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Pashto isolated character recognition using K-NN classifier.

Author(s)
N. AHMAD University of Engineering & Technology Peshawar, Pakistan
A. A. KHAN University of Engineering & Technology Peshawar, Pakistan
S. A. R. ABID University of Engineering & Technology Peshawar, Pakistan
M. YASIR University of Engineering & Technology Peshawar, Pakistan
Nasimullah NULL University of Engineering & Technology Peshawar, Pakistan
Abstract
This paper presents the development of Optical Character Recognition (OCR) system for printed Pashto text. The problem of the unavailability of the standard database for Pashto language has also been addressed by developing a medium size database with 25 different variations with a total number of 1125 entries in the final database. In the proposed approach, individual Pashto characters are recognized utilizing both high and low level features. High level features are based on the structural information from the characters and the resulting binary trees uniquely classify each of the characters. The approach though quite robust is affected slightly by the variation in size, orientation and writing style. An alternative low level feature approach based on K-Nearest Neighbors has been used giving an overall word recognition of 74.8%.
Publication Details
Page(s) 679-682
DOI DOI not available
Published Journal: Sindh University Research Journal, Volume: 45, Issue: 4, Year: 2013

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