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US 9,754,151 B2Granted
Derived virtual quality parameters for fingerprint matching
AssigneeMorphoTrak, LLC
InventorsHui Chen, Peter Zhen-Ping Lo
Life of this patent
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AssigneeMorphoTrak, LLC
InventorsHui Chen, Peter Zhen-Ping Lo
Estimating the term…
In some implementations, a computer-implemented method may include: identifying one or more neighboring minutiae within a particular octant neighborhood for the octant feature vector for each minutia included in a list of minutiae associated with a search fingerprint; computing, for each minutia included in the list of minutiae, a direction difference between each minutia included in the list of minutiae, and each of the one or more neighboring minutiae identified for the octant feature vector for each minutia included in the list of minutiae; computing, for each minutia included in the list of minutiae, a minutia quality confidence; and computing a fingerprint quality confidence.
A computer-implemented method for matching fingerprints, the method comprising:
A system comprising:
One or more non-transitory computer-readable media storing instructions that, when executed by one or more computers of a server system, cause the server system to perform operations comprising:
Dependencies are inferred from the claim text.
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Preprocessing; Feature extraction: extracting features related to minutiae or pores
Analysing: matching criteria, e.g. proximity measures
Matching; Classification: matching features related to minutiae or pores
Image and video recognition
About 9 years 1 month of term left · ends 16 Nov 2035 (estimated)
The present disclosure relates generally to fingerprint identification systems.
Pattern matching systems such as ten-print or fingerprint matching systems play a critical role in criminal and civil applications. For example, fingerprint identification is often used for identify and track suspects and in criminal investigations. Similarly, fingerprint verification is used in civil applications to prevent fraud and support other security processes.
Although significant improvements in fingerprint recognition have been achieved, the design of highly accurate matching systems that use only minutiae information remains challenging. For instance, embedded fingerprint matching systems utilize limited sets of features, such as minutiae and singularity points, from a fingerprint due to storage and computational constraints. However, common matching methods that use only minutiae information often use different minutia descriptors rather than integrating minutiae attributes to compute a similarity score. Consequently, these methods often omit analysis of mated and non-mated minutiae, which can impact matching accuracy.
FIG. 1A is a block diagram of an exemplary automatic fingerprint identification system.
FIG. 1B is a block diagram of an exemplary feature extraction process.
FIG. 2 is an exemplary illustration of geometric relationships between a reference minutia and a neighboring minutia.
In general, one innovative aspect described throughout this disclosure includes improved minutiae matching techniques using derived virtual quality parameters. For instance, the derived virtual quality parameters may be generated based on comparing a number of mated minutiae between a search fingerprint and a reference fingerprint, and a number of non-mated minutiae between the search fingerprint and the reference fingerprint. Since the number of mated and non-mated minutiae within the search fingerprint indicate different types of correspondence between the search fingerprint and the reference fingerprint, calculation of derived virtual quality parameters, and consideration of the virtual quality parameters in computing a similarity score enables a stronger matching accuracy between the search fingerprint and the reference fingerprint.
System Architecture
FIG. 1 is a block diagram of an exemplary automatic fingerprint identification system 100. Briefly, the automatic fingerprint identification system 100 may include a computing device including a memory device 110, a processor 115, a presentation interface 120, a user input interface 130, and a communication interface 135. The automatic fingerprint identification system 100 may be configured to facilitate and implement the methods described through this specification. In addition, the automatic fingerprint identification system 100 may incorporate any suitable computer architecture that enables operations of the system described throughout this specification.