Facial Recognition Using Retina

With common face databases, this study's investigation into the use of ocular traits for face detection and identification yielded encouraging findings. The principal contributions include face detection, eye detection, and person identification techniques that target anatomical features such as the mouth, nose, eyes, and retina. The centers of the eyes, the distance between the eyes, and the brows are important characteristics for eye recognition. For a comprehensive recognition pipeline, the study makes use of the Python deep face library and the Arc Face module from the insight face project. Applications include crowd identification, missing person searches, area security, and high-security monitoring in places like parliaments and bank vaults. [1]