Iris Recognition: An Emerging Biometric Technology


Iris recognition

Iris Recognition System

Iris Recognition Based on Neural Networks

Phase-Based Iris Identification

Moving Average Filter Iris Recognition

Iris Identification Based on 2D Wavelet

DCT-Based Iris Recognition

Hybrid Iris Recognition

LBP Iris Recognition

Iris Recognition Based on Genetic Algorithms

One-to-One Iris Recognition System

External resources

Advanced Source Code .Com

Neural Networks .It

Genetic Algorithms .It

Face Recognition .It

Hybrid Iris Recognition

Download now Matlab source code
Requirements: Matlab, Matlab Image Processing Toolbox, Matlab Signal Processing Toolbox, Matlab Wavelet Toolbox.

The use of biometric signatures, instead of tokens such as identification cards or computer passwords, continues to gain increasing attention as an efficient means of identification and verification of individuals for controlling access to secured areas, materials, or systems and a wide variety of biometrics has been considered over the years in support of these challenges. Iris recognition is especially attractive due to the stability of the iris texture patterns with age and health conditions. Iris image segmentation and localisation is a key step in iris recognition and plays an essential role the accuracy of matching. We have developed a fast and accurate scheme for iris segmentation. On CASIA Iris Database the average time required for iris detection is 0.1901 seconds.

By adopting an hybrid scheme for features extraction we have achieved an excellent recognition rate of 97.6852% (108 classes, 3 training images and 4 test images for each class, hence there are 324 training images and 432 test images with no overlap between the training and test images).

Index Terms: Matlab, source, code, iris, recognition, segmentation, detection, verification, matching.

Release 1.0 Date 2008.11.24
Major features:

Iris Recognition . It Luigi Rosa mobile +39 3207214179