Optical Character Recognition for Handwritten Cursive English characters

Optical Character Recognition (OCR) is the technique which enables a machine to automatically recognize the characters or scripts written in the users’ language. Optical Character Recognition (OCR) has become one of the most successful applications of technology in the field of pattern recognition and artificial intelligence. In this project a scanned image is translated into machine editable text by means of using Optical Character Recognition. Here a hand written English cursive word is scanned and this image is fed into the computer in which it is recognized using Hidden Markov Model, and converted into the same word in equivalent printed characters . A new combination algorithm is developed and has been used for this recognition and generation work, which is implemented in MATLAB 2010 a. Among the heavy competition in this application area, this project is being developed to achieve better accuracy and overcome all the draw backs found in the other available OCR algorithms. KEYWORDS-Optical Character Recognition (OCR), Cursive Handwriting, Hidden Markov Model (HMM)