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Fingerprints are rich in details which are in the form of discontinuities in ridges known as minutiae which are unique for each person. The main desire of this book is to implement and evaluate National Institute of Science and Technology (NIST) Biometric Image Software (NBIS) for fingerprint recognition through extracting minutiae and matching the minutiae in MATLAB environment. Minutiae extraction and minutiae matching algorithms are in C-language and are interfaced with MATLAB using MEX-Files. A function is developed with NBIS for performing pre-processing and post-processing operations on the grayscale fingerprint images to extract good minutiae. The extracted minutiae are passed through the function with NBIS that match two minutiae patterns and produce a match score. Finally the performance of the system is evaluated on various fingerprint databases from different people and results are presented in Receiver Operating characteristics (ROC) graphs.
Fingerprints are rich in details which are in the form of discontinuities in ridges known as minutiae. The main purpose of this book is to implement and evaluate National Institute of Standards and Technology (NIST) Biometric Image Software (NBIS) for fingerprint recognition using the system developed in Matlab environment. This is performed by using C- language MEX-files which enables to run original C- language code without reimplementing it as Matlab script. A function is developed with NBIS which helps to extract minutiae from grayscale fingerprint image and match two minutiae patterns to produce a match score. In this work 60 unique users with 8 fingerprints per user i.e., 480 fingerprints had been used for evaluating the system. Scores obtained from minutia matcher after comparing with genuine and imposter matching had been plotted using Receiver Operating Characteristic (ROC) graphs. Finally the performance of the system is evaluated by analyzing plotted ROC graphs. The results obtained by using this functionality can be used for comparing the results obtained with other techniques for measuring the system performance using ROC graphs.
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