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- W2145728402 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. Moreover, the user can choose different ways to combine information." @default.
- W2145728402 created "2016-06-24" @default.
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- W2145728402 date "2005-01-01" @default.
- W2145728402 modified "2023-10-17" @default.
- W2145728402 title "Combined Geometric-Texture Image Classification" @default.
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- W2145728402 doi "https://doi.org/10.1007/11567646_14" @default.
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