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Combinatorial Color Space Models for Skin Detection in Sub-continental Human Images

机译:用于次大陆人类图像中皮肤检测的组合颜色空间模型

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摘要

Among different color models HSV, HLS, YIQ, YCbCr, YUV, etc. have been most popular for skin detection. Most of the research done in the field of skin detection has been trained and tested on human images of African, Mongolian and Anglo-Saxon ethnic origins, skin colors of Indian sub-continentals have not been focused separately. Combinatorial algorithms, without affecting asymptotic complexity can be developed using the skin detection concepts of these color models for boosting detection performance. In this paper a comparative study of different combinatorial skin detection algorithms have been made. For training and testing 200 images (skin and non skin) containing pictures of sub-continental male and females have been used to measure the performance of the combinatorial approaches, and considerable development in success rate with True Positive of 99.5% and True Negative of 93.3% have been observed.
机译:在不同的颜色模型中,HSV,HLS,YIQ,YCbCr,YUV等对于皮肤检测最为流行。在皮肤检测领域进行的大多数研究都是针对非洲,蒙古和盎格鲁-撒克逊人血统的人类图像进行训练和测试的,印度次大陆的肤色尚未单独关注。可以使用这些颜色模型的皮肤检测概念来开发组合算法,而不会影响渐近复杂性,从而提高检测性能。在本文中,对不同组合皮肤检测算法进行了比较研究。为了训练和测试200张包含次大陆男性和女性照片的图像(皮肤和非皮肤),已用于衡量组合方法的性能,并取得了相当大的发展,成功率为99.5%,正确率为93.3。已观察到%。

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