抽象的な

STATISTICAL FEATURE EXTRACTION TO CLASSIFY ORAL CANCERS

Anuradha.K, Dr. K. Sankaranarayanan

Oral Cancer is the most common cancer found in both men and women. The proposed system segments and classifies oral cancers at an earlier stage. The tumor is detected using Marker Controlled Watershed segmentation. The features extracted using Gray Level Co occurrence Matrix (GLCM) is Energy, Contrast, Entropy, Correlation, Homogeneity. The extracted features are fed into Support Vector Machine (SVM) Classifier to classify the tumor as benign or malignant. The accuracy obtained for the proposed system is 92.5%.