A large-scale statistical analysis of barefoot impressions.

In an earlier paper, outlines of footprints of persons walking normally were studied to determine whether different people make verifiably distinct footprints. Our basic null hypothesis is: given a footprint outline trace made by Subject A (Alice), then Subject B (Bob), a distinct person, cannot produce a footprint outline trace indistinguishable from that of Alice. We showed in the previous work that the probability of a chance match is less than 10(-8). In this paper we report two new advances in our research. First, we establish a rigorous mathematical framework for calculating worstcase and average chance-match probabilities. Second, we repeat the previous experiment to substantiate the earlier results, but with an expanded population sample size and a more representative and significantly bigger repeated sample. These improvements and a new automated tracing procedure for extracting all numerical measures lead to a sharpened accuracy with average chance match probabilities of 7.88 x 10-(10) for a general population. In other words, the odds of a chance match are one in 1.27 billion.

Statistical analysis of barefoot impressions.

Comparison of the shapes of barefoot impressions from an individual with footprints or shoes linked to a crime may be useful as a means of including or excluding that individual as possibly being at the scene of a crime. The question of the distinguishability of a person's barefoot print arises frequently. This study indicates that measurements taken from the outlines of inked footprint impressions show a great degree of variability between donors and a great degree of similarity for multiple impressions taken from the same donor. The normality of the set of measurements on footprint outlines that we have selected for this study is confirmed. A statistical justification for the use of the product rule on individual statistical precisions is developed.