Publication Type : Journal Article
Publisher : Journal of Theoretical and Applied Information Technology
Source : Journal of Theoretical and Applied Information Technology, Volume 52, Number 2, p.142-153 (2013)
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science, Mathematics
Year : 2013
Abstract : Optical Character Recognition (OCR) system aims to convert optically scanned text image to a machine editable text form. Multiple approaches to preprocessing and segmentation exist for various scripts. However, only a restricted combination of the same has been experimented on Devanagari script. This paper proposes a study which aims to explore and bring out an alternative and efficient strategy of preprocessing and segmentation in handling OCR for Devanagari scripts. Efficiency evaluation of the proposed alternative has been undertaken by subjecting it to documents with varying degree of noise severity and border artifacts. The experimental results confirm our proposition to be superior approach over other conventional methodologies to OCR system implementation for Devanagari scripts. Also described is detailed approach to conventional pre-processing involved in initial stage of OCR, including noise removal techniques, along with the other conventional approaches to segmentation. The proposed alternative has been deployed to reach character and top character segmentation level. © 2005 - 2013 JATIT amp; LLS. All rights reserved.
Cite this Research Publication : Dr. Deepa Gupta and Nair, LbMadhu, “Improving OCR by effective pre-processing and segmentation for Devanagiri script:A quantified study”, Journal of Theoretical and Applied Information Technology, vol. 52, pp. 142-153, 2013.