Moving Shadow Detection and Removal for Traffic Sequences

Mei Xiao; Chong-Zhao Han; Lei Zhang

doi:10.1007/s11633-007-0038-z

Volume 4 Issue 1

December. 2006

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Mei Xiao, Chong-Zhao Han and Lei Zhang. Moving Shadow Detection and Removal for Traffic Sequences. International Journal of Automation and Computing, vol. 4, no. 1, pp. 38-46, 2007. DOI: 10.1007/s11633-007-0038-z

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Moving Shadow Detection and Removal for Traffic Sequences

1.
School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, PRC;
2.
Taibai Campus, Chang'an University, Xi'an 710064, PRC

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The work was supported by the National Natural Science Foundation of PRC (No.60574033);the National Key Fundamental Research Development Programs(973)of PRC (No.2001CB309403)

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Received Date: November 21, 2005
Revised Date: March 05, 2006

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Abstract

Abstract

Segmentation of moving objects in a video sequence is a basic task for application of computer vision.However,shadows extracted along with the objects can result in large errors in object localization and recognition.In this paper,we propose a method of moving shadow detection based on edge information,which can effectively detect the cast shadow of a moving vehicle in a traffic scene.Having confirmed shadows existing in a figure,we execute the shadow removal algorithm proposed in this paper to segment the shadow from the foreground.The shadow eliminating algorithm removes the boundary of the cast shadow and preserves object edges firstly;secondly,it reconstructs coarse object shapes based on the edge information of objects;and finally,it extracts the cast shadow by subtracting the moving object from the change detection mask and performs further processing.The proposed method has been further tested on images taken under different shadow orientations,vehicle colors and vehicle sizes,and the results have revealed that shadows can be successfully eliminated and thus good video segmentation can be obtained.
- Moving shadow detection,
- moving shadow removal,
- edge information,
- traffic scene

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References (19)

References

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