A methodology for hierarchical image segmentation evaluation



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Rodríguez, Juan Tinguaro and Guada, C. and Gomez, D. and Yáñez, Javier and Montero, Javier (2016) A methodology for hierarchical image segmentation evaluation. In Information Processing and Management of Uncertainty in Knowledge-Based Systems. Communications in Computer and Information Science, I (610). Springer, pp. 635-647. ISBN 978-3-319-40596-4

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Official URL: http://dx.doi.org/10.1007/978-3-319-40596-4_53


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.

Item Type:Book Section
Additional Information:

16th International Conference, IPMU 2016
Eindhoven, The Netherlands, June 20–24, 2016

Uncontrolled Keywords:Edge-based image segmentation evaluation; Hierarchical network clustering; Image segmentation.
Subjects:Sciences > Mathematics > Mathematical statistics
ID Code:39024
Deposited On:13 Sep 2016 08:54
Last Modified:02 Feb 2017 11:20

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