A background subtraction algorithm for indoor monitoring surveillance systems

Mohamed Bachir Boubekeur, Senlin Luo, Hocine Labidi

科研成果: 书/报告/会议事项章节会议稿件同行评审

4 引用 (Scopus)

摘要

The use of the gray level intensity is a common practice for most of background subtraction algorithms due to speed matters in real time applications, and performance related considerations, yet using the RGB color representation could increase the efficiency of object detection thus the accuracy of the algorithm increases. In this paper, a non-parametric background subtraction algorithm based on samples modeling, adaptive threshold, and color layers combination is presented. The proposed framework showed an increase in performances regarding the accuracy and the robustness of the detection in indoor situations. The presented performance analysis supports the robustness of the algorithm to gradual illumination changes and ghost artifact.

源语言英语
主期刊名2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9781479960910
DOI
出版状态已出版 - 14 7月 2015
活动2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015 - Shenzhen, 中国
期限: 12 6月 201514 6月 2015

出版系列

姓名2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015

会议

会议2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015
国家/地区中国
Shenzhen
时期12/06/1514/06/15

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