A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Personal Identification Based on Iris Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
CIT '04 Proceedings of the The Fourth International Conference on Computer and Information Technology
Localized iris image quality using 2-d wavelets
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Robust and fast assessment of iris image quality
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
A study on iris image restoration
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
UBIRIS: a noisy iris image database
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
IEEE Transactions on Circuits and Systems for Video Technology
Local quality method for the iris image pattern
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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During the video and fixed image acquisition procedure of an automatic iris recognition system, it is essential to acquire focused iris images. If defocus iris images are acquired, the performance of the iris recognition is degraded, because iris images don't have enough feature information. Therefore it's important to adopt the image quality evaluation method before the image processing. In this paper, it is analyzed and compared four representative quality assessment methods on the MBGC iris database. Through methods, it can fast grade the images and pick out the high quality iris images from the video sequence captured by real-time iris recognition camera. The experimental results of the four methods according to the receiver operating characteristic (ROC) curve are shown. Then the optimal method of quality evaluation that allows better performance in an automatic iris recognition system is founded. This paper also presents an analysis in terms of computation speed of the four methods.