Vinny Sharma Professor, Department of Forensic Science, Galgotias University, Greater Noida, Uttar Pradesh,, India
Rashi Verma Ph.D. Scholar, Department of Forensic Science, Galgotias University, Greater Noida, Uttar Pradesh, India
Ranjeet Kr. Singh Assistant Professor, Department of Management Studies, G.L. Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh,, India
Manjeet Kumar Assistant Professor, Department of Management Studies, G.L. Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh,, India
Address for correspondence: Vinny Sharma, Professor, Department of Forensic Science, Galgotias University, Greater Noida, Uttar Pradesh,, India E-mail: vinnysharma4n6@gmail.com
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Verma R, Sharma V, Singh RK, et al. Forensic Footwear Comparison: Leveraging AI Tools for Enhanced Analysis. Indian J Forensic Med Pathol. 2025;18(2 Suppl):162-174.
Timeline
Received : May 06, 2024
Accepted : June 21, 2024
Published : June 30, 2025
Abstract
Footwear impressions serve as a crucial type of evidence in forensic investigations, effectively linking suspects to crime scenes with remarkable accuracy. This research explores the efficacy of three widely utilized casting materials - Plaster of Paris, Latex Rubber, and Dental Stone when applied to various soil types. Additionally,
the study examines the impact of artificial intelligence (AI) in enhancing the analysis of these impressions. The main objectives were to investigate footwear impressions differ across diverse surfaces, identify which casting material captures the most precise details, and evaluate whether AI tools can provide more dependable comparisons than traditional visual inspection. Digital images of both the original and cast impressions were analyzed using an AI algorithm that included grayscale conversion and histogram analysis. Statistical technique
chi-square tests, indicated significant differences based on the type of surface and material used. The findings revealed that original impressions exhibited superior clarity and detail compared to cast impressions. This study highlights the necessity of careful material selection and the incorporation of AI to enhance accuracy and
reliability in the forensic examination of footwear impressions.
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Data Sharing Statement
There are no additional data available. All raw data and code are available upon request.
Funding
This research received no funding.
Author Contributions
All authors contributed significantly to the work and approve its publication.
Ethics Declaration
This article does not involve any human or animal subjects, and therefore does not require ethics approval.
Acknowledgements
We would like to express our gratitude to the patients, their families, and all those who have contributed to this study.
Conflicts of Interest
The authors report no conflicts of interest in this work.
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Cite this article
Verma R, Sharma V, Singh RK, et al. Forensic Footwear Comparison: Leveraging AI Tools for Enhanced Analysis. Indian J Forensic Med Pathol. 2025;18(2 Suppl):162-174.
This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.
This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.