Advance Study Of Skin Diseases Detection Using Image Processing Methods

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Dr. Mukta Jagdish , Sandra Paola Gualán Guamangate , María A. García López , Jhony A. De La Cruz-Vargas , Maleny Estefanía Roque Camacho


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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