Footwear evidence has tremendous forensic value; it can focus a criminal investigation, link suspects to scenes, help reconstruct a series of events, or otherwise provide information vital to the successful resolution of a case. When considering the specific utility of a linkage, the strength of the connection between source footwear and an impression left at the scene of a crime varies with the known rarity of the shoeprint itself, which is a function of the class characteristics, as well as the complexity, clarity, and quality of randomly acquired characteristics (RACs) available for analysis. In addressing this issue, the current study developed a partially automated image processing chain, including steps for automated feature characterization. This article details the methods, procedures, and type of results available for subsequent statistical analysis after processing a collection of just over 1,000 shoes and 57,426 randomly acquired characteristics. (publisher abstract modified)
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