Classification Methods of Skin Burn Images

Abstract

In this paper, methods to automatically detect and categorize the severity of skin burn images using various classification techniques are compared and presented. A database comprising of skin burn images belonging to patients of diverse ethnicity, gender and age are considered. First the images are preprocessed and then classified utilizing the pattern recognition techniques: Template Matching (TM), K nearest neighbor classifier (kNN) and Support Vector Machine (SVM). The classifier is trained for different skin burn grades using pre-labeled images and optimized for the features chosen. This algorithm developed, works as an automatic skin burn wound analyzer and aids in the diagnosis of burn victims.