A new segmentation method is presented. The watershed transformation is initially computed starting from all seeds detected as regional minima in the gradient image and a digging cost is associated to each pair of adjacent regions. Digging is performed for each pair of adjacent regions for which the cost is under a threshold, whose value is computed automatically, so originating a reduced set of seeds. Watershed transformation and digging are repeatedly applied, until no more seeds are filtered out. Then, region merging is accomplished, based on the size of adjacent regions. © 2011 Springer-Verlag.
CITATION STYLE
Frucci, M., & Di Baja, G. S. (2011). A new algorithm for image segmentation via watershed transformation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6979 LNCS, pp. 168–177). https://doi.org/10.1007/978-3-642-24088-1_18
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