JOURNAL OF MULTIMEDIA (JMM)
ISSN : 1796-2048
Volume : 1 Issue : 1 Date : April 2006
Invariant Robust 3-D Face Recognition based on the Hilbert Transform in Spectral Space
E. Paquet and M. Rioux
Full Text: PDF (531 KB)
One of the main objectives of face recognition is to determine whether an acquired face belongs to a
reference database and to subsequently identify the corresponding individual. Face recognition has
application in, for instance, forensic science and security. A face recognition algorithm, to be useful
in real applications, must discriminate in between individuals, process data in realtime and be
robust against occlusion, facial expression and noise.
A new method for robust recognition of three-dimensional faces is presented. The method is based
on harmonic coding, Hilbert transform and spectral analysis of 3-D depth distributions.
Experimental results with three-dimensional faces, which were scanned with a laser scanner, are
presented. The proposed method recognises a face with various facial expressions in the presence
of occlusion, has a good discrimination, is able to compare a face against a large database of
faces in real-time and is robust against shot noise and additive noise.
Correlation, Face Recognition, Fourier Transform, Hilbert Transform, Invariant, Robust, Spectral