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计算机工程 ›› 2012, Vol. 38 ›› Issue (5): 173-175. doi: 10.3969/j.issn.1000-3428.2012.05.053

• 人工智能及识别技术 • 上一篇    下一篇

基于弱阈值分割的运动人体阴影去除算法

李科伟,杨晓敏,何小海,张生军   

  1. (四川大学电子信息学院图像信息研究所,成都 610065)
  • 收稿日期:2011-08-19 出版日期:2012-03-05 发布日期:2012-03-05
  • 作者简介:李科伟(1987-),男,硕士研究生,主研方向:图像处 理,智能监控;杨晓敏,讲师;何小海,教授、博士生导师; 张生军,博士研究生
  • 基金资助:
    欧盟FP7-PEOPLE-IRSES-S2EuNet基金资助项目(247 083)

Shadow Removal Algorithm for Moving Pedestrian Based on Weak Thresholds Segmentation

LI Ke-wei, YANG Xiao-min, HE Xiao-hai, ZHANG Sheng-jun   

  1. (Institute of Image Information, College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China)
  • Received:2011-08-19 Online:2012-03-05 Published:2012-03-05

摘要: 提出一种基于弱阈值分割的运动人体阴影去除算法。从阈值选取的角度出发,定义强阈值与弱阈值,使用混合高斯模型获取运动前景,在颜色空间与梯度空间中提取弱阈值目标,融合提取出的多个目标区域,经过邻域处理后得到不包含阴影点的运动人体目标。实验结果证明了该算法的有效性。

关键词: 弱阈值分割, 混合高斯模型, 阴影去除, 颜色空间, 梯度空间

Abstract: This paper proposes a shadow removal algorithm for moving pedestrian based on weak thresholds segmentation. The thresholds for segmentation are classified into weak and strong. The foreground is extracted by Gaussian Mixture Model(GMM). The weak thresholds are applied in color space and gradient space respectively to get partial objects, which are merged next. After the neighbour fixing, the complete object with no shadow pixels is obtained. Experimental results prove the validity of the algorithm.

Key words: weak thresholds segmentation, Gaussian Mixture Model(GMM), shadow removal, color space, gradient space

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