Innovative Technique for Character Recognition

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Sumant Raj Chauhan
Punit Soni


Development of OCRs for Indian script is an active area of activity today. Optical character recognition (OCR) is the mechanical or
electronic translation of images of handwritten, typewritten or printed text (usually captured by a scanner) into machine-editable text. In simple
words OCR is a visual recognition process that turns printed or written text into an electronic character based file. OCR is a field of research in
pattern recognition, artificial intelligence and machine vision. Indian scripts present great challenges to an OCR designer due to the large number
of letters in the alphabet, the sophisticated ways in which they combine, and the complicated graphemes they result in. The problem is
compounded by the unstructured manner in which popular fonts are designed. There is a lot of common structure in the different Indian scripts.
All existing OCR systems developed for various Indian scripts do not provide sufficient efficiency due to various factors. The objective of this
paper is to discuss a more efficient character recognition technique. This paper introduces a new technical approach to recognize Indian script
characters which are unpredictable due to different problems in other OCR’s.


Keywords: OCR, Segmented Character, Broken Character, Skew, Skewed Character, Character Recognition, Artificial Neural Network.


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