Citation
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
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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 |
| Statistic Details: | View Download Statistic |
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