This paper presents a handwritten Kannada and English Character recognition system based on spatial features. Directional spatial features viz stroke density, stroke length and the number of stokes are employed as potential features to characterize the handwritten Kannada numerals/vowels and English uppercase alphabets. KNN classifier is used to classify the characters based on these features with four fold cross validation. The proposed system achieves the recognition accuracy as 96.2%, 90.1% and 91.04% for handwritten Kannada numerals, vowels and English uppercase alphabets respectively.

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OCR Spatial Features K-Nearest Neighbor