Moving Objects Detection Based on Hysteresis Thresholding

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

doi:10.1007/978-3-642-35473-1_29

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 proceeding › Chapter

2 Citations (Scopus)

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 language	English
Title of host publication	Advances in Intelligent Systems and Applications - Volume 2
Subtitle of host publication	Proceedings of the International Computer
Editors	Chang Ruay-Shiung, Peng Sheng-Lung, Lin Chia-Chen
Pages	289-298
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-642-35473-1_29
Publication status	Published - 2013
Externally published	Yes

Publication series

Name	Smart Innovation, Systems and Technologies
Volume	21
ISSN (Print)	2190-3018
ISSN (Electronic)	2190-3026

Keywords

Background modeling
Hysteresis thre-sholding
Moving objects detection

ASJC Scopus subject areas

General Decision Sciences
General Computer Science

Access to Document

10.1007/978-3-642-35473-1_29

Cite this

Lai, H. E., Lin, C. Y., Chen, M. K., Kang, L. W., & Yeh, C. H. (2013). Moving Objects Detection Based on Hysteresis Thresholding. In C. Ruay-Shiung, P. Sheng-Lung, & L. Chia-Chen (Eds.), Advances in Intelligent Systems and Applications - Volume 2: Proceedings of the International Computer (pp. 289-298). (Smart Innovation, Systems and Technologies; Vol. 21). https://doi.org/10.1007/978-3-642-35473-1_29

Moving Objects Detection Based on Hysteresis Thresholding. / Lai, Hsiang Erh; Lin, Chih Yang; Chen, Ming Kai et al.
Advances in Intelligent Systems and Applications - Volume 2: Proceedings of the International Computer. ed. / Chang Ruay-Shiung; Peng Sheng-Lung; Lin Chia-Chen. 2013. p. 289-298 (Smart Innovation, Systems and Technologies; Vol. 21).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Lai, HE, Lin, CY, Chen, MK, Kang, LW & Yeh, CH 2013, Moving Objects Detection Based on Hysteresis Thresholding. in C Ruay-Shiung, P Sheng-Lung & L Chia-Chen (eds), Advances in Intelligent Systems and Applications - Volume 2: Proceedings of the International Computer. Smart Innovation, Systems and Technologies, vol. 21, pp. 289-298. https://doi.org/10.1007/978-3-642-35473-1_29

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title = "Moving Objects Detection Based on Hysteresis Thresholding",

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.",

keywords = "Background modeling, Hysteresis thre-sholding, Moving objects detection",

author = "Lai, {Hsiang Erh} and Lin, {Chih Yang} and Chen, {Ming Kai} and Kang, {Li Wei} and Yeh, {Chia Hung}",

note = "Funding Information: This work was supported in part by the National Science Council, Taiwan, under Grants NSC101-2221-E-468-021.",

year = "2013",

doi = "10.1007/978-3-642-35473-1_29",

language = "English",

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AU - Lai, Hsiang Erh

AU - Lin, Chih Yang

AU - Chen, Ming Kai

AU - Kang, Li Wei

AU - Yeh, Chia Hung

N1 - Funding Information: This work was supported in part by the National Science Council, Taiwan, under Grants NSC101-2221-E-468-021.

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

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KW - Hysteresis thre-sholding

KW - Moving objects detection

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ER -

Moving Objects Detection Based on Hysteresis Thresholding

Abstract

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Keywords

ASJC Scopus subject areas

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