Abstract: Vehicle gate access, in general, still relies heavily on manual inspection of identification cards and visual verification by security guards, which is slow, tedious, and susceptible to spoofing. Single-modality, computerized systems that utilize license plates, vehicle appearance, and facial recognition can partially alleviate this difficulty. Still, they are prone to spoofing and generally perform poorly in real-world scenarios (e.g., glare, occlusion, and tinted glass). This study presents TRI-GATE, a tri-modal anti-spoofing framework that unifies vehicle, license plate, and face recognition within a single, real-time decision pipeline. The system employs YOLOv4-tiny for vehicle detection and a MobileNetV2-based classifier for make–model recognition, a retrained MTCNN and LPRNet pair for license plate detection and recognition on Saudi-specific datasets (17,000 images for detection and 35,000 for recognition), and RetinaFace with InsightFace embeddings, along with a linear SVM, for driver identification. An IoU-based best-frame selection scheme reduces latency by forwarding only the most informative frame to the recognition modules. Score-level fusion is then performed by a linear SVM that learns the relative importance of each modality for the final access decision. Evaluated on a dedicated tri-modal dataset, TRI-GATE achieves 97% gate-level accuracy with an end-to-end latency of 66 ms per frame (≈ 15.15 FPS), and demonstrates robust performance in a real-world gate-like deployment, substantially improving both security and operational efficiency over existing single- and bi-modal solutions.

Muhannad Alsultan, Thamer Alghonaim, Abdulaziz Alorf, Bandar Alwazzan, Faisal Alsakakir, Abdullah Alhassan and Yousif Hussain. “TRI-GATE: A Tri-Modal Anti-Spoofing System for Gate Access Using Vehicle, License Plate, and Face Recognition”. International Journal of Advanced Computer Science and Applications (IJACSA) 17.1 (2026). http://dx.doi.org/10.14569/IJACSA.2026.0170192

@article{Alsultan2026,
title = {TRI-GATE: A Tri-Modal Anti-Spoofing System for Gate Access Using Vehicle, License Plate, and Face Recognition},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2026.0170192},
url = {http://dx.doi.org/10.14569/IJACSA.2026.0170192},
year = {2026},
publisher = {The Science and Information Organization},
volume = {17},
number = {1},
author = {Muhannad Alsultan and Thamer Alghonaim and Abdulaziz Alorf and Bandar Alwazzan and Faisal Alsakakir and Abdullah Alhassan and Yousif Hussain}
}