The foreground detection algorithm combined the temporal–spatial information and adaptive visual background extraction. (2nd January 2017)

• Record Type: Journal Article
• Authors: Qu, Z.; Huang, X.-L.
• Is Part Of: Imaging science journal. Volume 65:Number 1(2017)
• Page Start: 49
• Page End: 61
• Publication Date: 2017-01-02
• Subjects: Visual background extraction -- Background model -- Ghost -- Illumination change; Imaging systems -- Periodicals; 621.36705
• DOI: 10.1080/13682199.2016.1258509
• Languages: English
• ISSNs: 1368-2199

Abstract

ABSTRACT: Visual background extraction algorithm, which utilises a global threshold to complete the foreground segmentation, cannot adapt to illumination change well. It will easily choose the wrong pixels to initialise the background model, resulting in the emergence of the ghost in the beginning of detection. In order to address these problems, this article proposes an improved algorithm based on pixel's temporal–spatial information to initialise the background model. First of all, the pixels in video image sequences and their neighbourhood pixels are used to complete background model initialisation in the first five frames. Second, the segmentation threshold is adaptively obtained by the complexity of background that uses the spatial neighbourhood pixels. Finally, the background model of the neighbourhood pixels is updated by a dynamic update rate which is gained by calculating the Euclidean distance between pixels. Experimental results and comparative study illustrate that the improved method can not only increase the accuracy of target detection by reducing the impact of illumination change effectively but also eliminate the ghost quickly.