Psoriasis image identification using k-means clustering with morphological processing

We present a preliminary design and experimental results of psoriasis objects tracking method for color-skin images that utilizes k-means clustering with morphological processing technique. The method is capable of solving unable exactly contoured psoriasis objects problem in color-skin image by adding the morphological reconstruction operation. The key idea of the proposed image processing procedure is the k-means clustering method helps the rough segmentation, then the dilation and erosion method are adapted to refine previous results. In this paper we investigate the possibility of employing this approach for psoriasis image application. The application of the proposed method for tracking psoriasis is demonstrated to help pathologists distinguish exactly its size and region. In this paper, we propose a psoriasis image segmentation procedure to improve the accuracy. The experimental results demonstrate that the misclassification error is very small between the proposed result and hand drawing.