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Self-Structural Syntax-Directed Pattern Recognition of Dimensioning Components in Engineering Drawings

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Structured Document Image Analysis

Abstract

A mechanical engineering drawing is a set of orthogonal 2D views of a 3D object. To establish vision-based communication among CAD/CAM systems and to implement 3D reconstruction, drawings need to be preprocessed to exploit the information conveyed by the annotation before separating it from the geometry. A rationale for a machine drawing understanding system is first argued. A context-free dimensioning grammar provides a basis for a self-structural, syntax-directed pattern recognition scheme. It employs learning the characteristic parameters of arrowheads and text from a detected sample, and using them to detect the entire population. Syntactic considerations that significantly decrease the search space help predict the spatial location and orientation of potential components. The underlying ideas of the scheme may be applicable to a broad scope of tasks involving intelligent recognition.

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Author notes

  1. Dov Dori

    Present address: Faculty of Industrial Engineering and Management, Technion, Israel Institute of Technology, Technion City, Haifa, 32000, Israel

Authors and Affiliations

  1. Department of Computer Science, The University of Kansas, Lawrence, Kansas, 66045, USA

    Dov Dori

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  1. Dov Dori
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Editor information

Editors and Affiliations

  1. Computing Science Research Center, AT&T Bell Laboratories, 600 Mountain Avenue, Room 2C-322, P. O. Box 636, 07974-0636, Murray Hill, NJ, USA

    Henry S. Baird

  2. Institut für Informatik und angewandte Mathematik, Universität Bern, Länggass-Str. 51, CH-3012, Bern, Switzerland

    Horst Bunke

  3. Machine Understanding Division, Electrotechnical Laboratory, 1-1-4, Umezono, 305, Tsukuba Science City Ibaraki, Japan

    Kazuhiko Yamamoto

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© 1992 Springer-Verlag Berlin Heidelberg

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Dori, D. (1992). Self-Structural Syntax-Directed Pattern Recognition of Dimensioning Components in Engineering Drawings. In: Baird, H.S., Bunke, H., Yamamoto, K. (eds) Structured Document Image Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77281-8_17

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  • DOI: https://doi.org/10.1007/978-3-642-77281-8_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-77283-2

  • Online ISBN: 978-3-642-77281-8

  • eBook Packages: Springer Book Archive

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