针对运动提取算法总是将运动阴影错误检测为运动前景,提出一种基于边缘信息的室内运动阴影去除算法.首先用Canny算子提取输入图像的边缘,同时对输入图像进行梯度分割;其次利用运动边缘的属性提取属于真实前景的运动边缘;再次得到靠近运动边缘的真实前景的部分边界;最后通过文中提出的边界跟踪技术构建出完整的前景边界,从而提高运动前景的检测精度.仿真实验表明,对不同的光源距离、不同的阴影投影方向及不同颜色前景引起的运动阴影,算法都能鲁棒地分离目标及其阴影区域.
Abstract
Because the moving shadows usually were extracted along with objects by motion detection algorithms, an edgebased approach to remove moving shadows for indoor sequences is proposed. Firstly, edges of input images are found using Canny operator and the input image is segmented according to gradient magnitude. Next, the moving edges of real moving object are obtained using moving edge properties, then the part boundaries of real foregrounds near the moving edges are found. Finally, the complete foreground objects are constructed by means of the proposed border tracing technique, thus the moving object detection exactitude is improved. Simulation results show that the proposed method can effectively separate the moving objects from their shadows caused by different distances of the lamphouse, diverse shadows directions and foreground colors.
关键词
阴影去除 /
运动边缘提取 /
边界跟踪 /
室内视频
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Key words
Shadow Removal /
Moving Edges Extraction /
Border Tracing /
Indoor Video Sequences
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参考文献
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(夏良正.数字图像处理.南京:东南大学出版社, 1999: 222-223)
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脚注
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基金
国家自然科学基金项目(No.60574033)、国家重点基础研究发展规划项目(No.2001CB309403)资助
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