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Simple and Effective Techniques for Skew Correction, Slant Correction and Core-Region Detection for Cursive Word Recognition

  • Kota Virajitha
  • B. Navya
  • L. N. Phaneendra Kumar Boggavarapu
  • Radhe Syam Vaddi
  • Hima Deepthi Vankayalapati
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 132)

Abstract

For the past decades, the advancement in the field of Image Processing has been paving a profound way in digital treatment of Human written data. Handwriting Recognition, a subset, is now a major research area to study as it is providing a mean for automatic processing of large volumes of data in reading and office automation. Intelligent word recognition systems which are used in processing important documents like bank cheques, old scripts are the need of the hour. Through this paper we present a new approach for Cursive word and Signature recognition. We propose Core-region detection technique which enables us to identify the crucial features of the hand written signatures by the extracting ’Ascenders and Descenders’. Skew and Slant corrections, if needed, are performed as preprocessing steps. A significant reduction in computation complexity has been observed than the previous attempts of researchers in detection of core-region.

Keywords

Word Recognition Foreground Pixel Word Image Slant Angle Tilt Correction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Kota Virajitha
    • 1
  • B. Navya
    • 1
  • L. N. Phaneendra Kumar Boggavarapu
    • 1
  • Radhe Syam Vaddi
    • 1
  • Hima Deepthi Vankayalapati
    • 2
  1. 1.Department of Information TechnologyV R Siddhartha Engineering CollegeVijayawadaIndia
  2. 2.Department of Computer Science & EngineeringV R Siddhartha Engineering CollegeVijayawadaIndia

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