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- W2145467624 abstract "In this paper, we propose a framework to carry out supervised classification of images containing both textured and non textured areas. Our approach is based on active contours. Using a decomposition algorithm inspired by the recent work of Y. Meyer, we can get two channels from the original image to classify: one containing the geometrical information, and the other the texture. Using the logic framework by Chan and Sandberg, we can then combine the information from both channels in a user definable way. Thus, we design a classification algorithm in which the different classes are characterized both from geometrical and textured features. Since natural images are combinations of both textured and non textured patterns, this integrative approach enlarges the scope of possible applications for active contours-based classification algorithms." @default.
- W2145467624 created "2016-06-24" @default.
- W2145467624 creator A5003735769 @default.
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- W2145467624 date "2006-10-01" @default.
- W2145467624 modified "2023-09-25" @default.
- W2145467624 title "Combining geometrical and textured information to perform image classification" @default.
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- W2145467624 doi "https://doi.org/10.1016/j.jvcir.2006.02.001" @default.
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