Facial Recognition System

Facial Recognition System Explained

Facial Recognition System is a biometric technology which makes use of computer programs for automatic identification of any person. This technology was started in 1960. In this technology, several facial features of the person are used and then it is compared with the existing images in the database for final identification. Facial recognitions systems are used as an additional and mass security measure and are comparable to the other biometric security systems available today such as retina scanners, fingerprint scanners, etc…

Facial Recognition System Types

Two-Dimensional Facial Recognition System :

Long before the advent of sophisticated computing technologies and image enhancement software, the technology involving two-dimensional facial recognition system had evolved. But this technology didn’t last for long as it had some big drawbacks. The most important drawback being the fact that the person to be identified must be facing the camera at no more than 35 degrees for accurate identification to be possible. Light differences and facial expressions also contributed to low accuracy in recognition of such systems.

Three-Dimensional Facial Recognition System :

The two dimensional facial recognition system soon became a thing of the past. And it made a way for the three dimensional facial recognition system. This system was much more accurate and stable than its predecessors. Unlike the two dimensional facial recognition systems, this system made use of distinct features in a human face and used them as nodes to create a face print of the person. The three dimensional facial recognition system recognizes a face even when it is turned 90 degrees away from the camera. Moreover, it remains unaffected by the differences in lighting and facial expressions of the subject.

Facial Recognition System Steps

Steps in facial recognition :

  • Acquire a real or image or two dimensional image of the person to be targeted.
  • Determine the alignment of the face based on the position of the nose, the mouth, etc…
  • The alignment is followed by the creation of a facial template
  • The facial template created is finally matched with the existing images in the database