dc.contributor.author | Ali, Hafsa Moontari | |
dc.contributor.author | Corraya, Sonia | |
dc.date.accessioned | 2018-03-18T07:33:03Z | |
dc.date.available | 2018-03-18T07:33:03Z | |
dc.date.issued | 2/21/2017 | |
dc.identifier.citation | Ali, H. M., & Corraya, S. (2017). Line profile-based fingerprint matching. Paper presented at the IWCI 2016 - 2016 International Workshop on Computational Intelligence, 115-119. 10.1109/IWCI.2016.7860350 | en_US |
dc.identifier.isbn | 9.78151E+12 | |
dc.identifier.uri | http://hdl.handle.net/10361/9666 | |
dc.description | This conference paper was published in the IWCI 2016 - 2016 International Workshop on Computational Intelligence [© 2016 IEEE.] and the definitive version is available at: http://doi.org/10.1109/IWCI.2016.7860350 The Journal's website is at: http://ieeexplore.ieee.org/document/7860350/?reload=true | en_US |
dc.description.abstract | Traditional fingerprint matching algorithms primarily focus on minutiae points on fingertip surface. In this paper, a novel approach is proposed for fingerprint matching that is based on ridge and valley characteristics of fingerprints. At first, the input fingerprint image is normalized and the registration point of that particular fingerprint is detected. Then a line profile is generated centering on that reference point. The distances between the reference point and ridges and the count of intersection points of line profile and ridges are stored in database. This process is repeated after every 15-degree angle to 345-degree in clock-wise direction and for orientation angle, the distances are stored sequentially. For matching intersection point count number along with the sequence of distance values are compared with the stored values. This new method can detect fingerprint from any orientation angle. Experimental result shows 90.87% accuracy of the proposed method. | en_US |
dc.language.iso | en | en_US |
dc.publisher | © 2017 Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.uri | http://ieeexplore.ieee.org/document/7860350/?reload=true | |
dc.subject | Fingerprint match | en_US |
dc.subject | Line profile | en_US |
dc.subject | Registration point | en_US |
dc.subject | Ridge line | en_US |
dc.subject | Biometrics | en_US |
dc.title | Line profile-based fingerprint matching | en_US |
dc.type | Conference paper | en_US |
dc.description.version | Published | |
dc.contributor.department | Department of Computer Science and Engineering, BRAC University | |
dc.identifier.doi | http://doi.org/10.1109/IWCI.2016.7860350 | |