Abstract

This study presents an efficient approach for automatic face recognition based on Spectral Graph Wavelet Theory (SGWT). SGWT is analogous to wavelet transform and the transform functions are defined on the vertices of a weighted graph. The given face image is decomposed by SGWT at first. The energies of obtained sub-bands are fused together and considered as feature vector for the corresponding image. The performance of proposed system is analyzed on ORL face database using nearest neighbor classifier. The face images used in this study has variations in pose, expression and facial details. The results indicate that the proposed system based on SGWT is better than wavelet transform and 94% recognition accuracy is achieved.

Keywords:

Chebyshev polynomial , face recognition , nearest neighbor classifier, spectral graph wavelet theory,

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Competing interests

The authors have no competing interests.

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The authors have no competing interests.