Face recognition is a type of biometric system that uses analysis and comparison of facial patterns to identify individuals from digital images. It works by detecting distinct nodal points on the face and measuring relationships between features like eye separation, nose width, and jaw line. The process involves image acquisition, processing, locating distinguishing characteristics, and template matching. Some advantages are its ability to identify from photos and operate without cooperation, while weaknesses include reduced accuracy from environmental changes or aging. Applications include security, child pickup verification, and banking authentication.

1. Face recognition
Author: ASIF GUL
Institute: QUAID-E-AWAM
UNIVERSITY OF SCIENCE &
TECHNOLOGY, NAWABSHAH,
SINDH, PAKISTAN
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2. Outline
Biometric & its types
Facial recognition.
Implementation.
Process of working.
Strengths & weaknesses.
Applications.
References.
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3. 3
Biometric
The measuring and analysis of such physical attributes as facial features ,
voice or retinal scans.
This technology is can be used to define an individual’s unique identity.
Types of Biometrics
Behavioral Biometrics
 Voice scan
Signature scan
Keystroke scan
Physiological Biometrics
Finger-scan
Facial recognition
Hand-scan
Retina-scan

4. Face recognition
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Face recognition(facial recognition) is a type of
biometric system application that can identify
specific individual in digital image by analyzing and
comparing patterns.

5. Face recognition
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Types of comparison
 Verification:
In verification the system compares the input
digital image with the particular which the
user says he/she is.
 Identification:
In this type of comparison the system
compares the taken digital image with
the whole records in database.

6. Face recognition
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Implementation of the face recognition
technology includes the following four stages.
Image acquisition
Image processing
Distinctive characteristics location
Template creation
Template matching

7. How Face recognition works
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 There are some variances that make up the different facial
features
 Visionics defines these landmarks as nodal points. There
are 80 nodal points on human face.
Few are given below
Distance between the eyes
Width of the nose
Cheekbones
Jaw line
Chin

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Face recognition algorithm working
Face Localization
Lighting Compensation
Skin Color Detection
Color Space Transformation
Variance-based Segmentation
Connected Component &
Grouping
Face Boundary Detection
Verifying/ Weighting
Eyes-Mouth Triangles
Eye/ Mouth Detection
Facial Feature Detection
Input Image
Output Image

9. Strengths and weakness.
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Strengths:
 it can search against static such as driver’s license
photograph.
 It is the only biometric that is able to operate without
cooperation .
Weakness:
Changes in acquisition environment reduce matching
accuracy.
Changes in physiological characteristics reduce matching
accuracy
It has the potential for privacy abuse due to non-
cooperative enrollment and identification capabilities.

10. Applications of face recognition
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 Security: access control, comparing
surveillance images to know terrorist.
 Day care: verifying the identity of
individuals picking up the children
 Residential security: alert the homeowners
of approaching personal.
Banking using ATM: the software is able to
quickly verify the customer’s face.
 Voter verification:

11. References
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 https://en.wikipedia.org/wiki/facial_reco
gnition_system
 https://boimetricgroup.com/wily
 https://www.youtube.com