Özet:

In this research advanced study of skin disease detection using image processing methods is considered. As we know skin diseases vary accordingly from symptom and severity. They can represent permanent or temporary or painful or painless based on affected disease. Some diseases have a genetic cause or some situational. Some diseases can be found life threatens or some minor based condition. But as per the survey report, many skin diseases become serious issues. So it is very important to continuously monitor and detect skin disease to provide proper treatment and faster recovery protocols. In this investigation, advance study of skin disease detection using fuzzy clustering with machine learning methods KNN and SVM classification algorithm with wavelet analysis is tested with 50 sample images. The results represent the K-Nearest Neighbor classification algorithm works well compared to the Support vector machine (SVM) classification technique with an accuracy of 91.2%. The algorithm also identifies the type of skin disease using classification methods.

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