| Full text | |
| Author(s): |
Ferreira, C. D.
;
Santos, J. A.
;
Torres, R. da S.
;
Goncalves, M. A.
;
Rezende, R. C.
;
Fan, Weiguo
Total Authors: 6
|
| Document type: | Journal article |
| Source: | PATTERN RECOGNITION LETTERS; v. 32, n. 1, p. 11-pg., 2011-01-01. |
| Abstract | |
This paper presents two content-based image retrieval frameworks with relevance feedback based on genetic programming. The first framework exploits only the user indication of relevant images. The second one considers not only the relevant but also the images indicated as non-relevant. Several experiments were conducted to validate the proposed frameworks. These experiments employed three different image databases and color, shape, and texture descriptors to represent the content of database images. The proposed frameworks were compared, and outperformed six other relevance feedback methods regarding their effectiveness and efficiency in image retrieval tasks. (C) 2010 Elsevier B.V. All rights reserved. (AU) | |
| FAPESP's process: | 07/53607-9 - Semi-automatic recognition and vectorization of regions in remote sensing images |
| Grantee: | Jefersson A dos Santos |
| Support Opportunities: | Scholarships in Brazil - Master |
| FAPESP's process: | 09/18438-7 - Large-scale classification and retrieval for complex data |
| Grantee: | Ricardo da Silva Torres |
| Support Opportunities: | Regular Research Grants |