Evaluation of Methods for Ridge and Valley Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multilocal creaseness based on the level-set extrinsic curvature
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Direct Gray-Scale Extraction of Features for Character Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multivariate Saddle Point Detection for Statistical Clustering
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
n-Dimensional Distribution Reduction Preserving its Structure
Proceedings of the 2006 conference on Artificial Intelligence Research and Development
A System to Segment Text and Symbols from Color Maps
Graphics Recognition. Recent Advances and New Opportunities
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One main process in Computer Vision is image segmentation as a tool to other visual tasks. Although there are many approaches to grey scale image segmentation, nowadays most of the digital images are colour images. This paper introduces a new method for colour image segmentation. We focus our work on a topological study of colour distribution, e.g., image histogram. We argue that this point of view bring us the possibility to find dominant colours by preserving the spatial coherence of the histogram. To achieve it, we find and extract ridges of the colour distribution and assign a unique colour at every ridge as a representative colour of an interest region. This method seems to be not affected by shadows in a wide range of tested images.