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Open AccessArticle

WePBAS: A Weighted Pixel-Based Adaptive Segmenter for Change Detection

College of Computer Science and Technology, Jilin University, Changchun 130012, China
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Author to whom correspondence should be addressed.
Sensors 2019, 19(12), 2672; https://doi.org/10.3390/s19122672
Received: 24 May 2019 / Revised: 8 June 2019 / Accepted: 9 June 2019 / Published: 13 June 2019
(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing 2019)
The pixel-based adaptive segmenter (PBAS) is a classic background modeling algorithm for change detection. However, it is difficult for the PBAS method to detect foreground targets in dynamic background regions. To solve this problem, based on PBAS, a weighted pixel-based adaptive segmenter named WePBAS for change detection is proposed in this paper. WePBAS uses weighted background samples as a background model. In the PBAS method, the samples in the background model are not weighted. In the weighted background sample set, the low-weight background samples typically represent the wrong background pixels and need to be replaced. Conversely, high-weight background samples need to be preserved. According to this principle, a directional background model update mechanism is proposed to improve the segmentation performance of the foreground targets in the dynamic background regions. In addition, due to the “background diffusion” mechanism, the PBAS method often identifies small intermittent motion foreground targets as background. To solve this problem, an adaptive foreground counter was added to the WePBAS to limit the “background diffusion” mechanism. The adaptive foreground counter can automatically adjust its own parameters based on videos’ characteristics. The experiments showed that the proposed method is competitive with the state-of-the-art background modeling method for change detection. View Full-Text
Keywords: change detection; weighted sample; background model update mechanism; adaptive foreground counter change detection; weighted sample; background model update mechanism; adaptive foreground counter
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Li, W.; Zhang, J.; Wang, Y. WePBAS: A Weighted Pixel-Based Adaptive Segmenter for Change Detection. Sensors 2019, 19, 2672.

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