Segmentation and grading of eczema skin lesions

In this paper Eczema skin lesions are segmented and graded using image processing and analysis. For preprocessing adaptive light compensation and gamma correction has been used. The effect of color space normalization has been studied for lesion segmentation. K-means algorithm is used for segmentation. We have used RGB and CIELab color models; and their normalized I and II versions. The experimental results show that normalized color spaces give better segmentation results than the normal color spaces. Our proposed algorithm gives best segmentation accuracy of 84.6% for RGB normalized II color space for the G channel for adaptive light compensation. The grading accuracy for erythema is around 70%.