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Fusing multi-cues description for partial-duplicate image retrieval.
- Source :
-
Journal of Visual Communication & Image Representation . Oct2014, Vol. 25 Issue 7, p1726-1731. 6p. - Publication Year :
- 2014
-
Abstract
- In traditional image retrieval, images are commonly represented using Bag-of-visual-Words (BoW) built from image local features. However, the lack of spatial and structural information suppresses its performance in applications. In this paper, we introduce a multi-cues description by fusing structural, content and spatial information for partial-duplicate image retrieval. Firstly, we propose a rotation-invariant Local Self-Similarity Descriptor (LSSD), which captures the internal structural layouts in the local textural self-similar regions around interest points. Then, based on the spatial pyramid model, we make use of both LSSD and SIFT to construct an image representation with multi-cues. Finally, we formulate the Semi-Relative Entropy as the distance metric. Comparison experiments with state-of-the-art methods on four popular databases show the efficiency and effectiveness of our approach. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10473203
- Volume :
- 25
- Issue :
- 7
- Database :
- Academic Search Index
- Journal :
- Journal of Visual Communication & Image Representation
- Publication Type :
- Academic Journal
- Accession number :
- 98578067
- Full Text :
- https://doi.org/10.1016/j.jvcir.2014.06.005