Teeth Image Recognition for Biometrics

Tae-Woo KIM; Tae-Kyung CHO

doi:10.1093/ietisy/e89-d.3.1309

Teeth Image Recognition for Biometrics

Tae-Woo KIM, Tae-Kyung CHO

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This paper presents a personal identification method based on BMME and LDA for images acquired at anterior and posterior occlusion expression of teeth. The method consists of teeth region extraction, BMME, and pattern recognition for the images acquired at the anterior and posterior occlusion state of teeth. Two occlusions can provide consistent teeth appearance in images and BMME can reduce matching error in pattern recognition. Using teeth images can be beneficial in recognition because teeth, rigid objects, cannot be deformed at the moment of image acquisition. In the experiments, the algorithm was successful in teeth recognition for personal identification for 20 people, which encouraged our method to be able to contribute to multi-modal authentication systems.

Publication: IEICE TRANSACTIONS on Information Vol.E89-D No.3 pp.1309-1313

Publication Date: 2006/03/01

Publicized

Online ISSN: 1745-1361

DOI: 10.1093/ietisy/e89-d.3.1309

Type of Manuscript: LETTER

Category: Image Recognition, Computer Vision

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Tae-Woo KIM, Tae-Kyung CHO, "Teeth Image Recognition for Biometrics" in IEICE TRANSACTIONS on Information, vol. E89-D, no. 3, pp. 1309-1313, March 2006, doi: 10.1093/ietisy/e89-d.3.1309.
Abstract: This paper presents a personal identification method based on BMME and LDA for images acquired at anterior and posterior occlusion expression of teeth. The method consists of teeth region extraction, BMME, and pattern recognition for the images acquired at the anterior and posterior occlusion state of teeth. Two occlusions can provide consistent teeth appearance in images and BMME can reduce matching error in pattern recognition. Using teeth images can be beneficial in recognition because teeth, rigid objects, cannot be deformed at the moment of image acquisition. In the experiments, the algorithm was successful in teeth recognition for personal identification for 20 people, which encouraged our method to be able to contribute to multi-modal authentication systems.
URL: https://globals.ieice.org/en_transactions/information/10.1093/ietisy/e89-d.3.1309/_p

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@ARTICLE{e89-d_3_1309,
author={Tae-Woo KIM, Tae-Kyung CHO, },
journal={IEICE TRANSACTIONS on Information},
title={Teeth Image Recognition for Biometrics},
year={2006},
volume={E89-D},
number={3},
pages={1309-1313},
abstract={This paper presents a personal identification method based on BMME and LDA for images acquired at anterior and posterior occlusion expression of teeth. The method consists of teeth region extraction, BMME, and pattern recognition for the images acquired at the anterior and posterior occlusion state of teeth. Two occlusions can provide consistent teeth appearance in images and BMME can reduce matching error in pattern recognition. Using teeth images can be beneficial in recognition because teeth, rigid objects, cannot be deformed at the moment of image acquisition. In the experiments, the algorithm was successful in teeth recognition for personal identification for 20 people, which encouraged our method to be able to contribute to multi-modal authentication systems.},
keywords={},
doi={10.1093/ietisy/e89-d.3.1309},
ISSN={1745-1361},
month={March},}

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TY - JOUR
TI - Teeth Image Recognition for Biometrics
T2 - IEICE TRANSACTIONS on Information
SP - 1309
EP - 1313
AU - Tae-Woo KIM
AU - Tae-Kyung CHO
PY - 2006
DO - 10.1093/ietisy/e89-d.3.1309
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E89-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2006
AB - This paper presents a personal identification method based on BMME and LDA for images acquired at anterior and posterior occlusion expression of teeth. The method consists of teeth region extraction, BMME, and pattern recognition for the images acquired at the anterior and posterior occlusion state of teeth. Two occlusions can provide consistent teeth appearance in images and BMME can reduce matching error in pattern recognition. Using teeth images can be beneficial in recognition because teeth, rigid objects, cannot be deformed at the moment of image acquisition. In the experiments, the algorithm was successful in teeth recognition for personal identification for 20 people, which encouraged our method to be able to contribute to multi-modal authentication systems.
ER -