Statistical Models for Multidisciplinary Applications of Image Segmentation and Labelling

Jan Cornelis, Edgard Nyssen, Antonis Katartzis, Luc Van Kempen, Piet Boekaerts, Rudi Deklerck, Alexandru Salomie Ioan

Onderzoeksoutput: Conference paper

Samenvatting

Three classes of statistical techniques used to solve image segmentation and labelling problems are reviewed: (1) supervised and unsupervised pixel classification, (2) exploitation of the probability distribution map as a way to model image structure, (3) Markov random field modelling combined with MAP statistical classification. Diverse examples illustrate the potential of the three approaches that are described as generic methods belonging to a common framework for image segmentation/labelling
Originele taal-2English
TitelWCC 2000 - ICSP2000, World Computer Conference 2000 - 5th International Conference on Signal Processing Proceedings; Beijing, China III/III ; Aug 2000.
RedacteurenYuan Baozong, Tang Xiaofang
Uitgeverij16 th World Computer Conference 2000 (WCC 2000) - 5th International Conference on Signal Processing (ICSP2000) Proceedings, Vol. III, pp. 2103-2110, Beijing, China.
Pagina's2103-2110
Aantal pagina's8
VolumeIII
StatusPublished - aug 2000

Bibliografische nota

16 th World Computer Conference 2000 (WCC 2000) - 5th International Conference on Signal Processing (ICSP2000) Proceedings, Vol. III, pp. 2103-2110, Beijing, China.
Series editor: Yuan Baozong, Tang Xiaofang

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