Reaction-diffusion based level set method with local entropy thresholding for melasma image segmentation

Abstract

This paper proposes a new method for melasma pigmentary area segmentation utilizing re action-diffusion based level set model (RDLSM) together with local entropy thresholding. In the adopted level set model, a diffusion term is used to regularize the level set function while a reaction term with anticipated sign property is used to force the zero level set towards desired locations. Then local entropy thresholding is applied to address the over-segmentation issue of RDLSM and to extract desired boundaries with higher overall local entropy. As a result, the melasma pigmentary areas and the normal skin areas can be better identified. Experimental results show that the proposed method performs well for melasma image segmentation, especially for cases with severe non-uniform illumination distribution.