Digital Image Processing
An Automated Video-Based System for Iris Recognition
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Measurement of defocus level in iris images using different convolution kernel methods
MCPR'10 Proceedings of the 2nd Mexican conference on Pattern recognition: Advances in pattern recognition
Iris segmentation using a statistical approach
MCPR'10 Proceedings of the 2nd Mexican conference on Pattern recognition: Advances in pattern recognition
A study on fast iris restoration based on focus checking
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
Localized iris image quality using 2-d wavelets
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Real-Time Image Restoration for Iris Recognition Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Circuits and Systems for Video Technology
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Recent researches on iris recognition without user cooperation have introduced video-based iris capturing approach. Indeed, it provides more information and more flexibility in the image acquisition stage for noncooperative iris recognition systems. However, a video sequence can contain images with different level of quality. Therefore, it is necessary to select the highest quality images from each video to improve iris recognition performance. In this paper, we propose as part of a video quality assessment module, a new local quality iris image method based on spectral energy analysis. This approach does not require the iris region segmentation to determine the quality of the image such as most of existing approaches. In contrast to other methods, the proposed algorithm uses a significant portion of the iris region to measure the quality in that area. This method evaluates the energy of 1000 images which were extracted from 200 iris videos from the MBGC NIR video database. The results show that the proposed method is very effective to assess the quality of the iris information. It obtains the highest 2 images energies as the best 2 images from each video in 226 milliseconds.