At BTAS'10, a new framework to transform a fingerprint minutiae template into a binary feature vector of fixed
length is described. A fingerprint is characterized by its similarity with a fixed number set of representative local
minutiae vicinities. This approach by representative leads to a fixed length binary representation, and, as the
approach is local, it enables to deal with local distortions that may occur between two acquisitions.
We extend this construction to incorporate additional information in the binary vector, in particular on
localization of the vicinities. We explore the use of position and orientation information. The performance
improvement is promising for utilization into fast identification algorithms or into privacy protection algorithms.
Conference Committee Involvement (2)
Biometric Technology for Human Identification IX
23 April 2012 | Baltimore, Maryland, United States
Biometric Technology for Human Identification VIII
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