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Sensors 2016, 16(4), 456; doi:10.3390/s16040456

Background Subtraction Based on Three-Dimensional Discrete Wavelet Transform

College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
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Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 8 January 2016 / Revised: 13 March 2016 / Accepted: 23 March 2016 / Published: 30 March 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [12997 KB, uploaded 30 March 2016]   |  

Abstract

Background subtraction without a separate training phase has become a critical task, because a sufficiently long and clean training sequence is usually unavailable, and people generally thirst for immediate detection results from the first frame of a video. Without a training phase, we propose a background subtraction method based on three-dimensional (3D) discrete wavelet transform (DWT). Static backgrounds with few variations along the time axis are characterized by intensity temporal consistency in the 3D space-time domain and, hence, correspond to low-frequency components in the 3D frequency domain. Enlightened by this, we eliminate low-frequency components that correspond to static backgrounds using the 3D DWT in order to extract moving objects. Owing to the multiscale analysis property of the 3D DWT, the elimination of low-frequency components in sub-bands of the 3D DWT is equivalent to performing a pyramidal 3D filter. This 3D filter brings advantages to our method in reserving the inner parts of detected objects and reducing the ringing around object boundaries. Moreover, we make use of wavelet shrinkage to remove disturbance of intensity temporal consistency and introduce an adaptive threshold based on the entropy of the histogram to obtain optimal detection results. Experimental results show that our method works effectively in situations lacking training opportunities and outperforms several popular techniques. View Full-Text
Keywords: background subtraction; three-dimensional discrete wavelet transform; intensity temporal consistency; wavelet shrinkage background subtraction; three-dimensional discrete wavelet transform; intensity temporal consistency; wavelet shrinkage
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Han, G.; Wang, J.; Cai, X. Background Subtraction Based on Three-Dimensional Discrete Wavelet Transform. Sensors 2016, 16, 456.

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