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- W2280104865 abstract "Several applications demand the segmentation of images in skin and non-skin regions, such as face recognition, hand gesture detection, nudity recognition, among others. Human skin detection is still a challenging task and, although color attribute is a very important clue, it usually generates high rate of false positives. This work proposes and analyzes a skin segmentation method improved by texture energy. Experimental results on a challenging public data set demonstrate significant improvement of the proposed skin segmentation method over color-based state-of-the-art approaches." @default.
- W2280104865 created "2016-06-24" @default.
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- W2280104865 date "2015-01-01" @default.
- W2280104865 modified "2023-10-14" @default.
- W2280104865 title "Human Skin Segmentation Improved by Texture Energy Under Superpixels" @default.
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- W2280104865 doi "https://doi.org/10.1007/978-3-319-25751-8_5" @default.
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