| EPSRC Reference: |
EP/D03633X/1 |
| Title: |
ShoePrint Recognition and Analysis Technology (SPRAT) |
| Principal Investigator: |
Allinson, Professor NM |
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| Department: |
Electronic and Electrical Engineering |
| Organisation: |
University of Sheffield |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 November 2005 |
Ends: |
31 October 2006 |
Value (£): |
48,943
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| EPSRC Research Topic Classifications: |
| Image & Vision Computing |
Information & Knowledge Mgmt |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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Summary on Grant Application Form |
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Impressions left by shoes at crime scenes can greatly assist in solving crimes. They are not as unique as some other types of forensic evidence, such as fingerprints or DNA, but it is much more difficult not to leave some trace of shoe-prints. Shoe-prints can identify linked crime scenes, can link suspects in custody to other crime scenes, permit the targeting of prolific offenders and, where detailed matching of mark and shoe exist, provide strong courtroom evidence. Changes in the law, through the Serious and Organised Crime Bill (April 2005) allow for the first time the Police to take shoe-print impressions from suspects. There is expected to be a very large increase in the gathering of shoe-print evidence and the need to automate much of the processes.Impressions left by shoes are very variable in quality, completeness and in the possible evidence they can provide. This feasibility study will examine what the current status of automatic shoe-print identification systems (which compared to computerised approaches for other types of objects have been somewhat ignored), look at possible methods to extract the different levels of information that would help forensic scientists (ranging from Size 12 trainer to exact matching of impressions with a particular shoe). The study will work closely with Police experts, the Home Office and companies involved in providing current analysis systems to the Police. The outcome will be a much better understanding on how to develop powerful automatic shoeprint recognition systems that can cope with 1000s of shoe types and 10,000s impressions. It will, hopefully, assist in reducing crime and increasing the clear-up rate - especially for volume crimes.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.shef.ac.uk |