A data reduction method for efficient document skew estimation based on Hough transformation

Younki Min, Sung Bae Cho, Yillbyung Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

Abstract

Document recognition usually requires several preprocessing steps in which skew estimation and correction are critical to get a useful system. This paper proposes an efficient data reduction method to enhance the performance of document skew estimation by using a Hough transformation. The time complexity of the Hough transformation is O(/spl Theta/N), where N is the number of black pixels in a document and /spl Theta/ is the skew estimation range divided by /spl Delta//spl theta/. We might enhance the performance by reducing N or /spl Theta/. The proposed method uses an efficient data reduction method called the modified version of divided horizontal histograms, which reduces the number of black pixels N, while retaining the skewness of document. In order to show the superiority of the proposed method, we have also performed experiments with scanned documents, comparing the result with those of the usual data reduction methods: vertical run-length and connected component methods.

Original languageEnglish
Title of host publicationTrack C
Subtitle of host publicationApplications and Robotic Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages732-736
Number of pages5
ISBN (Print)081867282X, 9780818672828
DOIs
Publication statusPublished - 1996
Event13th International Conference on Pattern Recognition, ICPR 1996 - Vienna, Austria
Duration: 1996 Aug 251996 Aug 29

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume3
ISSN (Print)1051-4651

Other

Other13th International Conference on Pattern Recognition, ICPR 1996
Country/TerritoryAustria
CityVienna
Period96/8/2596/8/29

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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