Facial recognition is a way of recognizing a human face through technology. A facial recognition system uses biometrics to map facial features from a photograph or video. It compares the information with a database of known faces to find a match.
1. FACE RECOGINITION FOR FINDING CRIMINALS
BY VISHNU V NAIR
Fully Automated surveillance system
2. Basics
The Human faces plays an important role in our social interaction, conveying
People’s identity.
Face recognition system is a computer based digital technology and is an
Active area of research.
Like all biometric, Face recognition technology measure and matches the
Unique characteristics for Identification and verification.
Face recognition is a task that human perform routinely and effortlessly in
their Daily life
3. Face Recognition
A facial recognition system is a technology capable of identifying or
verifying a person from a digital image or a video frame from a video
source.
4. Proposed System
The main thing that a person pays attention to is the eyes, cheekbones,
nose, mouth, and eyebrows, as well as the texture and color of the skin.
At the same time, our brain processes the face as a whole and is able to
identify a person even by half of the face.
5. The main thing that a person pays attention
to is the eyes, cheekbones, nose, mouth, and
eyebrows, as well as the texture and color of
the skin.
Deep Learning in Facial Recognition
It turns out that the characteristics that seem
obvious to us humans (for example, eye
color) do not make sense for a computer
analyzing individual pixels in an image.
Deep learning, in turn, allows much better
and faster identification.
6. Collection of
Faces
Feature Extraction
Face Database
Template Matching
END
Acquisition by
Camera
Detection
Pre-processing
Feature Extraction
ID Identified
Matched Not Matched
9. Feasibility and implementation
A system can be easily integrated into the
existing CCTV ,traffic cameras and other
surveillance setups.
A computer is powerful enough to handle the
data and process it needs to be made.
The effectiveness of the system depends
upon the power of the computer, quality of
camera feeds and algorithms put in the
place.