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Semi-supervised Probabilistic Relaxation for Image Segmentation

Authors :
Henry Anaya-Sánchez
Filiberto Pla
Adolfo Martínez-Usó
José Martínez Sotoca
Source :
Pattern Recognition and Image Analysis ISBN: 9783642212567, IbPRIA
Publication Year :
2011
Publisher :
Springer Berlin Heidelberg, 2011.

Abstract

In this paper, a semi-supervised approach based on probabilistic relaxation theory is presented. Focused on image segmentation, the presented technique combines two desirable properties; a very small number of labelled samples is needed and the assignment of labels is consistently performed according to our contextual information constraints. Our proposal has been tested on medical images from a dermatology application with quite promising preliminary results. Not only the unsupervised accuracies have been improved as expected but similar accuracies to other semi-supervised approach have been obtained using a considerably reduced number of labelled samples. Results have been also compared with other powerful and well-known unsupervised image segmentation techniques, improving significantly their results.

Details

ISBN :
978-3-642-21256-7
ISBNs :
9783642212567
Database :
OpenAIRE
Journal :
Pattern Recognition and Image Analysis ISBN: 9783642212567, IbPRIA
Accession number :
edsair.doi...........c58c5bed7040ba64116e293173059b68