Edge, Junction, and Corner Detection Using Color Distributions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color Image Segmentation for Multimedia Applications
Journal of Intelligent and Robotic Systems
Characterization of empirical discrepancy evaluation measures
Pattern Recognition Letters
Color-texture image segmentation by integrating directional operators into JSEG method
Pattern Recognition Letters
Extrapolative Spatial Models for Detecting Perceptual Boundaries in Colour Images
International Journal of Computer Vision
Color-texture image segmentation by integrating directional operators into JSEG method
Pattern Recognition Letters
Automatic generation of consensus ground truth for the comparison of edge detection techniques
Image and Vision Computing
Journal of Visual Communication and Image Representation
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
A novel image enhancement approach based on wavelet transformation
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Evaluation of global thresholding techniques in non-contextual edge detection
Pattern Recognition Letters
An efficient method for robust gradient estimation of RGB color images
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Active contouring based on gradient vector interaction and constrained level set diffusion
IEEE Transactions on Image Processing
Real-time object tracking on iPhone
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
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This paper discusses an approach for detecting edges in color images. A color image is represented by a vector field, and the color image edges are detected as differences in the local vector statistics. These statistical differences can include local variations in color or spatial image properties. The proposed approach can easily accommodate concepts, such as multiscale edge detection, as well as the latest developments in vector order statistics for color image processing. A distinction between the proposed approach and previous approaches for color edge detection using vector order statistics is that, besides the edge magnitude, the local edge direction is also provided. Note that edge direction information is a relevant feature to a variety of image analysis tasks (e.g., texture analysis)