A study on Iris Recognition using Wavelet Transformation and Nonlinear Function

다국어 초록 (Multilingual Abstract)

In todays security industry, personal identification is also based on biometric. Biometric identification is performed basing on the measurement and comparison of physiological and behavioral characteristics, Biometric for recognition includes voice dynamics, signature dynamics, hand geometry, fingerprint, iris, etc.
Iris can serve as a kind of living passport or living password. Iris recognition system is the one of the most reliable biometrics recognition system. This is applied to client/server system such as the electronic commerce and electronic banking from stand-alone system or networks, ATMs, etc.
A new algorithm using nonlinear function in recognition process is proposed in this paper.
An algorithm is proposed to determine the localized iris from the iris image received from iris input camera in client. For the first step, the algorithm determines the center of pupil. For the second step, the algorithm determines the outer boundary of the iris and the pupillary boundary.
The localized iris area is transform into polar coordinates. After performing three times Wavelet transformation, normalization was done using sigmoid function.
The converting binary process performs normalized value of pixel from 0 to 255 to be binary value, and then the converting binary process is compare pairs of two adjacent pixels.
The binary code of the iris is transmitted to the server by the network. In the server, the comparing process compares the server, the comparing process compares the binary value of presented iris to the reference value in the database. Process of recognition or rejection is dependent on the value of Hamming Distance.
After matching the binary value of presented iris with the database stored in the server, the result is transmitted to the client.

목차 (Table of Contents)

• Abstract
• 1. Introduction
• 2. Determine the center and the outer boundary of the Iris and the pupillary boundary
• 3. Transform the localized iris's part and wavelet transformation
• 4. Results and Discussions
• 5. Conclusion
• Aknowledgement
• References