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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