By Arun Ross, Anil K. Jain (auth.), Stan Z. Li, Jianhuang Lai, Tieniu Tan, Guocan Feng, Yunhong Wang (eds.)
Following the former 4 annual meetings, the fifth chinese language convention on Biometrics popularity (Sinobiometrics 2004) was once held in Guangzhou, China in December 2004. The convention this 12 months used to be aimed toward selling the foreign alternate of principles and offering a chance for maintaining abreast of the most recent advancements in biometric algorithms, platforms, and purposes. the first Biometrics Verification festival (BVC) on face, iris, and fingerprint attractiveness used to be additionally performed along side the convention. This publication consists of seventy four papers awarded at Sinobiometrics 2004, contributed by way of researchers and commercial practitioners from Korea, Japan, Singapore, Hong Kong, France, united kingdom, US, in addition to China. of those, 60 papers have been chosen from one hundred forty submissions and 14 have been invited. The papers not just offered contemporary technical advances, but in addition addressed matters in biometric process layout, standardization, and functions. incorporated one of the invited have been 4 function papers at the rules and algorithms of the best-performing biometric engines, which have been both pageant winners on the Face Authentication try (FAT) 2004 or the Fingerprint Verification festival (FVC) 2004, or they have been the best-performing iris and palmprint reputation algorithms. The papers have been complemented by way of 5 keynote lectures on biometrics, and face, fingerprint, and iris authentication and multimodal fusion by way of Arun Ross (West Virginia college) and Anil okay. Jain (Michigan kingdom University), Josef Kittler (University of Surrey), John Daugman (University of Cambridge), Raffaele Cappelli (University of Bologna), and Stan Z. Li (Chinese Academy of Sciences).
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Additional resources for Advances in Biometric Person Authentication: 5th Chinese Conference on Biometric Recognition, SINOBIOMETRICS 2004, Guangzhou, China, December 13-14, 2004. Proceedings
S. Patent No. 5,291,560: Biometric Personal Identification System Based on Iris Analysis. (1994) US Government Printing Office, Washington DC 10. : Statistical richness of visual phase information: Update on recognizing persons by their iris patterns. Int’l J. Computer Vision 45 (2001) 25-38 11. : Demodulation, predictive coding, and spatial vision. J. Opt. Soc. Amer. A 12 (1995) 641-660 12. : Epigenetic randomness, complexity, and singularity of human iris patterns. Proceedings of the Royal Society: Biological Sciences 268 (2001) 1737-1740 13.
The Equal Error Rate. The Equal Error (EE) operating point, as shown in Figure 3, leads us to the Equal Error Rate (EER) which is an obvious, simple choice to judge the quality of a matcher. The Equal Error point of a biometric matcher is the operating point at the intersection of the line FMR = FNMR with the ROC of the matcher. The equal error rate is the value of the error rates at this point The EER (subject to statistical significance ) can certainly tell us that one matcher is better than another, but only does so for a narrow range of operating points in the neighborhood of the EER operating point.
H. ) Academic Press: London (1962) 14. : Face recognition for smart environments. Computer 33 (2000) 50-55 15. : An introduction to evaluating biometric systems. Computer 33 (2000) 56-63 16. : The FERET evaluation methodology for face-recognition algorithms. IEEE Trans. Pattern Analysis and Machine Intelligence 22 (2000) 1090-1104 17. : An evaluation of iridology. J. Amer. Med. Assoc. 242 (1979) 1385-1387 18. : Binomial and negative binomial analogues under correlated Bernoulli trials. uk Abstract.