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9 - Parametric Transforms

from Part III - Image Understanding

Published online by Cambridge University Press:  25 October 2017

Wesley E. Snyder  and
Hairong Qi
Wesley E. Snyder
Affiliation:
North Carolina State University
Hairong Qi
Affiliation:
University of Tennessee
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Fundamentals of Computer Vision , pp. 200 - 217
Publisher: Cambridge University Press
Print publication year: 2017

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References

[9.1] D., Ballard. Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition, 13 (2), 1981.Google Scholar
[9.2] Y., Cheng. Mean shift, mode seeking, and clustering. IEEE Trans. Pattern Anal. and Machine Intel., 17 (8), 1995.Google Scholar
[9.3] T., Hofmann and J., Buhmann. Pairwise data clustering by deterministic annealing. IEEE Trans. Pattern Anal. and Machine Intel., 19 (1), 1997.Google Scholar
[9.4] P. V. C., Hough. Method and means for recognizing complex patterns. U.S. Patent, 3069654, 1962.Google Scholar
[9.5] P., Liang and C., Taubes. Orientation-based differential geometric representations for computer vision applications. IEEE Trans. Pattern Anal. and Machine Intel., 16 (3), 1994.Google Scholar
[9.6] E., Lutton, H., Maitre, and J., Lopez-Krahe. Contribution to the determination of vanishing points using the Hough transform. IEEE Trans. Pattern Anal. and Machine Intel., 16 (4).
[9.7] G., McLean and D., Kotturi. Vanishing point detection by line clustering. IEEE Trans. Pattern Anal. and Machine Intel., 17 (11), 1995.Google Scholar
[9.8] M., Okutomi and T., Kanade. A multiple-baseline stereo. IEEE Trans. Pattern Anal. and Machine Intel., 15 (4), 1993.Google Scholar
[9.9] J., Princen, J., Illingworth, and J., Kittler. Hypothesis testing: A framework for analyzing and optimizing Hough transform performance. IEEE Trans. Pattern Anal. and Machine Intel., 16 (4), 1994.Google Scholar
[9.10] H., Wechsler and J., Sklansky. Finding the rib cage in chest radiographs. Pattern Recognition, 9, 1977.Google Scholar
[9.11] Y., Xie and Q., Ji. A new efficient ellipse detection method. I.ICRA, 2002.
[9.12] Ylä-Jääski and N., Kiryati. Adaptive termination of voting in the probabilistic circular Hough transform. IEEE Trans. Pattern Anal. and Machine Intel., 16 (9), 1994.Google Scholar

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  • Parametric Transforms
  • Wesley E. Snyder, North Carolina State University, Hairong Qi, University of Tennessee
  • Book: Fundamentals of Computer Vision
  • Online publication: 25 October 2017
  • Chapter DOI: https://doi.org/10.1017/9781316882641.014
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  • Parametric Transforms
  • Wesley E. Snyder, North Carolina State University, Hairong Qi, University of Tennessee
  • Book: Fundamentals of Computer Vision
  • Online publication: 25 October 2017
  • Chapter DOI: https://doi.org/10.1017/9781316882641.014
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Parametric Transforms
  • Wesley E. Snyder, North Carolina State University, Hairong Qi, University of Tennessee
  • Book: Fundamentals of Computer Vision
  • Online publication: 25 October 2017
  • Chapter DOI: https://doi.org/10.1017/9781316882641.014
Available formats
×