Predictive watershed: a fast watershed algorithm for video segmentation

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.