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Can lip prints change overnight?: a study of lip print stability across day and night as a forensic identification tool


Citation

Hamzah, Noor Hazfalinda and Osman, Khairul and Nadarajan, Naakshectra and Ci, Tham Jia and Khairuddin, Nurhanis and Sabri, Muhammad Izhan and Mohd Nasir, Atikah and Md Isa, Nur Mahiza (2026) Can lip prints change overnight?: a study of lip print stability across day and night as a forensic identification tool. Anil Aggrawal's Internet Journal of Forensic Medicine and Toxicology, 27 (1). ISSN 0972-8066; eISSN: 0972-8074

Abstract

Aim Lip prints have long been considered unique and stable over time, causing a boost of cheiloscopy research to understand the potential of lip prints for forensic identification. While studies looking at lip print stability over time are common, this study investigates the stability based on the day and night phenomenon. MethodologyLip prints were taken from 200 participants from the campus population using the standardised paper technique, wherein lip prints were made on A4 papers then digitised using a highresolution scanner. Lip prints similarity percentage were formed by comparison of the prints collected at the morning and evening, then analysed using Contrastive Language-Image Pretraining (CLIP) image analysis model. Statistical analysis included repeated-measures ANOVA to compare the lip print similarity percentage obtained at Day 1, Day 7 and Day 14. Intra-class correlation coefficient (ICC) is used to test the reliability of the CLIP model to analyse lip print images.Results Repeated measures ANOVA indicated significant variation in lip prints similarity percentage obtained at Day 1, Day 7 and Day 14. The intraclass correlation coefficient (ICC) was rated 0.649, between fair and good. Conclusion The study concludes that lip print morphology may not be as stable over short time intervals as previously assumed, and this variability should be considered in forensic evidence collection.


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Official URL or Download Paper: https://zenodo.org/doi/10.5281/zenodo.15743496

Additional Metadata

Item Type: Article
Subject: Pathology and Forensic Medicine
Subject: Toxicology
Subject: Law
Divisions: Faculty of Veterinary Medicine
DOI Number: https://doi.org/10.5281/zenodo.15743496
Publisher: Anil Aggrawal's Internet Journal of Forensic Medicine and Toxicology
Keywords: Cheiloscopy; Deep learning; Digital analysis; Icc; Lip prints
Sustainable Development Goals (SDGs): SDG 16: Peace, Justice and Strong Institutions, SDG 9: Industry, Innovation and Infrastructure, SDG 3: Good Health and Well-being
Depositing User: Ms. Siti Radziah Mohamed@mahmod
Date Deposited: 29 Apr 2026 09:11
Last Modified: 29 Apr 2026 09:11
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.5281/zenodo.15743496
URI: http://psasir.upm.edu.my/id/eprint/125041
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