Algorithm of Color Detection for Moving Video Objects Based on Mode Matching

Article Preview

Abstract:

It is urgent to study how to effectively identify color of moving objects from the video in the information era. In this paper, we present the color identification methods for moving objects on fixed camera. One kind of the methods is background subtraction that recognizes the foreground objects by compare the difference of pixel luminance between the current image and the background image at the same coordinates. Another kind is based on the statistics of HSV color and color matching which makes the detection more similar to the color identification of the human beings. According to the experiment results, after the completion of the background modelling, our algorithm of background subtraction, statistics of the HSV color and the color matching have strong color recognition ability on the moving objects of video.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1000-1003

Citation:

Online since:

December 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Z. Wu, S. Jiang, L. Li, P. Cui, Q. Huang, W. Gao: Vicept: link visual features to concepts for large-scale image understanding. ACM Multimedia 2010, pp.711-714.

DOI: 10.1145/1873951.1874059

Google Scholar

[2] J. Suo, L. Lin, S. Shan, X. Chen, W. Gao: High-Resolution Face Fusion for Gender Conversion. IEEE Transactions on Systems, Man, and Cybernetics, Part A 41(2) (2011) 226-237.

DOI: 10.1109/tsmca.2010.2064304

Google Scholar

[3] W. Gao, C.H. Lee, J. Yang, X. Chen, M. Eskenazi, Z. Zhang: Proceedings of the 12th International Conference on Multimodal Interfaces / 7. International Workshop on Machine Learning for Multimodal Interaction, ICMI-MLMI 2010, Beijing, China, November 8-12, 2010 ACM 2010.

DOI: 10.1145/1891903

Google Scholar

[4] D. Zhai, B. Li, H. Chang, S. Shan, X. Chen, W. Gao: Manifold Alignment via Corresponding Projections. BMVC 2010: 1-11.

DOI: 10.5244/c.24.3

Google Scholar