On the Effects of Image Quality Degradation on Minutiae- and Ridge-Based Automatic Fingerprint Recognition
This work addresses the problem of improving fingerprint recognition reliability under poor image conditions for security and biometric applications, but it is incremental as it compares existing methods.
The study investigated how image quality degradation affects automatic fingerprint recognition, finding that a ridge-based system is more robust than a minutiae-based system across various quality criteria.
The effect of image quality degradation on the verification performance of automatic fingerprint recognition is investigated. We study the performance of two fingerprint matchers based on minutiae and ridge information under varying fingerprint image quality. The ridge-based system is found to be more robust to image quality degradation than the minutiae-based system for a number of different image quality criteria.