Knowledge-based baseline detection and optimal thresholding for words segmentation in efficient pre-processing of handwritten arabic text

AlKhateeb, J. H. and Ren, Jinchang and Ipson, S. and Jiang, J.; Latifi, S, ed. (2008) Knowledge-based baseline detection and optimal thresholding for words segmentation in efficient pre-processing of handwritten arabic text. In: Proceedings of the 5th international conference on information technology. IEEE, USA, pp. 1158-1159. ISBN 9780769530994 (https://doi.org/10.1109/ITNG.2008.71)

Abstract

Techniques on detecting baseline and segmenting words in handwritten Arabic text are presented in this paper. Instead of using pure projection, knowledge of the location of the baseline is utilized for accurate baseline detection. Then, distances between words and subwords are respectively analyzed, and their statistical distributions are obtained to decide an optimal threshold in segmenting words. Results on IFN/ENIT database have validated our methods in terms of improved baseline detection and words segmentation for further recognition

ORCID iDs

Ren, Jinchang ORCID: https://orcid.org/0000-0001-6116-3194

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• Item metadata

  Item type:	Book Section
  ID code:	29419
  Dates:	Date Event 2008 Published
  Subjects:	Technology > Electrical engineering. Electronics Nuclear engineering
  Department:	Faculty of Engineering > Electronic and Electrical Engineering
  Depositing user:	Pure Administrator
  Date deposited:	20 May 2011 14:18
  Last modified:	11 Nov 2024 14:42
  URI:	https://strathprints.strath.ac.uk/id/eprint/29419