 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.

  2. An Efficient and Self-Adapted Approach to the Sharpening of Color Images

    PubMed Central

    Lee, Tien-Lin

    2013-01-01

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

  3. 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.

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

    PubMed Central

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

    2006-01-01

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

  5. 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.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2016-08-01

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

  8. 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

  9. 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.

  10. 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

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

    PubMed

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Nagashima, M.; Agrawal, B. N.

    2014-02-01

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

  13. 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. PMID:24211911

  14. 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...

  15. Computationally Efficient Locally Adaptive Demosaicing of Color Filter Array Images Using the Dual-Tree Complex Wavelet Packet Transform

    PubMed Central

    Aelterman, Jan; Goossens, Bart; De Vylder, Jonas; Pižurica, Aleksandra; Philips, Wilfried

    2013-01-01

    Most digital cameras use an array of alternating color filters to capture the varied colors in a scene with a single sensor chip. Reconstruction of a full color image from such a color mosaic is what constitutes demosaicing. In this paper, a technique is proposed that performs this demosaicing in a way that incurs a very low computational cost. This is done through a (dual-tree complex) wavelet interpretation of the demosaicing problem. By using a novel locally adaptive approach for demosaicing (complex) wavelet coefficients, we show that many of the common demosaicing artifacts can be avoided in an efficient way. Results demonstrate that the proposed method is competitive with respect to the current state of the art, but incurs a lower computational cost. The wavelet approach also allows for computationally effective denoising or deblurring approaches. PMID:23671575

  16. A novel method of target recognition based on 3D-color-space locally adaptive regression kernels model

    NASA Astrophysics Data System (ADS)

    Liu, Jiaqi; Han, Jing; Zhang, Yi; Bai, Lianfa

    2015-10-01

    Locally adaptive regression kernels model can describe the edge shape of images accurately and graphic trend of images integrally, but it did not consider images' color information while the color is an important element of an image. Therefore, we present a novel method of target recognition based on 3-D-color-space locally adaptive regression kernels model. Different from the general additional color information, this method directly calculate the local similarity features of 3-D data from the color image. The proposed method uses a few examples of an object as a query to detect generic objects with incompact, complex and changeable shapes. Our method involves three phases: First, calculating the novel color-space descriptors from the RGB color space of query image which measure the likeness of a voxel to its surroundings. Salient features which include spatial- dimensional and color -dimensional information are extracted from said descriptors, and simplifying them to construct a non-similar local structure feature set of the object class by principal components analysis (PCA). Second, we compare the salient features with analogous features from the target image. This comparison is done using a matrix generalization of the cosine similarity measure. Then the similar structures in the target image are obtained using local similarity structure statistical matching. Finally, we use the method of non-maxima suppression in the similarity image to extract the object position and mark the object in the test image. Experimental results demonstrate that our approach is effective and accurate in improving the ability to identify targets.

  17. 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.

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

    PubMed

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

    2015-01-01

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

  19. 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

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

    PubMed

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

    2014-01-01

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

  1. 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'.

  2. 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).

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

    PubMed

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

    2008-07-01

    Opsariichthys pachycephalus and Candidia barbatus are two phylogenetically related freshwater cyprinids that both exhibit colorful, yet quite different nuptial coloration. This study was designed to test the hypothesis that differences in nuptial coloration between two species could reflect differences in color perception ability and the opsin genes that coded for it. Genes encoding the visual pigments of these two species were cloned and sequenced, lambda(max) of cone photoreceptors and the reflectance spectra of their body coloration were measured to test the hypothesis. The 14-nm spectral shift between green-light-sensitive photoreceptors of these two cyprinids is found to correlate well with differences in their reflective spectra. The spectral shift could result from differential expression of opsin genes and the interactive effects of the amino acid replacements in various minor sites. These results support our hypothesis that nuptial coloration is tied to color perception ability and opsin genes. PMID:18571688

  4. Color Blindness Simulations

    MedlinePlus

    ... many disables? The fastest growing segment? Myths of disability The Law The Rules Accessibility Resources Page Updates, additions Contact Us For assistance contact your NOAA Line Office Section 508 Coordinator Color blindness Simulations Normal Color Vision Deuteranopia Color blindness marked ...

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

    PubMed Central

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

    2014-01-01

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

  6. 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.

  7. 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. PMID:26279309

  8. Semi-automatic medical image segmentation with adaptive local statistics in Conditional Random Fields framework.

    PubMed

    Hu, Yu-Chi J; Grossberg, Michael D; Mageras, Gikas S

    2008-01-01

    Planning radiotherapy and surgical procedures usually require onerous manual segmentation of anatomical structures from medical images. In this paper we present a semi-automatic and accurate segmentation method to dramatically reduce the time and effort required of expert users. This is accomplished by giving a user an intuitive graphical interface to indicate samples of target and non-target tissue by loosely drawing a few brush strokes on the image. We use these brush strokes to provide the statistical input for a Conditional Random Field (CRF) based segmentation. Since we extract purely statistical information from the user input, we eliminate the need of assumptions on boundary contrast previously used by many other methods, A new feature of our method is that the statistics on one image can be reused on related images without registration. To demonstrate this, we show that boundary statistics provided on a few 2D slices of volumetric medical data, can be propagated through the entire 3D stack of images without using the geometric correspondence between images. In addition, the image segmentation from the CRF can be formulated as a minimum s-t graph cut problem which has a solution that is both globally optimal and fast. The combination of a fast segmentation and minimal user input that is reusable, make this a powerful technique for the segmentation of medical images. PMID:19163362

  9. 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.

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2012-01-01

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

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

    PubMed

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

    2013-01-01

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

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

    PubMed Central

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

    2013-01-01

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

  15. 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

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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

  5. Segmentation-aided adaptive filtering for metal artifact reduction in radio-therapeutic CT images

    NASA Astrophysics Data System (ADS)

    Saint Olive, Celine; Kaus, Michael R.; Pekar, Vladimir; Eck, Kai; Spies, Lothar

    2004-05-01

    In CT imaging, high absorbing objects such as metal bodies may cause significant artifacts, which may, for example, result in dose inaccuracies in the radiation therapy planning process. In this work, we aim at reducing the local and global image artifact, in order to improve the overall dose accuracy. The key part f this approach is the correction of the original projection data in those regions, which feature defects caused by rays traversing the high attenuating objects in the patient. The affected regions are substituted by model data derived from the original tomogram deploying a segmentation method. Phantom and climnical studies demonstrate that the proposed method significantly reduces the overall artifacts while preserving the information content of the image as much as possible. The image quality improvements were quantified by determining the signal-to-noise ratio, the artifact level and the modulation transfer function. The proposed method is computationally efficient and can easily be integrated into commercial CT scanners and radiation therapy planning software.

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

    PubMed Central

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

    2010-01-01

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

  7. Active Segmentation

    PubMed Central

    Mishra, Ajay; Aloimonos, Yiannis

    2009-01-01

    The human visual system observes and understands a scene/image by making a series of fixations. Every fixation point lies inside a particular region of arbitrary shape and size in the scene which can either be an object or just a part of it. We define as a basic segmentation problem the task of segmenting that region containing the fixation point. Segmenting the region containing the fixation is equivalent to finding the enclosing contour- a connected set of boundary edge fragments in the edge map of the scene - around the fixation. This enclosing contour should be a depth boundary. We present here a novel algorithm that finds this bounding contour and achieves the segmentation of one object, given the fixation. The proposed segmentation framework combines monocular cues (color/intensity/texture) with stereo and/or motion, in a cue independent manner. The semantic robots of the immediate future will be able to use this algorithm to automatically find objects in any environment. The capability of automatically segmenting objects in their visual field can bring the visual processing to the next level. Our approach is different from current approaches. While existing work attempts to segment the whole scene at once into many areas, we segment only one image region, specifically the one containing the fixation point. Experiments with real imagery collected by our active robot and from the known databases 1 demonstrate the promise of the approach. PMID:20686671

  8. 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

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

    PubMed

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

    2011-10-01

    Intensity-invariant local phase features based on Log-Gabor filters have been recently shown to produce highly accurate localizations of bone surfaces from three-dimensional (3-D) ultrasound. A key challenge, however, remains in the proper selection of filter parameters, whose values have so far been chosen empirically and kept fixed for a given image. Since Log-Gabor filter responses widely change when varying the filter parameters, actual parameter selection can significantly affect the quality of extracted features. This article presents a novel method for contextual parameter selection that autonomously adapts to image content. Our technique automatically selects the scale, bandwidth and orientation parameters of Log-Gabor filters for optimizing local phase symmetry. The proposed approach incorporates principle curvature computed from the Hessian matrix and directional filter banks in a phase scale-space framework. Evaluations performed on carefully designed in vitro experiments demonstrate 35% improvement in accuracy of bone surface localization compared with empirically-set parameterization results. Results from a pilot in vivo study on human subjects, scanned in the operating room, show similar improvements. PMID:21821346

  10. 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, ...

  11. 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

  12. 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.

  13. [Using spectra and visual modeling to study animal coloration].

    PubMed

    Yang, Can-Chao; Liang, Wei

    2013-12-01

    Animal coloration has many adaptive functions and plays an important role in signal communication both among intra- and interspecies. For example, it has been widely used in mate choice, intrasexual competition, and as aposematic or cryptic coloration in predator avoidance. Many colors and pigments also function in microbial resistance, structural support, photoprotection, and thermoregulation. Differing from human vision, based on RGB system, many other animals have tetrachromatic vision system, which includes the ultraviolet (UV) range that is undetectable by human eyes. Previous studies showed that ultraviolet is important in some species' social signaling and communication. Moreover, cone inner segments of most classes of vertebrate contain an oil droplet, which acts as a cut-off filter absorbing wavelengths below a critical value, and transmitting longer wavelengths. Animal and human vision is significantly different in that the classification of color by human standards may be a misleading for measuring animal coloration. Here, we illuminate how to use fiber spectrophotometer to quantify animal coloration, and analyze it by spectra analysis and visual modeling. As an example, we obtained plumage reflectance spectra from male and female scarlet minivets (Pericrocotus flammeus). This bird species is sexually dimorphic that the males have plumage color in black and red, while the females have grey and yellow accordingly. These plumage colors are typically generated from melanin and carotenoid pigments, which have an effect on antioxidant activity. Analysis of spectra segments provides hue, chroma, brightness and relative brightness of each wave range. Visual modeling maps color patches on tetrahedral color space and Robinson projection, meanwhile, calculates color span and color space volume which describe the color contrast and color diversity, respectively. In visual modeling, ambient light irradiance and spectral sensitivity of animal retinas are included

  14. 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…

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

    PubMed

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

    2015-01-01

    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

  16. 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.

  17. Comparison of massively parallel hand-print segmenters

    SciTech Connect

    Wilkinson, R.A.; Garris, M.D.

    1992-09-01

    NIST has developed a massively parallel hand-print recognition system that allows components to be interchanged. Using this system, three different character segmentation algorithms have been developed and studied. They are blob coloring, histogramming, and a hybrid of the two. The blob coloring method uses connected components to isolate characters. The histogramming method locates linear spaces, which may be slanted, to segment characters. The hybrid method is an augmented histogramming method that incorporates statistically adaptive rules to decide when a histogrammed item is too large and applies blob coloring to further segment the difficult item. The hardware configuration is a serial host computer with a 1024 processor Single Instruction Multiple Data (SIMD) machine attached to it. The data used in this comparison is 'NIST Special Database 1' which contains 2100 forms from different writers where each form contains 130 digit characters distributed across 28 fields. This gives a potential 273,000 characters to be segmented. Running the massively parallel system across the 2100 forms, blob coloring required 2.1 seconds per form with an accuracy of 97.5%, histogramming required 14.4 seconds with an accuracy of 95.3%, and the hybrid method required 13.2 seconds with an accuracy of 95.4%. The results of this comparison show that the blob coloring method on a SIMD architecture is superior.

  18. 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

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

    PubMed

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

    2016-01-01

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

  20. Design and development of a 329-segment tip-tilt piston mirror array for space-based adaptive optics

    NASA Astrophysics Data System (ADS)

    Stewart, Jason B.; Bifano, Thomas G.; Bierden, Paul; Cornelissen, Steven; Cook, Timothy; Levine, B. Martin

    2006-01-01

    We report on the development of a new MEMS deformable mirror (DM) system for the hyper-contrast visible nulling coronagraph architecture designed by the Jet Propulsion Laboratory for NASA's Terrestrial Planet Finding (TPF) mission. The new DM is based largely upon existing lightweight, low power MEMS DM technology at Boston University (BU), tailored to the rigorous optical and mechanical requirements of the nulling coronagraph. It consists of 329-hexagonal segments on a 600μm pitch, each with tip/tilt and piston degrees of freedom. The mirror segments have 1μm of stroke, a tip/tilt range of 600 arc-seconds, and maintain their figure to within 2nm RMS under actuation. The polished polycrystalline silicon mirror segments have a surface roughness of 5nm RMS and an average curvature of 270mm. Designing a mirror segment that maintains its figure during actuation was a very significant challenge faced during DM development. Two design concepts were pursued in parallel to address this challenge. The first design uses a thick, epitaxial grown polysilicon mirror layer to add rigidity to the mirror segment. The second design reduces mirror surface bending by decoupling actuator diaphragm motion from the mirror surface motion. This is done using flexure cuts around the mirror post in the actuator diaphragm. Both DM architectures and their polysilicon microfabrication process are presented. Recent optical and electromechanical characterization results will also be discussed, in addition to plans for further improvement of DM figure to satisfy nulling coronagraph optical requirements.

  1. Segmental neurofibromatosis.

    PubMed

    Sobjanek, Michał; Dobosz-Kawałko, Magdalena; Michajłowski, Igor; Pęksa, Rafał; Nowicki, Roman

    2014-12-01

    Segmental neurofibromatosis or type V neurofibromatosis is a rare genodermatosis characterized by neurofibromas, café-au-lait spots and neurofibromas limited to a circumscribed body region. The disease may be associated with systemic involvement and malignancies. The disorder has not been reported yet in the Polish medical literature. A 63-year-old Caucasian woman presented with a 20-year history of multiple, flesh colored, dome-shaped, soft to firm nodules situated in the right lumbar region. A histopathologic evaluation of three excised tumors revealed neurofibromas. No neurological and ophthalmologic symptoms of neurofibromatosis were diagnosed. PMID:25610358

  2. Segmental neurofibromatosis

    PubMed Central

    Dobosz-Kawałko, Magdalena; Michajłowski, Igor; Pęksa, Rafał; Nowicki, Roman

    2014-01-01

    Segmental neurofibromatosis or type V neurofibromatosis is a rare genodermatosis characterized by neurofibromas, café-au-lait spots and neurofibromas limited to a circumscribed body region. The disease may be associated with systemic involvement and malignancies. The disorder has not been reported yet in the Polish medical literature. A 63-year-old Caucasian woman presented with a 20-year history of multiple, flesh colored, dome-shaped, soft to firm nodules situated in the right lumbar region. A histopathologic evaluation of three excised tumors revealed neurofibromas. No neurological and ophthalmologic symptoms of neurofibromatosis were diagnosed. PMID:25610358

  3. 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. PMID:22874883

  4. Adaptive Channel-Tracking Method and Equalization for MC-CDMA Systems over Rapidly Fading Channel under Colored Noise

    NASA Astrophysics Data System (ADS)

    Yang, Chang-Yi; Chen, Bor-Sen

    2010-12-01

    A recursive maximum-likelihood (RML) algorithm for channel estimation under rapidly fading channel and colored noise in a multicarrier code-division multiple-access (MC-CDMA) system is proposed in this paper. A moving-average model with exogenous input (MAX) is given to describe the transmission channel and colored noise. Based on the pseudoregression method, the proposed RML algorithm can simultaneously estimate the parameters of channel and colored noise. Following the estimation results, these parameters can be used to enhance the minimum mean-square error (MMSE) equalizer. Considering high-speed mobile stations, a one-step linear trend predictor is added to improve symbol detection. Simulation results indicate that the proposed RML estimator can track the channel more precisely than the conventional estimator. Meanwhile, the performance of the proposed enhanced MMSE equalizer is robust to the rapidly Rayleigh fading channel under colored noise in the MC-CDMA systems.

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

    PubMed

    King-Smith, P E; Carden, D

    1976-07-01

    We show how the processes of visual detection and of temporal and spatial summation may be analyzed in terms of parallel luminance (achromatic) and opponent-color systems; a test flash is detected if it exceeds the threshold of either system. The spectral sensitivity of the luminance system may be determined by a flicker method, and has a single broad peak near 555 nm; the spectral sensitivity of the opponent-color system corresponds to the color recognition threshold, and has three peaks at about 440, 530, and 600 nm (on a white background). The temporal and spatial integration of the opponent-color system are generally greater than for the luminance system; further, a white background selectively depresses the sensitivity of the luminance system relative to the opponent-color system. Thus relatively large (1 degree) and long (200 msec) spectral test flashes on a white background are detected by the opponent-color system except near 570 nm; the contribution of the luminance system becomes more prominent if the size or duration of the test flash is reduced, or if the white background is extinguished. The present analysis is discussed in relation to Stiles' model of independent eta mechanisms. PMID:978286

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

    PubMed Central

    2013-01-01

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

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

    PubMed

    Cohen, Laurent D; Deschamps, Thomas

    2007-08-01

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

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

    PubMed

    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

  9. 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

  10. 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

  11. 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

  12. 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.

  13. 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…

  14. 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

  15. 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.

  16. 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

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

    PubMed

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

    2016-08-01

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

  18. 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

  19. 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.

  20. 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 ...

