Skin Color Segmentation Using Multi-Color Space Threshold
Rahmat, Romi Fadillah
Sitompul, Opim Salim
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Skin color segmentation has proven to be useful in various application, such as face detection, hand gesture analysis, image content filtering, etc. There are some challenges on skin-color detection, such as wide variety of illumination condition and skin-like color objects appear in the background of image. Therefore, a method is required to cope with illumination condition while detecting skin color. In our proposed method, we combine the chrominance channels of three color spaces, namely HSV, YCbCr and Normalized RGB, to produce better rate result for skin color segmentation. The result shows that the proposed method is able to detect skin pixel and get up to 91.05% correct result while being tested in ECU and HGR Dataset. This result is significantly higher than the other single color spaces.