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- W569833863 abstract "Image segmentation occupies the important position in image processing, so both high-efficiency and accurate segmentation are of great importance to image’s subsequent research. In this paper, taking the color and texture features into account, the color features are combined with RGB and HSV color space features, and the texture features are made up with the mean value and standard deviation. Considering the advantages of support vector machine (SVM) in classification, we convert the segmentation problem into a classification problem, and we can get the satisfied segmentation result. Genetic Algorithms (GA) is used for the optimization of the parameters in SVM’s kernel which is combined with polynomial (poly) and radial basis function (rbf) kernel reasonably by mercer theorem. The experimental results show that we can segment various kinds of color images effectively." @default.
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- W569833863 date "2013-01-01" @default.
- W569833863 modified "2023-10-01" @default.
- W569833863 title "Color Image Segmentation Based-on SVM Using Mixed Features and Combined Kernel" @default.
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- W569833863 doi "https://doi.org/10.1007/978-3-642-42057-3_51" @default.
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