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Proceedings Paper

Model Based Segmentation And Hypothesis Generation For The Recognition Of Printed Documents
Author(s): A Dengel; A Luhn; B Ueberreiter
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Paper Abstract

The task of document recognition requires the scanning of a paper document and the analysis of its content and structure. The resulting electronic representation has to capture the content as well as the logic and layout structure of the document. The first step in the recognition process is scanning, filtering and binarization of the paper document. Based on the preprocessing results we delineate key areas like address or signature for a letter, or the abstract for a report. This segmentation procedure uses a specific document layout model. The validity of this segmentation can be verified in a second step by using the results of more time-consuming procedures like text/graphic classification, optical character recognition (OCR) and the comparison with more elaborate models for specific document parts. Thus our concept of model driven segmentation allows quick focussing of the analysis on important regions. The segmentation is able to operate directly on the raster image of a document without necessarily requiring CPU-intensive preprocessing steps for the whole document. A test version for the analysis of simple business letters has been implemented.

Paper Details

Date Published: 11 April 1988
PDF: 7 pages
Proc. SPIE 0860, Real-Time Image Processing: Concepts and Technologies, (11 April 1988); doi: 10.1117/12.943391
Show Author Affiliations
A Dengel, Universitat Stuttgart (Germany)
A Luhn, Siemens Corporate Research and Technology (Germany)
B Ueberreiter, Siemens Corporate Research and Technology (Germany)

Published in SPIE Proceedings Vol. 0860:
Real-Time Image Processing: Concepts and Technologies
Jean Besson, Editor(s)

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