Color image segmentation based on automatic morphological clustering

Abstract : We present an original method to segment color images using a classification in the 3-D color space. In the case of ordinary images, clusters that appear in 3-D histograms usually do not fit a well-known statistical model. For that reason, we propose a classifier that relies on mathematical morphology, and more precisely on the watershed algorithm. We show on various images that the expected color clusters are correctly identified by our method. Last, to segment color images into coherent regions, we perform a Markovian labeling that takes advantage of the morphological classification results.
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Communication dans un congrès
IEEE International Conference on Image Processing (ICIP'01), Oct 2001, Thessaloniki, Greece. 3, pp.70--73, 2001, Proceedings of the International Conference on Image Processing, 2001. 〈10.1109/ICIP.2001.958053〉
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https://hal.inria.fr/inria-00614669
Contributeur : Pierre-Yves Strub <>
Soumis le : dimanche 14 août 2011 - 23:20:04
Dernière modification le : mardi 23 août 2011 - 16:22:05

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Thierry Géraud, Pierre-Yves Strub, Jérome Darbon. Color image segmentation based on automatic morphological clustering. IEEE International Conference on Image Processing (ICIP'01), Oct 2001, Thessaloniki, Greece. 3, pp.70--73, 2001, Proceedings of the International Conference on Image Processing, 2001. 〈10.1109/ICIP.2001.958053〉. 〈inria-00614669〉

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