Spectral gradients for color-based object recognition and indexing
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
Cast shadow segmentation using invariant color features
Computer Vision and Image Understanding
Edge and Corner Detection by Photometric Quasi-Invariants
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modelling and segmentation of colour images in polar representations
Image and Vision Computing
Chromaticity-based separation of reflection components in a single image
Pattern Recognition
Performance evaluation of local colour invariants
Computer Vision and Image Understanding
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
A new approach for vehicle detection in congested traffic scenes based on strong shadow segmentation
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Robust color contour object detection invariant to shadows
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Shadow edge detection using geometric and photometric features
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Motion vector processing using the color information
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Orthophotoplan segmentation and colorimetric invariants for roof detection
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
A Probabilistic SVM Approach to Annotation of Calcification Mammograms
International Journal of Digital Library Systems
Closed contour specular reflection segmentation in laparoscopic images
Journal of Biomedical Imaging
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We aim at using color information to classify the physical nature of edges in video. To achieve physics-based edge classification, we first propose a novel approach to color edge detection by automatic noise-adaptive thresholding derived from sensor noise analysis. Then, we present a taxonomy on color edge types. As a result, a parameter-free edge classifier is obtained labeling color transitions into one of the following types: 1) shadow-geometry, 2) highlight edges, and 3) material edges. The proposed method is empirically verified on images showing complex real world scenes.