Please use this identifier to cite or link to this item:
doi:10.22028/D291-24905
Title: | A step towards understanding paper documents |
Author(s): | Dengel, Andreas |
Language: | English |
Year of Publication: | 1990 |
OPUS Source: | Kaiserslautern ; Saarbrücken : DFKI, 1990 |
SWD key words: | Künstliche Intelligenz |
DDC notations: | 004 Computer science, internet |
Publikation type: | Report |
Abstract: | This report focuses on analysis steps necessary for a paper document processing. It is divided in three major parts: a document image preprocessing, a knowledge-based geometric classification of the image, and a expectation-driven text recognition. It first illustrates the several low level image processing procedures providing the physical document structure of a scanned document image. Furthermore, it describes a knowledge-based approach, developed for the identification of logical objects (e.g., sender or the footnote of a letter) in a document image. The logical identifiers provide a context-restricted consideration of the containing text. While using specific logical dictionaries, a expectation-driven text recognition is possible to identify text parts of specific interest. The system has been implemented for the analysis of single-sided business letters in Common Lisp on a SUN 3/60 Workstation. It is running for a large population of different letters. The report also illustrates and discusses examples of typical results obtained by the system. |
Link to this record: | urn:nbn:de:bsz:291-scidok-36661 hdl:20.500.11880/24961 http://dx.doi.org/10.22028/D291-24905 |
Series name: | Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x] |
Series volume: | 90-08 |
Date of registration: | 27-Jun-2011 |
Faculty: | SE - Sonstige Einrichtungen |
Department: | SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Files for this record:
File | Description | Size | Format | |
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RR_90_08.pdf | 162,19 kB | Adobe PDF | View/Open |
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