@inproceedings {337, title = {Perceptually-adaptive color enhancement of still images for dichromacy deficiencies}, booktitle = {21st Canadian Conference on Electrical and Computer Engineering}, year = {2008}, abstract = {

Dichromacy is a medical condition in which a person is unable to distinguish all colors of the spectrum accurately due to the absence of one cone type within the retina of the eye. No known cure exists for dichromacy so techniques have been created to help improve color perception among affected individuals. This paper investigates a novel perceptually-adaptive technique for enhancing details within still images for persons suffering from dichromacy. A non-linear hue remapping is adaptively applied to the still images to improve color differentiation while preserving the aesthetics of the images. Simulations show that the enhanced images preserve visual detail and maintain the aesthetics of the original image.

}, keywords = {color perception, colour vision, dichromacy, eye, image colour analysis, image enhancement, nonlinear hue remapping, perceptually-adaptive technique, retina, vision defects, visual perception}, doi = {http://dx.doi.org/10.1109/CCECE.2008.4564901}, author = {A Wong and W Bishop} } @inproceedings {577, title = {Color image segmentation using connected regions}, booktitle = {16th Canadian Conference on Electrical and Computer Engineering}, year = {2003}, abstract = {

A color image segmentation algorithm based on region growing is presented. Each region is characterized using two parameters: within region color contrast and between region color contrast. The first parameter is the distance between the two most distant pixels in terms of color. The second parameter is the distance between the candidate pixel and its nearest neighbor in the region. The color similarity measure used is the vector angle, which is invariant to shading. Highlight invariance is accomplished by using a highlight removal transformation, which removes the average pixel intensity from each RGB coordinate. The first calculation is very computationally intensive. To reduce this computational burden, the algorithm keeps track of which pixels already in the region are furthest spatially from the pixel being considered. The assumption would be that the pixels the furthest away would be the ones most different from the pixel being considered. We will present results on artificial and real images to illustrate the effectiveness of the method.

}, keywords = {color image segmentation, color similarity measure, connected region, highlight invariance, highlight removal transformation, image colour analysis, image segmentation, pixel intensity, real image, realistic images, RGB coordinate, shading invariance, vector angle}, doi = {http://dx.doi.org/10.1109/CCECE.2003.1226114}, author = {S Wesolkowski and P Fieguth} } @inproceedings {591, title = {Adaptive color image segmentation using Markov random fields}, booktitle = {International Conference on Pattern Recognition}, year = {2002}, address = {Rochester, NY}, abstract = {

A new framework for color image segmentation is introduced generalizing the concepts of point-based and spatially-based methods. This framework is based on Markov random fields using a continuous Gibbs sampler. The Markov random fields approach allows for a rigorous computational framework where local and global spatial constraints can be globally optimized. Using a continuous Gibbs sampler enables the algorithm to adapt continuous-valued regional prototypes in a manner analogous to vector quantization while the discrete Gibbs sampler is used to adjust region boundaries.

}, keywords = {adaptive color image segmentation, adaptive signal processing, continuous Gibbs sampler, continuous-valued regional prototypes, discrete Gibbs sampler, global spatial constraints, image colour analysis, image sampling, image segmentation, local spatial constraints, Markov processes, Markov Random Fields, point-based methods, random processes, region boundaries adjustment, spatially-based methods, vector quantization}, doi = {http://dx.doi.org/10.1109/ICIP.2002.1039085}, author = {S Wesolkowski and P Fieguth} } @inproceedings {597, title = {A Markov random fields model for hybrid edge and region based colour image segmentation}, booktitle = {15th Canadian Conference on Electrical and Computer Engineering}, year = {2002}, abstract = {

A framework based on a Markov random field approach for color image segmentation enhanced by edge detection is presented. We use a previously developed methodology to transform the image into an R\&$\#$39;G\&$\#$39;B\&$\#$39; space to remove any highlight components preserving the vector-angle component, representing color hue but not intensity, to remove shading effects. To improve the segmentation process we describe the idea of a line process. This allows for the integration of region segmentation with edge detection in a Markov random field framework. We discuss the advantages of this new model with respect to the previously developed image segmentation model.

}, keywords = {color hue, color theory, dichromatic reflection model, edge detection, highlight components removal, hybrid edge-based color image segmentation, image colour analysis, image segmentation, line process, Markov processes, Markov random fields model, random processes, region segmentation, region-based color image segmentation, RGB space, shading effects removal, vector-angle component}, doi = {http://dx.doi.org/10.1109/CCECE.2002.1013070}, author = {S Wesolkowski and P Fieguth} } @inproceedings {499, title = {Analysis of corneal images for assessing contact lens trauma}, booktitle = {International Conference on Image Processing}, year = {2000}, address = {Vancouver}, abstract = {

Contact lens wearers are often affected by a condition known as conjuctival hyperaemia. This condition is characterised by dilated blood vessels visible in the sclera (the white portion of the eye). Optometrists need to be able to detect changes in the level of redness and to repeatably assess the absolute levels of redness found in a patient\&$\#$39;s eye in order to prescribe and evaluate treatment. The goal of this paper is to develop an automated method for grading the level of redness in human eyes. The selected features examine the average redness and length of arterial edges. The computed features are correlated with expert data collected to train the redness estimator

}, keywords = {arterial edges, blood vessels, conjuctival hyperaemia, contact lens trauma, corneal images, dilated blood vessels, edge detection, eye, Feature Extraction, human eyes, image colour analysis, medical image processing, patient, redness, redness estimator, sclera}, doi = {http://dx.doi.org/10.1109/ICIP.2000.900923}, author = {J Cullen and P Fieguth and S Pounder and K Whitear} }