31-07-2012, 04:44 PM
Recognition Of Human Iris Patterns For Person Identification
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INTRODUCTION
Biometric Technology
A biometric system provides automatic recognition of an individual based on some sort of unique feature or characteristic possessed by the individual. Biometric systems have been developed based on fingerprints, facial features, voice, hand geometry, handwriting, the retina and the one presented in this thesis, the iris.
Biometric systems work by first capturing a sample of the feature, such as recording a digital sound signal for voice recognition, or taking a digital colour image for face recognition. The sample is then transformed using some sort of mathematical function into a biometric template. The biometric template will provide a normalized, efficient and highly discriminating representation of the feature, which can then be objectively compared with other templates in order to determine identity. Most biometric systems allow two modes of operation. An enrolment mode for adding templates to a database, and an identification mode, where a template is created for an individual and then a match is searched for in the database of pre-enrolled templates.
The Human Iris
The iris is a thin circular diaphragm, which lies between the cornea and the lens of the human eye. A front-on view of the iris is shown in Figure
The function of the iris is to control the amount of light entering through the pupil, and this is done by the sphincter and the dilator muscles, which adjust the size of the pupil. The average diameter of the iris is 12 mm, and the pupil size can vary from 10% to 80% of the iris diameter.
The iris consists of a number of layers, the lowest is the epithelium layer, which contains dense pigmentation cells. The stromal layer lies above the epithelium layer, and contains blood vessels, pigment cells and the two iris muscles. The density of stromal
pigmentation determines the colour of the iris. The externally visible surface of the multi-layered iris contains two zones, which often differ in colour. An outer ciliary zone and an inner pupillary zone, and these two zones are divided by the collarette – which appears as a zigzag pattern.
Objective
The objective will be to implement an open-source iris recognition system in order to verify the claimed performance of the technology. The development tool used will be MATLAB, and emphasis will be only on the software for performing recognition, and not hardware for capturing an eye image. A rapid application development (RAD) approach will be employed in order to produce results quickly.
MATLAB provides an excellent RAD environment, with its image processing toolbox, and high level programming methodology. To test the system, two data sets of eye images will be used as inputs. A database of 756 grayscale eye images courtesy of The Chinese Academy of Sciences – Institute of Automation (CASIA), and a database of 120 digital grayscale images courtesy of the Lion‟s Eye Institute (LEI).
Organization of the Report
The report is organized as follows: The introduction of this mini-project has been given in chapter 1. In chapter 2, feature extraction techniques have been discussed. Segmentation and Normalisation technique are used for feature extraction. In chapter 3, Feature encoding and matching procedure has been explained. Feature Encoding is done by using wavelet encoding and matching is done by measuring the hamming distance. The software design and implementation procedure is explained in chapter 4. In Chapter 5 Experimental Results of the project has been shown. Results include both matced and mismatched condition of the iris. Chapter 6 concludes and presents perspectives of this project. Advantages and applications and the scope for future work have also been discussed. The papers, books and links that are referred are listed in the References section. The MATLAB source code that is used for implementing the project is given in the Appendix.