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Asian Journal of Scientific Research

Year: 2013 | Volume: 6 | Issue: 4 | Page No.: 805-811
DOI: 10.3923/ajsr.2013.805.811
Local Binary Pattern Approach to the Classification of Osteoarthritis in Knee X-ray Images
M. Subramoniam and V. Rajini

Abstract: The most common joint disorder, due to aging, wear and tear on a joint is Osteoarthritis (OA). Computer-aided diagnosis system is able to detect the osteoarthritis so that proper treatment options can be considered. In this study, a novel classification system for the classification of OA in knee X-ray images based on Local Binary Pattern (LBP) is presented. The classification is achieved by extracting the histograms of LBP of the knee x-ray image. The performance of the proposed system is analyzed by nearest neighbor classifier using 50 knee X-ray images. The proposed method predicts normal or abnormal knee X-ray image with 95.24% maximum accuracy and medium or worst cases with 97.37% maximum accuracy. Experimental results show that the proposed system could assist radiologists to detect OA earlier and faster.

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How to cite this article
M. Subramoniam and V. Rajini, 2013. Local Binary Pattern Approach to the Classification of Osteoarthritis in Knee X-ray Images. Asian Journal of Scientific Research, 6: 805-811.

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