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https://github.com/nikhil-swamix/dip-faceid-project-sem5

Final Project Repo For DIP Assignment
https://github.com/nikhil-swamix/dip-faceid-project-sem5

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Final Project Repo For DIP Assignment

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README 

        
# DIP-FaceID-Project-SEM5

Brief intro : Final Project Repo For DIP Assignment



![Banner](https://www.eff.org/files/2017/11/03/iowa_dot.jpg)



Please See Demo and other videos to get full understanding of project



# What is Face Recognition

A facial recognition system is a technology capable of matching a human face from a digital 

image or a video frame against a database of faces, typically employed to authenticate users through 

ID verification services, works by pinpointing and measuring facial features from a given image.

While initially a form of computer application, facial recognition systems have seen wider uses

in recent times on smartphones and in other forms of technology, such as robotics. Because computerized 

facial recognition involves the measurement of a human's physiological characteristics facial recognition 

systems are categorised as biometrics. Although the accuracy of facial recognition systems as a biometric 

technology is lower than iris recognition and fingerprint recognition, it is widely adopted due to its

contactless and non-invasive process.[1] Facial recognition systems have been deployed in advanced 

human-computer interaction, video surveillance and automatic indexing of images.[2] 



# How It Works

Face recognition systems use computer algorithms to pick out specific, 

distinctive details about a person’s face. These details, such as distance

between the eyes or shape of the chin, are then converted into a mathematical 

representation and compared to data on other faces collected in a face recognition 

database. The data about a particular face is often called a face template and is 

distinct from a photograph because it’s designed to only include certain details

that can be used to distinguish one face from another. 



Some face recognition systems, instead of positively identifying

an unknown person, are designed to calculate a probability match

score between the unknown person and specific face templates stored

in the database. These systems will offer up several potential matches,

ranked in order of likelihood of correct identification, instead of just

returning a single result. 



Face recognition systems vary in their ability to identify people under challenging conditions such as poor lighting, low quality image resolution, and suboptimal angle of view (such as in a photograph taken from above looking down on an unknown person).



# About FaceID History

Face ID is a facial recognition system designed and developed by Apple Inc.

for the iPhone (X, XS, XS Max, XR, 11, 11 Pro, 11 Pro Max, 12 Mini, 12, 12 Pro, 12 Pro Max)

and iPad Pro (third and fourth generation). A successor to Touch ID, the system allows 

biometric authentication for unlocking a device,[1] making payments, and accessing sensitive

data, as well as providing detailed facial expression tracking for Animoji and other features.

Initially released in November 2017 with the iPhone X, it has since been updated and 

introduced to most new iPhone models, and all iPad Pro models.[2]