Challenges of Developing an Automated Dental Identification System

Abdel-Mottaleb, Mohamed; Nomir, Omaima; Nassar, Diaa Eldin M.; Fahmy, Gamal; Ammar, H.H.

doi:10.1109/mwscas.2003.1562306

Cited by 48 publications

(34 citation statements)

References 3 publications

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“…Creating a fully automated computer-based system for human identification based on dental X-ray images has only been a focus of research for a little over a decade. Nassar et al [1], Fahmy et al [2] and Abdel-Mottaleb et al [3] outline the general components of what they define as an Automated Dental Identification System (ADIS) and the most important challenges of developing such a system. The initial research toward defining the ADIS [2], [3] states that the system should take as input a dental record consisting of one or more images and other pertinent information.…”

Section: B State-of-the-artmentioning

confidence: 99%

“…Some authors [3], [19] propose a segmentation method based on masking the image by the result of iterative thresholding followed by adaptive thresholding. This method has been used extensively by other authors [8], [11], [14], [20], [21], [22], [23], [24].…”

Section: ) Enhancementmentioning

confidence: 99%

“…One of the earliest fully automatic and most cited ap-proaches is that of integral intensity projection for both jaw and teeth separation [3].…”

Section: ) Enhancementmentioning

confidence: 99%

“…Though there are many who cite this approach, few give good explanations of how to consistently find the correct valleys for the teeth separation lines. Abdel-Mottaleb et al [3] use a threshold to find the valleys in the diagram of the vertical sums. Jain et al [27] states that the valleys are used, but not specifically how these valleys are found, leading to the assumption that they are either detected by threshold or manually specified.…”

Section: ) Enhancementmentioning

confidence: 99%

“…Abdel-Mottaleb et al [3] introduce a method based on salient points taken from high curvature areas of the contour. These points are then related to other salient points by distance and the signature vector.…”

Section: ) Feature Extraction and Matchingmentioning

confidence: 99%

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Automated Dental Identification with Lowest Cost Path-Based Teeth and Jaw Separation

Ølberg

Goodwin

2016

Scandinavian Journal of Forensic Science

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Abstract:Teeth are some of the most resilient tissues of the human body. Because of their placement, teeth often yield intact indicators even when other metrics, such as finger prints and DNA, are missing. Forensics on dental identification is now mostly manual work which is time and resource intensive. Systems for automated human identification from dental X-ray images have the potential to greatly reduce the necessary efforts spent on dental identification, but it requires a system with high stability and accuracy so that the results can be trusted. This paper proposes a new system for automated dental X-ray identification. The scheme extracts tooth and dental work contours from the X-ray images and uses the Hausdorff-distance measure for ranking persons. This combination of state-of-the-art approaches with a novel lowest cost path-based method for separating a dental X-ray image into individual teeth, is able to achieve comparable and better results than what is available in the literature. The proposed scheme is fully functional and is used to accurately identify people within a real dental database. The system is able to perfectly separate 88.7% of the teeth in the test set. Further, in the verification process, the system ranks the correct person in top in 86% of the cases, and among the top five in an astonishing 94% of the cases. The approach has compelling potential to significantly reduce the time spent on dental identification. Keywords:Path-finding, Human dental identification 44Copyright© Holstad Grafisk, Oslo -Print: prografia, Oslo -ISSN 1503-9552 FORENSIC SCIENCE Scandinavian journal of Nordisk rettsmedisinThe new separation method has the benefit of being able to recover from poor starting conditions, making it robust in cases where the teeth in the image are severely rotated or oddly shaped. A. Problem StatementThe ultimate goal of this work is to create an improved ADIS with new innovative methods as well as methods from related research. As part of the path towards this goal a few hypotheses will be tested. These can be listed as follows.1) It is possible to identify the persons in the data set using only tooth and dental work contour information extracted from the dental X-ray images.The particular combination of techniques and methods applied in this work has not been used to solve this problem before. This hypothesis helps find how the whole system performs with regards to ranking and retrieval accuracy.2) Pathfinding can be used effectively for separating teeth and jaws in dental X-ray images.The separation of dental X-ray images into smaller images each containing a single tooth is a significant problem during feature extraction from such images. B. OutlineFollowing the introduction, section II describes the previous work in the field. The proposed approach is presented in sec-tion III. Testing of both the new method and the methodology as a whole, with discussion, can be found in section IV. Subsequently, the conclusion is presented with a few thoughts on further work.

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Section: B State-of-the-artmentioning

confidence: 99%