  1. Color Blindness

    MedlinePlus

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

  2. 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 ...

  3. Applying Color.

    ERIC Educational Resources Information Center

    Burton, David

    1984-01-01

    Most schools teach the triadic color system, utilizing red, blue, and yellow as primary colors. Other systems, such as additive and subtractive color systems, Munsell's Color Notation System, and the Hering Opponent Color Theory, can broaden children's concepts and free them to better choose color in their own work. (IS)

  4. 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

  5. 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…

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

    PubMed

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

    2010-04-01

    Automatic segmentation of cell nuclei is an essential step in image cytometry and histometry. Despite substantial progress, there is a need to improve accuracy, speed, level of automation, and adaptability to new applications. This paper presents a robust and accurate novel method for segmenting cell nuclei using a combination of ideas. The image foreground is extracted automatically using a graph-cuts-based binarization. Next, nuclear seed points are detected by a novel method combining multiscale Laplacian-of-Gaussian filtering constrained by distance-map-based adaptive scale selection. These points are used to perform an initial segmentation that is refined using a second graph-cuts-based algorithm incorporating the method of alpha expansions and graph coloring to reduce computational complexity. Nuclear segmentation results were manually validated over 25 representative images (15 in vitro images and 10 in vivo images, containing more than 7400 nuclei) drawn from diverse cancer histopathology studies, and four types of segmentation errors were investigated. The overall accuracy of the proposed segmentation algorithm exceeded 86%. The accuracy was found to exceed 94% when only over- and undersegmentation errors were considered. The confounding image characteristics that led to most detection/segmentation errors were high cell density, high degree of clustering, poor image contrast and noisy background, damaged/irregular nuclei, and poor edge information. We present an efficient semiautomated approach to editing automated segmentation results that requires two mouse clicks per operation. PMID:19884070

  7. 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.

  8. Unified Saliency Detection Model Using Color and Texture Features

    PubMed Central

    Luo, Tiejian

    2016-01-01

    Saliency detection attracted attention of many researchers and had become a very active area of research. Recently, many saliency detection models have been proposed and achieved excellent performance in various fields. However, most of these models only consider low-level features. This paper proposes a novel saliency detection model using both color and texture features and incorporating higher-level priors. The SLIC superpixel algorithm is applied to form an over-segmentation of the image. Color saliency map and texture saliency map are calculated based on the region contrast method and adaptive weight. Higher-level priors including location prior and color prior are incorporated into the model to achieve a better performance and full resolution saliency map is obtained by using the up-sampling method. Experimental results on three datasets demonstrate that the proposed saliency detection model outperforms the state-of-the-art models. PMID:26889826

  9. 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 ...

  10. Color blindness

    MedlinePlus

    ... care provider or eye specialist can check your color vision in several ways. Testing for color blindness is ... Adams AJ, Verdon WA, Spivey BE. Color vision. In: Tasman W, Jaeger EA, eds. ... PA: Lippincott Williams & Wilkins; 2013:vol. 2, chap ...

  11. 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%.

  12. 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. PMID:23456062

  13. Reasoning about color in Prolog

    NASA Astrophysics Data System (ADS)

    Batchelor, Bruce G.; Whelan, Paul F.

    1994-10-01

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

  14. Color constancy of color-deficient observers under illuminations defined by individual color discrimination ellipsoids.

    PubMed

    Ma, Ruiqing; Kawamoto, Ken-Ichiro; Shinomori, Keizo

    2016-03-01

    We explored the color constancy mechanisms of color-deficient observers under red, green, blue, and yellow illuminations. The red and green illuminations were defined individually by the longer axis of the color discrimination ellipsoid measured by the Cambridge Colour Test. Four dichromats (3 protanopes and 1 deuteranope), two anomalous trichromats (2 deuteranomalous observers), and five color-normal observers were asked to complete the color constancy task by making a simultaneous paper match under asymmetrical illuminations in haploscopic view on a monitor. The von Kries adaptation model was applied to estimate the cone responses. The model fits showed that for all color-deficient observers under all illuminations, the adjustment of the S-cone response or blue-yellow chromatically opponent responses modeled with the simple assumption of cone deletion in a certain type (S-M, S-L or S-(L+M)) was consistent with the principle of the von Kries model. The degree of adaptation was similar to that of color-normal observers. The results indicate that the color constancy of color-deficient observers is mediated by the simplified blue-yellow color system with a von Kries-type adaptation effect, even in the case of brightness match, as well as by a possible cone-level adaptation to the S-cone when the illumination produces a strong S-cone stimulation, such as blue illumination. PMID:26974935

  15. 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

  16. 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

    PubMed Central

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

    2012-01-01

    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

  17. Colorful Chemistry.

    ERIC Educational Resources Information Center

    Williams, Suzanne

    1991-01-01

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

  18. Color Vision Defects: What Teachers Should Know.

    ERIC Educational Resources Information Center

    Lewis, Barbara A.; And Others

    1990-01-01

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

  19. Color image processing for date quality evaluation

    NASA Astrophysics Data System (ADS)

    Lee, Dah Jye; Archibald, James K.

    2010-01-01

    Many agricultural non-contact visual inspection applications use color image processing techniques because color is often a good indicator of product quality. Color evaluation is an essential step in the processing and inventory control of fruits and vegetables that directly affects profitability. Most color spaces such as RGB and HSV represent colors with three-dimensional data, which makes using color image processing a challenging task. Since most agricultural applications only require analysis on a predefined set or range of colors, mapping these relevant colors to a small number of indexes allows simple and efficient color image processing for quality evaluation. This paper presents a simple but efficient color mapping and image processing technique that is designed specifically for real-time quality evaluation of Medjool dates. In contrast with more complex color image processing techniques, the proposed color mapping method makes it easy for a human operator to specify and adjust color-preference settings for different color groups representing distinct quality levels. Using this color mapping technique, the color image is first converted to a color map that has one color index represents a color value for each pixel. Fruit maturity level is evaluated based on these color indices. A skin lamination threshold is then determined based on the fruit surface characteristics. This adaptive threshold is used to detect delaminated fruit skin and hence determine the fruit quality. The performance of this robust color grading technique has been used for real-time Medjool date grading.

  20. Progress in color night vision

    NASA Astrophysics Data System (ADS)

    Toet, Alexander; Hogervorst, Maarten A.

    2012-01-01

    We present an overview of our recent progress and the current state-of-the-art techniques of color image fusion for night vision applications. Inspired by previously developed color opponent fusing schemes, we initially developed a simple pixel-based false color-mapping scheme that yielded fused false color images with large color contrast and preserved the identity of the input signals. This method has been successfully deployed in different areas of research. However, since this color mapping did not produce realistic colors, we continued to develop a statistical color-mapping procedure that would transfer the color distribution of a given example image to a multiband nighttime image. This procedure yields a realistic color rendering. However, it is computationally expensive and achieves no color constancy since the mapping depends on the relative amounts of the different materials in the scene. By applying the statistical mapping approach in a color look-up-table framework, we finally achieved both color constancy and computational simplicity. This sample-based color transfer method is specific for different types of materials in a scene and can be easily adapted for the intended operating theatre and the task at hand. The method can be implemented as a look-up-table transform and is highly suitable for real-time implementations.

  1. Segmental neurofibromatosis.

    PubMed

    Galhotra, Virat; Sheikh, Soheyl; Jindal, Sanjeev; Singla, Anshu

    2014-07-01

    Segmental neurofibromatosis is a rare disorder, characterized by neurofibromas or cafι-au-lait macules limited to one region of the body. Its occurrence on the face is extremely rare and only few cases of segmental neurofibromatosis over the face have been described so far. We present a case of segmental neurofibromatosis involving the buccal mucosa, tongue, cheek, ear, and neck on the right side of the face. PMID:25565748

  2. A robust segmentation and tracking method for characterizing GNSS signals reception environment

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

    This paper is focused on the characterization of GNSS signals reception environment by estimation of the percentage of visible sky in real-time. On previous works, a new segmentation technique based on a color watershed using an adaptive combination of color and texture information was proposed. This information was represented by two morphological gradients, a classical color gradient and a morphological texture gradient based on mathematical morphology or co-occurrence matrices. The segmented images were then classified into two regions: sky and not-sky. However, this approach has high computational cost and thus, cannot be applied in real-time. On this paper, we present this adaptive segmentation method with a texture gradient calculated by the Gabor filter and a region-tracking method based on a block-matching estimation. This last step reduces the execution time of the application in order to respect the real-time conditions. Since the application works for fish-eye images, a calibration and rectification method is required before tracking and is also presented on this paper. The calibration method presented is based on the straight line condition and thus does not use real word coordinates. This prevents measurement errors. The tracking results are compared to the results of the classification method (which has already been evaluated on previous works). The evaluation shows that the proposed method has a very low error and decreases the execution time by ten times.

  3. 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.

  4. Uncalibrated color

    NASA Astrophysics Data System (ADS)

    Moroney, Nathan

    2006-01-01

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

  5. Segmental neurofibromatosis.

    PubMed

    Toy, Brian

    2003-10-01

    Segmental neurofibromatosis is a rare variant of neurofibromatosis in which skin lesions are confined to a circumscribed body segment. A case of a 72-year-old woman with this condition is presented. Clinical features and genetic evidence are reviewed. PMID:14594599

  6. Color realism and color science.

    PubMed

    Byrne, Alex; Hilbert, David R

    2003-02-01

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

  7. 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.

  8. 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…

  9. 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.

  10. Determination of CRT color gamut boundaries in perceptual color space

    NASA Astrophysics Data System (ADS)

    Wang, Yong; Xu, Haisong

    2005-02-01

    CRT color gamut boundaries can be determined by two steps workflow. Firstly, the display should be calibrated with the method recommended by CIE to characterize the relationship between CIE tristimulus values and DAC values. The nonlinear relationship of each electronic channel between the color of the radiant output of CRT displays and the digital DAC values can be characterized accurately with GOG model using parameters of gain, offset, and gamma. Secondly, color gamut boundary can be determined using a fast and accurate algorithm. Generally, in a color space, any chosen degree of lightness will reduce that space to a plane. The color gamut on this equal-lightness plane can be transformed into RGB DAC value space. Since locations on the edges and surfaces of RGB DAC value space will correspond colors with relatively high saturation, the boundary of the curved surface in RGB DAC value space can be quickly computed for certain lightness. The accurate color gamut is obtained by mapping this boundary over to such a perceptual color space as CIELAB or CIELUV uniform color space. The key issue of this algorithm is to compute the equal-lightness curved surface in RGB DAC value space. The resolution of device gamut description depends on the number of segments that the lightness axis is separated into in the perceptual color space.

  11. 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…

  12. 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…

  13. 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.

  14. 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…

  15. 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.

  16. Simulating coronas in color.

    PubMed

    Gedzelman, Stanley D; Lock, James A

    2003-01-20

    Coronas are simulated in color by use of the Mie scattering theory of light by small droplets through clouds of finite optical thickness embedded in a Rayleigh scattering atmosphere. The primary factors that affect color, visibility, and number of rings of coronas are droplet size, width of the size distribution, and cloud optical thickness. The color sequence of coronas and iridescence varies when the droplet radius is smaller than approximately 6-microm. As radius increases to approximately 3.5 microm, new color bands appear at the center of the corona and fade as they move outward. As the radius continues to increase to approximately 6 microm, successively more inner rings become fixed in the manner described by classical diffraction theory, while outer rings continue their outward migration. Wave clouds or rippled cloud segments produce the brightest and most vivid multiple ringed coronas and iridescence because their integrated dropsize distributions along sunbeams are much narrower than in convective or stratiform clouds. The visibility of coronas and the appearance of the background sky vary with cloud optical depth tau. First the corona becomes visible as a white aureole in a blue sky when tau approximately 0.001. Color purity then rapidly increases to an almost flat maximum in the range 0.05 < or = tau < or = 0.5 and then decreases, so coronas are almost completely washed out by a bright gray background when tau > or = 4. PMID:12570272

  17. [Hair colorants].

    PubMed

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

    1997-01-01

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

  18. 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

  19. Quantum Color

    ScienceCinema

    Lincoln, Don

    2016-07-16

    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.

  20. Segmented combustor

    NASA Technical Reports Server (NTRS)

    Halila, Ely E. (Inventor)

    1994-01-01

    A combustor liner segment includes a panel having four sidewalls forming a rectangular outer perimeter. A plurality of integral supporting lugs are disposed substantially perpendicularly to the panel and extend from respective ones of the four sidewalls. A plurality of integral bosses are disposed substantially perpendicularly to the panel and extend from respective ones of the four sidewalls, with the bosses being shorter than the lugs. In one embodiment, the lugs extend through supporting holes in an annular frame for mounting the liner segments thereto, with the bosses abutting the frame for maintaining a predetermined spacing therefrom.

  1. Colored Chaos

    NASA Technical Reports Server (NTRS)

    2004-01-01

    [figure removed for brevity, see original site]

    Released 7 May 2004 This daytime visible color image was collected on May 30, 2002 during the Southern Fall season in Atlantis Chaos.

    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 -34.5, Longitude 183.6 East (176.4 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's Office of

  2. 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…

  3. Color Poetry.

    ERIC Educational Resources Information Center

    Ferry, John E.

    1980-01-01

    Elementary students were asked to find 12 colors and 5 sounds in their immediate natural environment and to describe in writing where they saw each color in relationship to themselves. The writings formed a type of poetry which expressed involvement with and observation of the environment. (CM)

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

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

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

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

    USGS Publications Warehouse

    Irwin, E.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.

  6. Color rendering of color camera data

    NASA Technical Reports Server (NTRS)

    Wandell, Brian A.

    1986-01-01

    Conditions under which a computational procedure can be applied to arbitrary camera sensors to permit estimation of the human photoreceptor response are considered. The adopted procedures recover the effective surface reflectance at the time of measurement, and the reflectance estimates depend not only on the surface, but upon the viewing geometry. The present method for color rendering assumes that the observer's state of adaptation at the time of viewing the original and the rendered images is the same. The analysis aids in specifying which classes of surfaces are required to be accurately rendered, and for which surfaces some error can be tolerated.

  7. 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.

  8. Knowledge-based interpretation of outdoor natural color scenes

    SciTech Connect

    Ohta, Y.

    1985-01-01

    One of the major targets in vision research is to develop a total vision system starting from images to a symbolic description, utilizing various knowledge sources. This book demonstrates a knowledge-based image interpretation system that analyzes natural color scenes. Topics covered include color information for region segmentation, preliminary segmentation of color images, and a bottom-up and top-down region analyzer.

  9. [Segmental neurofibromatosis].

    PubMed

    Zulaica, A; Peteiro, C; Pereiro, M; Pereiro Ferreiros, M; Quintas, C; Toribio, J

    1989-01-01

    Four cases of segmental neurofibromatosis (SNF) are reported. It is a rare entity considered to be a localized variant of neurofibromatosis (NF)-Riccardi's type V. Two cases are male and two female. The lesions are located to the head in a patient and the other three cases in the trunk. No family history nor transmission to progeny were manifested. The rest of the organs are undamaged. PMID:2502696

  10. 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

  11. Adaptive window-length detection of underwater transients using wavelets.

    PubMed

    Carevic, Dragana

    2005-05-01

    This paper describes a detection method that adapts to unknown characteristics of the underlying transient signal, such as location, length, and time-frequency content. It applies a set of embedded detectors tuned to a number of signal partitions. The detectors are based on the wavelet theory, whereby two different techniques are examined, one using local Fourier transform and the other using discrete wavelet transform. The detection statistics are computed so as to enable prewhitening of unknown colored noise and to allow for a constant false-alarm rate detection. An adapted segmentation of the signal is next obtained with a goal of finding the largest detection statistics within each segment of the partition. The detectors are tested using several underwater acoustic transient signals buried in ambient sea noise. PMID:15957761

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

    PubMed

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

    2009-10-01

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

  13. Efficient threshold for volumetric segmentation

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  14. 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.

  15. Segmental neurofibromatosis.

    PubMed

    Adigun, Chris G; Stein, Jennifer

    2011-01-01

    A 59-year-old man presented for evaluation and excision of non-tender, fleshy nodules that were arranged in a dermatomal distribution from the left side of the chest to the left axilla. A biopsy specimen of a nodule was consistent with a neurofibroma. Owing to the lack of other cutaneous findings, the lack of a family history of neurofibromatosis, and the dermatomal distribution of the neurofibromas, this patient met the criteria for a diagnosis of segmental neurofibromatosis (SNF) according to Riccardi's definition of SNF and classification of neurofibromatosis. Because the patient has no complications of neurofibromatosis 1 no medical treatment is required. PMID:22031651

  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. Integrated transducer for color distinction

    NASA Astrophysics Data System (ADS)

    Kato, Hisao; Kojima, Masahiko; Yoshida, Akira

    1983-06-01

    A method for fabricating the improved version of an integrated transducer for color distinction is proposed. It consists of three SnO2(n)-Si(n) photodiodes on a Si wafer and a trichromatic filter prepared by arranging filters of the three primary colors (Eastman Kodak gelatin filters; Nos. 47B, 58, and 25) on an infrared glass filter (Hoya Glass; B-460). Its photoelectric characteristics and dependence of error of color distinction on the dimension of the transducer are reported. The photodiodes employed in this conversion assembly are produced by the simple spray method and are most suitable for detecting the low illumination. Since this transducer adapts the trichromatic color resolution method, highly accurate color distinction is possible. With this type of transducer, three photodiodes sensitive to the primary colors, red, green, and blue, respectively, are arranged on a plane. An error in color distinction can occur due to the differences in the strength of the light incident upon the respective photodiodes. This problem is reduced by making the transducer more compact. Finally, 11 kinds of colors are discerned in this experiment as an application of the transducer.

