Advanced SearchSearch Tips
CUDA based parallel design of a shot change detection algorithm using frame segmentation and object movement
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
CUDA based parallel design of a shot change detection algorithm using frame segmentation and object movement
Kim, Seung-Hyun; Lee, Joon-Goo; Hwang, Doo-Sung;
  PDF(new window)
This paper proposes the parallel design of a shot change detection algorithm using frame segmentation and moving blocks. In the proposed approach, the high parallel processing components, such as frame histogram calculation, block histogram calculation, Otsu threshold setting function, frame moving operation, and block histogram comparison, are designed in parallel for NVIDIA GPU. In order to minimize memory access delay time and guarantee fast computation, the output of a GPU kernel becomes the input data of another kernel in a pipeline way using the shared memory of GPU. In addition, the optimal sizes of CUDA processing blocks and threads are estimated through the prior experiments. In the experimental test of the proposed shot change detection algorithm, the detection rate of the GPU based parallel algorithm is the same as that of the CPU based algorithm, but the average of processing time speeds up about 6~8 times.
shot change detection;frame segmentation;Otsu's Threshold;CUDA;
 Cited by
David B. kirk, Wen-mei W. Hwu, "Programming Massively Parallel Processors: A Hands-on Approach," Elsevier, pp. 73-105, 2010.

S. H. Kim, D. S. Hwang, "A shot change detection algorithm based on frame segmentation and object movement," Journal of The Korea Society of Computer and Information, in press


J. R. Parker, "Algorithms for Image Processing and computer vision 2nd Edition," wiley publishing, pp. 149-151, 2011.

Puneet, Naresh Kumar Garg, "Binarization Techniques used for Grey Scale Images," International Journal of Computer Applications, Vol. 71, No. 1, pp. 8-11, June 2013.

H. J. Zhang, A. Kankanhalli, S. W. Smoliar, "Automatic partitioning of full-motion video," Multimedia Systems, Vol. 1, No. 1, pp. 10-28, 1993. crossref(new window)

Xiaoquan Yi, Nam Ling, "Fast Pixel-Based Video Scene Change Detection," IEEE Int. Symposium on circuits and Systems, Vol. 4, pp. 3343-3346, May 2005.

S. Y. Tak, S. Yoo, B. R. Lee, W. J. Lee, K. S. Ryu, T. G. Kim, H. C. Kang, "Scene change detection of various color space using difference of histogram," Proceedings of the Spring Conf. on The Korea Contents Association, pp. 466-468, May 2010.

S. M. Go, H. G. Kim, M. S. Oh, "A Study on block histogram's comparison for cut detection," Journal of The Korean Institute of Maritime Information and Communication Sciences, Vol. 5, No. 7, pp. 1301-1307, Dec. 2001.

S. J. Kang, S. I. Cho, S. J. Yoo, Y. H. Kim, "Scene Change Detection Using Multiple Histograms for Motion-Compensated Frame Rate Up-Conversion," Journal of Display Technology, Vol. 8, No. 3, pp. 121-126, March 2012. crossref(new window)

Yuancheng Luo, R. Duraiswami, "Canny edge detection on NVIDIA CUDA," Computer Vision and Pattern Recognition Workshops 2008. IEEE Computer Society Conference on, pp.1-8, June 2008.

Nan Zhang, Yun-shan Chen, Wang Jian?Li, "Image parallel processing based on GPU," Advanced Computer Control (ICACC), 2010 2nd International Conference on, Vol. 3, pp. 367-370, March 2010.

Z. Yang, Y. Zhu, Y. Pu, "Parallel Image Processing Based on CUDA,", 2008 International Conference on Computer Science and Software Engineering, Vol. 3, pp. 198-201, Dec. 2008.

Thorsten Scheuermann, Justin Hensley, "Efficient histogram generation using scattering on GPUs," Proceedings of the 2007 symposium on Interactive 3D graphics and games(I3D), pp. 33-37, April 2007.

J. G. Lee, S. H. Kim, B. M. Yoo, D. S. Hwang, "Parallel Design and Implementation of Shot Boundary Detection Algorithm," Journal of the Institute of Electronics Engineers of Korea, Vol. 51, No. 2, pp.76-84, Feb. 2014.

National Archives of Korea,

OpenCV document,