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Shape-based image retrieval using support vector machines, Fourier descriptors and self-organizing maps
- Source :
-
Information Sciences . Apr2007, Vol. 177 Issue 8, p1878-1891. 14p. - Publication Year :
- 2007
-
Abstract
- Abstract: Image retrieval based on image content has become an important topic in the fields of image processing and computer vision. In this paper, we present a new method of shape-based image retrieval using support vector machines (SVM), Fourier descriptors and self-organizing maps. A list of predicted classes for an input shape is obtained using the SVM, ranked according to their estimated likelihood. The best match of the image to the top-ranked class is then chosen by the minimum mean square error. The nearest neighbors can be retrieved from the self-organizing map of the class. We employ three databases of 99, 216, and 1045 shapes for our experiment, and obtain prediction accuracy of 90%, 96.7%, and 84.2%, respectively. Our method outperforms some existing shape-based methods in terms of speed and accuracy. [Copyright &y& Elsevier]
- Subjects :
- *IMAGE processing
*COMPUTER vision
*IMAGE retrieval
*MULTIMEDIA systems
Subjects
Details
- Language :
- English
- ISSN :
- 00200255
- Volume :
- 177
- Issue :
- 8
- Database :
- Academic Search Index
- Journal :
- Information Sciences
- Publication Type :
- Periodical
- Accession number :
- 23869003
- Full Text :
- https://doi.org/10.1016/j.ins.2006.10.008