Detection of Vitiligo Skin Disease using LVQ Neural Network

Digital image processing is a combination of various algorithms and technique to process different types of images. It is applied in various types of image to process and get a valuable outcome from the image. The Digital image processing is the experimented on image to extract different features of the image. This paper provides the idea which is used to detect the affected area of the Vitiligo disease with help of image captured by camera and classified the affected area from non-affected area in image. Vitiligo is the deep rooted skin disease which is depigmentation of the skin in which human skin starts losing or loss of pigment from the skin. The certain portion of the skin of body became white patches. The Vitiligo is visible in dark skin persons because of some genetic problem or environmental issues. Here, the learning vector quantization neural network is used to classify Vitiligo image in affected vs. non-affected region to detect disease. The implementation of LVQ neural network gives very good accuracy of 92.22% and kappa value of 0.810 which is very good for proposed technique.