DocumentCode
1943618
Title
Dental Biometrics: Alignment and Matching of Dental Radiographs
Author
Chen, Hong ; Jain, Anil K.
Author_Institution
Dept. of Comput. Sci. & Eng., Michigan State Univ., East Lansing, MI
Volume
1
fYear
2005
fDate
5-7 Jan. 2005
Firstpage
316
Lastpage
321
Abstract
Dental biometrics utilizes the evidence revealed by dental radiographs for human identification. This evidence includes the tooth contours, the relative positions of neighboring teeth, and the shapes of the dental work (e.g., crowns, fillings and bridges). The proposed system has two main stages: feature extraction, and matching. The feature extraction stage uses anisotropic diffusion to enhance the images and a mixture of Gaussians model to segment the dental work. The matching stage has three sequential steps: shape registration, computation of image similarity, and subject identification. In shape registration, we align the tooth contours and obtain the distance between them. A second method based on overlapped areas is used to match the dental work. The distance between the shapes of the teeth and the distance between the shapes of the dental work are then combined using likelihood estimates to improve the retrieval accuracy. At the second step, the correspondence of teeth between two given images is established. A distance measure based on this correspondence is then used to represent the similarity between the two images. Finally, the distances are used to infer the subject´s identity.
Keywords
Gaussian processes; biometrics (access control); dentistry; diagnostic radiography; feature extraction; image matching; image registration; medical image processing; Gaussians model; dental biometrics; feature extraction; image enhancement; image matching; image similarity; radiograph alignment; radiograph matching; shape registration; subject identification; tooth contours; Anisotropic magnetoresistance; Biometrics; Bridges; Dentistry; Feature extraction; Filling; Humans; Radiography; Shape; Teeth;
fLanguage
English
Publisher
ieee
Conference_Titel
Application of Computer Vision, 2005. WACV/MOTIONS '05 Volume 1. Seventh IEEE Workshops on
Conference_Location
Breckenridge, CO
Print_ISBN
0-7695-2271-8
Type
conf
DOI
10.1109/ACVMOT.2005.41
Filename
4129497
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