Statistical feature based classification of arthritis in knee X-ray images using local binary pattern

Arthritis is the most common inflammation that occurs in bone joints. The possibility of early disability and joint deformities are high for a person affected by arthritis. By the early diagnosis and treatment of the Arthritis, the damage to the joins can be reduced. A number of therapeutic approaches are now widely available for the diagnosis of this disease. Imaging of the affected joints plays a vital role in the analysis. This paper discuss the classification of arthritis using KNN and Bayesian classifiers based on the feature extracted from digital X-ray images using local binary pattern.