Counterfeit footwear has evolved from a copyright infringement issue to a key piece in criminal investigations. High-precision 3D scanning, using equipment such as the Artec Micro, captures the geometry of injection molds with micrometric accuracy. These molds, far from being perfect, accumulate wear and micro-defects that are transferred to every sole produced, making them a unique and reproducible signature.
Technical pipeline: from micro-scanning to failure correlation 🔬
The workflow begins with digitizing the suspect mold using the Artec Micro, which offers a resolution of up to 0.01 mm. The resulting point cloud is imported into GOM Inspect for deviation analysis. Here, micro-defects such as burrs, porosities, or erosion marks are identified and labeled. This data is processed in MATLAB to generate a mathematical signature of the mold, comparing it with footprint impressions recovered from the crime scene using surface matching algorithms. Finally, Rhino 3D is used to reconstruct the geometry of the counterfeit sole and virtually overlay it onto the ground impression, confirming the compatibility of wear patterns.
The polymer's digital fingerprint 🧬
This approach raises the standard of expert evidence. It no longer relies solely on the tread design, which can be generic. Micro-defects act as a fingerprint of the specific mold, linking an entire batch of counterfeit sneakers to a single injection press. For the digital forensics expert, this technique transforms an everyday object into irrefutable evidence, closing the loop between illegal manufacturing and the crime scene.
How can high-precision 3D scanning of a shoe sole differentiate between a normal wear footprint and a forensic impression linked to a specific crime?
(PS: In the forensic pipeline, the most important thing is not to mix the evidence with the reference models... or you'll end up with a ghost at the scene.)