This research looked to validate the use of footwear impressions as a source of forensic evidence.
The objectives of this study were to: 1) simplify footwear impression data acquisition; 2) establish the baseline performance of an automated footwear classification algorithm; and 3) mathematically evaluate the frequency and similarity of randomly acquired characteristics (RACs) in high quality examples versus crime-scene-like impressions as a function of RAC shape, perimeter, and area. Results show that the unpredictable nature of crime scene print deposition causes RAC loss that varies from 33-100% with an average loss of 85%, and that up to 10% of the crime scene impressions fully lacked any identifiable RACs. Despite the loss of features present in the crime-scene-like impressions, there was a 0.74 probability that the actual shoe's high quality RAC map would rank higher in an ordered list than a known non-match map when queried with the crime-scene-like print. Moreover, this was true despite the fact that 64% of the crime-scene-like impressions exhibit 10 or fewer RACs.