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41. G. Zonios, U. Shankar, and V. K. Iyer, Pulse oximetry theory and calibration for low saturations, IEEE Trans. Biomed. Eng. 51:818 822, 2004. 42. M. D. Wiederhold, S. A. Israel, R. P. Meyer, and J. M. Irvine, Human identi cation by analysis of physiometric variation, SAIC, United States; 2006. 43. D. P. Jang, S. A. Israel, B. K. Wiederhold, M. D. Wiederhold, S. B. McGehee, L. W. Gavshon, R. Meyer, and J. M. Irvine, Protocols for protecting patient information within a biometric analysis, in Biometrics Section of the International Conference on Information Security, Seoul, Korea, 2001. 44. R. G. Congalton and K. Green, Assessing the Accuracy of Remotely Sensed Data: Principles and Practices FL:Lewis Publishers, Boca Raton, 1991. 45. S. E. Fienberg, An Iterative Procedure for Estimation in Contingency Tables, The Ann. Math. Stat. 41:907 917, 1970. 46. D. F. Morrison, Multivariate Statistical Methods, 2nd edition, McGraw-Hill, New York, 1976. 47. S. C. Dass, Y. Zhu, and A. K. Jain, Validating a Biometric Authentication System: Sample Size Requirements, IEEE Trans. Pattern Anal. Mach. Intell. 26:1902 1913, 2006. 48. N. Poh, A. Martin, and S. Bengio, Performance generalization in biometric authentication using joint user-speci c and sample bootstrap, IEEE Trans. Pattern Anal. Mach. Intell. 29:492 498, 2007. 49. J. L. Wayman, Error-rate equations for the general biometric system, IEEE Robot. Autom. Mag. March:35 48, 1999. 50. D. L. Hall and J. Llinas, An introduction to multisensor data fusion, Proc. IEEE 85:6 23, 1997. 51. I. Bloch, A. Hunter, A. Appriou, A. Ayoun, S. Benferhat, P. Besnard, L. Cholvy, R. Cooke, F. Cuppens, D. Dubois, H. Fargier, H. Parade, A. Saf otti, P. Smets, and C. Sossai, Fusion: General Concepts and Characteristics, Int. J. Intell. Syst. 16:1107 1134, 2001. 52. L. I. Kuncheva, Switching between selection and fusion in combining classi ers: An experiment, IEEE Trans. Syst. Man Cybern. Part B: Cybern. 32:146 156, 2002. 53. P. C. Smits, Multiple classi er systems for supervised remote sensing image classi cation based on dynamic classi er selection, IEEE Trans. Geosci. Remote Sens. 40:801 813, 2002. 54. D. L. Hall and J. Llinas, Handbook of Multisensor Data Fusion, CRC Press, Boca Raton, FL, 2001. 55. J. Kittler and F. M. Alkoot, Sum versus vote fusion in multiple classi er systems, IEEE Trans. Pattern Anal. Mach. Intell. 25:110 115, 2003. 56. S. A. Israel, Performance metrics: How and when, Geocarto Int. 21:23 32, 2006. 57. J. M. Irvine and S. A. Israel, 2009. A sequential procedure for individual identity veri cation using ECG, EURASIP J. Adv. Signal Processing: Recent advances in Biometric systems: A signal processing perspective, 2009 (243215) 13 pp, doi:10.1155/2009/243215. 58. J. M. Irvine, S. A. Israel, M. D. Wiederhold, and B. K. Wiederhold, EigenPulse: robust human identi cation from cardiovascular function, Pattern Recogn. 41(12), 2008.
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The term biometry is derived from the Greek words bios (life) and metron (measure). In the broader sense, biometry can be de ned as the measurement of body characteristics. With this nontechnological meaning, this term has been used in medicine, biology, agriculture, and pharmacy. For example, in biology, biometry is a branch that studies biological phenomena and observations by means of statistical analysis. However, the rise of new technologies since the second half of the twentieth century to measure and evaluate physical or behavioral characteristics of living organisms automatically has given the word a second meaning. In the present study, the term biometrics refers to the following de nition [1]: Biometry, however, has also acquired another meaning in recent decades, focused on the characteristic to be measured rather than the technique or methodology used [1]:
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The term biometry refers to automated methods and techniques that analyze human characteristics in order to recognize a person, or distinguish this person from another, based on a physiological or behavioral characteristic. A biometric is a unique, measurable characteristic or trait of a human being for automatically recognizing or verifying identity.
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Biometrics: Theory, Methods, and Applications. Edited by Boulgouris, Plataniotis, and Micheli-Tzanakou Copyright 2010 the Institute of Electrical and Electronics Engineers, Inc.
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