Fast Hough Transform on GPUs : Exploration of Algorithm Trade-Offs

G.J.W. Braak, van den; C. Nugteren; B. Mesman; H. Corporaal

doi:10.1007/978-3-642-23687-7_55

Fast Hough Transform on GPUs : Exploration of Algorithm Trade-Offs

G.J.W. Braak, van den, C. Nugteren, B. Mesman, H. Corporaal

Electronic Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

32 Citations (Scopus)

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Abstract

The Hough transform is a commonly used algorithm to detect lines and other features in images. It is robust to noise and occlusion, but has a large computational cost. This paper introduces two new implementations of the Hough transform for lines on a GPU. One focuses on minimizing processing time, while the other has an input-data independent processing time. Our results show that optimizing the GPU code for speed can achieve a speed-up over naive GPU code of about 10×. The implementation which focuses on processing speed is the faster one for most images, but the implementation which achieves a constant processing time is quicker for about 20% of the images. Fulltext Preview

Original language	English
Title of host publication	Proceedings of ACIVS'11 : Advanced Concepts for Intelligent Vision systems, 22-25 August 2011, Heidelberg, Germany
Editors	Jacques Blanc-Talon, Richard Kleihorst, Wilfried Philips, Dan Popescu, Paul Scheunders
Place of Publication	Berlin
Publisher	Springer
Pages	611-622
ISBN (Print)	978-3-642-23686-0
DOIs	https://doi.org/10.1007/978-3-642-23687-7_55
Publication status	Published - 2011
Event	conference; ACIVS'11, Gehnt, Belgium; 2011-08-22; 2011-08-25 - Duration: 22 Aug 2011 → 25 Aug 2011

Conference

Conference	conference; ACIVS'11, Gehnt, Belgium; 2011-08-22; 2011-08-25
Period	22/08/11 → 25/08/11
Other	ACIVS'11, Gehnt, Belgium

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10.1007/978-3-642-23687-7_55

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Braak, van den, G. J. W., Nugteren, C., Mesman, B., & Corporaal, H. (2011). Fast Hough Transform on GPUs : Exploration of Algorithm Trade-Offs. In J. Blanc-Talon, R. Kleihorst, W. Philips, D. Popescu, & P. Scheunders (Eds.), Proceedings of ACIVS'11 : Advanced Concepts for Intelligent Vision systems, 22-25 August 2011, Heidelberg, Germany (pp. 611-622). Springer. https://doi.org/10.1007/978-3-642-23687-7_55

Braak, van den, G.J.W. ; Nugteren, C. ; Mesman, B. et al. / Fast Hough Transform on GPUs : Exploration of Algorithm Trade-Offs. Proceedings of ACIVS'11 : Advanced Concepts for Intelligent Vision systems, 22-25 August 2011, Heidelberg, Germany. editor / Jacques Blanc-Talon ; Richard Kleihorst ; Wilfried Philips ; Dan Popescu ; Paul Scheunders. Berlin : Springer, 2011. pp. 611-622

@inproceedings{c239575195764aabb54abf9a49cea486,

title = "Fast Hough Transform on GPUs : Exploration of Algorithm Trade-Offs",

abstract = "The Hough transform is a commonly used algorithm to detect lines and other features in images. It is robust to noise and occlusion, but has a large computational cost. This paper introduces two new implementations of the Hough transform for lines on a GPU. One focuses on minimizing processing time, while the other has an input-data independent processing time. Our results show that optimizing the GPU code for speed can achieve a speed-up over naive GPU code of about 10×. The implementation which focuses on processing speed is the faster one for most images, but the implementation which achieves a constant processing time is quicker for about 20% of the images. Fulltext Preview",

author = "{Braak, van den}, G.J.W. and C. Nugteren and B. Mesman and H. Corporaal",

year = "2011",

doi = "10.1007/978-3-642-23687-7_55",

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editor = "Jacques Blanc-Talon and Richard Kleihorst and Wilfried Philips and Dan Popescu and Paul Scheunders",

booktitle = "Proceedings of ACIVS'11 : Advanced Concepts for Intelligent Vision systems, 22-25 August 2011, Heidelberg, Germany",

publisher = "Springer",

address = "Germany",

note = "conference; ACIVS'11, Gehnt, Belgium; 2011-08-22; 2011-08-25 ; Conference date: 22-08-2011 Through 25-08-2011",

