This paper explains the Genetic Algorithm (GA)
evolution of optimized wavelet that surpass the cdf9/7
wavelet for fingerprint compression and reconstruction.
Optimized wavelets have already been evolved in previous
works in the literature, but they are highly computationally
complex and time consuming. Therefore, in this work, a simple
approach is made to reduce the computational complexity of
the evolution algorithm. A training image set comprised of
three 32x32 size cropped images performed much better than
the reported coefficients in literature. An average
improvement of 1.0059 dB in PSNR above the classical cdf9/7
wavelet over the 80 fingerprint images was achieved. In
addition, the computational speed was increased by 90.18 %.
The evolved coefficients for compression ratio (CR) 16:1
yielded better average PSNR for other CRs also. Improvement
in average PSNR was experienced for degraded and noisy
images as well
Description:
2012 International Conference on Advances in Computing and Communications
Poulose Jacob,K; Binsu, Kovoor C; Supriya, M H(First International Conference on Computational Science and Engineering (CSE-2013), 2013)
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Abstract:
Biometrics has become important in security applications. In comparison with many other
biometric features, iris recognition has very high recognition accuracy because it depends on
iris which is located in a place that still stable throughout human life and the probability to find
two identical iris's is close to zero. The identification system consists of several stages including
segmentation stage which is the most serious and critical one. The current segmentation
methods still have limitation in localizing the iris due to circular shape consideration of the
pupil. In this research, Daugman method is done to investigate the segmentation techniques.
Eyelid detection is another step that has been included in this study as a part of segmentation
stage to localize the iris accurately and remove unwanted area that might be included. The
obtained iris region is encoded using haar wavelets to construct the iris code, which contains
the most discriminating feature in the iris pattern. Hamming distance is used for comparison of
iris templates in the recognition stage. The dataset which is used for the study is UBIRIS
database. A comparative study of different edge detector operator is performed. It is observed
that canny operator is best suited to extract most of the edges to generate the iris code for
comparison. Recognition rate of 89% and rejection rate of 95% is achieved
Description:
Computer Science & Information Technology (CS & IT)