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Feature extraction is the most important step of character recognition. Accuracy of the recognition mostly depends on it. Ten regional features are proposed in this paper. Principal component analysis is used to reduce the data set as well as to remove redundancy. For recognition, K-nearest neighbor classifier is used and that yields a very high rate of 100%.