Research on an improved watershed algorithm to image segmentation

We discuss image reconstruction and segmentation in an improved watershed algorithm by using a plug-in function in flooding process. This extends the watershed transform for segmentation by allowing the integration of a priori information about image objects into flooding simulation processes. This method can customize the initial seeding, region growing and stopping rules of the watershed flooding process according to user-defined functions incorporating prior information. We demonstrate that simple model functions operating on binary images can be effectively used to control all aspects of the flooding process. We proved that through simulation experiments, this method shows very low error rates compared with the recent literature and in comparisons with other algorithms, while being easily adapted to new imaging contexts.