Experiments with an improved iris segmentation algorithm

Proceedings - Fourth IEEE Workshop on Automatic Identification Advanced Technologies, AUTO ID 2005

Volumn 2005, Issue , 2005, Pages 118-123

  Liu, Xiaomei ^a   Bowyer, Kevin W ^a   Flynn, Patrick J ^a  

^a University of Notre Dame   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DATA ACQUISITION; DATABASE SYSTEMS; PATTERN RECOGNITION;

IRIS IMAGES; IRIS RECOGNITION SYSTEMS;

IMAGE SEGMENTATION;

EID: 33750963269     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AUTOID.2005.21     Document Type: Conference Paper

References (9)

1. http://iris.nist.gov/ice/.
2. http://www.iridiantech.com/.
3. J. Daugman. High confidence visual recognition of persons by a test of statistical independence. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(11), November 1993.
4. J. Daugman. Statistical richness of visual phase information: Update on recognizing persons by iris patterns. International Journal of Computer Vision, 45(1):25-38, 2001.
5. J. Daugman. The importance of being random: Statistical principles of iris recognition. Pattern Recognition, 36(2):279-291, 2003.
6. J. Daugman. How iris recognition works. IEEE Trans. Circuits and Systems for Video Technology, 14:1:21-30, 2004.
7. X. Liu, K. Bowyer, and P. Flynn. Experimental evaluation of iris recognition. Proc. Face Recognition Grand Challenge Workshop, 2005.
8. L. Masek. Recognition of Human Iris Patterns for Biometric Identification. http://www.csse.uwa.edu.au/~pk/studentprojects/libor/, The University of Western Australia.
9. P. J. Phillips. Overview of the face recognition grand challenge. IEEE Conference on Computer Vision and Pattern Recognition, 1:947-954, 2005.