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  1. 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.

  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. Colorful television

    NASA Astrophysics Data System (ADS)

    Carlowicz, Michael

    What are the challenges and rewards for American men and women of color who chose to become scientists? The Public Broadcasting Service intends to show us through an upcoming 6-hour documentary series entitled “Breakthrough: The Changing Face of Science in America.”

  4. Colorful Accounting

    ERIC Educational Resources Information Center

    Warrick, C. Shane

    2006-01-01

    As instructors of accounting, we should take an abstract topic (at least to most students) and connect it to content known by students to help increase the effectiveness of our instruction. In a recent semester, ordinary items such as colors, a basketball, and baseball were used to relate the subject of accounting. The accounting topics of account…

  5. Color measurements based on a color camera

    NASA Astrophysics Data System (ADS)

    Marszalec, Elzbieta A.; Pietikaeinen, Matti

    1997-08-01

    The domain of color camera applications is increasing all time due to recent progress in color machine vision research. Colorimetric measurement tasks are quite complex as the purpose of color measurement is to provide a quantitative evaluation of the phenomenon of colors as perceived by human vision. A proper colorimetric calibration of the color camera system is needed in order to make color a practical tool in machine vision. This paper discuses two approaches to color measurements based on a color camera and includes an overview of practical approaches to color camera calibration under unstable illumination conditions.

  6. Integrated segmentation of cellular structures

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

  7. Parallel Fuzzy Segmentation of Multiple Objects.

    PubMed

    Garduño, Edgar; Herman, Gabor T

    2008-01-01

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

  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. PMID:27557192

  9. Adaptive background model

    NASA Astrophysics Data System (ADS)

    Lu, Xiaochun; Xiao, Yijun; Chai, Zhi; Wang, Bangping

    2007-11-01

    An adaptive background model aiming at outdoor vehicle detection is presented in this paper. This model is an improved model of PICA (pixel intensity classification algorithm), it classifies pixels into K-distributions by color similarity, and then a hypothesis that the background pixel color appears in image sequence with a high frequency is used to evaluate all the distributions to determine which presents the current background color. As experiments show, the model presented in this paper is a robust, adaptive and flexible model, which can deal with situations like camera motions, lighting changes and so on.

  10. 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.

  11. 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.

  12. 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. PMID:20039220

  13. Eleven Colors That Are Almost Never Confused

    NASA Astrophysics Data System (ADS)

    Boynton, Robert M.

    1989-08-01

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

  14. 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.

  15. Multi-skin color clustering models for face detection

    NASA Astrophysics Data System (ADS)

    Zainuddin, Roziati; Naji, Sinan A.

    2010-02-01

    Automatic face detection in colored images is closely related to face recognition systems, as a preliminary critical required step, where it is necessary to search for the precise face location. We propose a reliable approach for skin color segmentation to detect human face in colored images under unconstrained scene conditions that overcoming the sensitivity to the variation in face size, pose, location, lighting conditions, and complex background. Our approach is based on building multi skin color clustering models using HSV color space, multi-level segmentation, and rule-based classifier. We proposed to use four skin color clustering models instead of single skin clustering model, namely: standard-skin model, shadow-skin model, light-skin model, high-red-skin model. We made an independent skin color clustering models by converting 3-D color space to 2-D without losing color information in order to find the classification boundaries for each skin color pattern class in 2-D. Once we find the classification boundaries, we process the input image with the first-level skin-color segmentation to produce four layers; each layer reflecting its skin-color clustering model. Then an iterative rule-based region grow is performed to create one solid region of interest which is presumed to be a face candidate region that will be passed to the second-level segmentation. In this approach we combine pixel-based segmentation and region-based segmentation using the four skin layers. We also propose skin-color correction (skin lighting) at shadow-skin layer to improve detection rate. In the second-level segmentation we use gray scale to segment the face candidate region into the most significant features using thresholding. Next step is to compute the X-Y-reliefs to locate the accurate position of facial features in each face candidate region and match it with our geometrical knowledge in order to classify the face candidate region to a face or non-face region. We present

  16. Digital image colorization based on distance transformation

    NASA Astrophysics Data System (ADS)

    Lagodzinski, Przemyslaw; Smolka, Bogdan

    2008-01-01

    Colorization is a term introduced by W. Markle1 to describe a computerized process for adding color to black and white pictures, movies or TV programs. The task involves replacing a scalar value stored at each pixel of the gray scale image by a vector in a three dimensional color space with luminance, saturation and hue or simply RGB. Since different colors may carry the same luminance value but vary in hue and/or saturation, the problem of colorization has no inherently "correct" solution. Due to these ambiguities, human interaction usually plays a large role. In this paper we present a novel colorization method that takes advantage of the morphological distance transformation, changes of neighboring pixel intensities and gradients to propagate the color within the gray scale image. The proposed method frees the user of segmenting the image, as color is provided simply by scribbles which are next automatically propagated within the image. The effectiveness of the algorithm allows the user to work interactively and to obtain the desired results promptly after providing the color scribbles. In the paper we show that the proposed method allows for high quality colorization results for still images.

  17. Color space conversion for linear color grading

    NASA Astrophysics Data System (ADS)

    Lee, Dah-Jye

    2000-10-01

    Color grading is an important process for various industries such as food processing, fruit and vegetable grading, etc. Quality and price are often determined by the color of product. For example, darker red color for apples means higher price. In color machine vision applications, image is acquired with a color CCD camera that outputs color information in three channels, red, gree, and blue. When grading color, these three primary colors must be processed to determine the color level for separation. A very popular color space conversion technique for color image processing is RGB-to-HSI, where HSI represents hue, saturation, and intensity, respectively. However, the conversion result is still 3D information that makes determining color grades very difficult. A new color space conversion technique that can be implemented for high-speed real-time processing for color grading is introduced in this paper. Depending on the application, different color space conversion equations must be used. The result of this technique is a simple one-dimensional array that represents different color levels. This linear array makes linear color grading adjustment possible.

  18. 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.

  19. 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.

  20. Segmentation of financial seals and its implementation on a DSP-based system

    NASA Astrophysics Data System (ADS)

    He, Jin; Liu, Tiegen; Guo, Jingjing; Zhang, Hao

    2009-11-01

    Automatic seal imprint identification is an important part of modern financial security. Accurate segmentation is the basis of correct identification. In this paper, a DSP (digital signal processor) based identification system was designed, and an adaptive algorithm was proposed to extract binary seal images from financial instruments. As the kernel of the identification system, a DSP chip of TMS320DM642 was used to implement image processing, controlling and coordinating works of each system module. The proposed algorithm consisted of three stages, including extraction of grayscale seal image, denoising and binarization. A grayscale seal image was extracted by color transform from a financial instrument image. Adaptive morphological operations were used to highlight details of the extracted grayscale seal image and smooth the background. After median filter for noise elimination, the filtered seal image was binarized by Otsu's method. The algorithm was developed based on the DSP development environment CCS and real-time operation system DSP/BIOS. To simplify the implementation of the proposed algorithm, the calibration of white balance and the coarse positioning of the seal imprint were implemented by TMS320DM642 controlling image acquisition. IMGLIB of TMS320DM642 was used for the efficiency improvement. The experiment result showed that financial seal imprints, even with intricate and dense strokes can be correctly segmented by the proposed algorithm. Adhesion and incompleteness distortions in the segmentation results were reduced, even when the original seal imprint had a poor quality.

  1. [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

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

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

  3. Cognitive aspects of color

    NASA Astrophysics Data System (ADS)

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

    1995-04-01

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

  4. 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. PMID:17218741

  5. 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.

  6. Visual enhancement of unmixed multispectral imagery using adaptive smoothing

    USGS Publications Warehouse

    Lemeshewsky, G.P.

    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.

  7. Using color management in color document processing

    NASA Astrophysics Data System (ADS)

    Nehab, Smadar

    1995-04-01

    Color Management Systems have been used for several years in Desktop Publishing (DTP) environments. While this development hasn't matured yet, we are already experiencing the next generation of the color imaging revolution-Device Independent Color for the small office/home office (SOHO) environment. Though there are still open technical issues with device independent color matching, they are not the focal point of this paper. This paper discusses two new and crucial aspects in using color management in color document processing: the management of color objects and their associated color rendering methods; a proposal for a precedence order and handshaking protocol among the various software components involved in color document processing. As color peripherals become affordable to the SOHO market, color management also becomes a prerequisite for common document authoring applications such as word processors. The first color management solutions were oriented towards DTP environments whose requirements were largely different. For example, DTP documents are image-centric, as opposed to SOHO documents that are text and charts centric. To achieve optimal reproduction on low-cost SOHO peripherals, it is critical that different color rendering methods are used for the different document object types. The first challenge in using color management of color document processing is the association of rendering methods with object types. As a result of an evolutionary process, color matching solutions are now available as application software, as driver embedded software and as operating system extensions. Consequently, document processing faces a new challenge, the correct selection of the color matching solution while avoiding duplicate color corrections.

  8. Efficient lossless coding model for medical images by applying integer-to-integer wavelet transform to segmented images

    NASA Astrophysics Data System (ADS)

    Yang, Shuyu; Zamora, Gilberto; Wilson, Mark; Mitra, Sunanda

    2000-06-01

    Existing lossless coding models yield only up to 3:1 compression. However, a much higher lossless compression can be achieved for certain medical images when the images are segmented prior to applying integer to integer wavelet transform and lossless coding. The methodology used in this research work is to apply a contour detection scheme to segment the image first. The segmented image is then wavelet transformed with integer to integer mapping to obtain a lower weighted entropy than the original. An adaptive arithmetic model is then applied to code the transformed image losslessly. For the male visible human color image set, the overall average lossless compression using the above scheme is around 10:1 whereas the compression ratio of an individual slice can be as high as 16:1. The achievable compression ratio depends on the actual bit rate of the segmented images attained by lossless coding as well as the compression obtainable from segmentation alone. The computational time required by the entire process is fast enough for application on large medical images.

  9. 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...

  10. 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.

  11. Early Visual Mechanisms Do Not Contribute to Synesthetic Color Experience

    PubMed Central

    Hong, Sang Wook; Blake, Randolph

    2008-01-01

    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 canceling 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. PMID:18316107

  12. 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.

  13. 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. PMID:22128304

  14. 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

  15. 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.

  16. Urine - abnormal color

    MedlinePlus

    ... straw-yellow. Abnormally colored urine may be cloudy, dark, or blood-colored. Causes Abnormal urine color may ... red blood cells, or mucus in the urine. Dark brown but clear urine is a sign of ...

  17. Modeling color percepts of dichromats.

    PubMed

    Wachtler, Thomas; Dohrmann, Ulrike; Hertel, Rainer

    2004-11-01

    Protanopes and deuteranopes, despite lacking a chromatic dimension at the receptor level, use the color terms "red" and "green", together with "blue" and "yellow", to describe their color percepts. Color vision models proposed so far fail to account for these findings in dichromats. We confirmed, by the method of hue scaling, the consistent use of these color terms, as well as their dependence on intensity, in subjects shown to have only a single X-chromosomal opsin gene each. We present a model for the processing of photoreceptor signals which, under physiologically plausible assumptions, achieves a trichromat-like representation of dichromatic receptor signals. Key feature of the dichromat model is the processing of the photoreceptor signals in parallel channels with different gains and nonlinearities. In this way, the two-dimensional receptor signals are represented on a manifold in a higher-dimensional space, supporting categorization for efficient image segmentation. Introducing a third cone opsin yields a model that explains normal, trichromat hue scaling. PMID:15342228

  18. Segment alignment control system

    NASA Technical Reports Server (NTRS)

    Aubrun, JEAN-N.; Lorell, Ken R.

    1988-01-01

    The segmented primary mirror for the LDR will require a special segment alignment control system to precisely control the orientation of each of the segments so that the resulting composite reflector behaves like a monolith. The W.M. Keck Ten Meter Telescope will utilize a primary mirror made up of 36 actively controlled segments. Thus the primary mirror and its segment alignment control system are directly analogous to the LDR. The problems of controlling the segments in the face of disturbances and control/structures interaction, as analyzed for the TMT, are virtually identical to those for the LDR. The two systems are briefly compared.

  19. Sipunculans and segmentation

    PubMed Central

    Kristof, Alen; Brinkmann, Nora

    2009-01-01

    Comparative molecular, developmental and morphogenetic analyses show that the three major segmented animal groups—Lophotrochozoa, Ecdysozoa and Vertebrata—use a wide range of ontogenetic pathways to establish metameric body organization. Even in the life history of a single specimen, different mechanisms may act on the level of gene expression, cell proliferation, tissue differentiation and organ system formation in individual segments. Accordingly, in some polychaete annelids the first three pairs of segmental peripheral neurons arise synchronously, while the metameric commissures of the ventral nervous system form in anterior-posterior progression. Contrary to traditional belief, loss of segmentation may have occurred more often than commonly assumed, as exemplified in the sipunculans, which show remnants of segmentation in larval stages but are unsegmented as adults. The developmental plasticity and potential evolutionary lability of segmentation nourishes the controversy of a segmented bilaterian ancestor versus multiple independent evolution of segmentation in respective metazoan lineages. PMID:19513266

  20. Segmented trapped vortex cavity

    NASA Technical Reports Server (NTRS)

    Grammel, Jr., Leonard Paul (Inventor); Pennekamp, David Lance (Inventor); Winslow, Jr., Ralph Henry (Inventor)

    2010-01-01

    An annular trapped vortex cavity assembly segment comprising includes a cavity forward wall, a cavity aft wall, and a cavity radially outer wall there between defining a cavity segment therein. A cavity opening extends between the forward and aft walls at a radially inner end of the assembly segment. Radially spaced apart pluralities of air injection first and second holes extend through the forward and aft walls respectively. The segment may include first and second expansion joint features at distal first and second ends respectively of the segment. The segment may include a forward subcomponent including the cavity forward wall attached to an aft subcomponent including the cavity aft wall. The forward and aft subcomponents include forward and aft portions of the cavity radially outer wall respectively. A ring of the segments may be circumferentially disposed about an axis to form an annular segmented vortex cavity assembly.

  1. [Bilateral segmental neurofibromatosis].

    PubMed

    Rose, I; Vakilzadeh, F

    1991-12-01

    Segmental neurofibromatosis is a rare type of neurofibromatosis. We report a case of bilateral manifestation, review the literature on this extremely uncommon variant, and discuss the possible causative mechanisms and the genetic risk of segmental neurofibromatosis. PMID:1765491

  2. 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...

  3. [Segmentation of Winter Wheat Canopy Image Based on Visual Spectral and Random Forest Algorithm].

    PubMed

    Liu, Ya-dong; Cui, Ri-xian

    2015-12-01

    Digital image analysis has been widely used in non-destructive monitoring of crop growth and nitrogen nutrition status due to its simplicity and efficiency. It is necessary to segment winter wheat plant from soil background for accessing canopy cover, intensity level of visible spectrum (R, G, and B) and other color indices derived from RGB. In present study, according to the variation in R, G, and B components of sRGB color space and L*, a*, and b* components of CIEL* a* b* color space between wheat plant and soil background, the segmentation of wheat plant from soil background were conducted by the Otsu's method based on a* component of CIEL* a* b* color space, and RGB based random forest method, and CIEL* a* b* based random forest method, respectively. Also the ability to segment wheat plant from soil background was evaluated with the value of segmentation accuracy. The results showed that all three methods had revealed good ability to segment wheat plant from soil background. The Otsu's method had lowest segmentation accuracy in comparison with the other two methods. There were only little difference in segmentation error between the two random forest methods. In conclusion, the random forest method had revealed its capacity to segment wheat plant from soil background with only the visual spectral information of canopy image without any color components combinations or any color space transformation. PMID:26964234

  4. Possible and Impossible Segments.

    ERIC Educational Resources Information Center

    Walker, Rachel; Pullum, Geoffrey K.

    1999-01-01

    Examines the relationship between phonetic possibility and phonological permissibility of segment types. Specific focus is on whether there are any phonetically impossible segments phonologically permissible, and whether there are any phonetically possible segments phonologically impermissable. Examines the case of nasality spreading in Sudanese…

  5. Segmentation of prostate cancer tissue microarray images

    NASA Astrophysics Data System (ADS)

    Cline, Harvey E.; Can, Ali; Padfield, Dirk

    2006-02-01

    Prostate cancer is diagnosed by histopathology interpretation of hematoxylin and eosin (H and E)-stained tissue sections. Gland and nuclei distributions vary with the disease grade. The morphological features vary with the advance of cancer where the epithelial regions grow into the stroma. An efficient pathology slide image analysis method involved using a tissue microarray with known disease stages. Digital 24-bit RGB images were acquired for each tissue element on the slide with both 10X and 40X objectives. Initial segmentation at low magnification was accomplished using prior spectral characteristics from a training tissue set composed of four tissue clusters; namely, glands, epithelia, stroma and nuclei. The segmentation method was automated by using the training RGB values as an initial guess and iterating the averaging process 10 times to find the four cluster centers. Labels were assigned to the nearest cluster center in red-blue spectral feature space. An automatic threshold algorithm separated the glands from the tissue. A visual pseudo color representation of 60 segmented tissue microarray image was generated where white, pink, red, blue colors represent glands, epithelia, stroma and nuclei, respectively. The higher magnification images provided refined nuclei morphology. The nuclei were detected with a RGB color space principle component analysis that resulted in a grey scale image. The shape metrics such as compactness, elongation, minimum and maximum diameters were calculated based on the eigenvalues of the best-fitting ellipses to the nuclei.

  6. 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.

