An Improved ViBe Algorithm of Moving Target Extraction for Night Infrared Surveillance Video

• Zhiqiang Feng,
• Xiaogang Wang,
• Zhongfan Yang,
• Shaojie Guo,
• Xingzhong Xiong,

Vol. 15, No. 12, December 31, 2021
10.3837/tiis.2021.12.002, Download Paper (Free):

• moving target extraction
• illumination change
• Adaptive threshold
• image entropy
• regional growth

Abstract

For the research field of night infrared surveillance video, the target imaging in the video is easily affected by the light due to the characteristics of the active infrared camera and the classical ViBe algorithm has some problems for moving target extraction because of background misjudgment, noise interference, ghost shadow and so on. Therefore, an improved ViBe algorithm (I-ViBe) for moving target extraction in night infrared surveillance video is proposed in this paper. Firstly, the video frames are sampled and judged by the degree of light influence, and the video frame is divided into three situations: no light change, small light change, and severe light change. Secondly, the ViBe algorithm is extracted the moving target when there is no light change. The segmentation factor of the ViBe algorithm is adaptively changed to reduce the impact of the light on the ViBe algorithm when the light change is small. The moving target is extracted using the region growing algorithm improved by the image entropy in the differential image of the current frame and the background model when the illumination changes drastically. Based on the results of the simulation, the I-ViBe algorithm proposed has better robustness to the influence of illumination. When extracting moving targets at night the I-ViBe algorithm can make target extraction more accurate and provide more effective data for further night behavior recognition and target tracking.

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