Comparison of Face Recognition on RGB and Grayscale Color with Deep Learning in Forensic Science

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.