Face Recognition Technology

Humans are very good at recognizing faces and if computers complex patterns. Even a passage of time doesn't affect this capability and therefore it would help become as robust as humans in face recognition. Machine recognition of human faces from still or video images has attracted a great deal of attention in the psychology, image processing, pattern recognition, neural science, computer security, and computer vision communities. Face recognition is probably one of the most non-intrusive and user-friendly biometric authentication methods currently available.

          Face recognition technology uses the software i.e. “FaceIt”. Facial recognition methods generally involve a series of steps that serve to capture, analyze and compare a face to a database of stored images. The basic processes used by the FaceIt system to capture and compare images.

Steps involved in process of F.R.T. that are  -

1.   Detection 
2.      Normalization 
3.   Representation
4.   Comparing

Here are a few of the nodal points that are measured by the software: 

- Distance between eyes 
- Width of nose 
- Depth of eye sockets 
- Cheekbones 
- Jaw line 
- Chin
         These nodal points are measured to create a numerical code, a string of numbers that represents the face in a database. This code is called a faceprint. Only 14 to 22 nodal points are needed for the FaceIt software to complete the recognition process.

How Facial Recognition Systems Work

FR Application