Semester
Fall
Date of Graduation
2012
Document Type
Thesis
Degree Type
MS
College
Statler College of Engineering and Mineral Resources
Department
Lane Department of Computer Science and Electrical Engineering
Committee Chair
Arun A. Ross
Committee Co-Chair
Donald Adjeroh
Committee Member
Katerina Goseva-Popstojanova.
Abstract
Fingerprint is a biometric trait that is widely used for human identification and verification. Most fingerprint biometric systems make use of certain salient features on the fingerprint, including minutiae points, pores, and singular points, for comparing two fingerprint images. In this work, we explore the possibility of using fingerprint creases for comparing two fingerprints. Creases can be described as white lines or scars on a fingerprint image. Recent studies have determined that some creases are genetically influenced although the origin of creases has not been completely characterized. While no published work exists for crease matching, some studies have explored the problem of automated crease detection. In this thesis, we study the possibility of using creases for fingerprint matching. We also suggest two techniques to automatically extract creases from an input fingerprint image. Finally, we study the correlation between fingerprint creases and age of an individual.
Recommended Citation
Laseinde, Olaoluwa Peter, "Analysis and detection of fingerprint creases" (2012). Graduate Theses, Dissertations, and Problem Reports. 434.
https://researchrepository.wvu.edu/etd/434