基于HLBP特征的运动阴影检测方法  

Moving Shadow Detection Approach Based on HLBP Feature

作　　者：文凌艳[1,2] 尹东[1,2] 

机构地区：[1]中国科学技术大学信息科学技术学院,合肥230027 [2]中国科学院电磁空间信息重点实验室,合肥230027

出　　处：《光电工程》2016年第10期84-89,共6页Opto-Electronic Engineering

基　　金：安徽省科技厅项目"海量人脸图像快速检索云服务平台及应用示范"

摘　　要：视频运动检测中,运动阴影常被误检为运动目标。针对这一问题,提出了一种利用哈尔型特性局部二元模式(HLBP)检测运动阴影的方法。首先,提取每个检测到的运动像素及其对应背景像素的HLBP特征向量。其次,使用曼哈顿距离度量HLBP纹理差异,获得纹理差异图。最后,利用最大类间方差算法(Ostu算法)对纹理差异图进行二值化处理,得到消除运动阴影后的目标结果。实验表明,该方法在多种室内外场景中能实时且有效地检测出运动阴影,具有较强的实用性。In video motion detection, moving shadow is often mistakenly detected as moving objects. In order to solve this problem, a moving shadow detection method is presented, which uses Haar Local Binary Pattern（HLBP） to detect shadow. Firstly, HLBP feature of detected moving regions and corresponding regions in the background is extracted. Secondly, it uses Manhattan Distance to measure the difference of HLBP feature between the two regions to get a map about texture difference. Finally, Ostu algorithm is employed to segment texture difference map to get a mask of moving objects, and then moving objects are extracted. The experimental results show that the proposed method can effectively detect moving shadow in some outdoor and indoor scenes in real time.

关 键 词：运动阴影检测 哈尔型特性局部二元模式 纹理差异 图像分割 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]