The goal of forensic dentistry is to identify individuals based on their dental characteristics. In this chapter, we present a system for automating that process by identifying people from dental x-ray images. Given a dental record 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 representative feature vectors for each tooth, which are later used for retrieval. We developed a new method for teeth segmentation and three different methods for representing and matching teeth. The system relies on the three different types of dental radiographs for identification. The identification procedure is carried out by integrating the results of using an individual’s three available types of dental radiographs. In this chapter, we address the problem of identifying individuals based on more than one type of dental radiographs for the first time, where three available types of dental radiographs are used. The experimental results show that using the three types of dental radiographs enhances the overall human identification procedure. Also, the experimental results of the different modules and the results of fusing the matching techniques are presented. To increase the accuracy of the identification process, the three matching techniques are fused together to improve the overall performance. We introduce some scenarios for fusing the three matchers at the score level as well as at the decision level.
|Original language||English (US)|
|Title of host publication||Case Studies in Intelligent Computing|
|Subtitle of host publication||Achievements and Trends|
|Number of pages||34|
|State||Published - Jan 1 2014|
ASJC Scopus subject areas
- Computer Science(all)