The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.11 - November (2004 vol.26)
pp: 1452-1458
ABSTRACT
This paper explores a statistical basis for a process often described in computer vision: image segmentation by region merging following a particular order in the choice of regions. We exhibit a particular blend of algorithmics and statistics whose segmentation error is, as we show, limited from both the qualitative and quantitative standpoints. This approach can be efficiently approximated in linear time/space, leading to a fast segmentation algorithm tailored to processing images described using most common numerical pixel attribute spaces. The conceptual simplicity of the approach makes it simple to modify and cope with hard noise corruption, handle occlusion, authorize the control of the segmentation scale, and process unconventional data such as spherical images. Experiments on gray-level and color images, obtained with a short readily available C-code, display the quality of the segmentations obtained.
INDEX TERMS
Grouping, image segmentation.
CITATION
Richard Nock, Frank Nielsen, "Statistical Region Merging", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.26, no. 11, pp. 1452-1458, November 2004, doi:10.1109/TPAMI.2004.110
18 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool