
Proceedings Paper
An integrated multispectral face recognition systemFormat | Member Price | Non-Member Price |
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Paper Abstract
A face recognition system usually consists of one recognition algorithm by processing single spectral images. For
example, face pattern byte (FPB) algorithm was initially created using thermal (LWIR) images, while Elastic Bunch
Graphic Matching (EBGM) algorithm was originated with visible (RGB) images. When there are two or more
recognition algorithms and/or spectral images available, system performance can be enhanced using information fusion.
In this paper, a score fusion with multispectral images is proposed to improve system performance, which is termed as
an integrated multispectral face recognition system. Score fusion actually combines several scores from multiple
matchers (algorithms) and/or multiple modalities (multispectra). The system performance is measured by the recognition
accuracy (AC; the higher the better) and false accept rate (FAR; the lower the better). Specifically, a fusion method will
combine the face scores from three matchers (Circular Gaussian Filter, FPB, EBGM) and from two-spectral bands
(visible and thermal). We present and compare the system performance using seven fusion methods: linear discriminant
analysis (LDA), k-nearest neighbor (KNN), support vector machine (SVM), binomial logistic regression (BLR),
Gaussian mixture model (GMM), artificial neural network (ANN), and hidden Markov model (HMM). Our experiments
are conducted with the Alcon State University multispectral face dataset that currently consists of two spectral images
from 105 subjects. The experimental results show that the KNN score fusion produces the best performance (AC =
98.98%; FAR = 0.35%); and the SVM yields the second best. Compared with the performance of the single best matcher
(AC = 91.67%, FAR = 8.33%), the integrated system with score fusion highly improves the accuracy, meanwhile
dramatically reduces the FAR.
Paper Details
Date Published: 31 December 2013
PDF: 11 pages
Proc. SPIE 9042, 2013 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments, 90420K (31 December 2013); doi: 10.1117/12.2036243
Published in SPIE Proceedings Vol. 9042:
2013 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments
Yongtian Wang; Xiaocong Yuan; Yunlong Sheng; Kimio Tatsuno, Editor(s)
PDF: 11 pages
Proc. SPIE 9042, 2013 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments, 90420K (31 December 2013); doi: 10.1117/12.2036243
Show Author Affiliations
Yufeng Zheng, Alcorn State Univ. (United States)
Published in SPIE Proceedings Vol. 9042:
2013 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments
Yongtian Wang; Xiaocong Yuan; Yunlong Sheng; Kimio Tatsuno, Editor(s)
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