16 December 2004 Automatic iris recognition using neural networks and wavelet
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Abstract
It's known that any iris recognition system is composed of four steps: iris image acquisition, iris texture isolation, features extraction, and classification. In the acquisition phase, our system begins with identifying the human iris automatically in a given image using neural networks to test whether it contains iris or not. If the iris exists in the acquired image it goes to the second step which is the iris texture isolation to localize the pupil boundaries, localize the iris boundaries, extract the iris texture, convert the iris texture to the polar coordinate system and then equalize the histogram of the rectangular iris texture. In the features extraction phase, our system uses the Haar wavelet to extract 72 features. In the classification phase, our system uses the matching ratio to identify or reject the subject.
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Mohamed Yousry Elgendi, Mohamed El-Adawy, Hisham Keshk, "Automatic iris recognition using neural networks and wavelet", Proc. SPIE 5616, Optics and Photonics for Counterterrorism and Crime Fighting, (16 December 2004); doi: 10.1117/12.578525; https://doi.org/10.1117/12.578525
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KEYWORDS
Iris recognition

Wavelets

Neural networks

Feature extraction

Classification systems

Image processing

Image filtering

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