Fingerprint presentation attack detection utilizing spatio-temporal features Articles uri icon

publication date

  • March 2021

start page

  • 2059


  • 6


  • 21

International Standard Serial Number (ISSN)

  • 1424-3210

Electronic International Standard Serial Number (EISSN)

  • 1424-8220


  • This paper presents a novel mechanism for fingerprint dynamic presentation attack detec-tion. We utilize five spatio-temporal feature extractors to efficiently eliminate and mitigate different presentation attack species. The feature extractors are selected such that the fingerprint ridge/valley pattern is consolidated with the temporal variations within the pattern in fingerprint videos. An SVM classification scheme, with a second degree polynomial kernel, is used in our presentation attack detection subsystem to classify bona fide and attack presentations. The experiment protocol and evaluation are conducted following the ISO/IEC 30107-3:2017 standard. Our proposed approach demonstrates efficient capability of detecting presentation attacks with significantly low BPCER where BPCER is 1.11% for an optical sensor and 3.89% for a thermal sensor at 5% APCER for both.


  • Electronics


  • anti-spoofing; fingerprint; presentation attack; presentation attack detection