Multimodal fusion decision logic system

Data processing: artificial intelligence – Neural network

Reexamination Certificate

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Details

C382S224000, C382S228000

Reexamination Certificate

active

11273824

ABSTRACT:
The present invention includes a method of deciding whether a data set is acceptable for making a decision. A first probability partition array and a second probability partition array may be provided. A no-match zone may be established and used to calculate a false-acceptance-rate (“FAR”) and/or a false-rejection-rate (“FRR”) for the data set. The FAR and/or the FAR may be compared to desired rates. Based on the comparison, the data set may be either accepted or rejected. The invention may also be embodied as a computer readable memory device for executing the methods.

REFERENCES:
patent: 2003/0031348 (2003-02-01), Kuepper et al.
patent: 2005/0238207 (2005-10-01), Tavares
Osadciw et al., “Optimum Fusion Rules Formultimodal Biometric Systems”, 2004.
Teoh et al., “Nearest Neighbourhood Classifiers in Biometric Fusion”, 2004.
Neyman et al., “On the Problem of the most Efficient Test of Statistical Hypotheses”, 1933.
Prabhakar, et al., Decision-level Fusion in Biometric Verification, Department of Computer Science and Engineering, Michigan State University, pp. 1-34.
Neyman, et al., On the Problem of the most Efficient Tests of Statistical Hypotheses, vol. CCXXXI.-A, 702, pp. 289-337.
Lindgren, Statistical Theory Third Edition, Ch. 6—Testing Hypotheses, pp. 276-324.
Maltoni, et al., Handbook of Fingerprint Recognition, Springer Professional Computing, Ch. 7—Multimodal Biometric Systems, pp. 233-255.
Duda, et al., Pattern Classification Second Edition, Ch. 2—Bayesian Decision Theory, Ch. 3—Maximum-Likelihood And Bayesian Parameter Estimation, first page of Ch. 4—Nonparametric Techniques, pp. 20-161.

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