Neural based Handwritten Character Recognition

This paper explores the existing ring based [2], the new sector based and the combination of these, termed as Fusion method for the recognition of handwritten English capital letters. The variability associated with the characters is accounted for by way of considering a fixed number of concentric rings in the case of ring based approach and a fixed number of sectors in the case of sector approach. Structural features such as end points, junction points and the number of branches are used for the preclassification of characters, the local features such as normalized vector lengths and angles derived from either ring or sector approaches are used in the training using the reference characters and subsequent recognition of the test characters. The recognition rates obtained are encouraging.