Facial Region Detection
- without hair effect Y’CbCr Color Space
Fig. 5. Facial region
detected with hair effect.
Fig. 4. Input Image
Eq1: Represents the luminance
variation at coordinates (x,y)
Thresholding
Fig. 6. Hair region detected
by luminance variation.
Fig. 7. Facial region detected
1
without hair effect
Eye Region Detection Using Template
Template
Facial region
image
Inverse & extract
Fig. 8. Extracted eye region
Fig. 9. Real eye region
Boundary
Rectangular
Apply the fact that the eyes are
located symmetrically in the
upper facial region and under
the eyebrows
Fig.10. Detected eye regions
using template matching
Sometimes the eyes shape is not accurate?
Improvement
2
Eye Region Detection Using Weighted Templates
Custom-Masks
Get more accurate eye shape by assigning a new search region.
Remark:
Black pixels are assigned with -1
Dark gray assigned with 1
Light gray assigned with 2
White assigned with 0
Fig. 10. Weighted templates for left, right, up, and down sides
The eye region is
extracted more
accurately (left & right)
Fig.11. Detected eye regions
using template matching
Fig.12. Detected eye regions after
using the weighted template
3
Eyebrow Region Detection
Fig.12. Detected eye regions after
using the weighted template
Luminance histograms
Estimated
Fig.13. Eyebrow search region
Thresholding using a luminance histogram
Fig.14. Processes of modifying a histogram and
determining a threshold value
Width = 2.5 eye Width
Height = 2.5 eye Height
Fig.15. Detected eyebrow region
4
Mouth Region Detection
A mouth search region is specified by the positions of the detected eyes
and the statistical data regarding the geometric information of a face.
Fig.16. Geometric structure of eyes and mouth
Eq2: Coordinates of mouth search region
5
Mouth Region Detection
The mouth region also has a large luminance variance
Eq1: Represents the luminance variation at coordinates (x,y)
Fig.17. Input image for mouth region detection and a detected mouth region
6
FCP Extraction
Appoint 34 points for FCPs in the facial region
10 points
Eyes Region
16 points
Edge Detection
Eyebrows Region
Mouth Region
8 points
Fig.18. Appointed FCPs
7
Verification Experiment & Result
 Condition: The input image must be a bust shot (portrait), including a
front view of the face without glasses, and the background has to be
simple.
 The experiment is carried out with 150 images. It extracts valid FCPs
in 122 / 150 images (81.333 %)
Fig.19. The FCPs extracted
by the proposed algorithm
8
Verification Experiment & Result
1. The first case was due to background effects: The background with skin-color is
detected as the facial region.
2. The second case was because of long hair: Long hair covering the eyes and
eyebrows causes the wrong eye region detection and makes it impossible to detect the
remaining facial components.
3. The third case was affected by viewpoint (poses): The input images disagreed with
the geometric information of a face, the facial components cannot be normally detected.
4. The fourth case regards a problem with skin-color range: The skin-color of several
non-Caucasian people was out of the assumed Caucasian skin-color range and the
facial region could not be detected.
The front three cases were solved by cautious images acquisitions
The last case solved by adjusting a skin-color range to a race.
9
Conclusion-I
 The research proposed the improved method to detect the
facial components that used for extracting FCP-an important
information for facial expression and recognition.
 Future Work: Extract facial components using LabVIEW
& Vision Assistant
 Challenges ???
10
Why face detection is difficult ?
11
Facial Recognition Application
FaceCheck_Server
1
FaceCheck_Verify
6
2
FaceSnap_Recorder
Around
the world
5
FaceSnap_Fotomodul
FaceSnap_IsoShot
3
4
FaceSnap_FotoShot_TwainShot
12
FaceCheck_Server
Automatic Recognition and Comparison of Facial Images, and
Notification when a Person of Interest is Identified
13
FaceCheck_Server
FaceCheck Server receives facial images from FaceSnap imaging units
within an IP network. For optimal performance, real-time facial recording
queues all images for subsequent identification.
