Abstract: A method for updating biometric reference data for a person is provided. The biometric reference data is defined as a multi-template formed by a number of templates each representing an area of an associated biometric object of the person. The method comprises providing at least one template associated with a biometric image that depicts at least one area of a finger of the person. Moreover, the method comprises matching the at least one template to the multi-template of the biometric reference data and in the event of a match, updating the multi-template of the biometric reference data with at least one selected previously matched template stored in a candidate template queue. Furthermore, the method comprises storing the matched template in the candidate template queue.

Abstract: A method (10) for matching a biometric user template to at least one multi template is provided. Each multi template is formed by a group of sub templates each representing an area of an associated biometric object of a person. The method comprises a) determining (11) a first matching score between at least one of the sub templates for at least one of the multi-templates and the user template; b) determining (12) an order of the sub templates based on their first matching score and which multi template they belong to; c) processing (13) at least one of the sub templates successively based on the predetermined order, wherein said processing comprises for each sub template: d) determining (131) a second matching score between the sub template and the user template, e) comparing (132) the second matching score to a threshold score, and g) generating (133) a signal indicating a match if the second matching score is above the threshold score.

Abstract: A method for updating biometric reference data for a person is provided. The biometric reference data is defined as a multi-template formed by a number of templates each representing an area of an associated biometric object of the person. The method comprises providing at least one template associated with a biometric image that depicts at least one area of a finger of the person. Moreover, the method comprises matching the at least one template to the multi-template of the biometric reference data and in the event of a match, updating the multi-template of the biometric reference data with at least one selected previously matched template stored in a candidate template queue. Furthermore, the method comprises storing the matched template in the candidate template queue.

Abstract: A method of enrolling a biometric template from a biometric sensor arranged to collect a plurality of images is disclosed. Each image comprises an elongated part of a biometric object. The collection is made upon repeated placement of the finger on the biometric sensor.

Abstract: A method of matching fingerprints is disclosed. The method comprises, for a first minutia point, being assigned as a planet minutia point a) determining pairs including the planet minutia point and a satellite minutia point, respectively, such that a cluster is formed; b) comparing the clusters of the respective sets and excluding nonmatching satellites; c) counting links in the cluster formed by remaining pairs; and d) for remaining satellite minutia points, performing steps a) to c) with respective satellite minutia point assigned as planet minutia point to form a supercluster by iterating steps a) to d) and superadding the clusters; calculating a score of the supercluster based on the aggregate counted links; and comparing the score with a threshold. A biometric matching apparatus, a portable data carrier, a data processing unit comprising a matching apparatus and a computer program for implementing the invention are also disclosed.

Abstract: A method of matching fingerprints is disclosed. The method comprises, for a first minutia point, being assigned as a planet minutia point a) determining pairs including the planet minutia point and a satellite minutia point, respectively, such that a cluster is formed; b) comparing the clusters of the respective sets and excluding nonmatching satellites; c) counting links in the cluster formed by remaining pairs; and d) for remaining satellite minutia points, performing steps a) to c) with respective satellite minutia point assigned as planet minutia point to form a supercluster by iterating steps a) to d) and superadding the clusters; calculating a score of the supercluster based on the aggregate counted links; and comparing the score with a threshold. A biometric matching apparatus, a portable data carrier, a data processing unit comprising a matching apparatus and a computer program for implementing the invention are also disclosed.

Abstract: A method of matching fingerprints is disclosed. The method comprises, for a first minutia point, being assigned as a planet minutia point a) determining pairs including the planet minutia point and a satellite minutia point, respectively, such that a cluster is formed; b) comparing the clusters of the respective sets and excluding non-matching satellites; c) counting links in the cluster formed by remaining pairs; and d) for remaining satellite minutia points, performing steps a) to c) with respective satellite minutia point assigned as planet minutia point to form a supercluster by iterating steps a) to d) and superadding the clusters; calculating a score of the supercluster based on the aggregate counted links; and comparing the score with a threshold. A biometric matching apparatus, a portable data carrier, a data processing unit comprising a matching apparatus and a computer program for implementing the invention are also disclosed.

Abstract: A method of matching fingerprints is disclosed. The method comprises, for a first minutia point, being assigned as a planet minutia point a) determining pairs including the planet minutia point and a satellite minutia point, respectively, such that a cluster is formed; b) comparing the clusters of the respective sets and excluding non-matching satellites; c) counting links in the cluster formed by remaining pairs; and d) for remaining satellite minutia points, performing steps a) to c) with respective satellite minutia point assigned as planet minutia point to form a supercluster by iterating steps a) to d) and superadding the clusters; calculating a score of the supercluster based on the aggregate counted links; and comparing the score with a threshold. A biometric matching apparatus, a portable data carrier, a data processing unit comprising a matching apparatus and a computer program for implementing the invention are also disclosed.

Abstract: Method and device for fall prevention and detection, specifically for the elderly care based on digital image analysis using an intelligent optical sensor. The fall detection is divided into two main steps; finding the person on the floor, and examining the way in which the person ended up on the floor. When the first step indicates that the person is on the floor, data for a time period of a few seconds before and after the indication is analyzed in the second step. If this indicates a fall, a countdown state is initiated in order to reduce the risk of false alarms, before sending an alarm. The fall prevention is also divided into two main steps: identifying a person entering a bed; and identifying the person leaving the bed to end up standing beside it.

Abstract: Method and device for fall prevention and detection, specially for the elderly care based on digital image analysis using an intelligent optical sensor. The fall detection is divided into two main steps; finding the person on the floor, and examining the way in which the person ended up on the floor. The first step is further divided into algorithms investigating the percentage share of the body on the floor, the inclination of the body and the apparent length of the person. The second step includes algorithms examining the velocity and acceleration of the person. When the first step indicates that the person is on the floor, data for a time period of a few seconds before and after the indication is analysed in the second step. If this indicates fall, a countdown state is initiated in order to reduce the risk of false alarms, before sending an alarm.

Abstract: Method and device for fall prevention and detection, specifically for the elderly care based on digital image analysis using an intelligent optical sensor. The fall detection is divided into two main steps; finding the person on the floor, and examining the way in which the person ended up on the floor. When the first step indicates that the person is on the floor, data for a time period of a few seconds before and after the indication is analyzed in the second step. If this indicates a fall, a countdown state is initiated in order to reduce the risk of false alarms, before sending an alarm. The fall prevention is also divided into two main steps: identifying a person entering a bed; and identifying the person leaving the bed to end up standing beside it.

Abstract: Method and device for fall prevention and detection, specially for the elderly care based on digital image analysis using an intelligent optical sensor. The fall detection is divided into two main steps; finding the person on the floor, and examining the way in which the person ended up on the floor. The first step is further divided into algorithms investigating the percentage share of the body on the floor, the inclination of the body and the apparent length of the person. The second step includes algorithms examining the velocity and acceleration of the person. When the first step indicates that the person is on the floor, data for a time period of a few seconds before and after the indication is analysed in the second step. If this indicates fall, a countdown state is initiated in order to reduce the risk of false alarms, before sending an alarm.