Fast Background Extracting Algorithms of Video Sequence Based on Invariance

Zhi Zheng Zhou; Shu Ming Jiang

doi:10.4028/www.scientific.net/AMM.443.18

Paper Titles

Schedule System for Transport Aircraft Mission Simulation
p.3

Comparison between the Generative Computer Approach and the Traditional Design Approach in the MRHC with Parallel Layout
p.7

Maximum a Posteriori Image Denoising with Edge-Preserving Markov Random Field Regularization
p.12

Fast Background Extracting Algorithms of Video Sequence Based on Invariance
p.18

A New Image Demising Method Based on Partial Differential Equations
p.22

Study on the Application of Computer Three-Dimensional Model's Simulation Functions
p.27

Arithmetic Implementation of FSK Based on DSP
p.31

The Building of Three-Dimensional Geographic Information System Based on Virtual Reality
p.35

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 443Fast Background Extracting Algorithms of Video...

Fast Background Extracting Algorithms of Video Sequence Based on Invariance

Abstract:

In order to reduce the complexity and computation of the background extraction algorithm, this paper presents a new background extraction algorithm corresponding to the intelligent traffic environment based on the invariance of background. In the algorithm, we partition the background into sub-blocks, and compare the characteristics of the several continues frames in the video stream, then update the background block by fuzzy similarity processing in real time. The evaluation proves that the new algorithm can accomplish the higher efficient extraction with less computation complexity.

You might also be interested in these eBooks

Computer-Aided Design, Manufacturing, Modeling and Simulation III

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 443)

Pages:

18-21

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.443.18

Citation:

Cite this paper

Online since:

October 2013

Authors:

Zhi Zheng Zhou, Shu Ming Jiang

Keywords:

Invariance, Quick Background Extraction, Video Sequence

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Fan Xiao-liang, Yang Jin-ji: Background Extraction and Update Algorithm Based on Frame-difference, Computer Engineering. 3(22), 159-161 (2011).

Google Scholar

[2] Yuan Wei-cai, Xu Xiang-min: Effective algorithm of background extraction and updating, Computer Engineering and Applications. 3(4), 90-100 (2010).

Google Scholar

[3] Li Wei, Chen Lin-qiang, Yin Wei-liang: Background Modeling Approach Based on Self-adaptive Learning Rate. Computer Engineering. 3(15), 67-70 (2011).

Google Scholar

[4] Yu Ruo-fei: Extraction Method of Moving Object Contour Using Background Extraction and Level Set. Computer and Modernization. 2(7), 9-13 (2011).

Google Scholar

[5] Elgammal Ahmed M: Efficient Nonparametric Kernel Density Estimation for Real Time Computer Vision. Ann Arbor, MI, USA: Pro Quest Information and Learning Company. 5(2), 23-29 (2002).

Google Scholar

[6] Surendra Gupte, Osama Masoud, Robert. F. K Martin: Detection and classification of vehicles. IEEE Transactions on Intelligent Transportation Systems. 3(1), 37-47·(2002).

DOI: 10.1109/6979.994794

Google Scholar

[7] Tang Jia-lin, Wang Zhen-bo, Chen Hua-chun: Background Extraction in Traffic Flow Eetection by Video, Shanxi Electronic Technology. 3(4), 39-40 (2011).

Google Scholar

[8] Huang Xin-juan, Zhou Jie-min, Liu Bo-yang: Moving objects detection approach based on adaptive mixture Gaussian background model. Journal of Computer Applications 7(1), 15-19 (2010).

DOI: 10.3724/sp.j.1087.2010.00071

Google Scholar

[9] Wu Liang, Ma Hong-xing: Analysis on background extraction technology of traffic information. Journal of Xi'an University of Science and Technology. 4(1), 56-60 (2010).

Google Scholar