Publication | Closed Access
From contours to regions: An empirical evaluation
442
Citations
43
References
2009
Year
Hierarchical SegmentationFeature DetectionEngineeringStatistical Shape AnalysisShape AnalysisGeneric Grouping AlgorithmImage Sequence AnalysisHierarchical SegmentationsImage AnalysisData SciencePattern RecognitionEdge DetectionComputational GeometryStatisticsComputational AnatomyGeometric ModelingMachine VisionMedical ImagingGeographyEmpirical EvaluationDeep LearningMedical Image ComputingComputer VisionNatural SciencesImage Segmentation
We propose a generic grouping algorithm that constructs a hierarchy of regions from the output of any contour detector. Our method consists of two steps, an oriented watershed transform (OWT) to form initial regions from contours, followed by construction of an ultra-metric contour map (UCM) defining a hierarchical segmentation. We provide extensive experimental evaluation to demonstrate that, when coupled to a high-performance contour detector, the OWT-UCM algorithm produces state-of-the-art image segmentations. These hierarchical segmentations can optionally be further refined by user-specified annotations.
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