Author
Computer Science Depart, University of Technology/ Baghdad, Iraq
Abstract
Human identification based on face images, as physical biometric means, plays an
imperative role in many applications area. The methods for human identification using
face image uses either part of the face, all face, or mixture from these methods, in either
time domain or frequency domain. This paper investigate the ability to implement the
eigenface in frequency domain, the result spectral eigenface is utilize as a feature vector
means for human identification. The converting from eigenface implementation in time
domain, into spectral eigenface implementation in frequency domain, is based on
implemented the correlation by using FFT. The Min-max is invoked as normalization
techniques that increase spectral eigenface robustness to variations in facial geometry
and illumination. Two face images are contrast in terms of their correlation distance. A
threshold (10.50x107) is used to restrict the impostor face image from being identified.
The experimental results point up the effectiveness of a new method in either using
varying (noisy images, unknown image, face expressions, illumine, and scale s), with
identification value of 100%.
Keywords
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