High Performance Iris Recognition Based on LDA and LPCC
ICTAI '05 Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence
Handbook of Biometrics
Face Recognition Based on DCT and 2DLDA
ICICIC '07 Proceedings of the Second International Conference on Innovative Computing, Informatio and Control
A Fast and Accurate Iris Recognition Method Using the Complex Inversion Map and 2DPCA
ICIS '08 Proceedings of the Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008)
A New Iris Recognition Method Based on Gabor Wavelet Neural Network
IIH-MSP '08 Proceedings of the 2008 International Conference on Intelligent Information Hiding and Multimedia Signal Processing
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal Processing
Efficient iris recognition by characterizing key local variations
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Performance comparison of DCT, FFT, WHT & Kekre's transform for on-line signature recognition
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
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In this paper we propose a novel iris recognition method which reduces the computational complexity and increases the accuracy. Iris recognition enjoys universality, high degree of uniqueness and moderate user co-operation. This makes Iris recognition systems unavoidable in emerging security & authentication mechanisms. Iris recognition is one of the important techniques and is rotation invariant. In this paper we have tested full 2-dimensional Discrete Cosine Transform (DCT), full 2-dimensional Walsh Transform (WHT), and the proposed method DCT/WHT row mean and column mean. Row mean DCT/WHT gives the best performance with the accuracy of 75.78% outperforming full 2-dimensional DCT/WHT with low accuracy around 66.10% further proposed Walsh Row/Column mean requires 99.96% less computations as that of full 2-D DCT. Thus our proposed method not only gives better accuracy but also reduces computational time considerably.