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Proceedings Paper

Adaptive removal of background and white space from document images using seam categorization
Author(s): Claude Fillion; Zhigang Fan; Vishal Monga
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Paper Abstract

Document images are obtained regularly by rasterization of document content and as scans of printed documents. Resizing via background and white space removal is often desired for better consumption of these images, whether on displays or in print. While white space and background are easy to identify in images, existing methods such as naïve removal and content aware resizing (seam carving) each have limitations that can lead to undesirable artifacts, such as uneven spacing between lines of text or poor arrangement of content. An adaptive method based on image content is hence needed. In this paper we propose an adaptive method to intelligently remove white space and background content from document images. Document images are different from pictorial images in structure. They typically contain objects (text letters, pictures and graphics) separated by uniform background, which include both white paper space and other uniform color background. Pixels in uniform background regions are excellent candidates for deletion if resizing is required, as they introduce less change in document content and style, compared with deletion of object pixels. We propose a background deletion method that exploits both local and global context. The method aims to retain the document structural information and image quality.

Paper Details

Date Published: 7 February 2011
PDF: 9 pages
Proc. SPIE 7879, Imaging and Printing in a Web 2.0 World II, 78790A (7 February 2011); doi: 10.1117/12.877266
Show Author Affiliations
Claude Fillion, Xerox Corp. (United States)
Zhigang Fan, Xerox Corp. (United States)
Vishal Monga, The Pennsylvania State Univ. (United States)

Published in SPIE Proceedings Vol. 7879:
Imaging and Printing in a Web 2.0 World II
Qian Lin; Jan P. Allebach; Zhigang Fan, Editor(s)

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