Name
Abstract | ||
|---|---|---|
The watershed transform is a key operator in video segmentation algorithms. However, the computation load of watershed transform is too large for real-time applications. In this paper, a new fast watershed algorithm, named P-watershed, for image sequence segmentation is proposed. By utilizing the temporal coherence property of the video signal, this algorithm updates watersheds instead of searching watersheds in every frame, which can avoid a lot of redundant computation. The watershed process can be accelerated, and the segmentation results are almost the same as those of conventional algorithms. Moreover, an intra-inter watershed scheme (IP-watershed) is also proposed to further improve the results. Experimental results show that this algorithm can save 20%-50% computation without degrading the segmentation results. This algorithm can be combined with any video segmentation algorithm to give more precise segmentation results. An example is also shown by combining a background registration and change-detection-based segmentation algorithm with P-Watershed. This new video segmentation algorithm can give accurate object masks with acceptable computation complexity. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/TCSVT.2003.811605 | IEEE Trans. Circuits Syst. Video Techn. |
Keywords | Field | DocType |
new fast watershed algorithm,conventional algorithm,video segmentation algorithm,precise segmentation result,intra-inter watershed scheme,watershed process,predictive watershed,segmentation result,new video segmentation algorithm,image sequence segmentation,change-detection-based segmentation algorithm,prediction algorithms,real time applications,image registration,degradation,sorting,change detection,image segmentation,watershed transform,indexing terms,computational complexity,acceleration | Computer vision,Scale-space segmentation,Pattern recognition,Segmentation,Computer science,Segmentation-based object categorization,Image segmentation,Watershed,Artificial intelligence,Image registration,Computational complexity theory,Computation | Journal |
Volume | Issue | ISSN |
13 | 5 | 1051-8215 |
Citations | PageRank | References |
32 | 1.43 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shao-Yi Chien | 1 | 1603 | 154.48 |
| Yu-Wen Huang | 2 | 1116 | 114.02 |
| Liang-Gee Chen | 3 | 3637 | 383.22 |