DocumentCode
2484713
Title
On segmentation evaluation metrics and region counts
Author
Hanbury, Allan ; Stöttinger, Julian
Author_Institution
Inst. of Comput.-Aided Autom., Vienna Univ. of Technol., Vienna
fYear
2008
fDate
8-11 Dec. 2008
Firstpage
1
Lastpage
4
Abstract
Five image segmentation algorithms are evaluated: mean shift, normalised cuts, efficient graph-based segmentation, hierarchical watershed, and waterfall. The evaluation is done using three evaluation metrics: probabilistic Rand index, global consistency error, and boundary precision-recall. We examine region-based metrics as a function of the number of regions produced by an algorithm. This allows new insights into algorithms and evaluation metrics to be gained.
Keywords
graph theory; image segmentation; probability; boundary precision-recall; global consistency error; graph-based segmentation; hierarchical watershed; image segmentation algorithm; mean shift; normalised cut; probabilistic Rand index; region count; segmentation evaluation metric; waterfall; Automation; Biomedical imaging; Computer errors; Computer vision; Humans; Image analysis; Image segmentation; Labeling; Pixel; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location
Tampa, FL
ISSN
1051-4651
Print_ISBN
978-1-4244-2174-9
Electronic_ISBN
1051-4651
Type
conf
DOI
10.1109/ICPR.2008.4761582
Filename
4761582
Link To Document