A Deep Learning Approach for Optical Character Recognition of Handwritten Devanagari Script

Handwritten Character Recognition is one of the most challenging and demanding area of interest for researchers in domains of pattern recognition and image processing. Many researchers have worked with recognition of characters of different languages but there is comparatively less work carried for Devanagari Script. In past few years, however the work carried out in this direction is increasing to a great extent. Handwritten Devanagari Character Recognition is more challenging in comparison to the recognition of the Roman characters. The complexity is mostly due to the presence of a header line known as shirorekha that connects the Devanagari characters to form a word. The presence of this header line makes the segmentation process of characters more difficult. There is uniqueness to the handwriting styles of every individual which adds to the complexity. In this paper, we propose development of Convolutional Neural Network (CNN) based Optical Character Recognition system (OCR) for Handwritten Devanagari Script which is observed to recognize the characters accurately.