  7. A novel weighted-direction color interpolation

    NASA Astrophysics Data System (ADS)

    Tao, Jin-you; Yang, Jianfeng; Xue, Bin; Liang, Xiaofen; Qi, Yong-hong; Wang, Feng

    2013-08-01

    A digital camera capture images by covering the sensor surface with a color filter array (CFA), only get a color sample at pixel location. Demosaicking is a process by estimating the missing color components of each pixel to get a full resolution image. In this paper, a new algorithm based on edge adaptive and different weighting factors is proposed. Our method can effectively suppress undesirable artifacts. Experimental results based on Kodak images show that the proposed algorithm obtain higher quality images compared to other methods in numerical and visual aspects.

  8. Coloring random graphs and maximizing local diversity.

    PubMed

    Bounkong, S; van Mourik, J; Saad, D

    2006-11-01

    We study a variation of the graph coloring problem on random graphs of finite average connectivity. Given the number of colors, we aim to maximize the number of different colors at neighboring vertices (i.e., one edge distance) of any vertex. Two efficient algorithms, belief propagation and Walksat, are adapted to carry out this task. We present experimental results based on two types of random graphs for different system sizes and identify the critical value of the connectivity for the algorithms to find a perfect solution. The problem and the suggested algorithms have practical relevance since various applications, such as distributed storage, can be mapped onto this problem. PMID:17280022

  9. A Retinal Mechanism Inspired Color Constancy Model.

    PubMed

    Zhang, Xian-Shi; Gao, Shao-Bing; Li, Ruo-Xuan; Du, Xin-Yu; Li, Chao-Yi; Li, Yong-Jie

    2016-03-01

    In this paper, we propose a novel model for the computational color constancy, inspired by the amazing ability of the human vision system (HVS) to perceive the color of objects largely constant as the light source color changes. The proposed model imitates the color processing mechanisms in the specific level of the retina, the first stage of the HVS, from the adaptation emerging in the layers of cone photoreceptors and horizontal cells (HCs) to the color-opponent mechanism and disinhibition effect of the non-classical receptive field in the layer of retinal ganglion cells (RGCs). In particular, HC modulation provides a global color correction with cone-specific lateral gain control, and the following RGCs refine the processing with iterative adaptation until all the three opponent channels reach their stable states (i.e., obtain stable outputs). Instead of explicitly estimating the scene illuminant(s), such as most existing algorithms, our model directly removes the effect of scene illuminant. Evaluations on four commonly used color constancy data sets show that the proposed model produces competitive results in comparison with the state-of-the-art methods for the scenes under either single or multiple illuminants. The results indicate that single opponency, especially the disinhibitory effect emerging in the receptive field's subunit-structured surround of RGCs, plays an important role in removing scene illuminant(s) by inherently distinguishing the spatial structures of surfaces from extensive illuminant(s). PMID:26766375

  10. Multi-segment detector

    NASA Technical Reports Server (NTRS)

    George, Peter K. (Inventor)

    1978-01-01

    A plurality of stretcher detector segments are connected in series whereby detector signals generated when a bubble passes thereby are added together. Each of the stretcher detector segments is disposed an identical propagation distance away from passive replicators wherein bubbles are replicated from a propagation path and applied, simultaneously, to the stretcher detector segments. The stretcher detector segments are arranged to include both dummy and active portions thereof which are arranged to permit the geometry of both the dummy and active portions of the segment to be substantially matched.

  11. Segmentation and classification of dermatological lesions

    NASA Astrophysics Data System (ADS)

    Sáez, Aurora; Acha, Begoña; Serrano, Carmen

    2010-03-01

    Certain skin diseases are chronic, inflammatory and without cure. However, there are many treatment options that can clear them for a period of time. Measuring their severity and assessing their extent, is a fundamental issue to determine the efficacy of the treatment under test. Two of the most important parameters of severity assessment are Erythema (redness) and Scaliness. Physicians classify these parameters into several grades by visual grading method. In this paper a color image segmentation and classification algorithm is developed to obtain an assessment of erythema and scaliness of dermatological lesions. Color digital photographs taken under an acquisition protocol form the database. Difference between green band and blue band of images in RGB color space shows two modes (healthy skin and lesion) with clear separation. Otsu's method is applied to this difference in order to isolate the lesion. After the skin disease is segmented, some color and texture features are calculated and they are the inputs to a Fuzzy-ARTMAP neural network. The neural network classifies them into the five grades of erythema and the five grades of scaliness. The method has been tested with 31 images with a success percentage of 83.87 % when the images are classified in erythema, and 77.42 % for scaliness classification.

  12. Object-level Segmentation of RGBD Data

    NASA Astrophysics Data System (ADS)

    Huang, H.; Jiang, H.; Brenner, C.; Mayer, H.

    2014-08-01

    We propose a novel method to segment Microsoft™Kinect data of indoor scenes with the emphasis on freeform objects. We use the full 3D information for the scene parsing and the segmentation of potential objects instead of treating the depth values as an additional channel of the 2D image. The raw RGBD image is first converted to a 3D point cloud with color. We then group the points into patches, which are derived from a 2D superpixel segmentation. With the assumption that every patch in the point cloud represents (a part of) the surface of an underlying solid body, a hypothetical quasi-3D model - the "synthetic volume primitive" (SVP) is constructed by extending the patch with a synthetic extrusion in 3D. The SVPs vote for a common object via intersection. By this means, a freeform object can be "assembled" from an unknown number of SVPs from arbitrary angles. Besides the intersection, two other criteria, i.e., coplanarity and color coherence, are integrated in the global optimization to improve the segmentation. Experiments demonstrate the potential of the proposed method.

  13. Chips of many colors

    SciTech Connect

    Dickens, M.W.; Dorie, L.A.

    1982-07-01

    A large number of available color display tools generally fall into three categories. Intelligent terminals offer a wide range of color grpahics capability but require extensive software for specific applications. Large turn-key graphics systems, with color display consoles controlled by software, were made for electronic design. In color CAD workstations, color graphics is under hardware control and offers specific features for IC design. The authors look at the various colour graphics systems, and their advantages in VLSI chip design.

  14. Unsupervised flaw segmentation in textile materials under visible and NIR illumination

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

    An unsupervised novelty detection method for automatic flaw segmentation in textile materials that has no need of any defect-free references or a training stage is presented in this paper. The algorithm is based on the structural feature extraction of the weave repeat from the Fourier transform of the sample image. These features are used to define a set of multiresolution bandpass filters adapted to the fabric structure that operate in the Fourier domain. Inverse Fourier transformation, binarization and merging of the information obtained at different scales lead to the output image that contains flaws segmented from the fabric background. The whole process is fully automatic and can be implemented either optical or electronically. Fabrics having a superstructure of colored squares, bands, etc. superimposed to the basic web structure can be advantageously analyzed using NIR illumination and a camera sensitive to this region of the spectrum. The contrast reduction of the superstructure signal in the NIR image facilitates fabric structure inspection and defect segmentation. Underdetection and misdetection errors can be noticeably reduced in comparison with the inspection performed under visible illumination. Experimental results are presented and discussed for a variety of fabrics and defects.

  15. 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.

  16. Segmentation of moving object in complex environment

    NASA Astrophysics Data System (ADS)

    Yong, Yang; Wang, Jingru; Zhang, Qiheng

    2005-02-01

    This paper presents a new automatic image segmentation method for segmenting moving object in complex environment by combining the motion information with edge information. We propose an adaptive optical flow method based on the Horn-Schunck algorithm to estimate the optical flow field. Our method puts different smoothness constraints on different directions and optical flow constraint is used according to the gradient magnitude. Canny edge detector can obtain the most edge information but miss some pixels. In order to restore these missing pixels the edge has a growing based on the continuity of optical flow field. Next, by remaining the block that has the longest edge could delete the noise in the background, and then the last segmentation result is obtained. The experimental result demonstrates that this method can segment the moving object in complex environment precisely.

  17. Vane segment support and alignment device

    DOEpatents

    McLaurin, Leroy Dixon; Sizemore, John Derek

    1999-01-01

    A support and alignment assembly for supporting and aligning a vane segment is provided. The support and alignment assembly comprises a torque plate which defines an opening for receiving an eccentric pin and a locking end member for receiving a lock socket member. An eccentric pin adjustably supported by the torque plate opening for supporting and aligning a vane segment is provided. A lock socket member adapted to securely receive the eccentric pin and rotated therewith, and adjustably engage the torque plate locking end is provided. The lock socket member receives the eccentric pin, such that when the eccentric pin is adjusted to align the vane segment, the lock socket member engages the torque plate locking end to secure the vane segment in the desired position.

  18. 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.

  19. 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. PMID:25700436

  20. 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.

  1. 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.

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

    PubMed Central

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

    2015-01-01

    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. R2-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. PMID:26691598

  3. Military display market segment: helicopters

    NASA Astrophysics Data System (ADS)

    Desjardins, Daniel D.; Hopper, Darrel G.

    2004-09-01

    The military display market is analyzed in terms of one of its segments: helicopter displays. Parameters requiring special consideration, to include luminance ranges, contrast ratio, viewing angles, and chromaticity coordinates, are examined. Performance requirements for rotary-wing displays relative to several premier applications are summarized. Display sizes having aggregate defense applications of 5,000 units or greater and having DoD applications across 10 or more platforms, are tabulated. The issue of size commonality is addressed where distribution of active area sizes across helicopter platforms, individually, in groups of two through nine, and ten or greater, is illustrated. Rotary-wing displays are also analyzed by technology, where total quantities of such displays are broken out into CRT, LCD, AMLCD, EM, LED, Incandescent, Plasma and TFEL percentages. Custom, versus Rugged commercial, versus commercial off-the-shelf designs are contrasted. High and low information content designs are identified. Displays for several high-profile military helicopter programs are discussed, to include both technical specifications and program history. The military display market study is summarized with breakouts for the helicopter market segment. Our defense-wide study as of March 2004 has documented 1,015,494 direct view and virtual image displays distributed across 1,181 display sizes and 503 weapon systems. Helicopter displays account for 67,472 displays (just 6.6% of DoD total) and comprise 83 sizes (7.0% of total DoD) in 76 platforms (15.1% of total DoD). Some 47.6% of these rotary-wing applications involve low information content displays comprising just a few characters in one color; however, as per fixed-wing aircraft, the predominant instantiation involves higher information content units capable of showing changeable graphics, color and video.

  4. 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.

  5. 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)

  6. Deformable segmentation via sparse shape representation.

    PubMed

    Zhang, Shaoting; Zhan, Yiqiang; Dewan, Maneesh; Huang, Junzhou; Metaxas, Dimitris N; Zhou, Xiang Sean

    2011-01-01

    Appearance and shape are two key elements exploited in medical image segmentation. However, in some medical image analysis tasks, appearance cues are weak/misleading due to disease/artifacts and often lead to erroneous segmentation. In this paper, a novel deformable model is proposed for robust segmentation in the presence of weak/misleading appearance cues. Owing to the less trustable appearance information, this method focuses on the effective shape modeling with two contributions. First, a shape composition method is designed to incorporate shape prior on-the-fly. Based on two sparsity observations, this method is robust to false appearance information and adaptive to statistically insignificant shape modes. Second, shape priors are modeled and used in a hierarchical fashion. More specifically, by using affinity propagation method, our deformable surface is divided into multiple partitions, on which local shape models are built independently. This scheme facilitates a more compact shape prior modeling and hence a more robust and efficient segmentation. Our deformable model is applied on two very diverse segmentation problems, liver segmentation in PET-CT images and rodent brain segmentation in MR images. Compared to state-of-art methods, our method achieves better performance in both studies. PMID:21995060

  7. Texture descriptors based on adaptive neighborhoods for classification of pigmented skin lesions

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

    Different texture descriptors are proposed for the automatic classification of skin lesions from dermoscopic images. They are based on color texture analysis obtained from (1) color mathematical morphology (MM) and Kohonen self-organizing maps (SOMs) or (2) local binary patterns (LBPs), computed with the use of local adaptive neighborhoods of the image. Neither of these two approaches needs a previous segmentation process. In the first proposed descriptor, the adaptive neighborhoods are used as structuring elements to carry out adaptive MM operations which are further combined by using Kohonen SOM; this has been compared with a nonadaptive version. In the second one, the adaptive neighborhoods enable geometrical feature maps to be defined, from which LBP histograms are computed. This has also been compared with a classical LBP approach. A receiver operating characteristics analysis of the experimental results shows that the adaptive neighborhood-based LBP approach yields the best results. It outperforms the nonadaptive versions of the proposed descriptors and the dermatologists' visual predictions.

  8. 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 ...

  9. 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 ...

  10. What color is it?

    NASA Astrophysics Data System (ADS)

    Eschbach, Reiner; Sharma, Gaurav; Unal, Gozde B.

    2005-01-01

    Color management allows the deterministic handling of color data from input to output. This, of course, assumes that the first digital representation of our data is the "correct" color. It assumes that we did not make any errors in the input definitions, did not use wrong color input profiles, captured the user's intent, or fell prey to a host of other potential problems. After we have made those assumptions, we now can deterministically transfer the color from one place to another. Note that there is a big difference between "reproducing" one color at a different location and "deterministically transferring one set of color data to another location". The deterministic transfer is limited to the small set of physical metrics we decided to call "color". All other components of color are ignored.

  11. What color is it?

    NASA Astrophysics Data System (ADS)

    Eschbach, Reiner; Sharma, Gaurav; Unal, Gozde B.

    2004-12-01

    Color management allows the deterministic handling of color data from input to output. This, of course, assumes that the first digital representation of our data is the "correct" color. It assumes that we did not make any errors in the input definitions, did not use wrong color input profiles, captured the user's intent, or fell prey to a host of other potential problems. After we have made those assumptions, we now can deterministically transfer the color from one place to another. Note that there is a big difference between "reproducing" one color at a different location and "deterministically transferring one set of color data to another location". The deterministic transfer is limited to the small set of physical metrics we decided to call "color". All other components of color are ignored.

  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. Color rendering indices in global illumination methods

    NASA Astrophysics Data System (ADS)

    Geisler-Moroder, David; Dür, Arne

    2009-02-01

    Human perception of material colors depends heavily on the nature of the light sources used for illumination. One and the same object can cause highly different color impressions when lit by a vapor lamp or by daylight, respectively. Based on state-of-the-art colorimetric methods we present a modern approach for calculating color rendering indices (CRI), which were defined by the International Commission on Illumination (CIE) to characterize color reproduction properties of illuminants. We update the standard CIE method in three main points: firstly, we use the CIELAB color space, secondly, we apply a Bradford transformation for chromatic adaptation, and finally, we evaluate color differences using the CIEDE2000 total color difference formula. Moreover, within a real-world scene, light incident on a measurement surface is composed of a direct and an indirect part. Neumann and Schanda1 have shown for the cube model that interreflections can influence the CRI of an illuminant. We analyze how color rendering indices vary in a real-world scene with mixed direct and indirect illumination and recommend the usage of a spectral rendering engine instead of an RGB based renderer for reasons of accuracy of CRI calculations.

  14. From A Physical Color Stimulus To A Psychological Color Percept

    NASA Astrophysics Data System (ADS)

    Sporea, Dan G.; Tonnquist, Gunnar

    1989-08-01

    The paper discusses the complexity of color vision in humans, considering the main aspects involved: the physical aspect, the psychophysical aspect, the physiological aspect and the psychological aspect. The meanings of the term color associated to each such aspect (asfor example, color stimulus, color valence, neural color signal and color percept) are introduced. Some types of color defective vision, relevant for color display users, are indicated. The methods to generate color stimuli in modern display devices, employing different technologies, are compared.

  15. 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.

  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. Trichromatic opponent color classification.

    PubMed

    Chichilnisky, E J; Wandell, B A

    1999-10-01

    Stimuli varying in intensity and chromaticity, presented on numerous backgrounds, were classified into red/green, blue/yellow and white/black opponent color categories. These measurements revealed the shapes of the boundaries that separate opponent colors in three-dimensional color space. Opponent color classification boundaries were generally not planar, but their shapes could be summarized by a piecewise linear model in which increment and decrement color signals are combined with different weights at two stages to produce opponent color sensations. The effect of background light on classification was largely explained by separate gain changes in increment and decrement cone signals. PMID:10615508

  18. 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.

  19. 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

  20. Color contrast enhancement method of infrared polarization fused image

    NASA Astrophysics Data System (ADS)

    Yang, Fan; Xie, Chen

    2015-10-01

    As the traditional color fusion method based on color transfer algorithm has an issue that the color of target and background is similar. A kind of infrared polarization image color fusion method based on color contrast enhancement was proposed. Firstly the infrared radiation intensity image and the polarization image were color fused, and then color transfer technology was used between color reference image and initial fused image in the YCbCr color space. Secondly Otsu segmentation method was used to extract the target area image from infrared polarization image. Lastly the H,S,I component of the color fusion image which obtained by color transfer was adjusted to obtain the final fused image by using target area in the HSI space. Experimental results show that, the fused result which obtained by the proposed method is rich in detail and makes the contrast of target and background more outstanding. And then the ability of target detection and identification can be improved by the method.

