A New Large Urdu Database for Off-Line Handwriting Recognition

  • Authors:

  • Malik Waqas Sagheer;Chun Lei He;Nicola Nobile;Ching Y. Suen

  • Affiliations:

  • CENPARMI (Centre for Pattern Recognition and Machine Intelligence) Computer Science and Software Engineering Department, Concordia University, Montreal, Canada;CENPARMI (Centre for Pattern Recognition and Machine Intelligence) Computer Science and Software Engineering Department, Concordia University, Montreal, Canada;CENPARMI (Centre for Pattern Recognition and Machine Intelligence) Computer Science and Software Engineering Department, Concordia University, Montreal, Canada;CENPARMI (Centre for Pattern Recognition and Machine Intelligence) Computer Science and Software Engineering Department, Concordia University, Montreal, Canada

  • Venue:
  • ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
  • Year:
  • 2009

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Abstract

A new large Urdu handwriting database, which includes isolated digits, numeral strings with/without decimal points, five special symbols, 44 isolated characters, 57 Urdu words (mostly financial related), and Urdu dates in different patterns, was designed at Centre for Pattern Recognition and Machine Intelligence (CENPARMI). It is the first database for Urdu off-line handwriting recognition. It involves a large number of Urdu native speakers from different regions of the world. Moreover, the database has different formats --- true color, gray level and binary. Experiments on Urdu digits recognition has been conducted with an accuracy of 98.61%. Methodologies in image pre-processing, gradient feature extraction and classification using SVM have been described, and a detailed error analysis is presented on the recognition results.