Earticle

초록

영어

Optical character recognition (OCR) refers to a process of generating a character input by optical means, like scanning, for recognition in subsequent stages by which a printed or handwritten text can be converted to a form which a computer can understand and manipulate. A generic character recognition system has different stages like noise removal, skew detection and correction, segmentation, feature extraction and classification. Results of the later stages can affect the performance of the subsequent stages in the OCR process. To make the results of the subsequent stages more accurate, the skew detection and correction and segmentation play an important role. In this paper, we have proposed schemes for skew detection and correction, segmentation of handwritten Kannada document using bounding box technique, Hough transform and contour detection respectively. An average segmentation rate of 91% and 70% for lines and words is obtained respectively.

목차

Abstract
 1. Introduction
 2. The Characteristics of Kannada Script
 3. Skew Angle Detection and Correction
  3.1 Related Work
  3.2 Proposed Methodology
 4. Segmentation
  4.1 Related Work
  4.2 Proposed Methodology
 5. Experimental Results
 6. Comparative Study
 7. Conclusion
 Acknowledgements
 References

키워드

저자

• Mamatha Hosalli Ramappa [ Department of Information Science and Engineering P E S Institute of Technology, Bangalore, India ]
• Srikantamurthy Krishnamurthy [ Department of Computer Science and Engineering P E S Institute of Technology (South Campus), Bangalore, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Advanced Science and Technology

• 간기

  월간

• pISSN

  2005-4238

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605