Comparison of Psoriasis Disease Detection and Classification Through Various Image Processing Techniques-A Review

Skin disease is the major problem that we facing today. There are many reasons for skin diseases such as food, water, environmental conditions and so on. Among such diseases, Psoriasis is one of them. Psoriasis could be a skin contamination that causes reddish, aggravated flaky patches, most normally on the knees, elbows, trunk and scalp. Psoriasis could be a typical, long haul contamination (tenacious) with no cure. It tends to go through cycles, which means it occurs continuously for weeks or months. Skin illnesses such as psoriasis has lower affect on death rate but have more prominent affect on the quality of life. There are various types of image processing techniques for the psoriasis disease identification and classification. In this paper we compare the different techniques used in past for preprocessing, segmentation, feature extraction and classification. After comparing different techniques we make a new model approach for the psoriasis disease detection and classification having high efficiency and accuracy.