TY - GEN
T1 - Gender recognition from face images with dyadic wavelet transform and local binary pattern
AU - Ullah, Ihsan
AU - Hussain, Muhammad
AU - Aboalsamh, Hatim
AU - Muhammad, Ghulam
AU - Mirza, Anwar M.
AU - Bebis, George
PY - 2012
Y1 - 2012
N2 - Gender recognition from facial images plays an important role in biometric applications. We investigated Dyadic wavelet Transform (DyWT) and Local Binary Pattern (LBP) for gender recognition in this paper. DyWT is a multi-scale image transformation technique that decomposes an image into a number of subbands which separate the features at different scales. On the other hand, LBP is a texture descriptor and represents the local information in a better way. Also, DyWT is a kind of translation invariant wavelet transform that has better potential for detection than DWT (Discrete Wavelet Transform). Employing both DyWT and LBP, we propose a new technique of face representation that performs better for gender recognition. DyWT is based on spline wavelets, we investigated a number of spline wavelets for finding the best spline wavelets for gender recognition. Through a large number of experiments performed on FERET database, we report the best combination of parameters for DyWT and LBP that results in maximum accuracy. The proposed system outperforms the stat-of-the-art gender recognition approaches; it achieves a recognition rate of 99.25% on FERET database.
AB - Gender recognition from facial images plays an important role in biometric applications. We investigated Dyadic wavelet Transform (DyWT) and Local Binary Pattern (LBP) for gender recognition in this paper. DyWT is a multi-scale image transformation technique that decomposes an image into a number of subbands which separate the features at different scales. On the other hand, LBP is a texture descriptor and represents the local information in a better way. Also, DyWT is a kind of translation invariant wavelet transform that has better potential for detection than DWT (Discrete Wavelet Transform). Employing both DyWT and LBP, we propose a new technique of face representation that performs better for gender recognition. DyWT is based on spline wavelets, we investigated a number of spline wavelets for finding the best spline wavelets for gender recognition. Through a large number of experiments performed on FERET database, we report the best combination of parameters for DyWT and LBP that results in maximum accuracy. The proposed system outperforms the stat-of-the-art gender recognition approaches; it achieves a recognition rate of 99.25% on FERET database.
UR - https://www.scopus.com/pages/publications/84866727034
U2 - 10.1007/978-3-642-33191-6_40
DO - 10.1007/978-3-642-33191-6_40
M3 - Conference Publication
AN - SCOPUS:84866727034
SN - 9783642331909
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 409
EP - 419
BT - Advances in Visual Computing - 8th International Symposium, ISVC 2012, Revised Selected Papers
T2 - 8th International Symposium on Visual Computing, ISVC 2012
Y2 - 16 July 2012 through 18 July 2012
ER -