Statistical region merging
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 bot...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1998. - 26(2004), 11 vom: 15. Nov., Seite 1452-8 |
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| Format: | Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2004
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Comparative Study Evaluation Study Journal Article Validation Study |
| Zusammenfassung: | 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 |
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| Beschreibung: | Date Completed 02.12.2004 Date Revised 10.12.2019 published: Print Citation Status MEDLINE |
| ISSN: | 0162-8828 |