Efficient moving object segmentation algorithm for illumination change in surveillance system

被引:0
|
作者
Jung, TY [1 ]
Kim, JY [1 ]
Kim, DG [1 ]
机构
[1] Kyungpook Natl Univ, Sch Elect Engn & Comp Sci, Taegu 702701, South Korea
来源
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An efficient algorithm to segment the moving object is very important in the surveillance system. In general, the change detection by comparing brightness value is a good and simple method, but it shows a poor performance under illumination change. Therefore, we propose the segmentation algorithm to extract effectively the object in spite of the illumination change. There are three modes to extract the object, the criteria of mode selection are both available background existence and illumination change. Then the object is finally obtained by using projection and the morphological operator in post-processing. Furthermore, the double binary method using the similarity of brightness value and spatial proximity is used to obtain more edge information. A good segmentation performance is demonstrated by the simulation result.
引用
收藏
页码:812 / 819
页数:8
相关论文
共 50 条
  • [21] Efficient Moving Object Segmentation Algorithm Based on the Improvement of Generalized Geodesic Active Contour Model
    Chen, Ying
    Yu, Qi
    PROCEEDINGS OF 2016 8TH IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION SOFTWARE AND NETWORKS (ICCSN 2016), 2016, : 630 - 635
  • [22] A framework of moving object segmentation in maritime surveillance inside a dynamic background
    Kushwaha, Alok Kumar Singh
    Srivastava, Rajeev
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, 9030 : 35 - 54
  • [23] Object Detection Using a Moving Camera under Sudden Illumination Change
    Shakeri, Moein
    Zhang Hong
    2013 32ND CHINESE CONTROL CONFERENCE (CCC), 2013, : 4001 - 4006
  • [24] A robust adaptive algorithm of moving object detection for video surveillance
    Elham Kermani
    Davud Asemani
    EURASIP Journal on Image and Video Processing, 2014
  • [25] Moving object detection using genetic Algorithm for traffic Surveillance
    Dey, Jayashree
    Praveen, N.
    2016 INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, AND OPTIMIZATION TECHNIQUES (ICEEOT), 2016, : 2289 - 2293
  • [26] An Automatic Moving Object Detection Algorithm for Video Surveillance Applications
    Zheng, Xiaoshi
    Zhao, Yanling
    Li, Na
    Wu, Huimin
    2009 INTERNATIONAL CONFERENCE ON EMBEDDED SOFTWARE AND SYSTEMS, PROCEEDINGS, 2009, : 541 - 543
  • [27] A robust adaptive algorithm of moving object detection for video surveillance
    Kermani, Elham
    Asemani, Davud
    EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING, 2014,
  • [28] Moving Object Segmentation Using Motion Orientation Histogram in Adaptively Partitioned Blocks for Consumer Surveillance System
    Lee, Seungwon
    Lee, Junghyun
    Chon, Ewoo
    Hayes, Monson H.
    Paik, Joonki
    2012 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS (ICCE), 2012, : 197 - +
  • [29] Moving object Segmentation
    Zinbi, Youssef
    Chahir, Youssef
    Elmoataz, Abder
    2008 3RD INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES: FROM THEORY TO APPLICATIONS, VOLS 1-5, 2008, : 1132 - 1136
  • [30] A Survey of Efficient Deep Learning Models for Moving Object Segmentation
    Hou, Bingxin
    Liu, Ying
    Ling, Nam
    Ren, Yongxiong
    Liu, Lingzhi
    APSIPA TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING, 2023, 12 (01)