Image Segmentation via Probabilistic Graph Matching

This paper presents an unsupervised and semi-automatic image segmentation approach where we formulate the segmentation as an inference problem based on unary and pairwise assignment probabilities computed using low-level image cues. The inference is solved via a probabilistic graph matching scheme,...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 25(2016), 10 vom: 14. Okt., Seite 4743-4752
1. Verfasser: Heimowitz, Ayelet (VerfasserIn)
Weitere Verfasser: Keller, Yosi
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2016
Zugriff auf das übergeordnete Werk:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:Journal Article
LEADER 01000naa a22002652 4500
001 NLM262429543
003 DE-627
005 20231224201725.0
007 cr uuu---uuuuu
008 231224s2016 xx |||||o 00| ||eng c
024 7 |a 10.1109/TIP.2016.2590832  |2 doi 
028 5 2 |a pubmed24n0874.xml 
035 |a (DE-627)NLM262429543 
035 |a (NLM)27416599 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Heimowitz, Ayelet  |e verfasserin  |4 aut 
245 1 0 |a Image Segmentation via Probabilistic Graph Matching 
264 1 |c 2016 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Revised 20.11.2019 
500 |a published: Print-Electronic 
500 |a Citation Status PubMed-not-MEDLINE 
520 |a This paper presents an unsupervised and semi-automatic image segmentation approach where we formulate the segmentation as an inference problem based on unary and pairwise assignment probabilities computed using low-level image cues. The inference is solved via a probabilistic graph matching scheme, which allows rigorous incorporation of low-level image cues and automatic tuning of parameters. The proposed scheme is experimentally shown to compare favorably with contemporary semi-supervised and unsupervised image segmentation schemes, when applied to contemporary state-of-the-art image sets 
650 4 |a Journal Article 
700 1 |a Keller, Yosi  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society  |d 1992  |g 25(2016), 10 vom: 14. Okt., Seite 4743-4752  |w (DE-627)NLM09821456X  |x 1941-0042  |7 nnns 
773 1 8 |g volume:25  |g year:2016  |g number:10  |g day:14  |g month:10  |g pages:4743-4752 
856 4 0 |u http://dx.doi.org/10.1109/TIP.2016.2590832  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 25  |j 2016  |e 10  |b 14  |c 10  |h 4743-4752