Implementation of Improved Segmentation Technique Based on Image Processing for Detection of Oral Tumor

Earlier Detection of cancer can save life. Image Processing plays a vital role in cancer detection. This paper discusses the use of Image Processing to detect and classify cancers from Dental X-Ray images. The current study proposed new segmentation algorithm namely Improved Marker Controlled Watershed Segmentation Algorithm (IMCWS). The proposed algorithm results in good accuracy and processing rate. Feature Extraction methods, Gray Level Co-occurrence Matrix (GLCM), Gray Level Run Length Matrix (GLRLM) and Intensity Histogram (IH) features are used to extract features from the segmented images. Later, classification between normal and abnormal cancer is made using Support Vector Machine (SVM).