Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/10938
Title: | CoMo: a scale and rotation invariant compact composite moment-based descriptor for image retrieval | Authors: | Vassou, Sotiris A. Anagnostopoulos, Nektarios Christodoulou, Klitos Amanatiadis, Angelos Chatzichristofis, Savvas A. |
Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | Compact composite descriptors;Content based image retrieval;Low level features | Issue Date: | 1-Feb-2019 | Source: | Multimedia Tools and Applications, 2019, vol. 78, no. 3, pp. 2765-2788 | Volume: | 78 | Issue: | 3 | Start page: | 2765 | End page: | 2788 | Journal: | Multimedia Tools and Applications | 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. | URI: | https://hdl.handle.net/20.500.14279/10938 | ISSN: | 13807501 | DOI: | 10.1007/s11042-018-5854-3 | Rights: | © Springer | Type: | Article | Affiliation : | Cyprus University of Technology Microsoft Neapolis University Pafos Democritus University of Thrace |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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