Paper Info
Title
Localizing global descriptors for content-based image retrieval
Abstract
In this paper, we explore, extend and simplify the localization of the description ability of the well-established MPEG-7 (Scalable Colour Descriptor (SCD), Colour Layout Descriptor (CLD) and Edge Histogram Descriptor (EHD)) and MPEG-7-like (Color and Edge Directivity Descriptor (CEDD)) global descriptors, which we call the SIMPLE family of descriptors. Sixteen novel descriptors are introduced that utilize four different sampling strategies for the extraction of image patches to be used as points of interest. Designing with focused attention for content-based image retrieval tasks, we investigate, analyse and propose the preferred process for the definition of the parameters involved (point detection, description, codebook sizes and descriptors’ weighting strategies). The experimental results conducted on four different image collections reveal an astonishing boost in the retrieval performance of the proposed descriptors compared to their performance in their original global form. Furthermore, they manage to outperform common SIFT- and SURF-based approaches while they perform comparably, if not better, against recent state-of-the-art methods that base their success on much more complex data manipulation.
Year
DOI
Venue
2015
10.1186/s13634-015-0262-6
EURASIP Journal on Advances in Signal Processing
Keywords
Field
DocType
Image retrieval, Local features, SIMPLE descriptors
Scale-invariant feature transform,Computer vision,Histogram,Weighting,Computer science,Image retrieval,Artificial intelligence,Point of interest,Machine learning,Content-based image retrieval,Visual Word,Codebook
Journal
Volume
Issue
ISSN
2015
1
1687-6180
Citations 
PageRank 
References 
6
0.43
45
Authors
6
Name
Order
Citations
PageRank
C. Iakovidou1595.10
Nektarios Anagnostopoulos2191.80
a ch kapoutsis3223.26
Yiannis S. Boutalis438926.96
Mathias Lux566570.36
Savvas A. Chatzichristofis681044.88