Face Detection using Gabor Wavelets and Neural Networks
This paper proposes new hybrid approaches for face
recognition. Gabor wavelets representation of face images is an
effective approach for both facial action recognition and face
identification. Perform dimensionality reduction and linear
discriminate analysis on the down sampled Gabor wavelet faces can
increase the discriminate ability. Nearest feature space is extended to
various similarity measures. In our experiments, proposed Gabor
wavelet faces combined with extended neural net feature space
classifier shows very good performance, which can achieve 93 %
maximum correct recognition rate on ORL data set without any preprocessing
step.
[1] R. W. Chellappa, C.L.; Sirohey, S., "Human and machine recognition of
faces: a survey," Proceedings of the IEEE, vol. 83, pp. 705-741, 1995.
[2] M. A. Turk and A. P. Pentland, "Face recognition using eigenfaces,"
presented at Proceedings CVPR -91., 1991. [3] P. N. Belhumeur, J. P.
Hespanha, and D. J. Kriegman, "Eigenfaces vs. Fisherfaces: recognition
using class specific linear projection," PAMI, IEEE Trans. on, vol. 19,
1997.
[3] A. M. Martinez and A. C. Kak, "PCA versus LDA," PAMI, IEEE Trans.
on, vol. 23, pp. 228-233, 2001.
[4] C. Liu and H. Wechsler, "Gabor feature based classification using the
enhanced fisher linear discriminant model for face recognition," Image
Processing, IEEE Trans. on, vol. 11, pp. 467-476, 2002.
[5] S. Z. Li and J. Lu, "Face recognition using the nearest feature line
method," Neural Networks, IEEE Trans. on, vol. 10, pp. 439-443, 1999.
[6] J.-T. Chien and C.-C. Wu, "Discriminant waveletfaces and nearest
feature classifiers for face recognition," PAMI, IEEE Trans. on, vol. 24,
pp. 1644-1649, 2002.
[7] ORL web site: www.uk.research.att.com/facedatabase.html.
[8] T. S. Lee, "Image representation using 2D Gabor wavelets," PAMI,
IEEE Trans. on, vol. 18, pp. 959-971, 1996.
[9] M. Lades, J. C. Vorbruggen, J. Buhmann, J. Lange, C. von der
Malsburg, R. P. Wurtz, and W. Konen, "Distortion invariant object
recognition in the dynamic link architecture," Computers, IEEE Trans.
on, vol. 42, pp. 300-311, 1993.
[1] R. W. Chellappa, C.L.; Sirohey, S., "Human and machine recognition of
faces: a survey," Proceedings of the IEEE, vol. 83, pp. 705-741, 1995.
[2] M. A. Turk and A. P. Pentland, "Face recognition using eigenfaces,"
presented at Proceedings CVPR -91., 1991. [3] P. N. Belhumeur, J. P.
Hespanha, and D. J. Kriegman, "Eigenfaces vs. Fisherfaces: recognition
using class specific linear projection," PAMI, IEEE Trans. on, vol. 19,
1997.
[3] A. M. Martinez and A. C. Kak, "PCA versus LDA," PAMI, IEEE Trans.
on, vol. 23, pp. 228-233, 2001.
[4] C. Liu and H. Wechsler, "Gabor feature based classification using the
enhanced fisher linear discriminant model for face recognition," Image
Processing, IEEE Trans. on, vol. 11, pp. 467-476, 2002.
[5] S. Z. Li and J. Lu, "Face recognition using the nearest feature line
method," Neural Networks, IEEE Trans. on, vol. 10, pp. 439-443, 1999.
[6] J.-T. Chien and C.-C. Wu, "Discriminant waveletfaces and nearest
feature classifiers for face recognition," PAMI, IEEE Trans. on, vol. 24,
pp. 1644-1649, 2002.
[7] ORL web site: www.uk.research.att.com/facedatabase.html.
[8] T. S. Lee, "Image representation using 2D Gabor wavelets," PAMI,
IEEE Trans. on, vol. 18, pp. 959-971, 1996.
[9] M. Lades, J. C. Vorbruggen, J. Buhmann, J. Lange, C. von der
Malsburg, R. P. Wurtz, and W. Konen, "Distortion invariant object
recognition in the dynamic link architecture," Computers, IEEE Trans.
on, vol. 42, pp. 300-311, 1993.
@article{"International Journal of Electrical, Electronic and Communication Sciences:58837", author = "Hossein Sahoolizadeh and Davood Sarikhanimoghadam and Hamid Dehghani", title = "Face Detection using Gabor Wavelets and Neural Networks", abstract = "This paper proposes new hybrid approaches for face
recognition. Gabor wavelets representation of face images is an
effective approach for both facial action recognition and face
identification. Perform dimensionality reduction and linear
discriminate analysis on the down sampled Gabor wavelet faces can
increase the discriminate ability. Nearest feature space is extended to
various similarity measures. In our experiments, proposed Gabor
wavelet faces combined with extended neural net feature space
classifier shows very good performance, which can achieve 93 %
maximum correct recognition rate on ORL data set without any preprocessing
step.", keywords = "Face detection, Neural Networks, Multi-layer
Perceptron, Gabor wavelets.", volume = "2", number = "9", pages = "1980-3", }