  1. 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

  2. Automatic image segmentation by dynamic region merging.

    PubMed

    Peng, Bo; Zhang, Lei; Zhang, David

    2011-12-01

    This paper addresses the automatic image segmentation problem in a region merging style. With an initially oversegmented image, in which many regions (or superpixels) with homogeneous color are detected, an image segmentation is performed by iteratively merging the regions according to a statistical test. There are two essential issues in a region-merging algorithm: order of merging and the stopping criterion. In the proposed algorithm, these two issues are solved by a novel predicate, which is defined by the sequential probability ratio test and the minimal cost criterion. Starting from an oversegmented image, neighboring regions are progressively merged if there is an evidence for merging according to this predicate. We show that the merging order follows the principle of dynamic programming. This formulates the image segmentation as an inference problem, where the final segmentation is established based on the observed image. We also prove that the produced segmentation satisfies certain global properties. In addition, a faster algorithm is developed to accelerate the region-merging process, which maintains a nearest neighbor graph in each iteration. Experiments on real natural images are conducted to demonstrate the performance of the proposed dynamic region-merging algorithm. PMID:21609885

  3. Light, Color, and Mirrors.

    ERIC Educational Resources Information Center

    Tiburzi, Brian; Tamborino, Laurie; Parker, Gordon A.

    2000-01-01

    Describes an exercise in which students can use flashlights, mirrors, and colored paper to discover scientific principles regarding optics. Addresses the concepts of angles of incidence and reflection, colored vs. white light, and mirror images. (WRM)

  4. Tooth - abnormal colors

    MedlinePlus

    ... things can cause tooth discoloration. The change in color may affect the entire tooth, or appear as spots or ... the tooth enamel. Your genes affect your tooth color. Other things ... include: Congenital diseases Environmental factors Infections ...

  5. Coloring with defect

    SciTech Connect

    Cowen, L.J.; Goddard, W.; Jesurum, C.E.

    1997-06-01

    An (ordinary vertex) coloring is a partition of the vertices of a graph into independent sets. The chromatic number is the minimum number of colors needed to produce such a partition. This paper considers a relaxation of coloring in which the color classes partition the vertices into subgraphs of degree at most d. d is called the defect of the coloring. A graph which admits a vertex coloring into k color classes, where each vertex is adjacent to at most d self-colored neighbors is said to be (k, d) colorable. We consider defective coloring on graphs of bounded degree, bounded genus, and bounded chromatic number, presenting complexity results and algorithms. For bounded degree graphs, a classic result of Lovasz yields a (k, [{Delta}/k]) coloring for graphs with E edges of maximum degree {Delta} in O({Delta}E) time. For graphs of bounded genus, (2, d), for d > 0 and (3,1)-coloring are proved NP-Complete, even for planar graphs. Results of easily can be transformed to (3,2) color any planar graph in linear time. We show that any toroidal graph is (3,2)- and (5, 1)-colorable, and quadratic-time algorithms are presented that find the colorings. For higher surfaces, we give a linear time algorithm to (3, {radical}12{gamma} + 6) color a graph of genus {gamma} > 2. It is also shown that any graph of genus {gamma} is ({radical}12{gamma}/(d + 1) + 6, d) colorable, and an O(d{radical}{gamma}E + V) algorithm is presented that finds the coloring. These bounds are within a constant factor of what is required for the maximum clique embeddable in the surface. Reductions from ordinary vertex coloring show that (k, d) coloring is NP-complete, and there exists an c > 0 such that no polynomial time algorithm can n{sup {epsilon}}-approximate the defective chromatic number unless P = NP. Most approximation algorithms to approximately color 3-colorable graphs can be extend to allow defects.

  6. 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. PMID:22418343

  7. 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.

  8. 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

  9. 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.

  10. 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…

  11. Sweetpotato Color Analyses

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Color is an important attribute that contributes to the appearance of a sweetpotato genotype. A consumer uses color, along with geometric attributes (e.g., gloss, luster, sheen, texture, opaqueness, shape), to subjectively evaluate the appearance of a sweetpotato root. Color can be quantified by t...

  12. 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)

  13. 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…

  14. 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.

  15. Skew Divergence-Based Fuzzy Segmentation of Rock Samples

    NASA Astrophysics Data System (ADS)

    Carvalho, Bruno M.; Garduño, Edgar; Santos, Iraçú O.

    2014-03-01

    Digital image segmentation is a process in which one assigns distinct labels to different objects in a digital image. The MOFS (Multi Object Fuzzy Segmentation) algorithm has been successfully applied to the segmentation of images from several modalities. However, the traditional MOFS algorithm fails when applied to images whose composing objects are characterized by textures whose patterns cannot be successfully described by simple statistics computed over a very restricted area. Here, we present an extension of the MOFS algorithm that achieves the segmentation of textures by employing adaptive affinity functions that use the Skew Divergence as a measure of distance between two distributions. These affinity functions are called adaptive because their associated area (neighborhood) changes according to the characteristics of the texture being processed. We performed experiments on mosaic images composed by combining rock sample images which show the effectiveness of the adaptive skew divergence based fuzzy affinity functions.

  16. Textural segmentation, second-order statistics, and textural elements.

    PubMed

    Beck, J

    1983-01-01

    Beck (1972, 1973) hypothesized that textural segmentation occurs strongly on the basis of simple properties such as brightness, color, size, and the slopes of contours and lines of the elemental descriptors of a texture or textural elements. The experiment reported supports the hypothesis that specific stimulus features, rather than second-order statistics, account for textural segmentation. The results agree with Julesz (1981a,b) who has reported evidence disproving his original conjecture of the importance of second-order statistics. Julesz (1981a,b) now hypothesizes textural segmentation to be a function of local features which he called textons. Textons are features that give textural segmentation when textures have identical second-order statistics. The two hypotheses are to date in complete agreement on the stimulus features producing textural segmentation, and the experiment reported is consistent with both. PMID:6626590

  17. Association of seed dormancy with red pericarp color in weedy rice arises from pleiotropy of a predicted transcription factor

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Seed dormancy has been associated with grain color in wheat and rice, with the red colored genotypes being more dormant than the white colored ones. However, it remains uncertain if the association arises from pleiotropy or linkage. We introduced a segment of chromosome harboring a cluster of quanti...

  18. Industrial Color Inspection

    NASA Astrophysics Data System (ADS)

    McCamy, C. S.

    1986-10-01

    Color is a very important property of many products and an essential feature of some. The commercial value of color is evident in the fact that customers reject product that is satisfactory in every other way, but is not the right color. Color isrumerically specified, measured, and controlled just as length or weight are. It has three dimensions: Hue, Value, and Chroma, and may be represented in a three-dimensional space. Colors of objects depend on the illumination and pairs of colors may match in one light but not in another. Controlled illumination is required for color matching. Illuminants were standardized by the International Commission on Illumination (CIE). As a basis for color measurement, the CIE adopted three spectral sensitivity functions representing a standard observer. Color may be measured by instruments using standard illumination and simulating the standard observer. It is better to measure spectral reflectance or transmittance and compute colorimetric quantities. Color may be inspected on a production line and the data obtained can be used to control the process. When production cannot be controlled as precisely as required, product may be sorted by color.

  19. 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.

  20. True Colors Shining Through

    NASA Technical Reports Server (NTRS)

    2004-01-01

    This image mosaic illustrates how scientists use the color calibration targets (upper left) located on both Mars Exploration Rovers to fine-tune the rovers' sense of color. In the center, spectra, or light signatures, acquired in the laboratory of the colored chips on the targets are shown as lines. Actual data from Mars Exploration Rover Spirit's panoramic camera is mapped on top of these lines as dots. The plot demonstrates that the observed colors of Mars match the colors of the chips, and thus approximate the red planet's true colors. This finding is further corroborated by the picture taken on Mars of the calibration target, which shows the colored chips as they would appear on Earth.

  1. Automatic and Quantitative Measurement of Collagen Gel Contraction Using Model-Guided Segmentation.

    PubMed

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

    2013-08-01

    Quantitative measurement of collagen gel contraction plays a critical role in the field of tissue engineering because it provides spatial-temporal assessment (e.g., changes of gel area and diameter during the contraction process) reflecting the cell behaviors and tissue material properties. So far the assessment of collagen gels relies on manual segmentation, which is time-consuming and suffers from serious intra- and inter-observer variability. In this study, we propose an automatic method combining various image processing techniques to resolve these problems. The proposed method first detects the maximal feasible contraction range of circular references (e.g., culture dish) and avoids the interference of irrelevant objects in the given image. Then, a three-step color conversion strategy is applied to normalize and enhance the contrast between the gel and background. We subsequently introduce a deformable circular model (DCM) which utilizes regional intensity contrast and circular shape constraint to locate the gel boundary. An adaptive weighting scheme was employed to coordinate the model behavior, so that the proposed system can overcome variations of gel boundary appearances at different contraction stages. Two measurements of collagen gels (i.e., area and diameter) can readily be obtained based on the segmentation results. Experimental results, including 120 gel images for accuracy validation, showed high agreement between the proposed method and manual segmentation with an average dice similarity coefficient larger than 0.95. The results also demonstrated obvious improvement in gel contours obtained by the proposed method over two popular, generic segmentation methods. PMID:24092954

  2. Relating color working memory and color perception.

    PubMed

    Allred, Sarah R; Flombaum, Jonathan I

    2014-11-01

    Color is the most frequently studied feature in visual working memory (VWM). Oddly, much of this work de-emphasizes perception, instead making simplifying assumptions about the inputs served to memory. We question these assumptions in light of perception research, and we identify important points of contact between perception and working memory in the case of color. Better characterization of its perceptual inputs will be crucial for elucidating the structure and function of VWM. PMID:25038028

  3. 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.

  4. 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

  5. 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.

  6. 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…

  7. 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.

  8. 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.

  9. On the purposes of color for living beings: toward a theory of color organization.

    PubMed

    Pinna, Baingio; Reeves, Adam

    2015-01-01

    Phylogenetic and paleontological evidence indicates that in the animal kingdom the ability to perceive colors evolved independently several times over the course of millennia. This implies a high evolutionary neural investment and suggests that color vision provides some fundamental biological benefits. What are these benefits? Why are some animals so colorful? What are the adaptive and perceptual meanings of polychromatism? We suggest that in addition to the discrimination of light and surface chromaticity, sensitivity to color contributes to the whole, the parts and the fragments of perceptual organization. New versions of neon color spreading and the watercolor illusion indicate that the visual purpose of color in humans is threefold: to inter-relate each chromatic component of an object, thus favoring the emergence of the whole; to support a part-whole organization in which components reciprocally enhance each other by amodal completion; and, paradoxically, to reveal fragments and hide the whole-that is, there is a chromatic parceling-out process of separation, division, and fragmentation of the whole. The evolution of these contributions of color to organization needs to be established, but traces of it can be found in Harlequin camouflage by animals and in the coloration of flowers. PMID:24374380

  10. 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.

  11. 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.

  12. Document segmentation for high-quality printing

    NASA Astrophysics Data System (ADS)

    Ancin, Hakan

    1997-04-01

    A technique to segment dark texts on light background of mixed mode color documents is presented. This process does not perceptually change graphics and photo regions. Color documents are scanned and printed from various media which usually do not have clean background. This is especially the case for the printouts generated from thin magazine samples, these printouts usually include text and figures form the back of the page, which is called bleeding. Removal of bleeding artifacts improves the perceptual quality of the printed document and reduces the color ink usage. By detecting the light background of the document, these artifacts are removed from background regions. Also detection of dark text regions enables the halftoning algorithms to use true black ink for the black text pixels instead of composite black. The processed document contains sharp black text on white background, resulting improved perceptual quality and better ink utilization. The described method is memory efficient and requires a small number of scan lines of high resolution color documents during processing.

  13. Image segmentation survey

    NASA Technical Reports Server (NTRS)

    Haralick, R. M.

    1982-01-01

    The methodologies and capabilities of image segmentation techniques are reviewed. Single linkage schemes, hybrid linkage schemes, centroid linkage schemes, histogram mode seeking, spatial clustering, and split and merge schemes are addressed.

  14. Segmentation of SAR images

    NASA Technical Reports Server (NTRS)

    Kwok, Ronald

    1989-01-01

    The statistical characteristics of image speckle are reviewed. Existing segmentation techniques that have been used for speckle filtering, edge detection, and texture extraction are sumamrized. The relative effectiveness of each technique is briefly discussed.

  15. Robust anchorperson detection for TV news segmentation

    NASA Astrophysics Data System (ADS)

    Lu, Ko-Yen; Chang, Min-Kuan; Yeh, Chia-Hung; Shih, Maverick

    2006-10-01

    In this paper, we proposed a scheme for TV news segmentation via exploring the efficient visual features. The proposed scheme can be divided into three parts, such as shot change detection based on skin color; probable anchorperson shot detection and anchorperson detection. According to experimental results, our proposed method can efficiently decompose TV news into anchorperson shots and report shots. Compared to the traditional face detection methods, the proposed method can robustly exclude the non-anchorperson shots in report shots such as the interview scenes. Experimental results are given to demonstrate the feasibility and efficiency of the proposed technique.

  16. Adjacent segment disease.

    PubMed

    Virk, Sohrab S; Niedermeier, Steven; Yu, Elizabeth; Khan, Safdar N

    2014-08-01

    EDUCATIONAL OBJECTIVES As a result of reading this article, physicians should be able to: 1. Understand the forces that predispose adjacent cervical segments to degeneration. 2. Understand the challenges of radiographic evaluation in the diagnosis of cervical and lumbar adjacent segment disease. 3. Describe the changes in biomechanical forces applied to adjacent segments of lumbar vertebrae with fusion. 4. Know the risk factors for adjacent segment disease in spinal fusion. Adjacent segment disease (ASD) is a broad term encompassing many complications of spinal fusion, including listhesis, instability, herniated nucleus pulposus, stenosis, hypertrophic facet arthritis, scoliosis, and vertebral compression fracture. The area of the cervical spine where most fusions occur (C3-C7) is adjacent to a highly mobile upper cervical region, and this contributes to the biomechanical stress put on the adjacent cervical segments postfusion. Studies have shown that after fusion surgery, there is increased load on adjacent segments. Definitive treatment of ASD is a topic of continuing research, but in general, treatment choices are dictated by patient age and degree of debilitation. Investigators have also studied the risk factors associated with spinal fusion that may predispose certain patients to ASD postfusion, and these data are invaluable for properly counseling patients considering spinal fusion surgery. Biomechanical studies have confirmed the added stress on adjacent segments in the cervical and lumbar spine. The diagnosis of cervical ASD is complicated given the imprecise correlation of radiographic and clinical findings. Although radiological and clinical diagnoses do not always correlate, radiographs and clinical examination dictate how a patient with prolonged pain is treated. Options for both cervical and lumbar spine ASD include fusion and/or decompression. Current studies are encouraging regarding the adoption of arthroplasty in spinal surgery, but more long

  17. Segmented pyroelector detector

    DOEpatents

    Stotlar, S.C.; McLellan, E.J.

    1981-01-21

    A pyroelectric detector is described which has increased voltage output and improved responsivity over equivalent size detectors. The device comprises a plurality of edge-type pyroelectric detectors which have a length which is much greater than the width of the segments between the edge-type electrodes. External circuitry connects the pyroelectric detector segments in parallel to provide a single output which maintains 50 ohm impedance characteristics.

  18. 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…

  19. Segmenting patients and physicians using preferences from discrete choice experiments.

    PubMed

    Deal, Ken

    2014-01-01

    students. Those segments were very different-where one wanted substantial penalties against cyberbullies and were willing to devote time to a prevention program, while the other felt no need to be involved in prevention and wanted only minor penalties. Segmentation recognizes key differences in why patients and physicians prefer different health programs and treatments. A viable segmentation solution may lead to adapting prevention programs and treatments for each targeted segment and/or to educating and communicating to better inform those in each segment of the program/treatment benefits. Segment members' revealed preferences showing behavioral changes provide the ultimate basis for evaluating the segmentation benefits to the health organization. PMID:24327338

  20. Segmental neurofibromatosis and malignancy.

    PubMed

    Dang, Julie D; Cohen, Philip R

    2010-01-01

    Segmental neurofibromatosis is an uncommon variant of neurofibromatosis type I characterized by neurofibromas and/or café-au-lait macules localized to one sector of the body. Although patients with neurofibromatosis type I have an associated increased risk of certain malignancies, malignancy has only occasionally been reported in patients with segmental neurofibromatosis. The published reports of patients with segmental neurofibromatosis who developed malignancy were reviewed and the characteristics of these patients and their cancers were summarized. Ten individuals (6 women and 4 men) with segmental neurofibromatosis and malignancy have been reported. The malignancies include malignant peripheral nerve sheath tumor (3), malignant melanoma (2), breast cancer (1), colon cancer (1), gastric cancer (1), lung cancer (1), and Hodgkin lymphoma (1). The most common malignancies in patients with segmental neurofibromatosis are derived from neural crest cells: malignant peripheral nerve sheath tumor and malignant melanoma. The incidence of malignancy in patients with segmental neurofibromatosis may approach that of patients with neurofibromatosis type I. PMID:21137621

  1. Colored Diffraction Catastrophes

    NASA Astrophysics Data System (ADS)

    Berry, M. V.; Klein, S.

    1996-03-01

    On fine scales, caustics produced with white light show vividly colored diffraction fringes. For caustics described by the elementary catastrophes of singularity theory, the colors are characteristic of the type of singularity. We study the diffraction colors of the fold and cusp catastrophes. The colors can be simulated computationally as the superposition of monochromatic patterns for different wavelengths. Far from the caustic, where the luminosity contrast is negligible, the fringe colors persist; an asymptotic theory explains why. Experiments with caustics produced by refraction through irregular bathroom-window glass show good agreement with theory. Colored fringes near the cusp reveal fine lines that are not present in any of the monochromatic components; these lines are explained in terms of partial decoherence between rays with widely differing path differences.

