Abstract
In this paper we propose a geometry-based image retrieval scheme that makes use of projectively invariant features. Cross-ratio (CR) is an invariant feature under projective transformations for collinear points. We compute the CRs of point sets in quadruplets and the CR histogram is used as the feature for retrieval purposes. Being a geometric feature, it allows us to retrieve similar images irrespective of view point and illumination changes. We can retrieve the same building even if the facade has undergone a fresh coat of paints! Color and textural features can also be included, if desired. Experimental results show a favorably very good retrieval accuracy when tested on an image database of size 4000. The method is very effective in retrieving images having man-made objects rich in polygonal structures like buildings, rail tracks, etc.
Original language | English |
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Pages (from-to) | 296-308 |
Number of pages | 13 |
Journal | Pattern Recognition |
Volume | 40 |
Issue number | 1 |
Early online date | 5 Jul 2006 |
DOIs | |
Publication status | Published - 31 Jan 2007 |
Keywords
- Cross-ratio
- Cross-ratio histogram
- Motif cooccurence matrix
- Perspective transformation
- Precision
- Projective invariance
- Recall
ASJC Scopus subject areas
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence