Publication: Object-based image labeling through learning by example and multi-level segmentation
dc.contributor.coauthor | Xu, Y | |
dc.contributor.coauthor | Duygulu, P | |
dc.contributor.coauthor | Saber, E | |
dc.contributor.coauthor | Yarman-Vural, FT | |
dc.contributor.department | Department of Electrical and Electronics Engineering | |
dc.contributor.kuauthor | Tekalp, Ahmet Murat | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.date.accessioned | 2024-11-09T22:55:57Z | |
dc.date.issued | 2003 | |
dc.description.abstract | We propose a method for automatic extraction and labeling of semantically meaningful image objects using "learning by example" and threshold-free multi-level image segmentation. The proposed method scans through images, each of which is pre-segmented into a hierarchical uniformity tree, to seek and label objects that are similar to an example object presented by the user. By representing images with stacks of multi-level segmentation maps, objects can be extracted in the segmentation map level with adequate detail. Experiments have shown that the proposed multi-level image segmentation results in significant reduction in computation complexity for object extraction and labeling (compared to a single fine-level segmentation) by avoiding unnecessary tests of combinations in finer levels. The multi-level segmentation-based approach also achieves better accuracy in detection and labeling of small objects. | |
dc.description.indexedby | WOS | |
dc.description.indexedby | Scopus | |
dc.description.issue | 6 | |
dc.description.openaccess | NO | |
dc.description.publisherscope | International | |
dc.description.sponsoredbyTubitakEu | N/A | |
dc.description.volume | 36 | |
dc.identifier.doi | 10.1016/S0031-3203(02)00250-9 | |
dc.identifier.issn | 0031-3203 | |
dc.identifier.quartile | Q1 | |
dc.identifier.scopus | 2-s2.0-0242600663 | |
dc.identifier.uri | https://doi.org/10.1016/S0031-3203(02)00250-9 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/7277 | |
dc.identifier.wos | 181591400013 | |
dc.keywords | Object-based image labeling | |
dc.keywords | Multi-level segmentation | |
dc.keywords | Hierarchical content description | |
dc.keywords | Learning by example retrieval | |
dc.keywords | Color | |
dc.keywords | Databases | |
dc.keywords | Information | |
dc.keywords | Semantics | |
dc.language.iso | eng | |
dc.publisher | Pergamon-Elsevier Science Ltd | |
dc.relation.ispartof | Pattern Recognition | |
dc.subject | Computer Science | |
dc.subject | Artificial intelligence | |
dc.subject | Electrical electronics engineering | |
dc.title | Object-based image labeling through learning by example and multi-level segmentation | |
dc.type | Journal Article | |
dspace.entity.type | Publication | |
local.contributor.kuauthor | Tekalp, Ahmet Murat | |
local.publication.orgunit1 | College of Engineering | |
local.publication.orgunit2 | Department of Electrical and Electronics Engineering | |
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