A Texture Based Shoe Retrieval System for Shoe Marks of Real Crime Scenes

  • Francesca Dardi
  • Federico Cervelli
  • Sergio Carrato
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5716)

Abstract

Shoeprints found on the crime scene contain useful information for the investigator: being able to identify the make and model of the shoe that left the mark on the crime scene is important for the culprit identification. Semi-automatic and automatic systems have already been proposed in the literature to face the problem, however all previous works have dealt with synthetic cases, i.e. shoe marks which have not been taken from a real crime scene but are artificially generated with different noise adding techniques.

Here we propose a descriptor based on the Mahalanobis distance for the retrieval of shoeprint images. The performance test of the proposed descriptor is performed on real crime scenes shoe marks and the results are promising.

Keywords

Scale Invariant Feature Transform Crime Scene Texture Region Canny Edge Detector Image Retrieval System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Francesca Dardi
    • 1
  • Federico Cervelli
    • 1
  • Sergio Carrato
    • 1
  1. 1.Dept. Electrical, Electronic and Information Engineering (DEEI)University of TriesteTriesteItaly

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