Shape decomposition-based handwritten compound character recognition for Bangla OCR

Proper recognition of complex-shaped handwritten compound characters is still a big challenge for Bangla OCR systems. In this paper, we propose a novel shape decomposition-based segmentation technique to decompose the compound characters into prominent shape components. This shape decomposition reduces the classification complexity in terms of less number of classes to recognize, and at the same time improves the recognition accuracy. The decomposition is done at the segmentation area where the two basic shapes are joined to form a compound character. We use chain code histogram feature set with multi-layer perceptron (MLP) based classifier with backpropagation learning for classification. On experimentation, the proposed method is observed to provide good recognition accuracy comparing with other existing methods.