Comparative Analysis of Robust Iris Recognition System Using Log Gabor Wavelet and Laplacian of Gaussian Filter

COMPARATIVE ANALYSIS OF ROBUST IRIS RECOGNITION SYSTEM USING LOG GABOR WAVELET AND LAPLACIAN OF GAUSSIAN FILTER Bhawna Chouhan1 and Shailja Shukla2 1M.E. VI SEM, JEC, Jabalpur, E-mail: [email protected] 2JEC, Jabalpur, E-mail: [email protected] A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Iris recognition is regarded as the most reliable and accurate biometric identification system available. Most commercial iris recognition systems use patented algorithms developed by Daugman, and these algorithms are able to produce perfect recognition rates. Especially it focuses on image segmentation and feature extraction by using Log Gabor wavelet and Laplacian of Gaussian filter for iris recognition process. The performance of iris recognition system highly depends on edge detection. The Canny Edge Detector is one of the most commonly used image processing tools, detecting edges in a very robust manner. This paper presents a straightforward approach for segmenting the iris patterns. The used method determines an automated global threshold and the pupil center. Experiments are performed using iris images obtained from CASIA database (Institute of Automation, Chinese Academy of Sciences) and Matlab application for its easy and efficient tools in image manipulation.