Teeth Segmentation and Feature Extraction for Odontological Biometrics. / Mairaj, Danish; Busch, Christoph; Wolthusen, Stephen D.

Proceedings of the 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing. IEEE Computer Society Press, 2010. p. 323-328.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Published

Standard

Teeth Segmentation and Feature Extraction for Odontological Biometrics. / Mairaj, Danish; Busch, Christoph; Wolthusen, Stephen D.

Proceedings of the 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing. IEEE Computer Society Press, 2010. p. 323-328.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Mairaj, D, Busch, C & Wolthusen, SD 2010, Teeth Segmentation and Feature Extraction for Odontological Biometrics. in Proceedings of the 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing. IEEE Computer Society Press, pp. 323-328. https://doi.org/10.1109/IIHMSP.2010.86

APA

Mairaj, D., Busch, C., & Wolthusen, S. D. (2010). Teeth Segmentation and Feature Extraction for Odontological Biometrics. In Proceedings of the 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (pp. 323-328). IEEE Computer Society Press. https://doi.org/10.1109/IIHMSP.2010.86

Vancouver

Mairaj D, Busch C, Wolthusen SD. Teeth Segmentation and Feature Extraction for Odontological Biometrics. In Proceedings of the 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing. IEEE Computer Society Press. 2010. p. 323-328 https://doi.org/10.1109/IIHMSP.2010.86

Author

Mairaj, Danish ; Busch, Christoph ; Wolthusen, Stephen D. / Teeth Segmentation and Feature Extraction for Odontological Biometrics. Proceedings of the 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing. IEEE Computer Society Press, 2010. pp. 323-328

BibTeX

@inproceedings{65a7fdb6116c4050b6370eff2af238a2,
title = "Teeth Segmentation and Feature Extraction for Odontological Biometrics",
abstract = "During the past few years, advancements in high end computers and sensor techniques made it possible to develop a real-time odontological biometric identification and verification system apart from the existing offline forensic odontological systems. However, this requires highly automated teeth image segmentation and feature extraction algorithms. In this paper, we propose a novel non-forensic biometric technique, employing 3D optical sensors for data acquisition and representing it as 3D surface meshes (stereo lithography format). Initially, feature regions are estimated using geometric curvature information and principal component analysis. Subsequently, active contours optimize these feature regions to segment exactly each tooth surface. Finally, a feature vector is computed for the set of teeth which is derived from the relative position and tilt orientation of each tooth relative to a well defined reference system.",
author = "Danish Mairaj and Christoph Busch and Wolthusen, {Stephen D.}",
year = "2010",
month = oct,
doi = "10.1109/IIHMSP.2010.86",
language = "English",
isbn = "978-1-4244-8378-5",
pages = "323--328",
booktitle = "Proceedings of the 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing",
publisher = "IEEE Computer Society Press",

}

RIS

TY - GEN

T1 - Teeth Segmentation and Feature Extraction for Odontological Biometrics

AU - Mairaj, Danish

AU - Busch, Christoph

AU - Wolthusen, Stephen D.

PY - 2010/10

Y1 - 2010/10

N2 - During the past few years, advancements in high end computers and sensor techniques made it possible to develop a real-time odontological biometric identification and verification system apart from the existing offline forensic odontological systems. However, this requires highly automated teeth image segmentation and feature extraction algorithms. In this paper, we propose a novel non-forensic biometric technique, employing 3D optical sensors for data acquisition and representing it as 3D surface meshes (stereo lithography format). Initially, feature regions are estimated using geometric curvature information and principal component analysis. Subsequently, active contours optimize these feature regions to segment exactly each tooth surface. Finally, a feature vector is computed for the set of teeth which is derived from the relative position and tilt orientation of each tooth relative to a well defined reference system.

AB - During the past few years, advancements in high end computers and sensor techniques made it possible to develop a real-time odontological biometric identification and verification system apart from the existing offline forensic odontological systems. However, this requires highly automated teeth image segmentation and feature extraction algorithms. In this paper, we propose a novel non-forensic biometric technique, employing 3D optical sensors for data acquisition and representing it as 3D surface meshes (stereo lithography format). Initially, feature regions are estimated using geometric curvature information and principal component analysis. Subsequently, active contours optimize these feature regions to segment exactly each tooth surface. Finally, a feature vector is computed for the set of teeth which is derived from the relative position and tilt orientation of each tooth relative to a well defined reference system.

U2 - 10.1109/IIHMSP.2010.86

DO - 10.1109/IIHMSP.2010.86

M3 - Conference contribution

SN - 978-1-4244-8378-5

SP - 323

EP - 328

BT - Proceedings of the 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing

PB - IEEE Computer Society Press

ER -