dc.contributor.author | Vassou, S. A. | |
dc.contributor.author | Anagnostopoulos, N. | |
dc.contributor.author | Amanatiadis, A. | |
dc.contributor.author | Chatzichristofis, Savvas A. | |
dc.contributor.author | Christodoulou, Klitos | |
dc.date.accessioned | 2018-03-19T13:04:27Z | |
dc.date.available | 2018-03-19T13:04:27Z | |
dc.date.issued | 2018-03-01 | |
dc.identifier.issn | 1573-7721 | |
dc.identifier.uri | http://hdl.handle.net/11728/10590 | |
dc.description.abstract | Low level features play a significant role in image retrieval. Image moments can effectively represent global information of image content while being invariant under translation, rotation, and scaling. This paper presents CoMo: a moment based composite and compact low-level descriptor that can be used effectively for image retrieval and robot vision tasks. The proposed descriptor is evaluated by employing the Bag-of-Visual-Words representation over various well-known benchmarking image databases. The findings from the experimental evaluation provide strong evidence of high and competitive retrieval performance against various state-of-the-art local descriptors. | en_UK |
dc.language.iso | en | en_UK |
dc.publisher | Springer International Publishing | en_UK |
dc.relation.ispartofseries | Multimedia Tools and Applications; | |
dc.rights | Springer International Publishing | en_UK |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en_UK |
dc.subject | Content based image retrieval | en_UK |
dc.subject | Low level features | en_UK |
dc.subject | Compact composite descriptors | en_UK |
dc.title | CoMo: a scale and rotation invariant compact composite moment-based descriptor for image retrieval | en_UK |
dc.type | Article | en_UK |
dc.affiliation | | |
dc.doi | https://doi.org/10.1007/s11042-018-5854-3 | en_UK |