Model Based Segmentation And Hypothesis Generation For The Recognition Of Printed Documents

A Dengel; A Luhn; B Ueberreiter

doi:10.1117/12.943391

11 April 1988 Model Based Segmentation And Hypothesis Generation For The Recognition Of Printed Documents

A Dengel, A Luhn, B Ueberreiter

Proceedings Volume 0860, Real-Time Image Processing: Concepts and Technologies; (1988) https://doi.org/10.1117/12.943391
Event: 1987 Symposium on the Technologies for Optoelectronics, 1987, Cannes, France

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.

Citation Download Citation

A Dengel, A Luhn, and B Ueberreiter "Model Based Segmentation And Hypothesis Generation For The Recognition Of Printed Documents", Proc. SPIE 0860, Real-Time Image Processing: Concepts and Technologies, (11 April 1988); https://doi.org/10.1117/12.943391

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