Skin detection is an important process in many of computer vision algorithms. It usually is a process that starts at a pixel-level, and that involves a pre-process of colorspace transformation followed by a classification process. A colorspace transformation is assumed to increase separability between skin and non-skin classes, to increase similarity among different skin tones, and to bring a robust performance under varying illumination conditions, without any sound reasonings. In this work, we examine if the colorspace transformation does bring those benefits by measuring four separability measurements on a large dataset of 805 images with different skin tones and illumination. Surprising results indicate that most of the colorspace transformations do not bring the benefits which have been assumed.
Does colorspace transformation make any difference on skin detection?
01.01.2002
284091 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Does Colorspace Transformation Make Any Difference on Skin Detection?
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