Title :
Gabor feature-based complete fisher discriminant framework for facial feature extraction
Author_Institution :
Sch. of Mech. Eng. & Autom., North Univ. of China, Taiyuan, China
Abstract :
In this paper, we propose a novel feature extraction approach using Gabor feature based complete fisher discriminant algorithm (GCFD). Four main steps are involved in the proposed GCFD: (i) Gabor features of different scales and orientations are extracted by the convolution of Gabor filter bank and original gray images; (ii) Complete fisher discriminant algorithm (CFD) is used for feature dimensionality reduction and to extract all discrimination information; (iii) Feature fusion algorithm and Euclidean distance based nearest neighbor classifier are finally used for classification. (iv)Simulation results show the effectiveness of our proposed GCFD.
Keywords :
Gabor filters; feature extraction; CFD; Euclidean distance based nearest neighbor classifier; Gabor feature based complete fisher discriminant algorithm; Gabor filter bank; complete fisher discriminant algorithm; convolution method; discrimination information; facial feature extraction; feature dimensionality reduction; feature extraction approach; feature fusion algorithm; gray images; Computational fluid dynamics; Data mining; Face recognition; Facial features; Feature extraction; Kernel; Linear discriminant analysis; Null space; Pixel; Scattering; Complete Fisher Discriminant Analysis (CFD); Gabor filter; feature extraction;
Conference_Titel :
Wireless Communications & Signal Processing, 2009. WCSP 2009. International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4856-2
Electronic_ISBN :
978-1-4244-5668-0
DOI :
10.1109/WCSP.2009.5371732