Some Approaches to the Recognition of Handwritten Numerals

The present work deals with the recognition of handwritten isolated numerals by utilizing a recent approach, which aims at tackling the variability in the writing styles. A two pronged approach involving pre-classification and the recognition has been followed in this paper. For the pre-classification of numerals, two approaches have been presented. The first is heuristic based and the second is stroke based. A recent feature extraction method, namely sector data method, which takes care of variability in the handwritten numerals, has been incorporated into the system thus the variability involved in the writing styles of different individuals is taken care of by extracting features from the sector based approach. The back propagation neural networks have been used in the recognition process using the features extracted from the sector-based approach. On the basis of recognition rates obtained with samples written by different individuals, it is concluded that the sector based approach is better suited for the recognition of numerals when pre-classification is made on the basis of strokes