Sinhala handwritten character recognition by using enhanced thinning and curvature histogram based method

This paper presents handwritten non-cursive Sinhala character recognition method based on discrete feature extraction of the well thinned character. Study presents adjacent pixel connectivity based thinning algorithm for skeletonizing handwritten characters and curvature based pattern matching and histogram formation method for recognition which can sensitively accessed the round, confusion shapes and complexity of modifier connectivity in Sinhala handwritten scripts. The devised feature vector has shown its strength in the feature classification with greater performance. Proposed method is able to recognize 21 handwritten Sinhala characters with over 90% accuracy.