Real Fingerprint Detection System (RFDS) Based on Image Quality Measures and Six Classifiers

Fingerprint detection in biometrics is an important field of study in our new modern world, many forensic departments around the world use fingerprints as the key to detect criminals and bring them justice. To improve the accuracy of fingerprint detection system we implemented a Real Fingerprint Detection System (RFDS) that has high performance level of detecting real and fake fingerprint images. In this thesis, we present an RFDS system based on image quality measures (IQM’s) to detect real fingerprint images and fake fingerprint images. We performed different RFDS experiments with 25, 10, 15, and 5 IQM’s; they showed sufficient quality of real and fake fingerprint images detection. We compared our RFDS using 25, 15, 10, and 5 IQM’s with RFDS that has used 25 IQMs. Based on the comparison in this thesis we can conclude that the best result from all these RFDS is the one with 25 IQMs, because it’s HTER score is the minimum one with 0.3%, and the worst RFDS is the one with the 15 IQMs which has the maximum HTER score with 14.8%. Keywords: Biometrics, Image Quality Measure, Real and Fake Fingerprint Image, Classifier.