Custom JPEG Quantization for Improved Iris Recognition Accuracy
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[1] Andreas Uhl,et al. Comparison of compression algorithms' impact on iris recognition accuracy II: revisiting JPEG , 2008, Electronic Imaging.
[2] Shing-Chow Chan,et al. Designing JPEG quantization matrix using rate-distortion approach and human visual system model , 1997, Proceedings of ICC'97 - International Conference on Communications.
[3] Randy P. Broussard,et al. Effects of image compression on iris recognition system performance , 2008, J. Electronic Imaging.
[4] R.W. Ives,et al. Effect of Image Compression on Iris Recognition , 2005, 2005 IEEE Instrumentationand Measurement Technology Conference Proceedings.
[5] Ping-Sing Tsai,et al. JPEG: Still Image Compression Standard , 2005 .
[6] Hyun-Sik Ahn,et al. JPEG Quantization Table Design for Face Images and Its Application to Face Recognition , 2006, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..
[7] Andreas Uhl,et al. Comparison of Compression Algorithms' Impact on Iris Recognition Accuracy , 2007, ICB.
[8] John Daugman,et al. Effect of Severe Image Compression on Iris Recognition Performance , 2008, IEEE Transactions on Information Forensics and Security.
[9] Gregory K. Wallace,et al. The JPEG Still Image Compression Standard , 1991 .
[10] Mo Chen,et al. Modification of standard image compression methods for correlation-based pattern recognition , 2004 .
[11] John Daugman,et al. How iris recognition works , 2002, IEEE Transactions on Circuits and Systems for Video Technology.
[12] Donald M. Monro,et al. Effects of Sampling and Compression on Human IRIS Verification , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.
[13] Stan Z. Li,et al. Advances in Biometrics, International Conference, ICB 2007, Seoul, Korea, August 27-29, 2007, Proceedings , 2007, ICB.