Paper
13 April 2009 High performance and fast face recognition technique based on components of phases of face images
Naser Zaeri, Abdallah Cherri
Author Affiliations +
Abstract
Most of the algorithm proposed for face recognition involve considerable amount of computations and hence they cannot be used on devices constrained with limited memory. In this paper, we propose a novel solution for efficient face recognition for systems which are charactered with small memory devices and demand fast performance. By dividing the face images into components, the scheme finds the discriminant phases of the Fourier transform of these components of face images. The discriminant phases are found by using linear discriminant analysis (LDA) to obtain a system that matches the criteria imposed by devices of limited memory and requiring fast recognition. Note that since the effects of face variation within an image are reduced when the image is divided into components, then the performance of the system is enhanced. Compared to spatial domain analysis, it will be shown that the use of component in the frequency domain produces better recognition performance. A thorough study and comprehensive experiments relating time consumption and computational complexity versus system performance are presented. The proposed technique increases the face recognition rate and at the same time achieves substantial saving in the computational time, when compared to other known systems. The experimental results reveal that a recognition rate of ≥99% is achieved, when applied to two independent and well known databases.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Naser Zaeri and Abdallah Cherri "High performance and fast face recognition technique based on components of phases of face images", Proc. SPIE 7340, Optical Pattern Recognition XX, 73400Q (13 April 2009); https://doi.org/10.1117/12.818126
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KEYWORDS
Databases

Facial recognition systems

Fourier transforms

Computing systems

Detection and tracking algorithms

Principal component analysis

Electrical engineering

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