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Determining Shoe Length from Partial Shoeprints
Author(s) -
Zhang He,
Liu Luoxi,
Luo Yaping,
Chang Ran
Publication year - 2020
Publication title -
journal of forensic sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.715
H-Index - 96
eISSN - 1556-4029
pISSN - 0022-1198
DOI - 10.1111/1556-4029.14544
Subject(s) - feature (linguistics) , mathematics , quadratic equation , statistics , computer science , geometry , philosophy , linguistics
The length of a shoe has significant value in reflecting characteristics of the owner, and thereby, it can help in tracking suspects in criminal cases. However, the shoeprints left at a crime scene are often incomplete, resulting in difficulties in assessing shoe length. To find a way to estimate the shoe length from a partial shoeprint, 109 shoes with different sizes and general patterns were collected, and their prints were lifted using magnetic powder. Four feature points were defined on a shoeprint, and the longest distance between the feature points was defined as shoe length. Using linear, quadratic, and cubic regression analyses, a total of 15 equations were obtained between the shoe length and the other distances between the feature points. Out of these, the five most accurate equations were selected as the optimal equation. The verified test, including another 18 pairs of shoes, showed an average error of equations between 0.591 cm and 0.732 cm. The equations were also applied in two practical cases, resulting in good accuracy. The study demonstrates that shoe length could be determined from partial shoeprints through the proven equations.