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Vectorization of raster mechanical drawings on the base of ternary segmentation and soft computing

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Abstract

The problem of automatic conversion of engineering drawings from paper carriers to an electronic vector form is very topical and is not solved yet at an acceptable level. The drawback inherent in many existing approaches lies in the fact that they are based on binary image segmentation. Under the conditions of low image quality, absolutely correct binarization is unattainable. Segmentation should be more flexible. It should divide pixels of the image not only into those belonging to the background and the objects but also take into account the existence of intermediate uncertain states. The purpose of this work is to increase quality of automatic vectorization of drawings having ambiguous situations: badly traced lines, areas of convergence and intersection of lines. The proposed approach includes stages of ternary segmentation of an image and fuzzy synthesis of a skeleton. Presented results of experiments show that, for grayscale and color drawing images of medium and low quality, the proposed approach provides better results than known methods.

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References

  1. Hilaire, X. and Tombre, K., Robust and accurate vectorization of line drawings, IEEE Trans. Pattern Analysis Machine Intelligence, 2006, vol. 28, no. 6, pp. 890–904.

    Article  Google Scholar 

  2. Dosch, P., Tombre, P., Ah-Soon, C., and Masini, G., A complete system for analysis of architectural drawings, Int. J. Document Analysis Recognition, 2000, vol. 3, no. 2, pp. 102–116.

    Article  Google Scholar 

  3. Wenyin, L., The third report of the arc segmentation contest, Lect. Notes Comput. Sci., 2005, vol. 3926, pp. 358–361.

    Article  Google Scholar 

  4. Al-Khaffaf, H.S.M., Talib, A.Z., Osman, M.A., and Wong, P.L., GREC'09 arc segmentation contest: Performance evaluation on old documents, Lect. Notes Comput. Sci., 2010, vol. 6020, pp. 251–259.

    Article  Google Scholar 

  5. Bera, S., Bhowmick, P., and Bhattacharya, B.B., Detection of circular arcs in a digital image using chord and sagitta properties, Lect. Notes Comput. Sci., 2010, vol. 6020, pp. 69–80.

    Article  Google Scholar 

  6. De, P., Mandal, S., Bhowmick, P., and Das, A., ASKME: Adaptive sampling with knowledge driven vectorization of mechanical engineering drawing, Int. J. Document Analysis Recognition, 2016, vol. 19, pp. 11–29.

    Article  Google Scholar 

  7. Bonnici, A. and Camilleri, K., A circle-based vectorization algorithm for drawings with shadows, Proc. of the Int. Symp. on Sketch-Based Interfaces and Modeling, Anaheim, California, 2013, pp. 69–77.

    Chapter  Google Scholar 

  8. Bartolo, A., Camilleri, K.P., Fabri, S.G., Borg, J.C., and Farrugia, P.J., Scribbles to vectors: Preparation of scribble drawings for CAD interpretation, Proc. of the 4th Eurographics Worshop on Sketch-Based Interfaces and Modeling, 2007, pp. 123–130.

    Chapter  Google Scholar 

  9. Wenyin, L. and Dori, D., A protocol for performance evaluation of line detection algorithms, Machine Vision Applications, 1997, vol. 9, nos. 5—6, pp. 240–250.

    Article  Google Scholar 

  10. Arc Segmentation Contest at the GREC2005 Workshop. http://www.cs.cityu.edu.hk/ liuwy/ArcContest//ArcSegContest.html

  11. VPstudio. http://www.softelec.com/enu/products/raster-to-vector/vpstudio.htm

  12. Scan2CAD. http://www.scan2cad.com/

  13. GTXRaster. http://www.gtx.com/products/detail.asp?idx

  14. Vextractor. http://www.vextrasoft.com/vextractor.htm

  15. Kasimov, D.R., Kuchuganov, A.V., and Kuchuganov, V.N., Individual strategies in the tasks of graphical retrieval of technical drawings, J. Visual Languages Computing, 2015, vol. 28, pp. 134–146.

    Article  MATH  Google Scholar 

Download references

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Authors and Affiliations

  1. Kalashnikov State Technical University, Izhevsk, ul. Studencheskaya 7, Izhevsk, Russia

    D. R. Kasimov, A. V. Kuchuganov, V. N. Kuchuganov & P. P. Oskolkov

Authors
  1. D. R. Kasimov
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  2. A. V. Kuchuganov
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  3. V. N. Kuchuganov
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  4. P. P. Oskolkov
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Corresponding author

Correspondence to D. R. Kasimov.

Additional information

Original Russian Text © D.R. Kasimov, A.V. Kuchuganov, V.N. Kuchuganov, P.P. Oskolkov, 2017, published in Programmirovanie, 2017, Vol. 43, No. 6.

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Kasimov, D.R., Kuchuganov, A.V., Kuchuganov, V.N. et al. Vectorization of raster mechanical drawings on the base of ternary segmentation and soft computing. Program Comput Soft 43, 337–344 (2017). https://doi.org/10.1134/S0361768817060056

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  • DOI: https://doi.org/10.1134/S0361768817060056