Physicians employ to diagnose a burn depth, in order to determine with experimentally proposed multidimensional scaling(MDS) analysis. These mathematical features are correlated with these physical characteristics analysis. This features have been improved with principal component analysis and a support vector machine classifier. This method to identify physical features that experienced plastic surgeons employ to classify burns into their depths. Finally these features are classified with k-nearest-neighbor (KNN) classifier and support vector machine (SVM). Burn injury is essential to initiate the correct first treatment. For diagnose the treatment is necessary to know the depth of the burn. Correct visual assessment of burn depth relies highly on specialized dermatological expertise. Epidermal burns are usually red, dry, and painful. The main problem encountered in the analysis of digital photographs of burn wounds. Burn depth from digital photographs have been published with encouraging results (82.26% success rate). Brainstorming to identify features in the images correlated to their coordinates in the multidimensional space.