Abstract
The goal of forensic dentistry is to identify individuals based on their dental characteristics. In this paper, we introduce a system that uses some scenarios to fuse three matching techniques for identifying individuals based on their dental X-ray images. The system integrates a method for teeth segmentation, and three different methods for representing and matching teeth. The first method for matching antemortem (AM) and postmortem (PM) images represents each tooth contour by a set of signature vectors obtained at salient points on the contour of the tooth. The second method uses hierarchical chamfer distance for matching AM and PM teeth to reduce the search space and accordingly reduce the retrieval time. The third matching method represents each tooth by a small set of features extracted using the forcefield energy function and Fourier descriptors. For each matcher, given a query PM image, AM radiographs that are mostly similar to the PM image, are found and presented to the user. To improve the performance of the system, we present different scenarios to fuse the three matchers. We fuse the matchers using three different approaches at the matching level, the decision level, and using the Bayesian framework. Preliminarily results demonstrate that fusing the matching techniques improves the overall performance of the dental identification system.
| Original language | English |
|---|---|
| Article number | 4472862 |
| Pages (from-to) | 223-233 |
| Number of pages | 11 |
| Journal | IEEE Transactions on Information Forensics and Security |
| Volume | 3 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jun 1 2008 |
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Keywords
- Antemortem (AM) radiographs
- Biometrics
- Dental images
- Force field
- Forensic radiology
- Fourier descriptors
- Fusion
- Human identification
- Image segmentation
- Postmortem (PM) radiographs
ASJC Scopus subject areas
- Computer Networks and Communications
- Safety, Risk, Reliability and Quality
Cite this
Fusion of matching algorithms for human identification using dental X-ray radiographs. / Nomir, Omaima; Abdel-Mottaleb, Mohamed.
In: IEEE Transactions on Information Forensics and Security, Vol. 3, No. 2, 4472862, 01.06.2008, p. 223-233.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Fusion of matching algorithms for human identification using dental X-ray radiographs
AU - Nomir, Omaima
AU - Abdel-Mottaleb, Mohamed
PY - 2008/6/1
Y1 - 2008/6/1
N2 - The goal of forensic dentistry is to identify individuals based on their dental characteristics. In this paper, we introduce a system that uses some scenarios to fuse three matching techniques for identifying individuals based on their dental X-ray images. The system integrates a method for teeth segmentation, and three different methods for representing and matching teeth. The first method for matching antemortem (AM) and postmortem (PM) images represents each tooth contour by a set of signature vectors obtained at salient points on the contour of the tooth. The second method uses hierarchical chamfer distance for matching AM and PM teeth to reduce the search space and accordingly reduce the retrieval time. The third matching method represents each tooth by a small set of features extracted using the forcefield energy function and Fourier descriptors. For each matcher, given a query PM image, AM radiographs that are mostly similar to the PM image, are found and presented to the user. To improve the performance of the system, we present different scenarios to fuse the three matchers. We fuse the matchers using three different approaches at the matching level, the decision level, and using the Bayesian framework. Preliminarily results demonstrate that fusing the matching techniques improves the overall performance of the dental identification system.
AB - The goal of forensic dentistry is to identify individuals based on their dental characteristics. In this paper, we introduce a system that uses some scenarios to fuse three matching techniques for identifying individuals based on their dental X-ray images. The system integrates a method for teeth segmentation, and three different methods for representing and matching teeth. The first method for matching antemortem (AM) and postmortem (PM) images represents each tooth contour by a set of signature vectors obtained at salient points on the contour of the tooth. The second method uses hierarchical chamfer distance for matching AM and PM teeth to reduce the search space and accordingly reduce the retrieval time. The third matching method represents each tooth by a small set of features extracted using the forcefield energy function and Fourier descriptors. For each matcher, given a query PM image, AM radiographs that are mostly similar to the PM image, are found and presented to the user. To improve the performance of the system, we present different scenarios to fuse the three matchers. We fuse the matchers using three different approaches at the matching level, the decision level, and using the Bayesian framework. Preliminarily results demonstrate that fusing the matching techniques improves the overall performance of the dental identification system.
KW - Antemortem (AM) radiographs
KW - Biometrics
KW - Dental images
KW - Force field
KW - Forensic radiology
KW - Fourier descriptors
KW - Fusion
KW - Human identification
KW - Image segmentation
KW - Postmortem (PM) radiographs
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UR - http://www.scopus.com/inward/citedby.url?scp=44049088552&partnerID=8YFLogxK
U2 - 10.1109/TIFS.2008.919343
DO - 10.1109/TIFS.2008.919343
M3 - Article
AN - SCOPUS:44049088552
VL - 3
SP - 223
EP - 233
JO - IEEE Transactions on Information Forensics and Security
JF - IEEE Transactions on Information Forensics and Security
SN - 1556-6013
IS - 2
M1 - 4472862
ER -