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Proceedings Paper

The research of a video segmentation algorithm based on image fusion in the wavelet domain
Author(s): Fan Yang; Jing Li; Shun-hua Xu; Guo-feng Pan
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Paper Abstract

For the shortcoming of a large number of computational complexity and time consuming of traditional Spatio-Temporal Fusion Segmentation Algorithm, an automatic video object segmentation algorithm based on the Spatio-Temporal Fusion in wavelet domain is proposed. The temporal segmentation in wavelet domain, firstly, wavelet transforms adjacent 3 frame image and uses a sub-band bi-directional difference method, then makes the two differential images fuse. In the low-frequency sub-band, choose options for integration strategies or a weighted average fusion strategy by setting the matching threshold; In the high-frequency sub-band, using the pixel that has the larger absolute value Strategy, which can enhance the edge information of the image and derive more movable information. Secondly, the spatial segmentation performs the improved watershed segmentation algorithm with the gradient and combination of internal and external constraints watershed segmentation algorithm in wavelet domain to resolve the issue of over-segmentation. Meanwhile, mark and extract sub-block segmentation region as the spatial segmentation template of the wavelet domain. The spatio-temporal fusion segmentation template in wavelet sub-band can be derived by mapping the spatial segmentation to the temporal one, statistics the probability of '1', which is belong to video object region (compose of '0' and '1') and then making them fusion in wavelet domain. Then after 'and' operation with the current frame and wavelet reverse transform, the outcome of the final segmentation is derived. The experimental results have shown that the method has a good result, i.e. the rooms' numbers of the improved spatial segmentation are 2~3 times less than traditional method, the processing speed is 8~9 times advanced averagely for each frame and the computational complexity of template operation is greatly reduced.

Paper Details

Date Published: 12 October 2010
PDF: 7 pages
Proc. SPIE 7659, 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Smart Structures and Materials in Manufacturing and Testing, 765918 (12 October 2010); doi: 10.1117/12.864536
Show Author Affiliations
Fan Yang, Hebei Univ. of Technology (China)
Jing Li, Hebei Univ. of Technology (China)
Shun-hua Xu, Hebei Univ. of Technology (China)
Guo-feng Pan, Hebei Univ. of Technology (China)

Published in SPIE Proceedings Vol. 7659:
5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Smart Structures and Materials in Manufacturing and Testing
Xiangang Luo; Georg von Freymann, Editor(s)

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