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Measures and meta-measures for the supervised evaluation of image segmentation
Pont Tuset, Jordi; Marqués Acosta, Fernando
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo
This paper tackles the supervised evaluation of image segmentation algorithms. First, it surveys and structures the measures used to compare the segmentation results with a ground truth database, and proposes a new measure: the precision-recall for objects and parts. To compare the goodness of these measures, it defines three quantitative meta-measures involving six state of the art segmentation methods. The meta-measures consist in assuming some plausible hypotheses about the results and assessing how well each measure reflects these hypotheses. As a conclusion, this paper proposes the precision-recall curves for boundaries and for objects-and-parts as the tool of choice for the supervised evaluation of image segmentation. We make the datasets and code of all the measures publicly available.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
Image segmentation
Image processing -- Digital techniques
Benchmark testing
Context
Current measurement
Databases
Image segmentation
Object detection
Partitioning algorithms
Imatges -- Processament -- Tècniques digitals
Vídeo digital
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
IEEE Computer Society Publications
         

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