TY - GEN
T1 - An improved fast face recognition algorithm based on adjacent pixel intensity difference quantization histogram
AU - Lee, Fei Fei
AU - Kotani, Koji
AU - Chen, Qiu
AU - Ohmi, Tadahiro
PY - 2008/12/1
Y1 - 2008/12/1
N2 - In this paper, we present an improved face recognition algorithm based on adjacent pixel intensity difference quantization (APIDQ) histogram method proposed by Kotani et al. [12]. We optimize the quantization method of APIDQ according to the maximum entropy principle (MEP), and determine the best parameters for APIDQ. Experimental results show maximum average recognition rate of 97.2 % for 400 images of 40 persons (10 images per person) from the publicly available AT&T face database.
AB - In this paper, we present an improved face recognition algorithm based on adjacent pixel intensity difference quantization (APIDQ) histogram method proposed by Kotani et al. [12]. We optimize the quantization method of APIDQ according to the maximum entropy principle (MEP), and determine the best parameters for APIDQ. Experimental results show maximum average recognition rate of 97.2 % for 400 images of 40 persons (10 images per person) from the publicly available AT&T face database.
KW - Adjacent pixel intensity difference quantization (APIDQ)
KW - Face recognition
KW - Maximum entropy principle (MEP)
UR - http://www.scopus.com/inward/record.url?scp=56749181685&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=56749181685&partnerID=8YFLogxK
U2 - 10.1109/ICWAPR.2008.4635796
DO - 10.1109/ICWAPR.2008.4635796
M3 - Conference contribution
AN - SCOPUS:56749181685
SN - 9781424422395
T3 - Proceedings of the 2008 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR
SP - 316
EP - 320
BT - Proceedings of the 2008 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR
T2 - 2008 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR
Y2 - 30 August 2008 through 31 August 2008
ER -