Title :
Segmentation of Printed Urdu Scripts Using Structural Features
Author :
Malik, Hamna ; Fahiem, Muhammad Abuzar
Author_Institution :
Lahore Coll. for Women Univ., Lahore, Pakistan
Abstract :
Character segmentation forms the basis for optical character recognition. In this paper, we have proposed a character segmentation approach for printed Urdu script. Urdu is cursive by nature and its script is written from right to left. Both these factors make the segmentation more difficult and require special attention. Our approach is based on structural features and we have overcome different problems like over segmentation and under segmentation, present in previous approaches. We have achieved an accuracy rate of 99.4% which is better than others. The approach may be very useful for developing an optical character recognition system for Urdu language.
Keywords :
image segmentation; natural language processing; optical character recognition; Urdu language; character segmentation; optical character recognition; printed Urdu script; structural features; Character recognition; Educational institutions; FCC; Hidden Markov models; Image segmentation; Neural networks; Optical character recognition software; Pixel; Shape; Visualization; Character segmentation; Cursive scripts; Ligature; Structural features; Urdu alphabets;
Conference_Titel :
Visualisation, 2009. VIZ '09. Second International Conference in
Conference_Location :
Barcelona
Print_ISBN :
978-0-7695-3734-4
DOI :
10.1109/VIZ.2009.12