JACKIE ABBAZIO

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Title: JACKIE ABBAZIO

1
Face Recognition Systems

2
Overview Face Biometrics

Facial recognition through the use of computer
analysis of facial structure.
Software measures a number of points of facial
characteristics such as eyes, nose, mouth, angles
of key features, and lengths of various portions.
Collected data is used to create a template
through a mathematical algorithm
(Neural-Networks, Eigenface) and the file is
stored within the database.
File is compared to other files within the
database in search of an identity match.

3
Face Biometrics Continued

Face biometric systems employee the capturing of
facial pattern characteristics through the use of
still photography or video clips.
Pattern recognition software relies on
Data collection raw data
Feature extraction eyes, nose, mouth, etc
Classification class the object is placed into
(male or female, skin tone, etc)

4
FAR FRR

FAR ( False Acceptance Rating) the false
acceptance rating is the probability that the
software will incorrectly declare a successful
match between the input data against the
database.
FRR (False Rejection Rating) the false
rejection rating is the probability that the
software will declare a failure to match the
input data against the database.

5
Face Biometric Systems Project

The face biometric systems project involved the
research and testing of various facial biometric
softwares based on criteria set by the clients.
Two face biometric softwares were chosen and
tested (Luxand FaceSDK VeriLook).

6
Software Comparison Table
7
Luxands FaceSDK 1.7

After extensive testing and researching the Face
Biometric Systems, we recommend purchasing
Luxands FaceSDK 1.7 software. It has the
following strengths
Easy to use
Ability to enroll all images
Matches work best at FAR of 50, but produces
matches at FAR of 10.
Works best for aging
Free demo version used

8
Luxand FaceSDK Example

9
Luxand FaceSDK Similarity Matrix
10
VeriLook 3.2

Designed for biometric system developers and
integrators.
Allows for easy integration and rapid development
of biometric applications using functionality.
Can perform simultaneous multiple face detections
with the ability to process 100,000 faces per
second and it recommends the minimum image size
to be 640x480 pixels .

11
VeriLook Test Result

Software works best with high resolution photos.
False Acceptance Rating set for 100
All images matched 100 against the same image in
the database. The score of 180 is interpreted as
an exact match.
Free demo version used

12
VeriLook Aging Result

The results show that the photo from 1969 matched
a photo from 2008 with a similarity score of 18
or 10.
This result is comparable with the FaceSDK age
identification test, where the same image from
1969 matched the same photo from 2008 with a
61.9 similarity rate.

13
Software Comparison TestLuxand FaceSDK -
VeriLook

Tests were run using both Luxand FaceSDK 1.7 and
VeriLook using the four photos seen here.
Similarity ratings varied from one software to
the other.
Luxand FaceSDK results provided more results
based on Similarity Rating than VeriLook .

14
Luxand VeriLook Comparison

15
Conclusion

Luxand FaceSDK 1.7
works very well in identifying face similarity
among people in a group
worked relatively well matching an image of the
subject as a child
VeriLook 3.2
had more limitations than FaceSDK, it only
accepted high-res images.
results for the similarity test were lower than
the FaceSDK software
PDA Security
none of the software tested was suitable for PDA
security use
Further Work
we recommend further work using 3-D face
biometrics software and scanners to find optimal
solution for PDA security