Fingerprint representation using localized texture features

Abstract

A system and method for processing fingerprints includes representing each minutiae in a fingerprint by determining quantized Gabor coefficients to represent texture content of the minutiae. A distance is computed between represented minutiae and stored minutiae. The minutiae matches are ranked based on the distance to identify the fingerprint.

1 . A method for processing fingerprints, comprising:
 representing each minutiae in a fingerprint by determining quantized Gabor coefficients to represent texture content of the minutiae;   computing a distance between represented minutiae and stored minutiae; and   ranking minutiae matches based on the distance to identify the fingerprint.   
     
     
         2 . The method as recited in  claim 1 , further comprising pooling evidence related to the fingerprint to assist in confirming the identity. 
     
     
         3 . The method as recited in  claim 1 , wherein computing includes computing a Hamming distance. 
     
     
         4 . The method as recited in  claim 1 , further comprising listing candidate identities based on a score. 
     
     
         5 . The method as recited in  claim 1 , wherein representing includes computing Gabor elementary function coefficients and the minutiae are represented using the coefficients. 
     
     
         6 . The method as recited in  claim 1 , further comprising optimizing the Gabor coefficients using a gradient descent approach. 
     
     
         7 . The method as recited in  claim 1 , further comprising reducing the number of Gabor coefficients to reduce the representative size of the print. 
     
     
         8 . The method as recited in  claim 1 , wherein representing includes representing each minutiae based on a 32 by 32 neighborhood of pixels. 
     
     
         9 . A method for processing fingerprints, comprising:
 inputting a fingerprint image;   identifying minutiae in the fingerprint image;   computing Gabor coefficients to represent texture content of each minutiae in the fingerprint; and   quantizing the Gabor coefficients for storage in memory.   
     
     
         10 . The method as recited in  claim 9 , further comprising storing evidence related to the fingerprint to assist in confirming the identity. 
     
     
         11 . The method as recited in  claim 9 , wherein computing Gabor coefficients includes optimizing Gabor coefficients using a gradient descent approach. 
     
     
         12 . The method as recited in  claim 9 , further comprising reducing the number of coefficients to reduce the representative size of the fingerprints. 
     
     
         13 . The method as recited in  claim 9 , wherein each minutiae in the image is represented by a 32 by 32 neighborhood of pixels. 
     
     
         14 . The method as recited in  claim 9 , wherein the memory includes a database and further comprising the association of an identity with a quantized representation of the fingerprint image in the database. 
     
     
         15 . A computer program product for processing fingerprints comprising a computer useable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform the steps of  claim 9 . 
     
     
         16 . A computer program product for processing fingerprints comprising a computer useable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform the steps of:
 representing each minutiae in a fingerprint by determining quantized Gabor coefficients to represent texture content of the minutiae;   computing a distance between represented minutiae and stored minutiae; and   ranking matches based on the distance to identify the fingerprint.   
     
     
         17 . A system for processing fingerprints, comprising:
 an input device configured to receive fingerprint images;   an extraction module configured to determine minutiae in the fingerprint;   a representation module configured to compute Gabor coefficients to represent texture content for each minutiae to represent the fingerprint; and   a comparing module for computing a distance between represented minutiae in the fingerprint and stored minutiae in memory to rank matches based on the distance to associate an identify with the fingerprint.   
     
     
         18 . The system as recited in  claim 17 , wherein computing includes computing a Hamming distance. 
     
     
         19 . The system as recited in  claim 17 , wherein the Gabor coefficients are optimized using a gradient descent approach. 
     
     
         20 . The system as recited in  claim 17 , wherein the system is a scalable 1:N identification system.