Multi-object motion segmentation in image sequence based on cellular neural networks

Shukai Meng; Yu Long Mo

doi:10.1117/12.481613

30 August 2002 Multi-object motion segmentation in image sequence based on cellular neural networks

Shukai Meng, Yu Long Mo

Proceedings Volume 4925, Electronic Imaging and Multimedia Technology III; (2002) https://doi.org/10.1117/12.481613
Event: Photonics Asia, 2002, Shanghai, China

Abstract

In this paper, a new approach to multi-objects motion segmentation in image sequence based on cellular neural networks (CNN) is proposed. As the core ofthis approach, difference merged image algorithm is presented. In order to realize the algorithm, the reverse CNN template, the addition CNN template, the patch-filled CNN template and the composition CNN template are presented and designed. For based on CNN, this approach can improve the capability of real-time in motion segmentation. And on the other hand, because difference merged image algorithm we improved is directly used in gray-scale image processing instead of in binary image processing, it can get more information of motion and increase the accuracy of segmentation. Finally, we show the experiment results, which prove that this approach has a good capability in multi-objects motion segmentation.

Citation Download Citation

Shukai Meng and Yu Long Mo "Multi-object motion segmentation in image sequence based on cellular neural networks", Proc. SPIE 4925, Electronic Imaging and Multimedia Technology III, (30 August 2002); https://doi.org/10.1117/12.481613

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