Main Article Content
Due to the fast lifestyle and less time for self monitoring through invasive methods which are accurate but needs time and costly too, research is going on to improve the accuracy of non-invasive method for disease identification. In India there is rapid increase in tongue related diseases like severe ulcers and cancer. Identification of the abnormalities at initial stage plays very important role in disease identification. Work in same field to find abnormality at earlier stage will be beneficial to patient so that if needed they may opt for invasive method for disease confirmation and its treatment at initial stage. This paper presents a hybrid algorithm using firefly algorithm and k-mean clustering algorithm along with parallel processing using CNN to identify normal and abnormal tongue images. Database of Oral cancer foundation and images available online are used and 150 normal and abnormal digital tongue images along with augmentation are used in CNN to obtain results. Results shows proposed method with CNN gives 90% validation accuracy and it is able to discriminate between normal and Normal tongue images.