Description

In this process, we propose the application of suitably selected texture discriminating features for detection of oral cancer lesions in dental images and classifying the types of disease. Support Vector Machine (SVM) is used to compare and validate the performance of different feature sets. The classification accuracy is observed to improve with the stability of the feature extraction by means of the CNN algorithm. Further improvement in accuracy is obtained by application of classifier by reducing the mis-classifications.