Khutlang, RethabileKhanyile, Nontokozo PMakinana, SisandaNelwamondo, Fulufhelo V2017-06-072017-06-072016-05Khutland, R., Khanyile, N.P., Makinana, S. et al. 2016. High resolution feature extraction from optical coherence tomography acquired internal fingerprint. 2016 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 30 May - 01 Jun 2016, Shanghai, p. 637-642. DOI: 10.1109/SNPD.2016.7515971978-1-5090-0804-9DOI: 10.1109/SNPD.2016.7515971http://ieeexplore.ieee.org/document/7515971/http://hdl.handle.net/10204/9132Copyright: 2016 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract version of the full text item. For access to the full text item, please consult the publisher's website.Biometric fingerprint scanners scan the external skin features onto a 2D image. The performance of the automatic fingerprint identification system suffers if the finger skin is wet, worn out, fake fingerprint is used et cetera. Swept source optical coherence tomography (OCT) can be used to scan the internal skin features, up to the depth of the papillary layer. OCT is contactless and scans in three dimensions. The papillary contour represents an internal fingerprint, which does not suffer external skin problems. In this paper, we present a feature extraction method that extracts features at high resolution from the internal fingerprint. First curvature of an internal fingerprint cross-section is removed by fitting a third order polynomial and shifting each column in depth by the value of the fitted curve. A 2D image of the internal fingerprint is formed by concatenating the individual cross-sections, averaged across the papillary contour. The internal fingerprint image is then enhanced and features are extracted at high resolution. We have evaluated performance of feature extraction by matching extracted minutiae to those extracted manually. Matching accuracy shows that features can be extracted at high resolution from an OCT internal fingerprint.enBiometric fingerprint scannersInformation securityOptical coherence tomographyOCTOCT internal fingerprintsConference PresentationKhutlang, R., Khanyile, N. P., Makinana, S., & Nelwamondo, F. V. (2016). High resolution feature extraction from optical coherence tomography acquired internal fingerprint. IEEE. http://hdl.handle.net/10204/9132Khutlang, Rethabile, Nontokozo P Khanyile, Sisanda Makinana, and Fulufhelo V Nelwamondo. "High resolution feature extraction from optical coherence tomography acquired internal fingerprint." (2016): http://hdl.handle.net/10204/9132Khutlang R, Khanyile NP, Makinana S, Nelwamondo FV, High resolution feature extraction from optical coherence tomography acquired internal fingerprint; IEEE; 2016. http://hdl.handle.net/10204/9132 .TY - Conference Presentation AU - Khutlang, Rethabile AU - Khanyile, Nontokozo P AU - Makinana, Sisanda AU - Nelwamondo, Fulufhelo V AB - Biometric fingerprint scanners scan the external skin features onto a 2D image. The performance of the automatic fingerprint identification system suffers if the finger skin is wet, worn out, fake fingerprint is used et cetera. Swept source optical coherence tomography (OCT) can be used to scan the internal skin features, up to the depth of the papillary layer. OCT is contactless and scans in three dimensions. The papillary contour represents an internal fingerprint, which does not suffer external skin problems. In this paper, we present a feature extraction method that extracts features at high resolution from the internal fingerprint. First curvature of an internal fingerprint cross-section is removed by fitting a third order polynomial and shifting each column in depth by the value of the fitted curve. A 2D image of the internal fingerprint is formed by concatenating the individual cross-sections, averaged across the papillary contour. The internal fingerprint image is then enhanced and features are extracted at high resolution. We have evaluated performance of feature extraction by matching extracted minutiae to those extracted manually. Matching accuracy shows that features can be extracted at high resolution from an OCT internal fingerprint. DA - 2016-05 DB - ResearchSpace DP - CSIR KW - Biometric fingerprint scanners KW - Information security KW - Optical coherence tomography KW - OCT KW - OCT internal fingerprints LK - https://researchspace.csir.co.za PY - 2016 SM - 978-1-5090-0804-9 T1 - High resolution feature extraction from optical coherence tomography acquired internal fingerprint TI - High resolution feature extraction from optical coherence tomography acquired internal fingerprint UR - http://hdl.handle.net/10204/9132 ER -