Psoriasis Detection Using Skin Color and Texture Features
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Nidhal K. Al abbadi* , Nizar Saadi Dahir*, Muhsin A. AL-Dhalimi*, Hind Restom*
* University of Kufa, Najaf - IRAQ
Abstract
In this work a skin disease diagnosis system was developed and tested. The system is used for diagnosis of psoriases skin disease. Our work relies on both skin color and texture features (features derives from the GLCM) to give a better and more efficient recognition accuracy of skin Diseases. We used feed forward neural networks to classify input images to be psoriases infected or non psoriasis infected. The system gave very encouraging results during the neural network training and generalization face.
In this work a skin disease diagnosis system was developed and tested. The system is used for diagnosis of psoriases skin disease. Our work relies on both skin color and texture features (features derives from the GLCM) to give a better and more efficient recognition accuracy of skin Diseases. We used feed forward neural networks to classify input images to be psoriases infected or non psoriasis infected. The system gave very encouraging results during the neural network training and generalization face.
Keywords: skin recognition, skin texture, computer aided disease diagnosis, texture analysis, neural networks, psoriasis.