Omaima Nomir

A system for human identification from X-ray dental radiographs

Forensic odontology is the branch of forensics that deals with human identification based on dental features. In this paper, we present a system for automating that process by identifying people from dental X-ray images. Given a dental image of a postmortem (PM), the proposed system retrieves the best matches from an antemortem (AM) database. The system automatically segments dental X-ray images into individual teeth and extracts the contour of each tooth. Features are extracted from each tooth and are used for retrieval. We developed a new method for teeth separation based on integral projection. We also developed a new method for representing and matching teeth contours using signature vectors obtained at salient points on the contours of the teeth. During retrieval, the AM radiographs that have signatures closer to the PM are found and presented to the user. Matching scores are generated based on the distance between the signature vectors of AM and PM teeth. Experimental results on a small database of dental radiographs are encouraging.

Human Identification From Dental X-Ray Images Based on the Shape and Appearance of the Teeth

Dental biometrics deal with human identification from dental characteristics. In this paper, we present a new technique for identifying people based upon shapes and appearances of their teeth from dental X-ray radiographs. The new technique represents each tooth by a feature vector obtained from the forcefield energy function of the grayscale image of the tooth and Fourier descriptors of the contour of the tooth. The feature vector is composed of the distances between a small number of potential energy wells as well as a small number of Fourier descriptors. Given a query image (i.e., postmortem radiograph), each tooth is matched with the archived teeth in the database (antemortem radiographs) that have the same tooth number. Then, voting is used to obtain a list of best matches for the query image based upon the matching results of the individual teeth. Our goal of using appearance and shape-based features together is to overcome the drawback of using only the contour of the tooth, which can be strongly affected by the quality of the images. The experimental results on a database of 162 antemortem images show that our method is effective in identifying individuals based on their dental radiographs

Hierarchical contour matching for dental X-ray radiographs

The goal of forensic dentistry is to identify individuals based on their dental characteristics. In this paper we present a new algorithm for human identification from dental X-ray images. The algorithm is based on matching teeth contours using hierarchical chamfer distance. The algorithm applies a hierarchical contour matching algorithm using multi-resolution representation of the teeth. Given a dental record, usually a postmortem (PM) radiograph, first, the radiograph is segmented and a multi-resolution representation is created for each PM tooth. Each tooth is matched with the archived antemortem (AM) teeth, which have the same tooth number, in the database using the hierarchical algorithm starting from the lowest resolution level. At each resolution level, the AM teeth are arranged in an ascending order according to a matching distance and 50% of the AM teeth with the largest distances are discarded and the remaining AM teeth are marked as possible candidates and the matching process proceeds to the following (higher) resolution level. After matching all the teeth in the PM image, voting is used to obtain a list of best matches for the PM query image based upon the matching results of the individual teeth. Analysis of the time complexity of the proposed algorithm prove that the hierarchical matching significantly reduces the search space and consequently the retrieval time is reduced. The experimental results on a database of 187 AM images show that the algorithm is robust for identifying individuals based on their dental radiographs.

Towards an Automated Dental Identification System (ADIS)

This paper addresses the problem of developing an automated system for postmortem identification using dental records. The Automated Dental Identification System (ADIS) can be used by law enforcement agencies to locate missing persons using databases of dental x-rays. Currently, this search and identification process is carried out manually, which makes it very time-consuming and unreliable. In this paper, we propose architecture for ADIS, we define the functionality of its components, and we briefly describe some of the techniques used in realizing these components.

Toward an automated dental identification system

Forensic odontology has long been carried out by forensic experts of law enforcement agencies for postmortem identification. We address the problem of developing an automated system for postmortem identification using dental records (dental radiographs). This automated dental identification system (ADIS) can be used by law enforcement agencies as well as military agencies throughout the United States to locate missing persons using databases of dental x rays of human remains and dental scans of missing or wanted persons. Currently, this search and identification process is carried out manually, which makes it very time-consuming in mass disasters. We propose a novel architecture for ADIS, define the functionality of its components, and describe the techniques used in realizing these components. We also present the performance of each of these components using a database of dental images.

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.

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.