Skip to main content

An Improvement of the Standard Hough Transform Method Based on Geometric Shapes

  • Conference paper
  • First Online:
Advances in Information and Communication Networks (FICC 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 887))

Included in the following conference series:

Abstract

Hough Transform is a well known method in image processing, for straight line recognition, very popular for detecting complex forms, such as circles, ellipses, arbitrary shapes in digital images. In this paper, we are interested in the Hough transform method that associates a point to a sine curve, named the standard hough transform, applied to a big set of continue points such as triangles, rectangles, octogons, hexagons in order to overcome time problem, due to the small size of a pixel and to establish optimization techniques for the Hough Transform method in time complexity, in the main purpose to obtain thick analytical straight line recognition, in following some parameters. The proposed methods, named Triangular Hough Transform and Rectangular Hough Transform considers an image as a grid, respectively represented in a triangular tiling or a rectangular tiling and contribute to have accumulator data to reduce computation time, accepting limited noises in straight line detection. The analysis also deals with the case of geometric shapes, such as octogons and hexagons where the tiling procedure of image space is necessary to obtain new Hough Transform methods based on these forms.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Dexet, M.: Architecture d’un modeleur géométrique base topologique d’objets discrets et méthodes de reconstruction en dimensions 2 et 3. Université de Poitiers, France, Thèse en informatique (2006)

    Google Scholar 

  2. Ballard, D.: Generalizing the Hough Transform to detect arbitrary shapes. Pattern Recogn. 13, 111–112 (1981)

    Article  Google Scholar 

  3. Guo, L., Chutatape, O.: Influence of discretization in image space on Hough Transform. Pattern Recognit. 32(4), 635–644 (1999)

    Article  Google Scholar 

  4. Maître, H.: Un panorama de la transformée de hough - a review on hough transform. traitement du signal 2(4), 305–317 (1985)

    MathSciNet  Google Scholar 

  5. Reveillés, J.-P.: Combinatorial pieces in digital lines and planes. In: Proceeding SPIE 2573, Vision Geometry, vol. 4, no. 23 (1995)

    Google Scholar 

  6. Fanelli, G., Gall, J., Van Goo, L.: Hough Transform-based mouth localization for audio-visual speech recognition. In: British Machine Vision Conference, September 2009

    Google Scholar 

  7. Yao, A., Gall, J., Van Gool, L.: A Hough Transform-based voting framework for action recognition. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010) (2010)

    Google Scholar 

  8. Sere, A.: Transformations analytiques appliquées aux images multi- échelles et bruitées, thèse en informatique, Université de Ouagadougou (2013)

    Google Scholar 

  9. Sere, A., Sie, O., Traore, S.: Extensions of standard Hough Transform based on object dual and applications. Int. J. Emer. Trends Comput. Inf. Sci. 6(1), 20–24 (2015)

    Google Scholar 

  10. Mukhopadhyay, P., Chaudhuri, B.B.: A survey of Hough Transform. Pattern Recogn. (2014). https://doi.org/10.1016/j.patcog.2014.08.027

  11. Lo, R.-C., Tsai, W.-H.: Gray-scale hough transform for thick line detection in gray-scale images. Pattern Recogn. 28(5), 647–661 (1995)

    Article  Google Scholar 

  12. Koc San, D., Turker, M.: Building extraction from high resolution satellite images using Hough Transform. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, Kyoto, Japan, vol. 38, Part 8 (2010)

    Google Scholar 

  13. Saha, S., Basu, S., Nasipuri, M., Basu, D.Kr.: A Hough Transform based technique for text segmentation. J. Comput. 2(2) (2010). ISSN 2151-9617

    Google Scholar 

  14. Han, J.H., Kóczy, L., Poston, T.: Fuzzy Hough Transform. Pattern Recogn. Lett. 15(7), 649–658 (1994)

    Article  Google Scholar 

  15. Nagy, B.: Number of words characterizing digital balls on the triangular tiling. In: The Proceedings of DGCI 2016 (2016)

    Google Scholar 

  16. Dexet, M., Andres, E.: A generalized preimage for the digital analytical hyperplane recognition. J. Discrete Appl. Math. 153(4), 476–489 (2009)

    Article  MathSciNet  Google Scholar 

  17. Sere, A., Sie, O., Andres, E.: Extended standard Hough Transform for Analytical Line Recognition. Int. J. Adv. Comput. Sci. Appl. (IJACSA) 4(3), 256–266 (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Abdoulaye Sere .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sere, A., Ouedraogo, F.T., Zerbo, B. (2019). An Improvement of the Standard Hough Transform Method Based on Geometric Shapes. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Advances in Information and Communication Networks. FICC 2018. Advances in Intelligent Systems and Computing, vol 887. Springer, Cham. https://doi.org/10.1007/978-3-030-03405-4_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-03405-4_25

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03404-7

  • Online ISBN: 978-3-030-03405-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics