Title :
Iris Recognition System Using Statistical Features for Biometric Identification
Author :
Kyaw, Khin Sint Sint
Author_Institution :
Dept. of Eng. Phys., Mandalay Technol. Univ. Mandalay, Mandalay
Abstract :
Iris recognition is a proven, accurate means to identify people. In this paper, it includes the preprocessing system, segmentation, feature extraction and recognition. Especially it focuses on image segmentation and statistical feature extraction for iris recognition process. The performance of iris recognition system highly depends on segmentation. For instance, even an effective feature extraction method would not be able to obtain useful information from an iris image that is not segmented properly. 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.
Keywords :
biometrics (access control); feature extraction; image segmentation; statistical analysis; CASIA database; Matlab; biometric identification; feature extraction; image manipulation; image segmentation; iris recognition system; statistical features; Biometrics; Feature extraction; Fingerprint recognition; Image databases; Image processing; Image segmentation; Iris recognition; Physics computing; Psychology; Speech; edge detection; feature vector; iris recognition; segmentation;
Conference_Titel :
Electronic Computer Technology, 2009 International Conference on
Conference_Location :
Macau
Print_ISBN :
978-0-7695-3559-3
DOI :
10.1109/ICECT.2009.129