International Journal of Innovative Research in Computer Science and Technology
Year: 2014, Volume: 2, Issue: 2
First page : ( 26) Last page : ( 29)
Online ISSN : 2350-0557.
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Shahid Shaikh, , Suyog Sankpal, Akshay Sonawane, Prasad Chavan
Handwritten character recognition is used frequently to describe the ability of computer to translate human writing into text. The technical challenges in character recognition arise mainly from three sources. First the symbols: the set of idealized shapes that can occur, often in a hierarchy where simple symbols are assembled into more complex ones, at several levels of organization. Second is deformation: the range of shape variations that each symbol is allowed to undergo, including geometric transformation (translation, rotation, scaling, Stretching, etc.) and more complex or time dependent distortion. Third is an image defect: the imperfections in image due to printing, optics, scanning, quantization, binarization [1], etc. Handwriting and machine print demand a different approach. Handwriting consists of elongated strokes, whereas the machine print consists of regularly spaced blobs. Approx. 500 million people around the world use Devnagari script. It provides written form to over forty languages which
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4th Year Undergraduate Student, Department of CSE, TCOER, Pune, India (Email-shahidsk444@gmail.com)
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