A system for recognizing a large class of engineering drawings

Yuhong Yu, A. Samal, S. C. Seth

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

We present a complete system for recognizing a large class of symbolic engineering drawings that includes flowcharts, chemical plant diagrams, and logic & electrical circuits. The output of the system, a netlist identifying the symbol types and interconnections, may be used for design verification or as a compact portable representation of the drawing. The automatic recognition task is done in two stages: (1) domain-independent rules segment symbols from connection lines in the preprocessed drawing image and (2) an understanding subsystem makes use of a set of domain-specific matchers to classify symbols and correct errors automatically. A graphical user interface is provided to correct residual errors interactively. The system has been tested on a large database of printed images drawn from four different domains.

Original languageEnglish (US)
Title of host publicationProceedings of the 3rd International Conference on Document Analysis and Recognition, ICDAR 1995
PublisherIEEE Computer Society
Pages791-794
Number of pages4
ISBN (Electronic)0818671289
DOIs
StatePublished - Jan 1 1995
Event3rd International Conference on Document Analysis and Recognition, ICDAR 1995 - Montreal, Canada
Duration: Aug 14 1995Aug 16 1995

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Volume2
ISSN (Print)1520-5363

Conference

Conference3rd International Conference on Document Analysis and Recognition, ICDAR 1995
CountryCanada
CityMontreal
Period8/14/958/16/95

Keywords

  • domain dependence
  • drawing understanding
  • flow diagrams
  • segmentation and labeling

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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    Yu, Y., Samal, A., & Seth, S. C. (1995). A system for recognizing a large class of engineering drawings. In Proceedings of the 3rd International Conference on Document Analysis and Recognition, ICDAR 1995 (pp. 791-794). [602020] (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR; Vol. 2). IEEE Computer Society. https://doi.org/10.1109/ICDAR.1995.602020