An Efficient Segmentation Technique for Urdu Optical Character Recognizer (OCR)

  • Saud Ahmed Malik
  • Muazzam MaqsoodEmail author
  • Farhan Aadil
  • Muhammad Fahad Khan
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 70)


In Cursive languages like Urdu, segmentation of handwritten text lines is such a problem because of context sensitivity, diagonality of text etc. In this work, we presented a simple and robust line segmentation algorithm for Urdu handwritten and printed text. In the proposed line segmentation algorithm, modified header and baseline detection method are used. This technique purely depends on the counting pixels approach. Which efficiently segment Urdu handwritten and printed text lines along with skew detection. Handwritten and printed Urdu text dataset is manually generated for evaluating algorithm. Dataset consists of 80 pages having 687 handwritten Urdu text lines and printed dataset consist of 48 pages having 495 printed text lines. The algorithm performed significantly well on printed documents and handwritten Urdu text documents with well-separated lines and moderately well on a document containing overlapping words.


Urdu OCR Text line segmentation Skew detection Header Baseline detection 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Saud Ahmed Malik
    • 1
  • Muazzam Maqsood
    • 1
    Email author
  • Farhan Aadil
    • 1
  • Muhammad Fahad Khan
    • 1
  1. 1.Department of Computer ScienceCOMSATS University IslamabadIslamabadPakistan

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