Moving Objects Detection Based on Hysteresis Thresholding

Hsiang Erh Lai*, Chih Yang Lin, Ming Kai Chen, Li Wei Kang, Chia Hung Yeh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Background modeling is the core of event detection in surveillance systems. The traditional Gaussian mixture model has some defects when encountering some situations like shadow interferences, lighting changes, and other problems causing foreground image broken. All of these cases will result in deficiencies of event detection. In this paper, we propose a new background modeling method to solve these problems. The model features of our method are the combination of texture and color characteristics, hysteresis thresholding, and the motion estimation to recover broken foreground objects.

Original languageEnglish
Title of host publicationAdvances in Intelligent Systems and Applications - Volume 2
Subtitle of host publicationProceedings of the International Computer
EditorsChang Ruay-Shiung, Peng Sheng-Lung, Lin Chia-Chen
Pages289-298
Number of pages10
DOIs
Publication statusPublished - 2013
Externally publishedYes

Publication series

NameSmart Innovation, Systems and Technologies
Volume21
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Keywords

  • Background modeling
  • Hysteresis thre-sholding
  • Moving objects detection

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Computer Science(all)

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