dc.contributor.author | Chatzichristofis, Savvas A. | |
dc.contributor.author | Boutalis, Yiannis S. | |
dc.contributor.author | Arampatzis, Avi | |
dc.date.accessioned | 2017-10-30T10:36:47Z | |
dc.date.available | 2017-10-30T10:36:47Z | |
dc.date.issued | 2011 | |
dc.identifier.issn | 1942-2644 | |
dc.identifier.uri | http://hdl.handle.net/11728/10171 | |
dc.description.abstract | In this paper, we are evaluating several accelerating
techniques for content-based image retrieval, suitable for
the Color and Edge Directivity Descriptor (CEDD). To date,
the experimental results presented in the literature have shown
that the CEDD achieves high rates of successful retrieval in
benchmark image databases. Although its storage requirements
are minimal, only 54 bytes per image, the time required for
retrieval may be practically too long when searching on large
databases. The proposed technique utilizes the Binary Haar
Wavelet Transform in order to extract from the CEDD a
smaller and more efficient descriptor, with a size of less than
2 bytes per image, speeding up retrieval from large image
databases. This descriptor describes the CEDD, but not necessarily
the image from which it is extracted. The effectiveness
of the proposed method is demonstrated through experiments
performed on several known benchmarking databases. | en_UK |
dc.language.iso | en | en_UK |
dc.publisher | IARIA | en_UK |
dc.relation.ispartofseries | International Journal on Advances in Networks and Services;Volume 4, no 1 & 2 | |
dc.rights | © Copyright by authors, Published under agreement with IARIA | en_UK |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en_UK |
dc.subject | CEDD | en_UK |
dc.subject | Binary Haar Wavelet Transform | en_UK |
dc.subject | Content Based Image Retrieval | en_UK |
dc.title | Fast Retrieval from Image Databases via Binary Haar Wavelet Transform on the Color and Edge Directivity Descriptor | en_UK |
dc.type | Article | en_UK |