Comparative Analysis of Human Face Recognition Using SURF and Neural Network Methods

Abstract

In computer vision, facial recognition technology is used to recognize every person. This approach is a revolution that is perfect for analyzing a graphic image or a video frame specially or differently. There are, however, systemic methods where facial appreciation schemes initiative, typically, and the effort by comparing chosen facial features from a specific image with faces in a database. It's also known as a Biometric Artificial Intelligence-based app that can see a person in extraordinary detail by dissecting structures related to their facial exteriors and figures. The professional employs a variety of techniques in order to complete the mission. The SURF and Neural Network methods are two of these methods. The writers of this paper address the methods mentioned above and how they operate. The emphasis of the debate is on the methods' accuracy rates and determining which approach produces the most reliable outcome based on facial image results.