RECOGNITION OF HANDWRITTEN NUMERALS WITH MULTIPLE FEATURE AND MULTISTAGE CLASSIFIER

Multiple experts system is shown to be a promising strategy for handwritten recognition. This paper presents a multiple experts system using neural networks. In the proposed system, the authors have developed: (1) an incremental clustering neural network algorithm with merging and canceling process, (2) a modified directional histogram feature extraction method, and (3) a subclass method with learning rejection neuron strategy. Our experimental results on a large set of data show the efficiency and robustness of the proposed system.