Computational Methods for the Analysis of Footwear Impression Evidence

Part of the Studies in Computational Intelligence book series (SCI, volume 555)

Abstract

Impressions of footwear are commonly found in crime scenes. Yet they are not routinely used as evidence due to: (i) the wide variability and quality of impressions, and (ii) the large number of footwear outsole designs which makes their manual comparison time-consuming and difficult. Computational methods hold the promise of better use of footwear evidence in investigations and also in providing assistance for court testimony. This paper begins with a comprehensive survey of existing methods, followed by identifying several gaps in technology. They include methods to improve image quality, computing features for comparison, measuring the degree of similarity, retrieval of closest prints from a database and determining the degree of uncertainty in identification. New algorithms for each of these problems are proposed. An end-to-end system is proposed where : (i) the print is represented by an attribute relational graph of straight edges and ellipses, (ii) a distance measure based on the earth-mover distance, (iii) clustering to speed-up database retrieval, and (iv) uncertainty evaluation based on likelihoods. Retrieval performance of the proposed design with real crime scene images is evaluated and compared to that of previous methods. Suggestions for further work and implications to the justice system are given.

Keywords

Footwear Impression evidence Computational forensics Image similarity Crime scene images 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Computer Science and Engineering, Center of Excellence for DocumentThe State University of New York SUNYNew YorkUSA

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