Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
The watershed transform: definitions, algorithms and parallelization strategies
Fundamenta Informaticae - Special issue on mathematical morphology
Yet Another Survey on Image Segmentation: Region and Boundary Information Integration
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Image segmentation evaluation: A survey of unsupervised methods
Computer Vision and Image Understanding
Robust fuzzy clustering-based image segmentation
Applied Soft Computing
Morphological segmentation of binary patterns
Pattern Recognition Letters
Medical image segmentation using genetic algorithms
IEEE Transactions on Information Technology in Biomedicine
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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.