Optical Character Recognition System for Urdu (Naskh Font) Using Pattern Matching Technique

The offline optical character recognition (OCR) for different languages has been developed over the recent years. Since 1965, the US postal service has been using this system for automating their services. The range of the applications under this area is increasing day by day, due to its utility in almost major areas of government as well as private sector. This technique has been very useful in making paper free environment in many major organizations as far as the backup of their previous file record is concerned. Our this system has been proposed for the Offline Character Recognition for Isolated Characters of Urdu language, as Urdu language forms words by combining Isolated Characters. Urdu is a cursive language, having connected characters making words. The major area of utility for Urdu OCR will be digitizing of a lot of literature related material already stocked in libraries. Urdu language is famous and spoken in more than 3 big countries including Pakistan, India and Bangladesh. A lot of work has been done in Urdu poetry and literature up to the recent century. Creation of OCR for Urdu language will make an important role in converting all those work from physical libraries to electronic libraries. Most of the stuff already placed on internet is in the form of images having text, which took a lot of space to transfer and even read online. So the need of an Urdu OCR is a must. The system is of training system type. It consists of the image preprocessing, line and character segmentation, creation of xml file for training purpose. While Recognition system includes taking xml file, the image to be recognized, segment it and creation of chain codes for character images and matching with already stored in xml file. Tabassam Nawaz, Syed Ammar Hassan Shah Naqvi, Habib ur Rehman & Anoshia Faiz International Journal of Image Processing, (IJIP)Volume (3) : Issue (3) 93 The system has been implemented and it has 89% recognition accuracy with a 15 char/sec recognition rate.

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