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Dataset of Digitized RACs and Their Rarity Score Analysis for Strengthening Shoeprint Evidence.

Authors
  • Wiesner, Sarena1
  • Shor, Yaron2
  • Tsach, Tsadok3
  • Kaplan-Damary, Naomi4
  • Yekutieli, Yoram5
  • 1 Questioned Documents Lab, DIFS, Israel Police, 1 Bar Lev Rd., Jerusalem, 91906, Israel. , (Israel)
  • 2 Toolmarks and Materials Lab, DIFS, Israel Police, 1 Bar Lev Rd., Jerusalem, 91906, Israel. , (Israel)
  • 3 R&D Unit, DIFS, Israel Police, 1 Bar Lev Rd., Jerusalem, 91906, Israel. , (Israel)
  • 4 Department of Statistics, The Hebrew University of Jerusalem, Jerusalem, 91905, Israel. , (Israel)
  • 5 Department of Computer Science, Hadassah Academic College, 37 Hanevi'im St., Jerusalem, 9101001, Israel. , (Israel)
Type
Published Article
Journal
Journal of forensic sciences
Publication Date
Nov 18, 2019
Identifiers
DOI: 10.1111/1556-4029.14239
PMID: 31738459
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

In recent years, there is a growing demand to fortify the scientific basis of forensic methodology. During 2016, the President's Council of Advisors on Science and Technology (PCAST) published a report that states there are no appropriate empirical studies that support the foundational validity of footwear analysis to associate shoeprints with particular shoes based on specific identifying marks, which is a basic scientific demand from the field. Furthermore, meaningful databases that can support such studies do not exist. Without such databases, statistical presentation of the comparison results cannot be fulfilled either. In this study, a database of over 13,000 randomly acquired characteristics (RACs) such as scratches, nicks, tears, and holes, as they appear on shoe sole test impressions, from nearly 400 shoe soles was collected semi-automatically. The location, orientation, and the contour of each RAC were determined for all the RACs on each test impression. The statistical algorithm Statistic Evaluation of Shoeprint Accidentals (SESA) was developed to calculate a score for finding another feature similar to a particular scanned and digitized RAC in the same shape, location, and orientation as the examined one. A correlation was found between the results of SESA and the results of real casework, strengthening our belief in the ability of SESA to assist the expert in reaching a conclusion while performing casework. The score received at the end of the process serves the expert as a guiding number, allowing more objective and accurate results and conclusions. © 2019 American Academy of Forensic Sciences.

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