Method of hash string extraction

• US 20060050937A1
• Filed: 10/24/2005
• Published: 03/09/2006
• Est. Priority Date: 07/25/2001
• Status: Active Grant

• Current Assignee: Activcard Ireland, Limited
• Original Assignee: Activcard Ireland, Limited
• Inventors: Hamid, Larry
• Granted Patent: US 7,564,997 B2
• Time in Patent Office: Days
• US Class Current: 382/124
• CPC Class Codes: G06V 40/1347 Preprocessing; Feature extraction
• CPC Class Codes: H04L 9/3231 Biological data, e.g. fingerprint, voice or retina network architectures or network communication protocols for supporting authentication of entities using biometrical features in a packet data network H04L63/0861
• CPC Class Codes: H04L 9/3236 using cryptographic hash functions

Abstract

A method of hash string extraction from biometric information is disclosed. The method comprises the steps of providing a biometric information sample in the form of a fingerprint for example, extracting features from the biometric information sample and encoding the features based on their location within the biometric information sample; and, generating a string of values based on the extracted features and their determined locations. The method further comprises the steps of hashing the string of symbols to produce a plurality of hash values for comparing the plurality of hash values against a stored hash value for identifying a user.

Claims

1-38. -38. (canceled)

39. A method of generating biometric data comprising:

receiving a first set of biometric data from a biometric input device, the first set of biometric data derived from a biometric sample;

extracting first feature data from the first set of biometric data corresponding to a first feature of the biometric sample; and

encoding the extracted first feature data to determine a plurality of features therein, the plurality of features comprising at least four features, to determine at least a parameter associated with each of the plurality of features, and to provide subset data corresponding to a plurality of overlapping subsets of the features, at least some of the overlapping subsets including fewer than all of the features within the set of data.

40. A method of generating biometric data according to claim 39 wherein the at least a parameter associated with the features comprises data relating to a feature type.

41. A method of generating biometric data according to claim 39 wherein the at least a parameter associated with the features comprises data indicative of a position of the feature relative to the first feature.

42. A method of generating biometric data according to claim 39 comprising hashing data corresponding to the plurality of overlapping subsets of the features.

43. A method of generating biometric data according to claim 42 wherein the hashing comprises using a hashing algorithm that is insensitive to the order of data provided thereto.

44. A method of generating biometric data according to claim 39 wherein the parameter associated with each of the plurality of features comprises data indicative of a position of the feature relative to the first feature.

45. A method of generating biometric data according to claim 39 comprising hashing data associated with the at least a parameter using a hashing algorithm to generate a hash value.

46. A method of generating biometric data according to claim 39 comprising hashing data associated with the at least a parameter using a hashing algorithm to generate a plurality of hash values, each of the hash values corresponding to a specific overlapping subset of the features.

47. A method of generating biometric data according to claim 46 wherein the hashing comprises using a hashing algorithm that is insensitive to the order of data provided thereto.

48. A method of generating biometric data according to claim 39 comprising:

receiving a set of user data from a second biometric input device, the set of user data derived from a biometric sample of a user;

identifying user data from the set of user data corresponding to a first user feature of the user biometric sample;

encoding the user data to determine user features therein and to determine at least a user parameter associated with the user features and for providing a plurality of overlapping subsets of the user features, at least some of the overlapping subsets including fewer than all of the user features within the set of user data;

hashing user data associated with the at least a parameter using a hashing algorithm to generate a user hash value; and

comparing the user hash value with the plurality of hash values to determine if the biometric sample of the user corresponds to the biometric sample.