Abstract
In this paper, an efficient method based on singular values and potential-field representation is proposed for face-image retrieval. Firstly, we theoretically prove that the leading singular values of an image can be used as a rotation-shift-scale-invariant global feature. Then, for the feature-extraction stage, we exploit these special properties of the singular values to devise a compact, global feature for face-image representation. We also use the singular values of the potential field derived from edge gradients to enhance the retrieval performance. Experimental results based on the GTAV database show that the use of singular values as rotation-shift-scale-invariant global features is able to produce plausible retrieval results.
| Original language | English |
|---|---|
| Pages (from-to) | 9-15 |
| Number of pages | 7 |
| Journal | Signal Processing |
| Volume | 100 |
| DOIs | |
| Publication status | Published - 1 Jul 2014 |
Keywords
- Face-image retrieval
- Potential-field representation
- Rotation-shift-scale-invariant feature
- Singular values
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering