Dental records have been widely used as tools in forensic identification. With the vast volume of cases that need to be investigated by forensic odontologists, a move towards a computer-aided dental identification system is necessary. We propose a computer-aided framework for efficient matching of dental x-rays for human identification purposes. Given a dental x-ray with a marked region of interest (ROI), we search the database of x-rays (presumed to be taken from known individuals) to retrieve a closest match. In this work we use a slightly extended Weighted Sum of Squared Differences (SSD) cost function to express the degree of similarity/overlap between two dental radiographs. Unlike other iterative Least Squares methods that use local information for gradient-based optimization, our method finds the globally optimal translation. In 90% of the identification trials, our method ranked the correct match in the top 10% using a database of 571 images. Experiments indicate that matching dental records using the extended SSD cost function is a viable method for human dental identification.
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