Browse > Article

A Scene Change Detection Technique using the Weighted $\chi^2$-test and the Automated Threshold-Decision Algorithm  

Ko, Kyong-Cheol (Dept. of Comp. Sci, Kunsan National University)
Rhee, Yang-Won (Dept. of Comp. Sci, Kunsan National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.42, no.4, 2005 , pp. 51-58 More about this Journal
Abstract
This paper proposes a robust scene change detection technique that uses the weighted chi-square test and the automated threshold-decision algorithms. The weighted chi-square test can subdivide the difference values of individual color channels by calculating the color intensities according to NTSC standard, and it can detect the scene change by joining the weighted color intensities to the predefined chi-square test which emphasize the comparative color difference values. The automated threshold-decision at algorithm uses the difference values of frame-to-frame that was obtained by the weighted chi-square test. At first, The Average of total difference values is calculated and then, another average value is calculated using the previous average value from the difference values, finally the most appropriate mid-average value is searched and considered the threshold value. Experimental results show that the proposed algorithms are effective and outperform the previous approaches.
Keywords
장면전환검출;차이 값;자동 임계치-결정 알고리즘;평균값;
Citations & Related Records
연도 인용수 순위
  • Reference
1 P. Browne, A. F. Smeaton, N. Murphy, N. O'Connor, 'Evaluation and Combining digital video shot boundary detection algorithms,' in Proc. of the 4th Irish Machine Vision and Information Processing Conference, Queens University Belfast, 2000
2 Z. Cernekova, C. Nikou, I. Pitas, 'Shot Detection in Video Sequences using Entroypy-Based Metrics,' ICIP 2002, Vol. 3, pp. 421-424, 2002
3 Alan Hanjalic, 'Shot-boundary detection: unraveled and resolved,' IEEE Transactions on Circuits and Systems for Video Technology, Vol. 12, No. 2, pp. 90-105, February. 2002   DOI   ScienceOn
4 I. K. Sethi and N. Patel, 'A statistical approach to scene change detection,' SPIE, vol. 2420, pp. 329-338, 1995   DOI
5 U. Gargi, S. Oswald, D. Kosiba, S. Devadiga, R. Kasturi, 'Evaluation of video sequence indexing and hierarchical video indexing,' In: Proc. SPIE'95, Storage Retrieval Image Video Databases III,(1995) 144-151   DOI
6 Rainer Lienhart, 'Comparison of Automatic Shot Boundary Detection Algorithms,' Storage and Retrieval for Still Image and Video Databases VII 1999, Proc. SPIE 3656-29, Jan, 1999   DOI
7 A. Nagasaka and Y. Tanaka, 'Automatic video indexing and full-video search for object appearances,' Visual Database Syst. II, pp. 113-127, 1992
8 A. Dailianas, R. B. Allen, P. England: Comparison of Automatic Video Segmentation Algorithms,' In Integration Issues in Large Commercial Media Delivery Systems, Proc. SPIE 2615, pp. 2-16, Oct. 1995
9 H. Zhang, A. Kankamhalli, and S. Smoliar, 'Automatic partitioning of full-motion video,' ACM Multimedia Systems, New York: ACM Press, Vol. 1 1993, pp. 10-28   DOI
10 C. L. Huang and B. Y. Liao, 'A Robust Scene Change Detection Method for Video Segmentation,' IEEE Trans on CSVT, Vol. 11, No. 12, pp. 1281-1288, December 2001
11 U. Gargi, R. Kasturi, and S. H. Strayer, 'Performance Characterization of Video Shot Change Detection Methods,' IEEE Trans on CSVT, Vol. 10, No. 1, pp. 0001-0013, February 2000   DOI   ScienceOn