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基于物理特性和形态学方法的阴影去除算法 被引量:1

Shadow Removal Algorithm Based on Physical Features and Morphological Method
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摘要 传统智能监控系统在阳光下进行测试时,阴影对检测结果影响较大。为此,提出一种用于视频的阴影去除算法,该算法用阴影的光亮、RGB和色差等物理特性得到初步去除阴影的目标结果,运用形态学方法扩充和完善目标,在获得目标的真实边缘和膨胀方向基础上,利用灰度、纹理和梯度的相似性对目标进行扩充。实验结果表明,该算法的平均正确率从68.47%提高到89.17%。 In intelligent surveillance system,the result is seriously influenced by shadow on sunny days.This paper proposes an algorithm to remove the shadow from images.It detects shadow regions using physical features of shadow for an initial result with less shadow.Three properties of shadow,luminance,RGB and chrominance are taken into account,to get the primary result.And uses morphological methods to improve result.Using the similarity of gray density,texture value and the gradient value,a good result can be obtained.Experimental result shows that the general accuracy of this algorithm is increased from 68.47% to 89.17%.
出处 《计算机工程》 CAS CSCD 2012年第10期131-133,共3页 Computer Engineering
基金 国家自然科学基金资助项目(61175009)
关键词 阴影检测 阴影去除 目标跟踪 智能监控系统 高斯混合模型 边缘检测 图像亮度 图像梯度 shadow detection shadow removal object tracking intelligent surveillance system Gaussian Mixture Model(GMM) contour detection image luminance image gradient
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参考文献5

  • 1Fung S K,Yung N H C,Pang G K H. Effective Moving Cast Shadow Detection for Monocular Color Image Sequences[A].Palermo,Italy,2001.404-409.
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同被引文献6

  • 1LIU Zhou,HUANG Kai-qi,TAN Tie-niu; Cast Shadow Rem- oval in a Hierarchical Manner Using MRF[C].IEEE Transa- ctions on Circuits and Systems for Video Technology, 2012.
  • 2YUAN Jin-juan, WU Jin, CHENG Yan-hu. Shadow detecting algorithms research for moving objects base on self-adaptive background [C]. Proceedings of International Conference on Modeling Identification & Control (ICMIC), 2012:197-200.
  • 3Rahmat R W, M-Tairi Z H, Saripan, M I. Sulaiman, P.S. Removing Shadow for Hand Segmentation Based on Background Subtraction [C]//Intemational Conference on Advanced Computer Science Applications and Technologies (ACSAT), 2012.481-485.
  • 4Buch N, Velastin S A, Orwell J. A Review of Computer Vision Techniques for the Analysis of Urban Traffic[C]//IEEE Transactions on Intelligent Transportation Systems, 2011,12 (3):920-393.
  • 5Porikli F, Thornton J. Shadow Flow: A Recursive Method to Learn Moving Cast Shadows [C]. International Conference on Computer Vision (ICCV) , 2005:891-898.
  • 6王小鹏,郭莉琼.公路车流量视频检测方法[J].计算机应用,2012,32(6):1585-1588. 被引量:21

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