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Enhanced skin tone detection using heuristic thresholding

Maheswari S, Reeba Korah

The segmentation of skin regions in color images is a preliminary step in several applications. Many different methods to discriminate between skin pixels and non-skin pixels are available in literature. The presence of skin or non-skin region in a digital image can be determined by manipulating tone and/or texture of pixels. The main problem in the detection of skin tone is that it is not satisfactory under illumination conditions and is rarely used for production of an enhanced image. The objective of this article is to enhance and ensure a robust skin tone detection approach which works better under varying lighting conditions and unconstrained environments. This paper outlines a method for detection of skin tone using a heuristic thresholding of YC_bC_r color space and skin tone enhancement. This approach is successfully applied for segmenting human skin and non-skin regions of single person and group of people in random internet images. Evaluation of the proposed approach can be done using different measures like F-measure, specificity and detection rate. Comparison of the proposed method is made with the HSV model. Experimental results demonstrate high objective quality in terms of detection rate and low false positive rates for the proposed model compared to HSV model for variety of images under varying lighting conditions.