Bangla off-line Handwritten Character Recognition Using Superimposed Matrices

This paper presents an off-line recognition system for Bangla handwritten characters using superimposed matrices. It is observed that, in all cases, the same character written by different individuals shows at least a minimum level of similarity. In this system, the Bangla text, accepted as an image file, is first segmented into lines and words and then each word is segmented into characters. Then the boundary of each character is determined. The characters are scaled to a standard size using an image scaling algorithm and are stored in a 32X32 matrix. This matrix is then compared with a knowledge base where all recognized characters given by various persons are stored in superimposed form. Finally, depending on the similarity of the character with the stored one, the system recognizes the character to use in the output. This system is suitable to convert handwritten texts into printed documents.