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Current Affairs

Facial recognition for identifying bodies and missing children

Date: 05 March 2020 Tags: Fourth Industrial Revolution

Issue

The Home Ministry has given approval to the automated facial recognition system (AFRS) for identification of unrecognised bodies, missing children and criminals.

 

Background

The approval has been accorded for implementation of AFRS by the National Crime Records Bureau (NCRB). AFRS will use police records and will be accessible only to law enforcement agencies.

 

Details

This will facilitate better identification of criminals, unidentified dead bodies and missing or found children and persons and will not violate privacy.

The new facial recognition system uses machine learning to identify similarities in faces seen on different pictures.

 

Facial recognition

  • Facial recognition is the process of identifying or verifying the identity of a person using their face. It captures, analyzes, and compares patterns based on the person's facial details.

  • The face detection process is an essential step as it detects and locates human faces in images and videos.

  • Although the accuracy of facial recognition system as a biometric technology is lower than iris recognition and fingerprint recognition, it is widely adopted due to its contactless and non-invasive process.

  • Some face recognition algorithms identify facial features by extracting landmarks, or features, from an image of the subject's face. For example, an algorithm may analyze the relative position, size, and/or shape of the eyes, nose, cheekbones, and jaw. These features are then used to search for other images with matching features.

  • Recognition algorithms can be divided into two main approaches: geometric, which looks at distinguishing features, or photometric, which is a statistical approach that distills an image into values and compares the values with templates to eliminate variances.

  • Some classify these algorithms into two broad categories: holistic and feature-based models. The former attempts to recognize the face in its entirety while the feature-based subdivide into components such as according to features and analyze each as well as its spatial location with respect to other features.