IT Finder

In recent times there has been a large increase in the birth of Identical Theft. Two faces in the form of images can be differentiated by using MTCNN and Artificial Intelligence technology. Multi-task Cascaded Convolutional Networks (MTCNN) is a framework developed as a solution for both face detection and face alignment. The process consists of three stages of convolutional networks that are able to recognize faces and landmark location such as eyes, nose, and mouth. A large data set is trained to identify images with similarities in faces and the similarity percentage is given. If the 2 images are considered to be similar if the percentage match is above 0.5. If not the images passed to the code are different persons. The technology can further be expanded in differentiating twins and Identical Twins

I. Introduction

IT Finder, sometimes known as Identity Theft Finder, compares two individuals who are provided to the software as photographs. Over the past few years, identity theft has become a more frequent occurrence. Alternative security measures that can safeguard the biometric system must be devised in light of the rise in crime over the past few decades. This inspired us to begin working on this project to ascertain whether two people get along. The primary goals of our project are to recognize identity.