  2. Color scene analysis

    NASA Astrophysics Data System (ADS)

    Celenk, Mehmet

    1994-05-01

    This paper describes a color scene analysis method for the object surfaces appearing in the noisy and imperfect images of natural scenes. It is developed based on the spatial and spectral grouping property of the human visual system. The uniformly colored surfaces are recognized by their monomodal 3-D color distributions and extracted in the spatial domain using the lightness and chromaticity network of the Munsell system. The textured image regions are identified by their irregular histogram distributions and isolated in the image plane using the Julesz connectivity detection rules. The method is applied to various color images corrupted by noise and degraded heavily by under-sampling and low color-contrast imperfections. The method was able to detect all the uniformly colored and heavily textured object areas in these images.

  3. 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.

  4. Colored diffraction catastrophes.

    PubMed Central

    Berry, M V; Klein, S

    1996-01-01

    On fine scales, caustics produced with white light show vividly colored diffraction fringes. For caustics described by the elementary catastrophes of singularity theory, the colors are characteristic of the type of singularity. We study the diffraction colors of the fold and cusp catastrophes. The colors can be simulated computationally as the superposition of monochromatic patterns for different wavelengths. Far from the caustic, where the luminosity contrast is negligible, the fringe colors persist; an asymptotic theory explains why. Experiments with caustics produced by refraction through irregular bathroom-window glass show good agreement with theory. Colored fringes near the cusp reveal fine lines that are not present in any of the monochromatic components; these lines are explained in terms of partial decoherence between rays with widely differing path differences. Images Fig. 1 Fig. 2 Fig. 3 Fig. 6 Fig. 8 Fig. 9 Fig. 10 PMID:11607642

  5. Chromatic settings and the structural color constancy index.

    PubMed

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

    2013-01-01

    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. PMID:23479473

  6. A probabilistic approach for color correction in image mosaicking applications.

    PubMed

    Oliveira, Miguel; Sappa, Angel Domingo; Santos, Vitor

    2015-02-01

    Image mosaicking applications require both geometrical and photometrical registrations between the images that compose the mosaic. This paper proposes a probabilistic color correction algorithm for correcting the photometrical disparities. First, the image to be color corrected is segmented into several regions using mean shift. Then, connected regions are extracted using a region fusion algorithm. Local joint image histograms of each region are modeled as collections of truncated Gaussians using a maximum likelihood estimation procedure. Then, local color palette mapping functions are computed using these sets of Gaussians. The color correction is performed by applying those functions to all the regions of the image. An extensive comparison with ten other state of the art color correction algorithms is presented, using two different image pair data sets. Results show that the proposed approach obtains the best average scores in both data sets and evaluation metrics and is also the most robust to failures. PMID:25438315

  7. Ghostscript color management

    NASA Astrophysics Data System (ADS)

    Vrhel, Michael J.; Johnston, Raymond

    2011-01-01

    This document introduces an updated color architecture that has been designed for Ghostscript. Ghostscript is a well known open source document rendering and conversion engine. Prior to this update, the handling of color in Ghostscript was based primarily upon PostScript color management. The new design results in a flexible ICC-based architecture that works well in Ghostscript's multi-threaded rendering environment.

  8. 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.

  9. Fingers that change color

    MedlinePlus

    ... conditions can cause fingers or toes to change color: Buerger disease Chilblains. Painful inflammation of small blood vessels. Cryoglobulinemia Frostbite Necrotizing vasculitis Peripheral artery disease ...

  10. 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.

  11. 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

  12. Color mixing models

    NASA Astrophysics Data System (ADS)

    Harrington, Steven J.

    1992-05-01

    In black-and-white printing the page image can be represented within a computer as an array of binary values indicating whether or not pixels should be inked. The Boolean operators of AND, OR, and EXCLUSIVE-OR are often used when adding new objects to the image array. For color printing the page may be represented as an array of continuous tone color values, and the generalization of these logic functions to gray-scale or full-color images is, in general, not defined or understood. When incrementally composing a page image new colors can replace old in an image buffer, or new colors and old can be combined according to some mixing function to form a composite color which is stored. This paper examines the properties of the Boolean operations and suggests full-color mixing functions which preserve the desired properties. These functions can be used to combine colored images, giving various transparency effects. The relationships between the mixing functions and physical models of color mixing are also discussed.

  13. Polarization encoded color camera.

    PubMed

    Schonbrun, Ethan; Möller, Guðfríður; Di Caprio, Giuseppe

    2014-03-15

    Digital cameras would be colorblind if they did not have pixelated color filters integrated into their image sensors. Integration of conventional fixed filters, however, comes at the expense of an inability to modify the camera's spectral properties. Instead, we demonstrate a micropolarizer-based camera that can reconfigure its spectral response. Color is encoded into a linear polarization state by a chiral dispersive element and then read out in a single exposure. The polarization encoded color camera is capable of capturing three-color images at wavelengths spanning the visible to the near infrared. PMID:24690806

  14. Visual color image processing

    NASA Astrophysics Data System (ADS)

    Qiu, Guoping; Schaefer, Gerald

    1999-12-01

    In this paper, we propose a color image processing method by combining modern signal processing technique with knowledge about the properties of the human color vision system. Color signals are processed differently according to their visual importance. The emphasis of the technique is on the preservation of total visual quality of the image and simultaneously taking into account computational efficiency. A specific color image enhancement technique, termed Hybrid Vector Median Filtering is presented. Computer simulations have been performed to demonstrate that the new approach is technically sound and results are comparable to or better than traditional methods.

  15. Spontaneous Regeneration of Human Photoreceptor Outer Segments

    PubMed Central

    Horton, Jonathan C.; Parker, Alicia B.; Botelho, James V.; Duncan, Jacque L.

    2015-01-01

    Photoreceptors are damaged in many common eye diseases, such as macular degeneration, retinal detachment, and retinitis pigmentosa. The development of methods to promote the repair or replacement of affected photoreceptors is a major goal of vision research. In this context, it would be useful to know whether photoreceptors are capable of undergoing some degree of spontaneous regeneration after injury. We report a subject who lost retinal function in a wide zone around the optic disc, giving rise to massive enlargement of the physiological blind spot. Imaging with an adaptive optics scanning laser ophthalmoscope (AOSLO) showed depletion of cone outer segments in the affected retina. A year later visual function had improved, with shrinkage of the enlarged blind spot. AOSLO imaging showed repopulation of cone outer segments, although their density remained below normal. There was a one-to-one match between sites of formerly missing outer segments and new outer segments that had appeared over the course of the year’s recovery. This correspondence provided direct morphological evidence that damaged cones are capable, under some circumstances, of generating new outer segments. PMID:26213154

  16. Bilayer segmentation of webcam videos using tree-based classifiers.

    PubMed

    Yin, Pei; Criminisi, Antonio; Winn, John; Essa, Irfan

    2011-01-01

    This paper presents an automatic segmentation algorithm for video frames captured by a (monocular) webcam that closely approximates depth segmentation from a stereo camera. The frames are segmented into foreground and background layers that comprise a subject (participant) and other objects and individuals. The algorithm produces correct segmentations even in the presence of large background motion with a nearly stationary foreground. This research makes three key contributions: First, we introduce a novel motion representation, referred to as "motons," inspired by research in object recognition. Second, we propose estimating the segmentation likelihood from the spatial context of motion. The estimation is efficiently learned by random forests. Third, we introduce a general taxonomy of tree-based classifiers that facilitates both theoretical and experimental comparisons of several known classification algorithms and generates new ones. In our bilayer segmentation algorithm, diverse visual cues such as motion, motion context, color, contrast, and spatial priors are fused by means of a conditional random field (CRF) model. Segmentation is then achieved by binary min-cut. Experiments on many sequences of our videochat application demonstrate that our algorithm, which requires no initialization, is effective in a variety of scenes, and the segmentation results are comparable to those obtained by stereo systems. PMID:21088317

  17. Color reproduction with a smartphone

    NASA Astrophysics Data System (ADS)

    Thoms, Lars-Jochen; Colicchia, Giuseppe; Girwidz, Raimund

    2013-10-01

    The world is full of colors. Most of the colors we see around us can be created on common digital displays simply by superposing light with three different wavelengths. However, no mixture of colors can produce a fully pure color identical to a spectral color. Using a smartphone, students can investigate the main features of primary color addition and understand how colors are made on digital displays.

  18. A combined spatial-spectral method for automated white blood cells segmentation

    NASA Astrophysics Data System (ADS)

    Li, Qingli; Wang, Yiting; Liu, Hongying; Wang, Jianbiao; Guo, Fangmin

    2013-12-01

    To overcome the shortcomings in the traditional white blood cells (WBCs) identification methods based on the color or gray images captured by light microscopy, a microscopy hyperspectral imaging system was used to analyze the blood smears. The system was developed by coupling an acousto-optic tunable filter (AOTF) adapter to a microscopy and driven by a SPF Model AOTF controller, which can capture hyperspectral images from 550 nm to 1000 nm with the spectral resolution 2-5 nm. Moreover, a combined spatial-spectral algorithm is proposed to segment the nuclei and cytoplasm of WBCs from the microscopy hyperspectral images. The proposed algorithm is based on the pixel-wise improved spectral angle mapper (ISAM) segmentation, followed by the majority voting within the active contour model regions. Experimental results show that the accuracy of the proposed algorithm is 91.06% (nuclei) and 85.59% (cytoplasm), respectively, which is higher than that of the spectral information divergence (SID) algorithm because the new method can jointly use both the spectral and spatial information of blood cells.

  19. 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. PMID:16485810

  20. Fault rupture segmentation

    NASA Astrophysics Data System (ADS)

    Cleveland, Kenneth Michael

    A critical foundation to earthquake study and hazard assessment is the understanding of controls on fault rupture, including segmentation. Key challenges to understanding fault rupture segmentation include, but are not limited to: What determines if a fault segment will rupture in a single great event or multiple moderate events? How is slip along a fault partitioned between seismic and seismic components? How does the seismicity of a fault segment evolve over time? How representative are past events for assessing future seismic hazards? In order to address the difficult questions regarding fault rupture segmentation, new methods must be developed that utilize the information available. Much of the research presented in this study focuses on the development of new methods for attacking the challenges of understanding fault rupture segmentation. Not only do these methods exploit a broader band of information within the waveform than has traditionally been used, but they also lend themselves to the inclusion of even more seismic phases providing deeper understandings. Additionally, these methods are designed to be fast and efficient with large datasets, allowing them to utilize the enormous volume of data available. Key findings from this body of work include demonstration that focus on fundamental earthquake properties on regional scales can provide general understanding of fault rupture segmentation. We present a more modern, waveform-based method that locates events using cross-correlation of the Rayleigh waves. Additionally, cross-correlation values can also be used to calculate precise earthquake magnitudes. Finally, insight regarding earthquake rupture directivity can be easily and quickly exploited using cross-correlation of surface waves.

  1. 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

  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. 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.

  4. Bootstrapping structured page segmentation

    NASA Astrophysics Data System (ADS)

    Ma, Huanfeng; Doermann, David S.

    2003-01-01

    In this paper, we present an approach to the bootstrap learning of a page segmentation model. The idea evolves from attempts to segment dictionaries that often have a consistent page structure, and is extended to the segmentation of more general structured documents. In cases of highly regular structure, the layout can be learned from examples of only a few pages. The system is first trained using a small number of samples, and a larger test set is processed based on the training result. After making corrections to a selected subset of the test set, these corrected samples are combined with the original training samples to generate bootstrap samples. The newly created samples are used to retrain the system, refine the learned features and resegment the test samples. This procedure is applied iteratively until the learned parameters are stable. Using this approach, we do not need to initially provide a large set of training samples. We have applied this segmentation to many structured documents such as dictionaries, phone books, spoken language transcripts, and obtained satisfying segmentation performance.

  5. 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.

  6. 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.

  7. Adapting to an aftereffect.

    PubMed

    Sheth, Bhavin R; Shimojo, Shinsuke

    2008-01-01

    We report a new type of orientation-contingent color aftereffect in which the color aftereffect is opposite to the classical McCollough effect, i.e., the perceived color of the aftereffect is the same as the inducer's color. Interleaved exposure to red, horizontal and achromatic (gray), horizontal gratings led to a long-lasting aftereffect in which achromatic horizontal gratings appeared reddish. The effect, termed the anti-McCollough effect, although weaker than the classical aftereffect, remained stable for a moderate duration of time (24 hours). Unlike the classical aftereffect, which is known to not transfer interocularly, the new after-aftereffect transferred 100%, suggesting that its locus in the brain was downstream of the classical effect. It is likely that neurons in a higher-order area adapted to the classical color aftereffect that was represented in a lower-order area, thus forming an aftereffect of an aftereffect, i.e., an after-aftereffect. Our finding has implications as to how neural activity in lower- and higher-level areas in the brain interacts to yield conscious visual experience. PMID:18484835

  8. 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…

  9. 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…

  10. 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…

  11. Color names, color categories, and color-cued visual search: Sometimes, color perception is not categorical

    PubMed Central

    Brown, Angela M; Lindsey, Delwin T; Guckes, Kevin M

    2011-01-01

    The relation between colors and their names is a classic case-study for investigating the Sapir-Whorf hypothesis that categorical perception is imposed on perception by language. Here, we investigate the Sapir-Whorf prediction that visual search for a green target presented among blue distractors (or vice versa) should be faster than search for a green target presented among distractors of a different color of green (or for a blue target among different blue distractors). Gilbert, Regier, Kay & Ivry (2006) reported that this Sapir-Whorf effect is restricted to the right visual field (RVF), because the major brain language centers are in the left cerebral hemisphere. We found no categorical effect at the Green|Blue color boundary, and no categorical effect restricted to the RVF. Scaling of perceived color differences by Maximum Likelihood Difference Scaling (MLDS) also showed no categorical effect, including no effect specific to the RVF. Two models fit the data: a color difference model based on MLDS and a standard opponent-colors model of color discrimination based on the spectral sensitivities of the cones. Neither of these models, nor any of our data, suggested categorical perception of colors at the Green|Blue boundary, in either visual field. PMID:21980188

  12. Peripheral Color Demo

    PubMed Central

    2015-01-01

    A set of structured demonstrations of the vividness of peripheral color vision is provided by arrays of multicolored disks scaled with eccentricity. These demonstrations are designed to correct the widespread misconception that peripheral color vision is weak or nonexistent. PMID:27551354

  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. PMID:27516874

  14. Language and Color Symbolism.

    ERIC Educational Resources Information Center

    Anderson, Earl R.

    1977-01-01

    Suggests discussion and a writing assignment on the ways color terms have changed from Old English and Indo-European roots; urges a study of Black-White polarity that goes beyond racial connotations of those terms. Provides informative materials on many specific color terms. (TJ)

  15. Adaptive evolutionary paths from UV reception to sensing violet light by epistatic interactions

    PubMed Central

    Yokoyama, Shozo; Altun, Ahmet; Jia, Huiyong; Yang, Hui; Koyama, Takashi; Faggionato, Davide; Liu, Yang; Starmer, William T.

    2015-01-01

    Ultraviolet (UV) reception is useful for such basic behaviors as mate choice, foraging, predator avoidance, communication, and navigation, whereas violet reception improves visual resolution and subtle contrast detection. UV and violet reception are mediated by the short wavelength–sensitive (SWS1) pigments that absorb light maximally (λmax) at ~360 nm and ~395 to 440 nm, respectively. Because of strong nonadditive (epistatic) interactions among amino acid changes in the pigments, the adaptive evolutionary mechanisms of these phenotypes are not well understood. Evolution of the violet pigment of the African clawed frog (Xenopus laevis, λmax = 423 nm) from the UV pigment in the amphibian ancestor (λmax = 359 nm) can be fully explained by eight mutations in transmembrane (TM) I–III segments. We show that epistatic interactions involving the remaining TM IV–VII segments provided evolutionary potential for the frog pigment to gradually achieve its violet-light reception by tuning its color sensitivity in small steps. Mutants in these segments also impair pigments that would cause drastic spectral shifts and thus eliminate them from viable evolutionary pathways. The overall effects of epistatic interactions involving TM IV–VII segments have disappeared at the last evolutionary step and thus are not detectable by studying present-day pigments. Therefore, characterizing the genotype-phenotype relationship during each evolutionary step is the key to uncover the true nature of epistasis. PMID:26601250

  16. 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. PMID:24025243

  17. Bayesian Analysis and Segmentation of Multichannel Image Sequences

    NASA Astrophysics Data System (ADS)

    Chang, Michael Ming Hsin

    This thesis is concerned with the segmentation and analysis of multichannel image sequence data. In particular, we use maximum a posteriori probability (MAP) criterion and Gibbs random fields (GRF) to formulate the problems. We start by reviewing the significance of MAP estimation with GRF priors and study the feasibility of various optimization methods for implementing the MAP estimator. We proceed to investigate three areas where image data and parameter estimates are present in multichannels, multiframes, and interrelated in complicated manners. These areas of study include color image segmentation, multislice MR image segmentation, and optical flow estimation and segmentation in multiframe temporal sequences. Besides developing novel algorithms in each of these areas, we demonstrate how to exploit the potential of MAP estimation and GRFs, and we propose practical and efficient implementations. Illustrative examples and relevant experimental results are included.

  18. 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.

