Dental biometrics: Human identification based on teeth and dental works in bitewing radiographs

Authors:
Phen-Lan Lin;Yan-Hao Lai;Po-Whei Huang
Affiliations:
Department of Computer Science and Information Engineering, Providence University, Shalu, Taichung 43301, Taiwan, ROC;Department of Computer Science and Engineering, National Chung Hsing University, 250 Kuo Kuang Rd., Taichung 40227, Taiwan, ROC;Department of Computer Science and Engineering, National Chung Hsing University, 250 Kuo Kuang Rd., Taichung 40227, Taiwan, ROC
Venue:
Pattern Recognition
Year:
2012

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Abstract

This paper presents an enhanced dental identification method based on both the contours of teeth and dental works. To reduce the alignment error caused from unreliable contours, we propose a point-reliability measuring method and weigh each point based on its reliability when calculating the Hausdorff distance (HD) between the contours. For reducing the alignment error caused from incomplete tooth contours, we propose an outlier detection method to prune the outliers from each contour and realign the pruned contours. And for compensating the error when matching with the spatial feature of dental works due to imperfect alignment of the teeth in which they reside, we propose using an additional alignment-invariant frequency feature of dental works. Experimental results show that our method can achieve (1) 94.3% and 100% image retrieval accuracy of the top-1 and -5 retrievals, respectively, when matching with the weighted HD for the pruned contour of a single tooth; (2) 100% accuracy of top-2 (top 6%) image retrievals when matching with both contours of teeth and dental works.