Evaluation for Uncertain Image Classification and Segmentation

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dc.creatorMartin, Arnaud
dc.creatorLaanaya, Hicham
dc.creatorArnold-Bos, Andreas
dc.date2008-06-11
dc.date.accessioned2026-07-07T12:19:28Z
dc.date.available2026-07-07T12:19:28Z
dc.descriptionEach year, numerous segmentation and classification algorithms are invented or reused to solve problems where machine vision is needed. Generally, the efficiency of these algorithms is compared against the results given by one or many human experts. However, in many situations, the location of the real boundaries of the objects as well as their classes are not known with certainty by the human experts. Furthermore, only one aspect of the segmentation and classification problem is generally evaluated. In this paper we present a new evaluation method for classification and segmentation of image, where we take into account both the classification and segmentation results as well as the level of certainty given by the experts. As a concrete example of our method, we evaluate an automatic seabed characterization algorithm based on sonar images.
dc.identifierhttps://arxiv.org/abs/0806.1796
dc.identifierhttp://arxiv.org/abs/0806.1796
dc.identifierPattern Recognition 39, 11 (2006) 1987-1995
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/212762
dc.subjectComputer Vision and Pattern Recognition
dc.subjectArtificial Intelligence
dc.subjectI.4; I.5
dc.titleEvaluation for Uncertain Image Classification and Segmentation
dc.typetext

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