Number of the records: 1
Unsupervised Hierarchical Weighted Multi-Segmenter
- 1.
SYSNO ASEP 0327029 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Unsupervised Hierarchical Weighted Multi-Segmenter Title Neřízená hierarchická vážená multi-segmentační metoda Author(s) Haindl, Michal (UTIA-B) RID, ORCID
Mikeš, Stanislav (UTIA-B) RID
Pudil, Pavel (UTIA-B) RIDSource Title Multiple Classifier Systems, LNCS 5519. - Berlin Heidelberg : Springer, 2009 / Benediktsson J.A. ; Kittler J. ; Roli F. - ISSN 0302-9743 - ISBN 3-642-02325-8 Pages s. 272-282 Number of pages 11 s. Publication form www - www Action Multiple Classifier Systems Event date 10.06.2009-12.06.2009 VEvent location Reykjavik Country IS - Iceland Event type WRD Language eng - English Country DE - Germany Keywords unsupervised image segmentation Subject RIV BD - Theory of Information R&D Projects 1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) GA102/08/0593 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z10750506 - UTIA-B (2005-2011) Annotation An unsupervised multi-spectral, multi-resolution, multiple-segmenter for textured images with unknown number of classes is presented. The segmenter is based on a weighted combination of several unsupervised segmentation results, each in different resolution, using the modified sum rule. Multi-spectral textured image mosaics are locally represented by four causal directional multi-spectral random field models recursively evaluated for each pixel. The single-resolution segmentation part of the algorithm is based on the underlying Gaussian mixture model and starts with an over segmented initial estimation which is adaptively modified until the optimal number of homogeneous texture segments is reached. The performance of the presented method is extensively tested on the Prague segmentation benchmark using the commonest segmentation criteria and compares favourably with several leading alternative image segmentation methods. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2010
Number of the records: 1