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Braak, van den, GJW, Nugteren, C, Mesman, B & Corporaal, H 2011, Fast Hough Transform on GPUs : Exploration of Algorithm Trade-Offs. in J Blanc-Talon, R Kleihorst, W Philips, D Popescu & P Scheunders (eds), Proceedings of ACIVS'11 : Advanced Concepts for Intelligent Vision systems, 22-25 August 2011, Heidelberg, Germany. Springer, Berlin, pp. 611-622, conference; ACIVS'11, Gehnt, Belgium; 2011-08-22; 2011-08-25, 22/08/11. https://doi.org/10.1007/978-3-642-23687-7_55

Fast Hough Transform on GPUs : Exploration of Algorithm Trade-Offs. / Braak, van den, G.J.W.; Nugteren, C.; Mesman, B. et al.

Proceedings of ACIVS'11 : Advanced Concepts for Intelligent Vision systems, 22-25 August 2011, Heidelberg, Germany. ed. / Jacques Blanc-Talon; Richard Kleihorst; Wilfried Philips; Dan Popescu; Paul Scheunders. Berlin : Springer, 2011. p. 611-622.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Fast Hough Transform on GPUs : Exploration of Algorithm Trade-Offs

AU - Braak, van den, G.J.W.

AU - Nugteren, C.

AU - Mesman, B.

AU - Corporaal, H.

PY - 2011

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N2 - The Hough transform is a commonly used algorithm to detect lines and other features in images. It is robust to noise and occlusion, but has a large computational cost. This paper introduces two new implementations of the Hough transform for lines on a GPU. One focuses on minimizing processing time, while the other has an input-data independent processing time. Our results show that optimizing the GPU code for speed can achieve a speed-up over naive GPU code of about 10×. The implementation which focuses on processing speed is the faster one for most images, but the implementation which achieves a constant processing time is quicker for about 20% of the images. Fulltext Preview

AB - The Hough transform is a commonly used algorithm to detect lines and other features in images. It is robust to noise and occlusion, but has a large computational cost. This paper introduces two new implementations of the Hough transform for lines on a GPU. One focuses on minimizing processing time, while the other has an input-data independent processing time. Our results show that optimizing the GPU code for speed can achieve a speed-up over naive GPU code of about 10×. The implementation which focuses on processing speed is the faster one for most images, but the implementation which achieves a constant processing time is quicker for about 20% of the images. Fulltext Preview

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DO - 10.1007/978-3-642-23687-7_55

M3 - Conference contribution

SN - 978-3-642-23686-0

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BT - Proceedings of ACIVS'11 : Advanced Concepts for Intelligent Vision systems, 22-25 August 2011, Heidelberg, Germany

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T2 - conference; ACIVS'11, Gehnt, Belgium; 2011-08-22; 2011-08-25

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Braak, van den GJW, Nugteren C, Mesman B, Corporaal H. Fast Hough Transform on GPUs : Exploration of Algorithm Trade-Offs. In Blanc-Talon J, Kleihorst R, Philips W, Popescu D, Scheunders P, editors, Proceedings of ACIVS'11 : Advanced Concepts for Intelligent Vision systems, 22-25 August 2011, Heidelberg, Germany. Berlin: Springer. 2011. p. 611-622 doi: 10.1007/978-3-642-23687-7_55

Fast Hough Transform on GPUs : Exploration of Algorithm Trade-Offs

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