Computed Aided Diagnosis System for Skin Disease Identification

Skin disease cases are expanding every day and hard to deal with because of the worldwide unevenness among skin disease patients and dermatologists, Skin infections are among the main 5 motivating reasons for the overall disease trouble, to decrease, CAD frameworks are greatly required, single skin disease characterization is the significant inadequacy in the current work. The characterization of various skin diseases is exceptionally tested because of the comparative attributes of skin illnesses. The pattern of skin infections will group skin condition details into one of the six non-covering groups such as healthy, acne, eczema, psoriasis, benign and malignant melanoma, etc. Four phases compose the proposed order structure, pre-processing, segmentation, feature extraction, and classification. To accomplish each stage, various digital image processing and machine learning techniques are used and achieving 90 to 95% accuracy using a Support Vector Machine. Result of CAD technique also supported to the doctor easily find out a detected area as compared to other techniques.