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Hand Geometry
Hand Geometry
Hand geometry is a biometric technique,
which identifies person through the hand
geometry measurements.
 Some geometric structures related to a
human hand (e.g., length and width of
hand) are relatively invariant to an
individual.
Where used
Access Control
Used to access Health clubs, Day care
centers,
Laboratories, Prisons, etc.
 Time & Attendance
 Personal Identification
Equipment
Scanner
 Pins
Screen
 Punch keys (if desired)
Swipe (if desired)
Hand Geometry Biometric System
Biometrics System
Image Processing
Feature Extraction
Feature Matching
Hand Geometry Verification System
Features extracted
Generate a feature vector Vh, including 5 lengths of fingers, 10 widths
of fingers, and the width between v1 to v2.
Performance Evaluation
 FAR and FRR stands for false acceptance rate
and false rejection rate, respectively. The FAR
and FRR are defined as below:
 Equal error rate (EER) where FAR = FRR.
Advantage
 Almost all of the working population has hand
 Fast capture/processing: It use low-computational
cost
 algorithms, which leads to fast results.
 Medium cost as it need a platform and a medium
 resolution CCD camera
 Very easy and attractive to users: leading to
nearly null user rejection
Advantage
 Less invasion of privacy and templates cannot
be “reverse engineered” to identify users
 Simple method of sensing
 Computations are easy wherefore system is easy
to build
 Easy to integrate with other biometrics as
fingerprint
 Storage efficient (9-25 bytes)
Limitations
 Large size of hand geometry devices
 Can only be used for verification
 Many hands are very similar in shape and size,
 system may confuse someone else’s hand for yours
 Would have to be combined with another system in
order for complete identification
 Training required
 Some people do not have hands or measurable
fingers for various reasons
Comparison between biometrics
Biometric Type Accuracy Ease of Use User Acceptance
Fingerprint High Medium Low
Hand Geometry Medium High Medium
Voice Medium High High
Retina High Low Low
Iris Medium Medium Medium
Signature Medium Medium High
Face Low High High

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Hand _geometry _information _hiding .ppt

  • 2. Hand Geometry Hand geometry is a biometric technique, which identifies person through the hand geometry measurements.  Some geometric structures related to a human hand (e.g., length and width of hand) are relatively invariant to an individual.
  • 3. Where used Access Control Used to access Health clubs, Day care centers, Laboratories, Prisons, etc.  Time & Attendance  Personal Identification
  • 4. Equipment Scanner  Pins Screen  Punch keys (if desired) Swipe (if desired)
  • 5. Hand Geometry Biometric System Biometrics System Image Processing Feature Extraction Feature Matching
  • 7. Features extracted Generate a feature vector Vh, including 5 lengths of fingers, 10 widths of fingers, and the width between v1 to v2.
  • 8. Performance Evaluation  FAR and FRR stands for false acceptance rate and false rejection rate, respectively. The FAR and FRR are defined as below:  Equal error rate (EER) where FAR = FRR.
  • 9. Advantage  Almost all of the working population has hand  Fast capture/processing: It use low-computational cost  algorithms, which leads to fast results.  Medium cost as it need a platform and a medium  resolution CCD camera  Very easy and attractive to users: leading to nearly null user rejection
  • 10. Advantage  Less invasion of privacy and templates cannot be “reverse engineered” to identify users  Simple method of sensing  Computations are easy wherefore system is easy to build  Easy to integrate with other biometrics as fingerprint  Storage efficient (9-25 bytes)
  • 11. Limitations  Large size of hand geometry devices  Can only be used for verification  Many hands are very similar in shape and size,  system may confuse someone else’s hand for yours  Would have to be combined with another system in order for complete identification  Training required  Some people do not have hands or measurable fingers for various reasons
  • 12. Comparison between biometrics Biometric Type Accuracy Ease of Use User Acceptance Fingerprint High Medium Low Hand Geometry Medium High Medium Voice Medium High High Retina High Low Low Iris Medium Medium Medium Signature Medium Medium High Face Low High High