A Color Correlation and Texture-Based Shadow Elimination Method for Rainy Highway Videos

Han Li; Qi Sheng Wu

doi:10.4028/www.scientific.net/AMR.457-458.593

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 457-458A Color Correlation and Texture-Based Shadow...

A Color Correlation and Texture-Based Shadow Elimination Method for Rainy Highway Videos

Abstract:

This paper presents a novel method for elimination of cast shadow and water tailing in rainy highway videos. Based on color and texture characteristics of vehicles, background, cast shadow and water tailing region, a fusion method is proposed. First, color correlation is estimated between pixels through dot product of HSI vectors. Second, the texture difference based on gradient of current region and background region is calculated. Then, these two results are fused to both eliminate cast shadow and water tailing region. Experiments show that our method is simple and efficient, also helpful to extract accurate traffic information.

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Periodical:

Advanced Materials Research (Volumes 457-458)

Pages:

593-599

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.457-458.593

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Online since:

January 2012

Authors:

Han Li, Qi Sheng Wu

Keywords:

AID, Color Correlation, Shadow Eliminations, Texture Difference

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References

[1] Akio Yoneyama, Chia-Hung Y, C-C J K, Robust vehicle and traffic information extraction for highway surveillance, EURASIP Journal of Applied Signal Processing, Vol. 14(2005), pp.2305-2321.

DOI: 10.1155/asp.2005.2305

Google Scholar

[2] Zengjia Yan, Hao Z, Huadong M, etc., Cast vehicle shadow segmentation based on contour analysis, proceeding of the 2007 IEEE Intelligent Transportation Systems Conference, (2007) pp.866-871.

DOI: 10.1109/itsc.2007.4357714

Google Scholar

[3] Hong LIU, Jintao LI, Qun LIU, etc., Moving cast shadow elimination based on color and gradient features, Journal of Computer-aided Design & Computer Graphics, Vol. 19(2007) , pp.1219-1225.

Google Scholar

[4] Mei Xiao, Chong-zhao Han, Lei Zhang, Moving shadow detection and removal for traffic sequences, International Journal of Automation and Computing, Vol. 4(2007), pp.38-46.

DOI: 10.1007/s11633-007-0038-z

Google Scholar

[5] Rong DONG, Bo LI, Qi-mei CHEN, Research and improvement on shadow detection in expressway video using HSV color model, Journal of Image and Graphics, Vol. 14(2009)., pp.2483-2488.

Google Scholar

[6] Yang LIU, Yu-shan LI, Da-pu ZHANGg, A chrominance distortion and texture based method for shadow suppression, Computer Science, Vol. 32 (2005), pp.211-215.

Google Scholar

[7] Stauffer C, Grimson W, Adaptive background mixture models for real-time tracking, Proceedings of the IEEE Conference on Computer vision and Pattern Recognition, Ft. Collins, North Carolina(1999), pp.246-252.

DOI: 10.1109/cvpr.1999.784637

Google Scholar