Static Filtered Skin Detection

A static skin filter defines explicitly (using a number of rules) the boundaries the skin cluster has in a color space. Single or multiple ranges of threshold values for each color space component are created and the image pixel values falling within these range(s) for all the chosen color components are defined as skin pixels. In this paper, we investigate and evaluate static skin filters for skin segmentation. As a contribution, two new static skin filters for the IHLS and CIELAB color spaces are developed. The two new static filters and four state-of-theart static filters in YCbCr, HSI, RGB and normalized RGB color spaces are evaluated on the two datasets DS1 and DS2, on the basis of F-measure. Experimental results reveal the feasibility of the developed static skin filters. We also found that since the static filters use static boundaries, any shift of skin color ranges from the static boundaries will result in varying performance. Therefore, the F-measure rankings of the color spaces are different for the datasets DS1 and DS2.

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