Comparison of Face Recognition on RGB and Grayscale Color with Deep Learning in Forensic Science
23
Issued Date
2023-03-10
Resource Type
Scopus ID
2-s2.0-85163371757
Journal Title
ACM International Conference Proceeding Series
Start Page
95
End Page
100
Rights Holder(s)
SCOPUS
Bibliographic Citation
ACM International Conference Proceeding Series (2023) , 95-100
Suggested Citation
Werukanjana P., Sa-Nga-Ngam P., Permpool N. Comparison of Face Recognition on RGB and Grayscale Color with Deep Learning in Forensic Science. ACM International Conference Proceeding Series (2023) , 95-100. 100. doi:10.1145/3589572.3589586 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/87877
Title
Comparison of Face Recognition on RGB and Grayscale Color with Deep Learning in Forensic Science
Author(s)
Author's Affiliation
Other Contributor(s)
Abstract
In forensic science face recognition, we cannot request high-quality face images from sources, but we have face images from CCTV grayscale on the crime scene at night, face images in RGB mode from Web Cameras, etc. This research needs to find a satisfying method of face recognition in forensic science to identify the "Who's face?"at the request of a police investigator. The experiment uses Siamese neural network face recognition of both RGB and GRAY color modes to compare and show the performance of both color modes. The evaluation shows a confusion matrix, F1-score ROC/AUC, and a strong recommend with Likelihood ratio (LR) that supports court in evidence identification recommended by NIST and ENFSI.