Prof Apostolos Antonacopoulos A.Antonacopoulos@salford.ac.uk
Professor
There is an ever increasing number of publications which do not have the “traditional” layout where printed regions are rectangu- lar. Text paragraphs and areas of graphic type may be of any shape, individually rotated and in any arrangement. Previous document analysis techniques are not well suited to such complex layouts. This paper introduces a new method for the segmentation of images of document pages having both traditional and complex layouts. The underlining idea is to efficiently produce a flexible description (by means of tiles) of the background space which surrounds the printed regions in the page image under all the above conditions. Using this description of space, the contours of printed regions are identified with significant accuracy. The new approach is fast as there is no need for skew detection and correction, and only few simple oper- ations are performed on the description of the background (not on the pixel-based data).
Antonacopoulos, A. (1998). Page segmentation using the description of the background. Computer Vision and Image Understanding, 70(3), 350-369. https://doi.org/10.1006/cviu.1998.0691
Journal Article Type | Article |
---|---|
Publication Date | Jan 1, 1998 |
Deposit Date | Oct 4, 2011 |
Journal | Computer Vision and Image Understanding |
Print ISSN | 1077-3142 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 70 |
Issue | 3 |
Pages | 350-369 |
DOI | https://doi.org/10.1006/cviu.1998.0691 |
Publisher URL | http://dx.doi.org/ 10.1006/cviu.1998.0691 |
A new deep CNN for 3D text localization in the wild through shadow removal
(2023)
Journal Article
NAME – A Rich XML Format for Named Entity and Relation Tagging
(2023)
Presentation / Conference Contribution
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
Apache License Version 2.0 (http://www.apache.org/licenses/)
Apache License Version 2.0 (http://www.apache.org/licenses/)
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search