22 research outputs found
Recommended from our members
Hierarchical Dental X-Ray Radiographs Matching
The goal of forensic dentistry is to identify individuals based on their dental characteristics. In this paper we present a new matching technique for identifying missing, and wanted individuals from their dental X-ray records. Given a dental record, usually a postmortem (PM) radiograph, the proposed technique searches a database of ante mortem (AM) radiographs and retrieves the best matches from the database. The technique is based on matching teeth contours using hierarchical Chamfer distance. The proposed technique has two main stages: feature extraction, and teeth matching. During retrieval, according to a matching distance between the AM and PM teeth, AM radiographs that are most similar to a given PM image, are found and presented to the user. The experimental results on a database of 162 AM images show that the technique is robust for identifying individuals based on their dental records
Combining Matching Algorithms for Human Identification using Dental X-Ray Radiographs
The goal of forensic dentistry is to identify individuals based on their dental characteristics. In this paper we present a system for identifying individuals from their dental X-ray records. Given a dental record, usually a postmortem (PM) radiograph, the system searches a database of ante mortem (AM) radiographs and retrieves the best matches from the database. The system automatically segments dental X-ray images into individual teeth and extracts representative feature vectors for each tooth, which are later used for retrieval. The system integrates one method for teeth segmentation, and two different methods for representing and matching teeth. The first matching method represents each tooth contour by 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. Given a query PM image, and according to a matching distance, AM radiographs that are most similar to the PM image, are found and presented to the user using the two matching methods. The experimental results show that the system is robust. We studied the performance of the different modules of the system as well as the results effusing the matching techniques
Recommended from our members
Fusion of Matching Algorithms for Human Identification Using Dental X-Ray Radiographs
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
Recommended from our members
Challenges of developing an automated dental identification system
Law enforcement agencies have been exploiting biometric identifiers for decades as key tools in forensic identification. A biometric identifier has to resist the early decay that affects body tissues. Because of their survivability and diversity, the best candidates for postmortem biometric identification are the dental features. In this paper, we present an overview of ADIS (automated dental identification system). We also present a new fully automated algorithm for identifying people from dental X-ray images as one of ADIS components. The algorithm automatically archives AM (antemortem) dental photographs by extracting teeth shapes and storing them in a database. Given a dental image of a PM (postmortem), the proposed algorithm retrieves the best matches from the databas