Line profile-based fingerprint matching
| bracu.type.group | Research Publications | |
| datacite.rights | Metadata Only | |
| dc.contributor.author | Ali, Hafsa Moontari | |
| dc.contributor.author | Corraya, Sonia | |
| dc.contributor.department | Department of Computer Science and Engineering | |
| dc.date.accessioned | 2026-07-12T10:26:28Z | |
| dc.date.available | 2026-07-12T10:26:28Z | |
| dc.date.issued | 2/21/2017 | |
| 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. | |
| dc.description.version | Published | |
| dc.format.extent | 115-119 | |
| dc.identifier.citation | H. M. Ali and S. Corraya, "Line profile-based fingerprint matching," 2016 International Workshop on Computational Intelligence (IWCI), Dhaka, Bangladesh, 2016, pp. 115-119, doi: 10.1109/IWCI.2016.7860350. | |
| dc.identifier.doi | 10.1109/IWCI.2016.7860350 | |
| dc.identifier.issn | 9.78151E+12 | |
| dc.identifier.other | 2-s2.0-85015912517 | |
| dc.identifier.uri | https://hdl.handle.net/10361/28527 | |
| dc.language.iso | en_US | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.relation.hasversion | 10.1109/IWCI.2016.7860350 | |
| dc.relation.ispartof | Iwci 2016 2016 International Workshop on Computational Intelligence | |
| dc.relation.ispartofseries | Iwci 2016 2016 International Workshop on Computational Intelligence | |
| dc.relation.uri | https://ieeexplore.ieee.org/document/7860350 | |
| dc.rights | FALSE | |
| dc.subject | Biometrics | |
| dc.subject | Fingerprint match | |
| dc.subject | Line profile | |
| dc.subject | Registration point | |
| dc.subject | Ridge line | |
| dc.subject.lcsh | Biometric identification. | |
| dc.subject.lcsh | Pattern Recognition. | |
| dc.subject.lcsh | Biometrics. | |
| dc.title | Line profile-based fingerprint matching | |
| dc.type | Conference Proceedings | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.identifier.scopus-author-id | 57206759948 | |
| person.identifier.scopus-author-id | 57193689667 |