An adaptive shadow detection algorithm using edge texture and sampling deduction

被引：1
作者：
Jiang, Ke [1 ]
Li, Aihua [1 ]
Su, Yanzhao [1 ]
机构：
[1] 502 Faculty, The Second Artillery Engineering University
来源：
Hsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University | 2013年 / 47卷 / 02期
关键词：
Adaptive thresholds; Edge texture; Moving object detection; Shadow detect; YUV color space;
D O I：
10.7652/xjtuxb201302007
中图分类号：
学科分类号：
摘要：
An adaptive shadow detection algorithm is proposed to improve the accuracy and scene adaptive capacity of the shadow detection and to raise the effect of moving object detection. The change ratios of YUV components between candidate foreground and original background are used to detect shadow pixels, and the global edge texture and sampling deduction methods are employed to estimate the detection threshold values. The algorithm automatically complete the processes of both thresholds estimation and shadow discriminant without any manual intervention, so the algorithm is adaptive to different light conditions and has a strong robustness. Experiment results on standard videos with different lighting conditions show that both the accuracy and stability are raised by the proposed algorithm and the average comprehensive index of the proposed algorithm can reach more than 94%.
引用
收藏
页码：39 / 46
页数：7
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