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Proceedings Paper

Document image orientation based on both text and image
Author(s): Yuejia Sun; Changsong Liu; Xiaoqing Ding; Zhigang Fan; Francis Tse
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Paper Abstract

This paper investigated the problem of orientation detection for document images with Chinese characters. These images may be in four orientations: right side up, up-side down, 90° and 270° rotated counterclockwise. First, we presented the structure of text-recognition-based orientation detection algorithm. Text line verification and orientation judgment methods were mainly discussed, afterwards multiple experiments were carried. Distance-difference based text line verification and confidence based text line verification were proposed and compared with methods without text line verification. Then, a picture-based orientation detection framework was adopted for the situation where no text line was detected. This high-level classification problem was solved by relatively low-level vision features including Color Moments (CM) and Edge Direction Histogram (EDH), with distant-based classification scheme. Finally, confidencebased classifier combination strategy was employed in order to make full use of the complementarity between different features and classifiers. Experiments showed that both text line verification methods were able to improve the accuracy of orientation detection, and picture-based orientation detection had a good performance for no-text image set.

Paper Details

Date Published: 21 February 2012
PDF: 13 pages
Proc. SPIE 8302, Imaging and Printing in a Web 2.0 World III, 83020U (21 February 2012); doi: 10.1117/12.912984
Show Author Affiliations
Yuejia Sun, Tsinghua Univ. (China)
Changsong Liu, Tsinghua Univ. (China)
Xiaoqing Ding, Tsinghua Univ. (China)
Zhigang Fan, Xerox Corp. (United States)
Francis Tse, Xerox Corp. (United States)

Published in SPIE Proceedings Vol. 8302:
Imaging and Printing in a Web 2.0 World III
Qian Lin; Jan P. Allebach; Zhigang Fan, Editor(s)

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