Skin Disease Recognition Method Based on Image Color and Texture Features

Skin diseases have a serious impact on people’s life and health. Current research proposes an efficient approach to identify singular type of skin diseases. It is necessary to develop automatic methods in order to increase the accuracy of diagnosis for multitype skin diseases. In this paper, three t...

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Bibliographic Details
Published in:Computational and mathematical methods in medicine 2018-01, Vol.2018 (2018), p.1-10
Main Authors: Wei, Li-sheng, Ji, Tao, Gan, Quan
Format: Article
Language:English
Subjects:
Color
Humans
Image Processing, Computer-Assisted
Skin Diseases - diagnosis
Support Vector Machine
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Summary:Skin diseases have a serious impact on people’s life and health. Current research proposes an efficient approach to identify singular type of skin diseases. It is necessary to develop automatic methods in order to increase the accuracy of diagnosis for multitype skin diseases. In this paper, three type skin diseases such as herpes, dermatitis, and psoriasis skin disease could be identified by a new recognition method. Initially, skin images were preprocessed to remove noise and irrelevant background by filtering and transformation. Then the method of grey-level co-occurrence matrix (GLCM) was introduced to segment images of skin disease. The texture and color features of different skin disease images could be obtained accurately. Finally, by using the support vector machine (SVM) classification method, three types of skin diseases were identified. The experimental results demonstrate the effectiveness and feasibility of the proposed method.
ISSN:1748-670X
1748-6718
DOI:10.1155/2018/8145713