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.     

A Study of the Human Decomposition Sequence in Central Texas*

Abstract: Decomposition studies utilizing nonhuman subjects as human analogues are well established, but fewer studies utilizing intact human remains exist. This study provides data from a controlled decomposition study involving human remains in Central Texas. A 63.5‐kg unmodified cadaver was placed in an open‐air site and observed over a 10‐week period from April 11 through June 19, 2008. A wire enclosure restricted scavenger access. State of decomposition and environmental conditions were recorded daily for the first 36 days and then every 2 weeks thereafter. Results indicated a high degree of correlation with other decomposition studies originating in the southwestern United States, although slight deviations for the average duration of early events were noted. The data were also utilized to test a quantitative method for estimating the postmortem interval. Results indicated preliminary support for a quantitative approach. Additional research is encouraged to further establish the human decomposition data set for Central Texas.