A framework for estimating probability of a match in forensic bite mark identification.

In forensic dentistry, a human expert typically does the comparison and identification based on bite marks. Unlike DNA analysis, however, there is no quantitative basis with which to assign a probability for this given match. This paper proposes a framework for empirically estimating the probability of such a bite mark match and reports on initial experimental results. The methodology involved collection of dental population data (3D dental casts and bite mark images), image analysis for quantitatively measuring the degree of match (based on chamfer distance), and performing a logistic regression analysis using the collected population data to estimate the probability of match from the calculated degree of match. The model correctly predicted 35 of the 42 matches and 585 of the 588 mismatches. The method also has potential for use in other forensic applications in which the assignment of quantitative probabilities is important.