An Analysis of Psoriasis Skin Images
Ashwini C. Bolkote1, M.B. Tadwalkar2
1Ashwini C. Bolkote, Department of Electronics and Telecomm Engineering, JSPMs, Jayawantrao Sawant College of Engg, Hadapsar, Pune 28, India.
2Prof. M. B. Tadwalkar, Department of Electronics and Telecomm Engineering, JSPMs, Jayawantrao Sawant College of Engg, Hadapsar, Pune 28, India.
Manuscript received on November 08, 2014. | Revised Manuscript Received on November 20, 2014. | Manuscript published on November 20, 2014. | PP: 17-22 | Volume-2, Issue-12, November 2014. | Retrieval Number: L05431121214/2014©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this study a skin disease diagnosis system was developed and tested. The system was used for diagnosis of psoriases skin disease. Present study relied on both skin color and texture features (features derives from the GLCM) to give a better and more efficient recognition accuracy of skin diseases. In this study feed forward neural networks is used to classify input images to be psoriases infected or non psoriasis infected.
Keywords: Skin recognition, skin texture, computer aided disease diagnosis, texture analysis, neural networks, Psoriasis.