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Line Identification by Hough Transform with Image Subdivision

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Part of the book series: Informatik-Fachberichte ((INFORMATIK,volume 290))

Zusammenfassung

To cope with memory and time requirements of the Hough transform when identifying lines here, a line parametrisation is investigated which allows a relatively small and compact accumulator, a fast algorithm to fill the accumulator and its implementation in parallel hardware is developed and finally,an algorithm to combine the lines identified in subimages is described: by this image subdivision Hough transform and cluster detection can be applied to proportionally smaller accumulators in parallel.

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References

  1. P.V.C. Hough: Methods and Means for Recognizing Complex Patterns. U.S. Patent 3069654, 1962.

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  4. R88] Thomas Risse: Yet Another Line Parametrization for Hough Transform. In H. Bunke et al., editors, Proceedings of the 10th DAGM Symposium on pattern recognition, Zurich, September 1988, Informatik Fachberichte 180,pages 142–150, DAGM, GI and SI, Springer-Verlag, 1988.

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  5. Thomas Risse: Hough Transform for Line Recognition: Complexity of Evidence Accumulation and Cluster Detection. Computer Vision, Graphics and Image Processing, 46(): 327–345, 1989.

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  6. Thomas Risse: A Line Parametrization for Hough Transform with Quadtree Image Subdivision. Technical Report, Wilhelm Schickard Institute, University of Tübingen, 1989.

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  7. Richard S. Wallace: A modified Hough Transform for Lines. In Proceedings of the Computer Vision and Pattern Recognition Conference 1985, pages 665–667, IEEE Computer Society Press/North Holland, June 1985.

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© 1991 Springer-Verlag Berlin Heidelberg

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Risse, T. (1991). Line Identification by Hough Transform with Image Subdivision. In: Radig, B. (eds) Mustererkennung 1991. Informatik-Fachberichte, vol 290. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-08896-8_23

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  • DOI: https://doi.org/10.1007/978-3-662-08896-8_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54597-2

  • Online ISBN: 978-3-662-08896-8

  • eBook Packages: Springer Book Archive

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