A novel technique for estimation of skew in binary text document images based on linear regression analysis

Shivakumara, P. and Hemantha Kumar, G. and Guru, D. S. and Nagabhushan, P. (2005) A novel technique for estimation of skew in binary text document images based on linear regression analysis. Sadhana, 30 (1). pp. 69-85. ISSN 0973-7677

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Official URL: https://doi.org/10.1007/BF02710080

Abstract

When a document is scanned either mechanically or manually for digitization, it often suffers from some degree of skew or tilt. Skew-angle detection plays an important role in the field of document analysis systems and OCR in achieving the expected accuracy. In this paper, we consider skew estimation of Roman script. The method uses the boundary growing approach to extract the lowermost and uppermost coordinates of pixels of characters of text lines present in the document, which can be subjected to linear regression analysis (LRA) to determine the skew angle of a skewed document. Further, the proposed technique works fine for scaled text binary documents also. The technique works based on the assumption that the space between the text lines is greater than the space between the words and characters. Finally, in order to evaluate the performance of the proposed methodology we compare the experimental results with those of well-known existing methods.

Item Type: Article
Subjects: D Physical Science > Computer Science
Divisions: Department of > Computer Science
Depositing User: manjula User
Date Deposited: 07 Sep 2019 10:16
Last Modified: 07 Sep 2019 10:16
URI: http://eprints.uni-mysore.ac.in/id/eprint/7771

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