We present in this paper a sample quality control approach for the case using a mobile phone’s camera as a fingerprintsensor for fingerprint recognition. Our approach directly estimates the maximum ridge frequency orientation by theamplitude-frequency features of the Fast Fourier Transform and takes the frequency features’ difference in twoperpendicular orientations as a distinguishing feature for ridge-like patterns. Then a decision criterion which combinesthe frequency components’ energy and ridge orientation features is used to determine if an image block should beclassified as high-quality fingerprint area or not. The number of such high-quality blocks can thus be used to indicate thewhole fingerprint sample’s quality. Experiments show this approach's effectiveness in distinguishing the high-qualityblocks from other low-quality ones or background area. Mapping the quality metric to the sample utility as derived fromthe the NIST minutiae extractor "mindtct" function is also given to verify the approach's quality prediction effectiveness.
展开▼
