Multi-Layer Feature Based Shoeprint Verification Algorithm for Camera Sensor Images

Sensors

Xinnian Wang¹  Yanjun Wu¹  Tao Zhang² 

[1] School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China;School of Physics and Electronics Technology, Liaoning Normal University, Dalian 116026, China;

关键词: shoeprint verification;    shoeprint partition model;    multi-layer feature;    forensic sciences;    shoeprint matching strategy;   

DOI  :  10.3390/s19112491

来源: DOAJ

【 摘 要 】

As a kind of forensic evidence, shoeprints have been treated as important as fingerprint and DNA evidence in forensic investigations. Shoeprint verification is used to determine whether two shoeprints could, or could not, have been made by the same shoe. Successful shoeprint verification has tremendous evidentiary value, and the result can link a suspect to a crime, or even link crime scenes to each other. In forensic practice, shoeprint verification is manually performed by forensic experts; however, it is too dependent on experts’ experience. This is a meaningful and challenging problem, and there are few attempts to tackle it in the literatures. In this paper, we propose a multi-layer feature-based method to conduct shoeprint verification automatically. Firstly, we extracted multi-layer features; and then conducted multi-layer feature matching and calculated the total similarity score. Finally, we drew a verification conclusion according to the total similarity score. We conducted extensive experiments to evaluate the effectiveness of the proposed method on two shoeprint datasets. Experimental results showed that the proposed method achieved good performance with an equal error rate (EER) of 3.2% on the MUES-SV1KR2R dataset and an EER of 10.9% on the MUES-SV2HS2S dataset.

【 授权许可】

Unknown