NDLI: A new interframe difference algorithm for moving target detection

Content Provider	IEEE Xplore Digital Library
Author	Muyun Weng Guoce Huang Xinyu Da
Copyright Year	2010
Description	Author affiliation: The Telecommunication Engineering Institute Air Force Engineering University, No.1 Fenghao Road, Xi'an, 710077, China (Muyun Weng; Guoce Huang; Xinyu Da)
Abstract	In this paper, a new interframe difference algorithm for moving target detection is proposed which is under a static background based on three-frame-difference method in combination with background subtraction method. Firstly, the current frame image subtracts the previous frame and the next frame image separately, their results are added together to get a gray-scale image of the three-frame-difference method. Secondly, the current frame image subtracts the background image to get another gray-scale image of background subtraction method. Thirdly, their sum of the two gray-scale images of above is translated into binary image after being judged by threshold. Finally, this binary image is processed by morphology filtering and connectivity analyzing. Therefore, moving region is obtained. This new algorithm takes advantage of the good performances of three-frame-difference method and background subtraction method adequately. The analysis in theory and experiment results all show that the algorithm is better in efficiency and effect for moving target detection compared to the other similarity method.
Starting Page	285
Ending Page	289
File Size	1525264
Page Count	5
File Format	PDF
ISBN	9781424465132
e-ISBN	9781424465163
DOI	10.1109/CISP.2010.5648259
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis interframe difference method Filtering background subtraction method Noise Morphology Object detection Apertures Moving target detection static background Pixel
Content Type	Text
Resource Type	Article

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