Title :
An improved fast face recognition algorithm based on adjacent pixel intensity difference quantization histogram
Author :
Lee, Fei-fei ; Kotani, Koji ; Chen, Qiu ; Ohmi, Tadahiro
Author_Institution :
New Ind. Creation Hatchery Center, Tohoku Univ., Sendai
Abstract :
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.
Keywords :
face recognition; image resolution; maximum entropy methods; quantisation (signal); APIDQ; AT&T face database; MEP; adjacent pixel intensity difference quantization histogram; improved fast face recognition algorithm; maximum entropy principle; Entropy; Face recognition; Filtering; Histograms; Image databases; Image recognition; Low pass filters; Pixel; Quantization; Wavelet analysis; Adjacent pixel intensity difference quantization (APIDQ); Face recognition; Maximum entropy principle (MEP);
Conference_Titel :
Wavelet Analysis and Pattern Recognition, 2008. ICWAPR '08. International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-2238-8
Electronic_ISBN :
978-1-4244-2239-5
DOI :
10.1109/ICWAPR.2008.4635796
