Accelerating line extraction based on GPU
Authors: 
Li Yu, Xiao'an Tang, Bo TangAuthors Info & Claims
Li Yu, Xiao'an Tang, Bo TangAuthors Info & ClaimsPages 407 - 410
Abstract
A new line extraction accelerating algorithm based upon graphics processing units (GPUs) is presented. Several techniques are proposed to optimize the GPU computation. Among those improvements, the most important one is the use of "seed pixels", which allows us to extract the lines while benefiting from the parallelism GPU architectures offer. Only a few bytes of data are transferred between GPU and CPU. The experimental results show that the proposed algorithm has a significant increase in speed when compared with a stand-alone CPU. In comparison to a traditional CPU implementation, the performance gains range from x5 to x10, depending on the image size.
References
[1]
Burns, J. B., Hanson, A., and Riseman, E. 1986. Extracting Straight Lines, IEEE Transactions on Pattern Analysis and Machine Intelligence, 8, 425--455.
[2]
Ho, C. T., and Chan, L. H. 1996. A high speed algorithm for line extraction, Pattern Recognition letters, 17, 5, 467--473.
[3]
Wang, C., Wen, G. J., and Wang, R. S. 2002. Line extraction for broadband image signals, Chinese Journal of Computers, vol.25 No.7, 753--758.
[4]
Fung, J. 2005. Chapter 40: Computer vision on the gpu. In GPU Gems 2: Programming Techniques for High-Performance Graphics and General Purpose, edited by M. Pharr, Addison-Wesley.
[5]
Harding, S., and Banzhaf, W. 2008. Genetic programming on GPUs for image processing, International Journal of High Performance Systems Architecture, 1, 4, 231--240.
[6]
Rahman, A., Houzet, D., Pellerin, D., and Agud, L. 2010. GPU implementation of motion estimation for visual saliency, In DASIP 2010, 222--227.
[7]
Fung, J., Mann, S., and Aimone, C. 2005. OpenVIDIA: Parallel GPU Computer Vision, In Proceedings of the 13th annual ACM international conference on Multimedia, 849--852.
[8]
Diard, F. 2010. Chapter 41: Using the Geometry Shader for Compact and Variable-Length GPU Feedback. In GPU Gems 3, edited by Hubert Nguyen, Addison- Wesley.
[9]
Podlozhnyuk, V. 2007. Image Convolution with CUDA, http://www.nvidia.com/object/cuda.home.html.
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Information & Contributors
Information
Published In
December 2011
617 pages
ISBN:9781450310604
DOI:10.1145/2087756
- General Chairs:
- Zhi-Qiang Liu,
- Joaquim Jorge,
- Zhigeng Pan,
- Program Chairs:
- Xiaopeng Zhang,
- Oscar Kin-Chung Au,
- Weiming Dong
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- SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
- VT Committee of the China Society of Image and Graphics
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 11 December 2011
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- Research-article
Conference
VRCAI '11
Sponsor:
VRCAI '11: The 10th International Conference on Virtual Reality Continuum and Its Applications in Industry
December 11 - 12, 2011
Hong Kong, China
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Overall Acceptance Rate 51 of 107 submissions, 48%
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