  19. Skin lesion image segmentation using Delaunay Triangulation for melanoma detection.

    PubMed

    Pennisi, Andrea; Bloisi, Domenico D; Nardi, Daniele; Giampetruzzi, Anna Rita; Mondino, Chiara; Facchiano, Antonio

    2016-09-01

    Developing automatic diagnostic tools for the early detection of skin cancer lesions in dermoscopic images can help to reduce melanoma-induced mortality. Image segmentation is a key step in the automated skin lesion diagnosis pipeline. In this paper, a fast and fully-automatic algorithm for skin lesion segmentation in dermoscopic images is presented. Delaunay Triangulation is used to extract a binary mask of the lesion region, without the need of any training stage. A quantitative experimental evaluation has been conducted on a publicly available database, by taking into account six well-known state-of-the-art segmentation methods for comparison. The results of the experimental analysis demonstrate that the proposed approach is highly accurate when dealing with benign lesions, while the segmentation accuracy significantly decreases when melanoma images are processed. This behavior led us to consider geometrical and color features extracted from the binary masks generated by our algorithm for classification, achieving promising results for melanoma detection. PMID:27215953

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. Phasing a segmented telescope.

    PubMed

    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. PMID:25768631

  6. 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

  7. Volume rendering for interactive 3D segmentation

    NASA Astrophysics Data System (ADS)

    Toennies, Klaus D.; Derz, Claus

    1997-05-01

    Combined emission/absorption and reflection/transmission volume rendering is able to display poorly segmented structures from 3D medical image sequences. Visual cues such as shading and color let the user distinguish structures in the 3D display that are incompletely extracted by threshold segmentation. In order to be truly helpful, analyzed information needs to be quantified and transferred back into the data. We extend our previously presented scheme for such display be establishing a communication between visual analysis and the display process. The main tool is a selective 3D picking device. For being useful on a rather rough segmentation, the device itself and the display offer facilities for object selection. Selective intersection planes let the user discard information prior to choosing a tissue of interest. Subsequently, a picking is carried out on the 2D display by casting a ray into the volume. The picking device is made pre-selective using already existing segmentation information. Thus, objects can be picked that are visible behind semi-transparent surfaces of other structures. Information generated by a later connected- component analysis can then be integrated into the data. Data examination is continued on an improved display letting the user actively participate in the analysis process. Results of this display-and-interaction scheme proved to be very effective. The viewer's ability to extract relevant information form a complex scene is combined with the computer's ability to quantify this information. The approach introduces 3D computer graphics methods into user- guided image analysis creating an analysis-synthesis cycle for interactive 3D segmentation.

  8. 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.

  9. Robust system for human airway-tree segmentation

    NASA Astrophysics Data System (ADS)

    Graham, Michael W.; Gibbs, Jason D.; Higgins, William E.

    2008-03-01

    Robust and accurate segmentation of the human airway tree from multi-detector computed-tomography (MDCT) chest scans is vital for many pulmonary-imaging applications. As modern MDCT scanners can detect hundreds of airway tree branches, manual segmentation and semi-automatic segmentation requiring significant user intervention are impractical for producing a full global segmentation. Fully-automated methods, however, may fail to extract small peripheral airways. We propose an automatic algorithm that searches the entire lung volume for airway branches and poses segmentation as a global graph-theoretic optimization problem. The algorithm has shown strong performance on 23 human MDCT chest scans acquired by a variety of scanners and reconstruction kernels. Visual comparisons with adaptive region-growing results and quantitative comparisons with manually-defined trees indicate a high sensitivity to peripheral airways and a low false-positive rate. In addition, we propose a suite of interactive segmentation tools for cleaning and extending critical areas of the automatically segmented result. These interactive tools have potential application for image-based guidance of bronchoscopy to the periphery, where small, terminal branches can be important visual landmarks. Together, the automatic segmentation algorithm and interactive tool suite comprise a robust system for human airway-tree segmentation.

  10. 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)

  11. Regional principal color based saliency detection.

    PubMed

    Lou, Jing; Ren, Mingwu; Wang, Huan

    2014-01-01

    Saliency detection is widely used in many visual applications like image segmentation, object recognition and classification. In this paper, we will introduce a new method to detect salient objects in natural images. The approach is based on a regional principal color contrast modal, which incorporates low-level and medium-level visual cues. The method allows a simple computation of color features and two categories of spatial relationships to a saliency map, achieving higher F-measure rates. At the same time, we present an interpolation approach to evaluate resulting curves, and analyze parameters selection. Our method enables the effective computation of arbitrary resolution images. Experimental results on a saliency database show that our approach produces high quality saliency maps and performs favorably against ten saliency detection algorithms. PMID:25379960

  12. 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.

  13. Genetic basis of sex-specific color pattern variation in Drosophila malerkotliana.

    PubMed

    Ng, Chen Siang; Hamilton, Andrew M; Frank, Amanda; Barmina, Olga; Kopp, Artyom

    2008-09-01

    Pigmentation is a rapidly evolving trait that can play important roles in mimicry, sexual selection, thermoregulation, and other adaptive processes in many groups of animals. In Drosophila, pigmentation can differ dramatically among closely related taxa, presenting a good opportunity to dissect the genetic changes underlying species divergence. In this report, we investigate the genetic basis of color pattern variation between two allopatric subspecies of Drosophila malerkotliana, a widespread member of the ananassae species subgroup. In D. malerkotliana malerkotliana, the last three abdominal segments are darkly pigmented in males but not in females, while in D. malerkotliana pallens both sexes lack dark pigmentation. Composite interval mapping in F2 hybrid progeny shows that this difference is largely controlled by three quantitative trait loci (QTL) located on the 2L chromosome arm, which is homologous to the 3R of D. melanogaster (Muller element E). Using highly recombinant introgression strains produced by repeated backcrossing and phenotypic selection, we show that these QTL do not correspond to any of the candidate genes known to be involved in pigment patterning and synthesis in Drosophila. These results, in combination with similar analyses in other Drosophila species, indicate that different genetic and molecular changes are responsible for the evolution of similar phenotypic traits in different lineages. This feature makes Drosophila color patterns a powerful model for investigating how the genetic basis of trait evolution is influenced by the intrinsic organization of regulatory pathways controlling the development of these traits. PMID:18723880

  14. Iridescence color of shells

    NASA Astrophysics Data System (ADS)

    Liu, Yan

    2002-06-01

    Some shells from both salt water and fresh water show the phenomenon of iridescence color. Pearls and mother-of-pearls also display this phenomenon. In the past, the cause of the iridescence color was attributed to interference. A scanning electron microscope (SEM) was used to study the surface structure of the shell of the mollusk Pinctada Margaritifera. There is a groove structure of reflection grating on the surface area in where the iridescence color appears. An optic experiment with a laser obtained a diffraction pattern produced by the reflection grating structure of the shell. The study led to a conclusion that the iridescence color of the shell is caused by diffraction. A SEM image of the shells of an abalone Haliotis Rufescens (red abalone) showed a statistically regularly arranged tile structure that serves as a two-dimensional grating. This grating structure causes the iridescence color of the shell of red abalone. The dominant color of the iridescence of shells is caused by the uneven grating efficiency in the visible wavelength range when a shell functions as a reflection grating. The wavelength of the dominant color should be at or near the wavelength of the maximum efficiency of the grating.

  15. 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.

  16. 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.

  17. Convex-relaxed kernel mapping for image segmentation.

    PubMed

    Ben Salah, Mohamed; Ben Ayed, Ismail; Jing Yuan; Hong Zhang

    2014-03-01

    This paper investigates a convex-relaxed kernel mapping formulation of image segmentation. We optimize, under some partition constraints, a functional containing two characteristic terms: 1) a data term, which maps the observation space to a higher (possibly infinite) dimensional feature space via a kernel function, thereby evaluating nonlinear distances between the observations and segments parameters and 2) a total-variation term, which favors smooth segment surfaces (or boundaries). The algorithm iterates two steps: 1) a convex-relaxation optimization with respect to the segments by solving an equivalent constrained problem via the augmented Lagrange multiplier method and 2) a convergent fixed-point optimization with respect to the segments parameters. The proposed algorithm can bear with a variety of image types without the need for complex and application-specific statistical modeling, while having the computational benefits of convex relaxation. Our solution is amenable to parallelized implementations on graphics processing units (GPUs) and extends easily to high dimensions. We evaluated the proposed algorithm with several sets of comprehensive experiments and comparisons, including: 1) computational evaluations over 3D medical-imaging examples and high-resolution large-size color photographs, which demonstrate that a parallelized implementation of the proposed method run on a GPU can bring a significant speed-up and 2) accuracy evaluations against five state-of-the-art methods over the Berkeley color-image database and a multimodel synthetic data set, which demonstrates competitive performances of the algorithm. PMID:24723519

  18. Automatic brain tumor segmentation

    NASA Astrophysics Data System (ADS)

    Clark, Matthew C.; Hall, Lawrence O.; Goldgof, Dmitry B.; Velthuizen, Robert P.; Murtaugh, F. R.; Silbiger, Martin L.

    1998-06-01

    A system that automatically segments and labels complete glioblastoma-multiform tumor volumes in magnetic resonance images of the human brain is presented. The magnetic resonance images consist of three feature images (T1- weighted, proton density, T2-weighted) and are processed by a system which integrates knowledge-based techniques with multispectral analysis and is independent of a particular magnetic resonance scanning protocol. Initial segmentation is performed by an unsupervised clustering algorithm. The segmented image, along with cluster centers for each class are provided to a rule-based expert system which extracts the intra-cranial region. Multispectral histogram analysis separates suspected tumor from the rest of the intra-cranial region, with region analysis used in performing the final tumor labeling. This system has been trained on eleven volume data sets and tested on twenty-two unseen volume data sets acquired from a single magnetic resonance imaging system. The knowledge-based tumor segmentation was compared with radiologist-verified `ground truth' tumor volumes and results generated by a supervised fuzzy clustering algorithm. The results of this system generally correspond well to ground truth, both on a per slice basis and more importantly in tracking total tumor volume during treatment over time.

  19. [Toxic anterior segment syndrome].

    PubMed

    Cornut, P-L; Chiquet, C

    2011-01-01

    Toxic anterior segment syndrome (TASS) is a general term used to describe acute, sterile postoperative inflammation due to a non-infectious substance that accidentally enters the anterior segment at the time of surgery and mimics infectious endophthalmitis. TASS most commonly occurs acutely following anterior segment surgery, typically 12-72h after cataract extraction. Anterior segment inflammation is usually quite severe with hypopyon. Endothelial cell damage is common, resulting in diffuse corneal edema. No bacterium is isolated from ocular samples. The causes of TASS are numerous and difficult to isolate. Any device or substance used during the surgery or in the immediate postoperative period may be implicated. The major known causes include: preservatives in ophthalmic solutions, denatured ophthalmic viscosurgical devices, bacterial endotoxin, and intraocular lens-induced inflammation. Clinical features of infectious and non-infectious inflammation are initially indistinguishable and TASS is usually diagnosed and treated as acute endophthalmitis. It usually improves with local steroid treatment but may result in chronic elevation of intraocular pressure or irreversible corneal edema due to permanent damage of trabecular meshwork or endothelial cells. PMID:21176994

  20. Theoretical aspects of color vision

    NASA Technical Reports Server (NTRS)

    Wolbarsht, M. L.

    1972-01-01

    The three color receptors of Young-Helmholtz and the opponent colors type of information processing postulated by Hering are both present in the human visual system. This mixture accounts for both the phenomena of color matching or hue discrimination and such perceptual qualities of color as the division of the spectrum into color bands. The functioning of the cells in the visual system, especially within the retina, and the relation of this function to color perception are discussed.

  1. Automatic brain segmentation in rhesus monkeys

    NASA Astrophysics Data System (ADS)

    Styner, Martin; Knickmeyer, Rebecca; Joshi, Sarang; Coe, Christopher; Short, Sarah J.; Gilmore, John

    2007-03-01

    Many neuroimaging studies are applied to primates as pathologies and environmental exposures can be studied in well-controlled settings and environment. In this work, we present a framework for both the semi-automatic creation of a rhesus monkey atlas and a fully automatic segmentation of brain tissue and lobar parcellation. We determine the atlas from training images by iterative, joint deformable registration into an unbiased average image. On this atlas, probabilistic tissue maps and a lobar parcellation. The atlas is then applied via affine, followed by deformable registration. The affinely transformed atlas is employed for a joint T1/T2 based tissue classification. The deformed atlas parcellation masks the tissue segmentations to define the parcellation. Other regional definitions on the atlas can also straightforwardly be used as segmentation. We successfully built average atlas images for the T1 and T2 datasets using a developmental training datasets of 18 cases aged 16-34 months. The atlas clearly exhibits an enhanced signal-to-noise ratio compared to the original images. The results further show that the cortical folding variability in our data is highly limited. Our segmentation and parcellation procedure was successfully re-applied to all training images, as well as applied to over 100 additional images. The deformable registration was able to identify corresponding cortical sulcal borders accurately. Even though the individual methods used in this segmentation framework have been applied before on human data, their combination is novel, as is their adaptation and application to rhesus monkey MRI data. The reduced variability present in the primate data results in a segmentation pipeline that exhibits high stability and anatomical accuracy.

  2. Natural and seamless image composition with color control.

    PubMed

    Yang, Wenxian; Zheng, Jianmin; Cai, Jianfei; Rahardja, Susanto; Chen, Chang Wen

    2009-11-01

    While the state-of-the-art image composition algorithms subtly handle the object boundary to achieve seamless image copy-and-paste, it is observed that they are unable to preserve the color fidelity of the source object, often require quite an amount of user interactions, and often fail to achieve realism when there exists salient discrepancy between the background textures in the source and destination images. These observations motivate our research towards color controlled natural and seamless image composition with least user interactions. In particular, based on the Poisson image editing framework, we first propose a variational model that considers both the gradient constraint and the color fidelity. The proposed model allows users to control the coloring effect caused by gradient domain fusion. Second, to have less user interactions, we propose a distance-enhanced random walks algorithm, through which we avoid the necessity of accurate image segmentation while still able to highlight the foreground object. Third, we propose a multiresolution framework to perform image compositions at different subbands so as to separate the texture and color components to simultaneously achieve smooth texture transition and desired color control. The experimental results demonstrate that our proposed framework achieves better and more realistic results for images with salient background color or texture differences, while providing comparable results as the state-of-the-art algorithms for images without the need of preserving the object color fidelity and without significant background texture discrepancy. PMID:19596637

  3. 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.

  4. 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.

  5. 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. PMID:25000236

  6. Coloring random graphs.

    PubMed

    Mulet, R; Pagnani, A; Weigt, M; Zecchina, R

    2002-12-23

    We study the graph coloring problem over random graphs of finite average connectivity c. Given a number q of available colors, we find that graphs with low connectivity admit almost always a proper coloring, whereas graphs with high connectivity are uncolorable. Depending on q, we find the precise value of the critical average connectivity c(q). Moreover, we show that below c(q) there exists a clustering phase c in [c(d),c(q)] in which ground states spontaneously divide into an exponential number of clusters and where the proliferation of metastable states is responsible for the onset of complexity in local search algorithms. PMID:12484862

  7. 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.

  8. A robust segmentation of scanned documents

    NASA Astrophysics Data System (ADS)

    Park, Hyung Jun; Yi, Ji Young

    2015-01-01

    The image quality of reprinted documents that were scanned at a high resolution may not satisfy human viewers who anticipate at least the same image quality as the original document. Moiré artifacts without proper descreening, text blurred by the poor scanner modulation transfer function (MTF), and color distortion resulting from misclassification between color and gray may make the reprint quality worse. To remedy these shortcomings from reprinting, the documents should be classified into various attributes such as image or text, edge or non-edge, continuous-tone or halftone, color or gray, and so on. The improvement of the reprint quality could be achieved by applying proper enhancement with these attributes. In this paper, we introduce a robust and effective approach to classify scanned documents into the attributes of each pixel. The proposed document segmentation algorithm utilizes simple features such as variance-to-mean (VMR), gradient, etc in various combinations of sizes and positions of a processing kernel. We also exploit each direction of gradients in the multiple positions of the same kernel to detect as small as 4-point text. Experimental results show that our proposed algorithm performs well over various types of the scanned documents including the documents that were printed in a resolution of low lines per inch (LPI).

  9. 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.

  10. Molecular basis for color vision.

    PubMed

    Yoshizawa, T

    1994-05-01

    Amino acid sequences of four kinds of chicken cone pigments and two kinds of nocturnal gecko visual pigment were determined. Calculations of amino acid identities indicate that gecko pigments should be cone pigments. A phylogenetic tree of visual pigments constructed demonstrated that cone pigments evolved earlier than rod pigments (rhodopsins), indicating that daylight vision including color vision appeared earlier than twilight vision. The divergence of cone pigments to rhodopsins would be caused by replacing basic amino acid residues to acidic ones according to net charge calculations. A comparison between chicken rhodopsin and cone pigments (chicken green and red) displayed that the cone pigments are faster in regeneration from 11-cis retinal and opsin, faster in formation of meta II-intermediate and shorter in lifetime of meta II-intermediate than rhodopsin. These facts would partly explain the rapid dark adaptation, the rapid light response and the low photosensitivity of cones compared with rods. In comparison with di- and tri-chromatic color visions, chicken tetra-chromatic vision was discussed on the basis of both absorption spectra of cone pigments and filtering effect of oil droplets. PMID:8011932

  11. 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.

