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Face recognition for images of persons against a general background using approximate parameter estimation of affine transform
Author(s) -
Izumi Tetsuya,
Hattori Tetsuo,
Qing yu Shu,
Kitajima Hiroyuki,
Yamasaki Toshinori
Publication year - 2009
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.10152
Subject(s) - affine transformation , karhunen–loève theorem , face (sociological concept) , representation (politics) , facial recognition system , pattern recognition (psychology) , taylor series , artificial intelligence , mathematics , image (mathematics) , affine shape adaptation , field (mathematics) , algorithm , vector field , computer science , affine combination , computer vision , mathematical analysis , geometry , pure mathematics , social science , sociology , politics , political science , law
A method for face recognition of acquaintance in a given people image with general background is proposed. We assume that the face pattern to be recognized in the input image is perturbed approximately by affine transform (rotated, enlarged or reduced, and translated) from a registered original one and also by a lighting variation. In order to estimate the parameters of the affine transform, the method uses a Karhunen–Loeve (KL) expansion, spatial correlation, and a correction equation based on Taylor's expansion of the transform. Moreover, in order to be insensitive to the lighting variations, we deal with a normalized gradient vector field (NGVF) pattern representation. The experimental result shows that the method using NGVF representation and approximate parameter estimation is considerably effective. © 2009 Wiley Periodicals, Inc. Electron Comm Jpn, 92(11): 1–8, 2009; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/ecj.10152