Support vector machine based approach for leaf occlusion detection in security surveillance video

doi:10.11772/j.issn.1001-9081.2014.07.2023

Journal of Computer Applications ›› 2014, Vol. 34 ›› Issue (7): 2023-2027.DOI: 10.11772/j.issn.1001-9081.2014.07.2023

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Support vector machine based approach for leaf occlusion detection in security surveillance video

YUAN Yuan¹,², DINGSheng¹,²,XU Xin¹,²,CHEN li¹,²

1. Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System(Wuhan University of Science and Technology), Wuhan Hubei 430065, China
2. School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan Hubei 430065, China;

Received:2013-12-30 Revised:2014-02-11 Online:2014-07-01 Published:2014-08-01
Contact: YUAN Yuan

基于支持向量机的监控视频遮挡树叶检测

袁渊¹,²,丁胜¹,²,徐新¹,²,陈黎¹,²

1. 武汉科技大学计算机科学与技术学院，武汉 430065
2. 智能信息处理与实时工业系统湖北省重点实验室(武汉科技大学)，武汉 430065

通讯作者: 袁渊
作者简介:袁渊(1990-)，男，湖北黄冈人，硕士研究生，主要研究方向：图像处理；丁胜(1975-)，男，湖北武汉人，副教授，博士，主要研究方向：图像处理；徐新(1982-)，男，湖北武汉人，讲师，博士，主要研究方向：图像处理；陈黎(1977-)，男，湖北武汉人，副教授，博士，主要研究方向：图像处理、计算机视觉、统计信号处理。
基金资助:
国家自然科学基金资助项目;湖北省高等学校优秀中青年科技创新团队计划项目;湖北省教育厅科学技术研究计划项目

Abstract

Abstract:

Aiming at the problem that the security surveillance cameras have been hidden by leaves, a leaf occlusion detection algorithm based on Support Vector Machine (SVM) was proposed. The algorithm contains three steps. First, the regions of the leaf existing in the video were segmented. The accumulated frame subtraction method was applied to achieve this purpose. Second, the color and area information of the whole video image and the segmented regions were extracted as the key features. Third, these features were used for modeling and detecting obstacle occlusion by SVM. For all the collected samples, the detection accuracy of this method can reach up to 84%. The experimental results show that the proposed algorithm can detect the leaf occlusion in security surveillance video effectively.

摘要：

针对安防监控摄像头被树叶遮挡的问题，提出一种基于支持向量机(SVM)的视频树叶遮挡检测算法。该算法利用视频的时域特性，采用累积帧差法实现对视频中疑似树叶区域的分割，提取视频中某一帧图像的整个区域和疑似树叶区域的颜色信息与面积信息作为视频的特征，最后采用支持向量机进行建模并用于视频树叶遮挡的检测。在有限样本前提下，算法准确率能够达到84%。实验结果表明，所提算法对于有树叶遮挡的监控视频能够进行有效识别。

CLC Number:

TP391.41

YUAN Yuan DINGSheng XU Xin CHEN li. Support vector machine based approach for leaf occlusion detection in security surveillance video[J]. Journal of Computer Applications, 2014, 34(7): 2023-2027.

袁渊丁胜徐新陈黎. 基于支持向量机的监控视频遮挡树叶检测[J]. 计算机应用, 2014, 34(7): 2023-2027.

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Support vector machine based approach for leaf occlusion detection in security surveillance video

基于支持向量机的监控视频遮挡树叶检测

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