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Erschienen in:
2016 | OriginalPaper | Buchkapitel
A Methodology for Hierarchical Image Segmentation Evaluation
verfasst von : J. Tinguaro Rodríguez, Carely Guada, Daniel Gómez, Javier Yáñez, Javier Montero
Erschienen in: Information Processing and Management of Uncertainty in Knowledge-Based Systems
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Abstract
This paper proposes a method to evaluate hierarchical image segmentation procedures, in order to enable comparisons between different hierarchical algorithms and of these with other (non-hierarchical) segmentation techniques (as well as with edge detectors) to be made. The proposed method builds up on the edge-based segmentation evaluation approach by considering a set of reference human segmentations as a sample drawn from the population of different levels of detail that may be used in segmenting an image. Our main point is that, since a hierarchical sequence of segmentations approximates such population, those segmentations in the sequence that best capture each human segmentation level of detail should provide the basis for the evaluation of the hierarchical sequence as a whole. A small computational experiment is carried out to show the feasibility of our approach.