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An Effective Vector Extraction Method on Architectural Imaging Using Drawing Characteristics

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Graphics Recognition Algorithms and Applications (GREC 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2390))

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Abstract

In this paper, vectorization is achieved by the recognition of architectural drawing images. To obtain vector components, an architectural drawing recognizer (ADR) is developed. The ADR recognizes line components such as main wall, dimension line and points that indicate the dimension of scanned architectural drawing images. A merging process from separately recognized line components is accomplished in order to increase the accuracy of result vectors. The recognition ratio and the vectorization of ADR is 98.3% over 9 real scanned apartment building images.

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References

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  4. Dov Dori, “Orthogonal Zig-Zag: an algorithm for vectorizing engineering drawings compared with Hough Transform”, Advances in Engineering Software, Vol. 28, pp. 11–24, 1997.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Chung-Ang University, 221 Heuksukdong, Dongjakku, Seoul, 156-756, Korea

    Young-Jun Park & Young-Bin Kwon

Authors
  1. Young-Jun Park
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  2. Young-Bin Kwon
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Editor information

Editors and Affiliations

  1. Computing and Information Science, Queen’s University, Kingston, Ontario, Canada, K7L 3N6

    Dorothea Blostein

  2. Department of Computer Engineering, Chung-Ang University, Seoul, 156-756, South Korea

    Young-Bin Kwon

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© 2002 Springer-Verlag Berlin Heidelberg

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Park, YJ., Kwon, YB. (2002). An Effective Vector Extraction Method on Architectural Imaging Using Drawing Characteristics. In: Blostein, D., Kwon, YB. (eds) Graphics Recognition Algorithms and Applications. GREC 2001. Lecture Notes in Computer Science, vol 2390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45868-9_26

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  • DOI: https://doi.org/10.1007/3-540-45868-9_26

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44066-6

  • Online ISBN: 978-3-540-45868-5

  • eBook Packages: Springer Book Archive

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