Watch lists
(Portrait Samples)
First In –First Out
FaceSnap imaging units
14
FaceCheck_Verify
The Reliable Facial Recognition System for High Security Access
Control and Identity Checks Based on ID Photos
The images of an enrolled user may be retrieved from a database or from a chip card. The verification
process is fully automatic, optionally allowing visual monitoring by an operator and automatic image
recording on all verification attempts (providing a data file for future reference)
Live Verification
of ID Photos
15
FaceSnap Fotomodul
A Time and Cost Saving Automatic Photo Cropping Tool
Recognizes and records facial images
 Automatically crops the image according to a pre
selected portrait format.
 Automatic brightness, contrast and color
corrections for best image impression.
 Automatic background removal
.The images can be acquired either by a TWAIN
interface or directly from a file in jpg format.
16
FaceSnap_FotoShot/TwainShot
Reliable Face Detection System for High Quality Portrait Capture
• The image is taken automatically when the facial recognition software “sees” a person
who poses correctly for an ID photo.
• Locates the face and then crops automatically, resizes and color corrects the image
for maximum user convenience.
17
FaceSnap_ IsoShot
Facial Detection and Quality Assessment Software
for ISO 19794-5 Compliant Portraits
Uses facial detection technology to
automatically generate standardized portraits
Automatically set facial
landmarks to adjust
image geometry
Captures live images through remote camera control
• Instantly enhances and resizes images
• Configures camera and facial image cropping settings.
19
FaceSnap_ Recorder
An Indispensable Facial Recognition Tool for Law Enforcement,
Post-Event Analysis, Business Security.
 Automatically recognize and record facial images from different viewing angles. Users
are ensured of receiving the visual information they need quickly, efficiently and reliably.
 For Identity checks, video observation, access monitoring.
20
Conclusion-II
 Facial recognition systems is very useful for maintaining security and safety of
visitors and employees in many organizations.
 Facial recognition technology is an ideal solution for high-traffic public areas
where access control and law enforcement are of paramount importance.
Airports and railway Stations
Cash machines
Casinos
Financial institutions
Government Offices
Public transportation facilities
Stadiums
Businesses of all types
21
References
[1]. R. Chellappa, C. H. Wilson, and S. Sirohey: Human and Machine Recognition of Faces: A
Survey. Proc. of the IEEE, vol. 83, no. 5 (1995) 705-740
[2]. Y. H. Han and S. H. Hong: Recognizing Human Facial Expressions and Gesture from Image
Sequence. Journal of Biomedical Engineering Research, vol. 20, no. 4 (1999) 419-425
[3]. R. Brunelli and T. Poggio: Face Recognition: Feature versus Templates. IEEE Trans. PAMI, vol.
15, no. 10 (1993)
[4]. G. Chow and X. Li: Towards a System for Automatic Facial Feature Detection. Pattern
Recognition, vol. 26, no. 12 (1993) 1739-1775
[5]. V. Govindaraju, S. N. Srihari, and D. B. Sher: A Computational Model for Face Location. Proc.
3rd Int. Conf. Computer Vision (1990) 718-721
[6]. R. C. Gonzalez and R. E. Woods: Digital Image Processing. Addison Wesley New York (1992)
[7]. J. C. Russ: The Image Processing Handbook, 3rd Ed.. IEEE Press (1999)
[8]. D. Chai and K. N. Ngan: Face Segmentation Using Skin-color Map in Videophone
Application. IEEE Trans. Circuits and Systems for Video Technology (1999) 551-564
[9]. H-S. Yoon, M. Wang, and B-W. Min: Skew Correction of Face Image Using Eye Components
Extraction. The Journal of the Korea Institute of Telematics and Electronics, vol. 33- B, no. 12 (1996)
71-83
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References
http://en.wikipedia.org/wiki/YCbCr
http://en.wikipedia.org/wiki/Color_space
http://en.wikipedia.org/wiki/Luminance_(video)
http://en.wikipedia.org/wiki/Chrominance
http://en.wikipedia.org/wiki/Luminance
http://www.azooptics.com/Details.asp?ArticleID=154
http://www.crossmatch.com/FaceCheckVerify.html
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