Skin lesion detection plays dominant role in computer-aided diagnosis system of dermoscopic image. Be different from existing segmentation algorithms which are based on traditional features like texture or color

the proposed algorithm is based on independent pigment concentration distribution. First

a dermoscopic imaging model is built based on Lambert-Beer law

followed by obtaining and visualizing pigment concentration distribution after applying ICA method. Then give the definition of Pigment Concentration Ratio(PCR)

which puts emphasize on gradient distribution of single pigment concentration. Final segmentation is created by applying global or local thresholding-based algorithm on PCR. Experiments show the robustness and generalization of proposed algorithm. Especially

expected segmentation result is achieved even if lesion regions of input image show very dim gradient.