Biometric recognition using a classification neural network
June 11, 2016. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.Patent ReferencesAutomatic pattern processing system System and method for identifying an individual utilizing grasping pressures Apparatus and method for matching image characteristics such as fingerprint minutiae Unforgeable personal identification system Method and apparatus for verifying identity using image correlation Fingerprint/signature synthesis Apparatus for generating a feature matrix based on normalized out-class and in-class variation matrices Method for identifying individuals from analysis of elemental shapes derived from biosensor data Data system and method Continuous biometric authentication matrix InventorApplicationNo. 664215 filed on 06/11/1996US Classes:382/115, Personnel identification (e.g., biometrics)382/124, Using a fingerprint382/156, Neural networks382/190, Feature extraction382/218, Comparator382/278CorrelationExaminersPrimary: Chang, JonAttorney, Agent or FirmForeign Patent References
International ClassesG06K 009/46G06K 009/62 AbstractA biometric recognition system involves two phases: creation of a master pattern set of authorized users biometric indicia and authentication using a classification neural network. To create the master pattern set, an image of an authorized biometric user's indicia is divided into a plurality of regions of interest or "features". The system determines which features are the most useful for identification purposes. Master patterns are then created from these master features, thus creating a master pattern set. During authentication, a sample pattern set of a user to be authenticated is similarly created. A neural network is used to compare the sample pattern set with the master pattern set to determine whether the user should be authenticated.Other References
Field of SearchClassificationUsing a fingerprint Extracting minutia such as ridge endings and bifurcations Template matching (e.g., specific devices that determine the best match) Comparator Personnel identification (e.g., biometrics) Feature extraction Neural networks Trainable classifiers or pattern recognizers (e.g., adaline, perceptron) Network learning techniques (e.g., back propagation) Correlation | |
