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Fourier-Cosine Transform Coefficients Fusion for Face Recognition

S. Priyadharshini*, Maheswaran U**

*-** Assistant Professor, Department of Electronics and Communication Engineering, Rajalakshmi Institute of Technology, Chennai, India.

Periodicity:June - August'2015
DOI : https://doi.org/10.26634/jpr.2.2.3564

Abstract

3D Face recognition has been an area of interest among researchers for the past few decades especially in pattern recognition. The main advantage of 3D Face recognition is the availability of geometrical information of the face structure which is more or less unique for a subject. This paper focuses on the problems of person recognition using 3D Face data. Use of unregistered 3D Face data drastically increases the operational speed of the system with huge database enrolment. In this effort, unregistered 3D Face data is fed to a classifier in multiple spectral representations of the same data. Discrete Fourier Transform (DFT) and Discrete Cosine Transform (DCT) are used for the spectral representations. The face recognition accuracy obtained when the feature extractors are used individually is evaluated. Fusion of the matching scores proves that the recognition accuracy can be improved significantly by fusion of scores of multiple representations. FRAV 3D database is used for testing the algorithm.

Keywords

Rotation Invariance, Pose Correction, Depth Map, Spectral Transformation, Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT)

How to Cite this Article?

Priyadharshini, S., and Maheswaran, U. (2015). Fourier-Cosine Transform Coefficients Fusion for Face Recognition. i-manager’s Journal on Pattern Recognition, 2(2), 1-8. https://doi.org/10.26634/jpr.2.2.3564

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