Forensic Investigation
Background and summary: Footwear impressions are one of the most frequently secured types of
evidence at crime scenes. A part of the daily life of Forensic experts all over the world is to assign
the crime scene impression to a reference impression. Through this process, the noisy and incomplete
evidence becomes a standardized information with outsole images, brand name, manufacturing time, etc.
Currently, no automated systems exist that can assess the similarity between a crime scene impression
and reference impressions, due to the severe image degradations induced by the impression formation
and lifting process.
The impression analysis task combines several challenging problems and therefore is at the heart of
pattern recognition research. The main challenges are the combination of unknown noise conditions
with rigid transformations and missing data. Furthermore, training and testing data are scarce.
Therefore, a higher-level understanding of the patterns is necessary in order to solve this task.
Goal: Find a way by which you can match new footprints with references in the database.
Input data: The databases contain samples of footwear impression evidence, that have been
secured at crime scenes by forensic experts. The digital images were produced either by scanning
gelatin lifters or by photographing the impression. Moreover, 1175 reference impressions are included
in the databases. The reference samples have been produced by applying gelatin lifters to the outsole
of the reference shoe, followed by scanning the lifters. Thus, the data generating process is very
similar for both types of impressions. The data is labelled, meaning that for each crime scene
impression, the name of the corresponding reference impression is known.
Data Included in this Project:
1. FID-300:
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2. CSFID-170: This database is a subset of the FID-300 database. It contains mostly footwear
impressions with periodic patterns:
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Relevant papers:
Probabilistic Compositional Active Basis
Models for Robust Pattern Recognition
Unsupervised Footwear Impression Analysis and
Retrieval from Crime Scene Data