Analysis of Chronic Burn Depth Assessment System in Multidimensional Image Based on Testing Records

Abstract

The Recent Developments carried out in the bio-medical image processing plays a vital role in the assessment of the image processing systems. The research contributions carried out in this image processing field helps in assessing the images of burns using the machine learning algorithms and this is possible with the aid of Support vector-based Machine learning approaches. In this work, the focus is on the analysis of the chronic burnt images, assessing the depth of these images using multidimensional image. The methodologies involved in the work are Two stage SVM proposed as Enhanced Support Vector Machine (ESVM) which is of two stages, firstly the training stage and secondly, the classification stage.The proposed ESVM is compared with supervised machine Learning (ML) algorithm with the precision, accuracy, success rate etc., and the ESVM out performs by 96.5 % accuracy and 81.20% success rate 84.66% Precision when compared with the existing algorithms and same is tested and validated in the study carried out and presented.