STATISTICAL FEATURE EXTRACTION TO CLASSIFY ORAL CANCERS

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, and 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%. Keywords: Marker Controlled Watershed Algorithm, GLCM, SVM