Automated dental identification system adis
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This research is supported in part by the U.S. National Science Foundation, the research is also supported from the Office of Justice Programs, National Institute of Justice, U.S. Department of Justice. Automated Dental Identification System (ADIS). Overview

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Automated Dental Identification System (ADIS)

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Automated dental identification system adis

This research is supported in part by the U.S. National Science Foundation, the research is also supported from the Office of Justice Programs, National Institute of Justice, U.S. Department of Justice.

Automated Dental Identification System (ADIS)

Overview

In this research we develop state-of-the-art techniques in digital image processing to build a prototype Automated Dental Identification System (ADIS). Given the dental record of a subject, the goal of ADIS is to accurately and timely find a short list of candidates that possess identical, or close, dental features to those of the subject. The forensic expert, then, decides which of the few candidates is the subject.

ADIS is a process automation tool, for postmortem identification, that is being designed to achieve accurate and timely identification results with minimum amount of human intervention. To this end, ADIS will not only automate most of the steps taken by forensic experts to examine MUP cases, it will also be intelligently analyzing radiographs to utilize underlying image structures that are often difficult to be assessed merely by visual examination.

The ADIS project is a collaboration between CJIS personnel, an expert in forensic odontology, and three research teams in WVU, MSU, and UM.

Image Comparison

System

* Completing/Integrating the pre-processing stage

* More testing of the decision-making stage.

* Developing a web-based testing environment to serve all research teams.

DIR prototype

Archiving/Retrieval

Segmentation

Feature-based Matching

Segmentation

Shape-based Matching

Matching

Probability

Preprocessing

Stage

Decision-making

Stage

Requirements Model

- Enhancement

- Segmentation

- Alignment

- Normalization

- Compression

- Feature Extraction

- Decision.


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