The week's pick
Reseach Article
Features Reduction using Wavelet and Discriminative Common Vector and Recognizing Faces using RBF
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 74 - Number 5 |
| Year of Publication: 2013 |
| Authors: T. Kathirvalavakumar, J. Jebakumari Beulah Vasanthi |
10.5120/12884-9796
|
T. Kathirvalavakumar, J. Jebakumari Beulah Vasanthi . Features Reduction using Wavelet and Discriminative Common Vector and Recognizing Faces using RBF. International Journal of Computer Applications. 74, 5 ( July 2013), 40-46. DOI=10.5120/12884-9796
Abstract
Recognizing patterns by radial basis function network using reduced features obtained through wavelet transformation and discriminative common vector is proposed. Wavelet coefficients obtained after applying wavelet transformations on input patterns, are used to extract significant features from the samples. The discriminative common vectors are extracted using the within-class scatter matrix method from the wavelet coefficients. The discriminative common vectors are classified using radial basis function network. The proposed system is validated using three face databases such as ORL, The Japanese Female Facial Expression (JAFFE) and Essex Face database. The proposed method reduces the number of features, minimizes the computational complexity and provides better recognition rates.
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