HYBRID CLASSIFIER TO CLASSIFY THE FINGER NAIL ABNORMALITIES

Nail diagnosis is a method to predict the possibilities of organ failures and various systemic diseases. abnormalities are considered as signs certain diseases in traditional medicines such Siddha Medicine, Ayurveda, Yunani Chinese medicine etc. In this paper, performance existing techniques SVM classifier KNN classifiers compared with proposed method. The metrics precision, recall, F-measure accuracy calculated compared. 100 images had taken for study novel segmentation gives best accuracy. experiment uses 480 (increase dataset) eight types abnormalities. 70% were used training 30% testing. (Discuss measure)