  12. Normalizing videos of anterior eye segment surgeries.

    PubMed

    Quellec, Gwénolé; Charriére, Katia; Lamard, Mathieu; Cochener, Béatrice; Cazuguel, Guy

    2014-01-01

    Anterior eye segment surgeries are usually video-recorded. If we are able to efficiently analyze surgical videos in real-time, new decision support tools will emerge. The main anatomical landmarks in these videos are the pupil boundaries and the limbus, but segmenting them is challenging due to the variety of colors and textures in the pupil, the iris, the sclera and the lids. In this paper, we present a solution to reliably normalize the center and the scale in videos, without explicitly segmenting these landmarks. First, a robust solution to track the pupil center is presented: it uses the fact that the pupil boundaries, the limbus and the sclera / lid interface are concentric. Second, a solution to estimate the zoom level is presented: it relies on the illumination pattern reflected on the cornea. The proposed solution was assessed in a dataset of 186 real-live cataract surgery videos. The distance between the true and estimated pupil centers was equal to 8.0 ± 6.9% of the limbus radius. The correlation between the estimated zoom level and the true limbus size in images was high: R = 0.834. PMID:25569912

  13. 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. PMID:24212005

  14. The activation of segmental and tonal information in visual word recognition.

    PubMed

    Li, Chuchu; Lin, Candise Y; Wang, Min; Jiang, Nan

    2013-08-01

    Mandarin Chinese has a logographic script in which graphemes map onto syllables and morphemes. It is not clear whether Chinese readers activate phonological information during lexical access, although phonological information is not explicitly represented in Chinese orthography. In the present study, we examined the activation of phonological information, including segmental and tonal information in Chinese visual word recognition, using the Stroop paradigm. Native Mandarin speakers named the presentation color of Chinese characters in Mandarin. The visual stimuli were divided into five types: color characters (e.g., , hong2, "red"), homophones of the color characters (S+T+; e.g., , hong2, "flood"), different-tone homophones (S+T-; e.g., , hong1, "boom"), characters that shared the same tone but differed in segments with the color characters (S-T+; e.g., , ping2, "bottle"), and neutral characters (S-T-; e.g., , qian1, "leading through"). Classic Stroop facilitation was shown in all color-congruent trials, and interference was shown in the incongruent trials. Furthermore, the Stroop effect was stronger for S+T- than for S-T+ trials, and was similar between S+T+ and S+T- trials. These findings suggested that both tonal and segmental forms of information play roles in lexical constraints; however, segmental information has more weight than tonal information. We proposed a revised visual word recognition model in which the functions of both segmental and suprasegmental types of information and their relative weights are taken into account. PMID:23400856

  15. Early embryonic determination of the sexual dimorphism in segment number in geophilomorph centipedes

    PubMed Central

    2013-01-01

    Background Most geophilomorph centipedes show intraspecific variability in the number of leg-bearing segments. This intraspecific variability generally has a component that is related to sex, with females having on average more segments than males. Neither the developmental basis nor the adaptive role of this dimorphism is known. Results To determine when this sexual dimorphism in segment number is established, we have followed the development of Strigamia maritima embryos from the onset of segmentation to the first post-embryonic stage where we could determine the sex morphologically. We find that males and females differ in segment number by Stage 6.1, a point during embryogenesis when segment addition pauses while the embryo undergoes large-scale movements. We have confirmed this pattern by establishing a molecular method to determine the sex of single embryos, utilising duplex PCR amplification for Y chromosomal and autosomal sequences. This confirms that male embryos have a modal number of 43 segments visible at Stage 6, while females have 45. In our Strigamia population, adult males have a modal number of 47 leg-bearing segments, and females have 49. This implies that the sexual dimorphism in segment number is determined before the addition of the last leg-bearing segments and the terminal genital segments. Conclusions Sexual dimorphism in segment number is not associated with terminal segment differentiation, but must instead be related to some earlier process during segment patterning. The dimorphism may be associated with a difference in the rate and/or duration of segment addition during the main phase of rapid segment addition that precedes embryonic Stage 6. This suggests that the adaptive role, if any, of the dimorphism is likely to be related to segment number per se, and not to sexual differentiation of the terminal region. PMID:23919293

  16. 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.

  17. 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)

  18. Urine - abnormal color

    MedlinePlus

    ... can be caused by: Beets, blackberries, or certain food colorings Hemolytic anemia Injury to the kidneys or urinary tract Medicine Porphyria Urinary tract disorders that cause ... or drugs Bilirubin Medicines, including methylene blue Urinary ...

  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. Colored Contact Lens Dangers

    MedlinePlus

    ... Halloween Hazard: The Hidden Dangers of Buying Decorative Contact Lenses Without a Prescription Sep. 26, 2013 It ... she first put in a pair of colored contact lenses, Laura Butler of Parkersburg, W.Va., had " ...

  1. Hypergraph coloring complexes.

    PubMed

    Breuer, Felix; Dall, Aaron; Kubitzke, Martina

    2012-08-28

    The aim of this paper is to generalize the notion of the coloring complex of a graph to hypergraphs. We present three different interpretations of those complexes-a purely combinatorial one and two geometric ones. It is shown, that most of the properties, which are known to be true for coloring complexes of graphs, break down in this more general setting, e.g., Cohen-Macaulayness and partitionability. Nevertheless, we are able to provide bounds for the [Formula: see text]- and [Formula: see text]-vectors of those complexes which yield new bounds on chromatic polynomials of hypergraphs. Moreover, though it is proven that the coloring complex of a hypergraph has a wedge decomposition, we provide an example showing that in general this decomposition is not homotopy equivalent to a wedge of spheres. In addition, we can completely characterize those hypergraphs whose coloring complex is connected. PMID:23483700

  2. Colors of the Sky.

    ERIC Educational Resources Information Center

    Bohren, Craig F.; Fraser, Alistair B.

    1985-01-01

    Explains the physical principles which result in various colors of the sky. Topics addressed include: blueness, mystical properties of water vapor, ozone, fluctuation theory of scattering, variation of purity and brightness, and red sunsets and sunrises. (DH)

  3. Color Associations of Children.

    ERIC Educational Resources Information Center

    Byrnes, Deborah A.

    1983-01-01

    Free color associations were collected from a total of 337 children in the fourth through sixth grades to 12 concepts: hope, anger, sadness, honesty, fear, happiness, pain, love, death, strength, school, and life. (Author/RH)

  4. Phoenix Color Targets

    NASA Technical Reports Server (NTRS)

    2008-01-01

    These images of three Phoenix color targets were taken on sols 1 and 2 by the Surface Stereo Imager (SSI) on board the Phoenix lander. The bottom target was imaged in approximate color (SSI's red, green, and blue filters: 600, 530, and 480 nanometers), while the others were imaged with an infrared filter (750 nanometers). All of them will be imaged many times over the mission to monitor the color calibration of the camera. The two at the top show grains 2 to 3 millimeters in size that were likely lifted to the Phoenix deck during landing. Each of the large color chips on each target contains a strong magnet to protect the interior material from Mars' magnetic dust.

    The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  5. Color harmonization for images

    NASA Astrophysics Data System (ADS)

    Tang, Zhen; Miao, Zhenjiang; Wan, Yanli; Wang, Zhifei

    2011-04-01

    Color harmonization is an artistic technique to adjust a set of colors in order to enhance their visual harmony so that they are aesthetically pleasing in terms of human visual perception. We present a new color harmonization method that treats the harmonization as a function optimization. For a given image, we derive a cost function based on the observation that pixels in a small window that have similar unharmonic hues should be harmonized with similar harmonic hues. By minimizing the cost function, we get a harmonized image in which the spatial coherence is preserved. A new matching function is proposed to select the best matching harmonic schemes, and a new component-based preharmonization strategy is proposed to preserve the hue distribution of the harmonized images. Our approach overcomes several shortcomings of the existing color harmonization methods. We test our algorithm with a variety of images to demonstrate the effectiveness of our approach.

  6. Tooth - abnormal colors

    MedlinePlus

    ... appear as spots or lines in the tooth enamel. Your genes affect your tooth color. Other things ... Infections Inherited diseases may affect the thickness of enamel or the calcium or protein content of the ...

  7. Chemistry, Color, and Art.

    ERIC Educational Resources Information Center

    Orna, Mary Virginia

    2001-01-01

    Describes pigments and artists' colors from a chronological perspective. Explains how chemical analysis can be used to distinguish the differences between artists' palettes, identify the evolution of art, and lead to restoration of an art work. (Contains 13 references.) (YDS)

  8. Color Doppler flow imaging.

    PubMed

    Foley, W D; Erickson, S J

    1991-01-01

    The performance requirements and operational parameters of a color Doppler system are outlined. The ability of an operator to recognize normal and abnormal variations in physiologic flow and artifacts caused by noise and aliasing is emphasized. The use of color Doppler flow imaging is described for the vessels of the neck and extremities, upper abdomen and abdominal transplants, obstetrics and gynecology, dialysis fistulas, and testicular and penile flow imaging. PMID:1898567

  9. Physics of structural colors

    NASA Astrophysics Data System (ADS)

    Kinoshita, S.; Yoshioka, S.; Miyazaki, J.

    2008-07-01

    In recent years, structural colors have attracted great attention in a wide variety of research fields. This is because they are originated from complex interaction between light and sophisticated nanostructures generated in the natural world. In addition, their inherent regular structures are one of the most conspicuous examples of non-equilibrium order formation. Structural colors are deeply connected with recent rapidly growing fields of photonics and have been extensively studied to clarify their peculiar optical phenomena. Their mechanisms are, in principle, of a purely physical origin, which differs considerably from the ordinary coloration mechanisms such as in pigments, dyes and metals, where the colors are produced by virtue of the energy consumption of light. It is generally recognized that structural colors are mainly based on several elementary optical processes including thin-layer interference, diffraction grating, light scattering, photonic crystals and so on. However, in nature, these processes are somehow mixed together to produce complex optical phenomena. In many cases, they are combined with the irregularity of the structure to produce the diffusive nature of the reflected light, while in some cases they are accompanied by large-scale structures to generate the macroscopic effect on the coloration. Further, it is well known that structural colors cooperate with pigmentary colors to enhance or to reduce the brilliancy and to produce special effects. Thus, structure-based optical phenomena in nature appear to be quite multi-functional, the variety of which is far beyond our understanding. In this article, we overview these phenomena appearing particularly in the diversity of the animal world, to shed light on this rapidly developing research field.

  10. Segmentation of stereo terrain images

    NASA Astrophysics Data System (ADS)

    George, Debra A.; Privitera, Claudio M.; Blackmon, Theodore T.; Zbinden, Eric; Stark, Lawrence W.

    2000-06-01

    We have studied four approaches to segmentation of images: three automatic ones using image processing algorithms and a fourth approach, human manual segmentation. We were motivated toward helping with an important NASA Mars rover mission task -- replacing laborious manual path planning with automatic navigation of the rover on the Mars terrain. The goal of the automatic segmentations was to identify an obstacle map on the Mars terrain to enable automatic path planning for the rover. The automatic segmentation was first explored with two different segmentation methods: one based on pixel luminance, and the other based on pixel altitude generated through stereo image processing. The third automatic segmentation was achieved by combining these two types of image segmentation. Human manual segmentation of Martian terrain images was used for evaluating the effectiveness of the combined automatic segmentation as well as for determining how different humans segment the same images. Comparisons between two different segmentations, manual or automatic, were measured using a similarity metric, SAB. Based on this metric, the combined automatic segmentation did fairly well in agreeing with the manual segmentation. This was a demonstration of a positive step towards automatically creating the accurate obstacle maps necessary for automatic path planning and rover navigation.

  11. Color measurement and discrimination

    NASA Technical Reports Server (NTRS)

    Wandell, B. A.

    1985-01-01

    Theories of color measurement attempt to provide a quantative means for predicting whether two lights will be discriminable to an average observer. All color measurement theories can be characterized as follows: suppose lights a and b evoke responses from three color channels characterized as vectors, v(a) and v(b); the vector difference v(a) - v(b) corresponds to a set of channel responses that would be generated by some real light, call it *. According to theory a and b will be discriminable when * is detectable. A detailed development and test of the classic color measurement approach are reported. In the absence of a luminance component in the test stimuli, a and b, the theory holds well. In the presence of a luminance component, the theory is clearly false. When a luminance component is present discrimination judgements depend largely on whether the lights being discriminated fall in separate, categorical regions of color space. The results suggest that sensory estimation of surface color uses different methods, and the choice of method depends upon properties of the image. When there is significant luminance variation a categorical method is used, while in the absence of significant luminance variation judgments are continuous and consistant with the measurement approach.

  12. Color planner for designers based on color emotions

    NASA Astrophysics Data System (ADS)

    Cheng, Ka-Man; Xin, John H.; Taylor, Gail

    2002-06-01

    During the color perception process, an associated feeling or emotion is induced in our brains, and this kind of emotion is termed as 'color emotion.' The researchers in the field of color emotions have put many efforts in quantifying color emotions with the standard color specifications and evaluating the influence of hue, lightness and chroma to the color emotions of human beings. In this study, a color planner was derived according to these findings so that the correlation of color emotions and standard color specifications was clearly indicated. Since people of different nationalities usually have different color emotions as different cultural and traditional backgrounds, the subjects in this study were all native Hong Kong Chinese and the color emotion words were all written in Chinese language in the visual assessments. Through the color planner, the designers from different areas, no matter fashion, graphic, interior or web site etc., can select suitable colors for inducing target color emotions to the customers or product-users since different colors convey different meanings to them. In addition, the designers can enhance the functionality and increase the attractiveness of their designed products by selecting suitable colors.

  13. FEASIBILITY of “TRACEABLE” COLOR STANDARDS for COTTON COLOR

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton color is measured on the Uster® High Volume Instrument (HVI) for Rd (diffuse reflectance) and +b (yellowness). Rd and +b are cotton-specific color parameters, and they are not as well known as other globally recognized color systems (e.g., L*a*b*). Further, the standards used for HVI color...

  14. The intensity dependent spread model and color constancy

    NASA Technical Reports Server (NTRS)

    Kurrasch, Ellie

    1990-01-01

    Odetics is investigating the use of the intensity dependent spread (IDS) model for determining color constancy. Object segmentation is performed effortlessly by the human visual systems, but creating computer vision that takes an image as input and performs object identification on the basis of color has some difficulties. The unknown aspects of the light illuminating a scene in space or anywhere can seriously interfere with the use of color for object identification. The color of an image depends not only on the physical characteristics of the object, but also on the wavelength composition of the incident illumination. IDS processing provides the extraction of edges and of reflectance changes across edges, independent of variations in scene illumination. IDS depends solely on the ratio of the reflectances on the two sides of the edge. Researchers are in the process of using IDS to recover the reflectance image.

  15. 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. PMID:26560917

  16. Insect segmentation: Genes, stripes and segments in "Hoppers".

    PubMed

    French, V

    2001-11-13

    Recent work has revealed that orthologues of several segmentation genes are expressed in the grasshopper embryo, in patterns resembling those shown in Drosophila. This suggests that, despite great differences between the embryos, a hierarchy of gap/pair-rule/segment polarity gene function may be a shared and ancestral feature of insect segmentation. PMID:11719236

  17. Adaptation and perceptual norms

    NASA Astrophysics Data System (ADS)

    Webster, Michael A.; Yasuda, Maiko; Haber, Sara; Leonard, Deanne; Ballardini, Nicole

    2007-02-01

    We used adaptation to examine the relationship between perceptual norms--the stimuli observers describe as psychologically neutral, and response norms--the stimulus levels that leave visual sensitivity in a neutral or balanced state. Adapting to stimuli on opposite sides of a neutral point (e.g. redder or greener than white) biases appearance in opposite ways. Thus the adapting stimulus can be titrated to find the unique adapting level that does not bias appearance. We compared these response norms to subjectively defined neutral points both within the same observer (at different retinal eccentricities) and between observers. These comparisons were made for visual judgments of color, image focus, and human faces, stimuli that are very different and may depend on very different levels of processing, yet which share the property that for each there is a well defined and perceptually salient norm. In each case the adaptation aftereffects were consistent with an underlying sensitivity basis for the perceptual norm. Specifically, response norms were similar to and thus covaried with the perceptual norm, and under common adaptation differences between subjectively defined norms were reduced. These results are consistent with models of norm-based codes and suggest that these codes underlie an important link between visual coding and visual experience.

  18. Low voltage solid-state lateral coloration electrochromic device

    DOEpatents

    Tracy, C.E.; Benson, D.K.; Ruth, M.R.

    1984-12-21

    A solid-state transition metal oxide device comprising a plurality of layers having a predisposed orientation including an electrochromic oxide layer. Conductive material including anode and cathode contacts is secured to the device. Coloration is actuated within the electrochromic oxide layer after the application of a predetermined potential between the contacts. The coloration action is adapted to sweep or dynamically extend across the length of the electrochromic oxide layer.

  19. Low voltage solid-state lateral coloration electrochromic device

    DOEpatents

    Tracy, C. Edwin; Benson, David K.; Ruth, Marta R.

    1987-01-01

    A solid-state transition metal oxide device comprising a plurality of lay having a predisposed orientation including an electrochromic oxide layer. Conductive material including anode and cathode contacts is secured to the device. Coloration is actuated within the electrochromic oxide layer after the application of a predetermined potential between the contacts. The coloration action is adapted to sweep or dynamically extend across the length of the electrochromic oxide layer.

  20. An ecological valence theory of human color preference

    PubMed Central

    Palmer, Stephen E.; Schloss, Karen B.

    2010-01-01

    Color preference is an important aspect of visual experience, but little is known about why people in general like some colors more than others. Previous research suggested explanations based on biological adaptations [Hurlbert AC, Ling YL (2007) Curr Biol 17:623–625] and color-emotions [Ou L-C, Luo MR, Woodcock A, Wright A (2004) Color Res Appl 29:381–389]. In this article we articulate an ecological valence theory in which color preferences arise from people’s average affective responses to color-associated objects. An empirical test provides strong support for this theory: People like colors strongly associated with objects they like (e.g., blues with clear skies and clean water) and dislike colors strongly associated with objects they dislike (e.g., browns with feces and rotten food). Relative to alternative theories, the ecological valence theory both fits the data better (even with fewer free parameters) and provides a more plausible, comprehensive causal explanation of color preferences. PMID:20421475