Skin texture analysis for medical diagnosis

Authors:
Nabanita Bhattacharjee;Ranjan Parekh
Affiliations:
West Bengal University of Technology, Kolkata, West Bengal, India;Jadavpur University, Kolkata, West Bengal, India
Venue:
Proceedings of the 2011 International Conference on Communication, Computing & Security
Year:
2011

Citing 4
Cited 0

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Abstract

This paper proposes an automated system for recognizing disease conditions of human skin in context to health informatics. The disease conditions are recognized by analyzing skin texture images using a set of normalized symmetrical Grey Level Co-occurrence Matrices (GLCM). Directional GLCMs are computed along four directions viz. horizontal, vertical, right diagonal, left diagonal, and a set of features viz. Contrast, Homogeneity, Mean, Variance and Energy computed from each, are averaged to provide an estimation of the texture class. The system is tested on a set of medical images displaying three dermatological skin conditions viz. Acne, Eczema, and Urticaria. The features are considered in various combinations viz. individually, and in joint 2-D feature spaces, using L1 and L2 metrics as well as neural network classifiers, to study which combination produces best recognition accuracies.