Human Face Recognition

 Comparison of various biometric technologies

Introduction

Biometrics_and_
human_biometrics

Comparison_of_various_
biometric_technologies

Biometric_systems

Performance_of_
biometric_system

Correlation_pattern_
recognition_for_face
_recognition

Overview_of_correlation_filters

Face_recognition_with
_correlation_filters

Graceful_degradation

Shift_invariance

Phase_only_correlation

1d_phase_only_correlation

Face_recognition_methods

3_d_face_recognition

Achieving_illumination_
invariance

Method_details

Adaptive_framework

Pca_and_lda_based_
neural_network_
for_human_face_recognition

Principal_component_analysis

Linear_discriminant_analysis

Neural_networks

Feedforward_neural_networks

Learning_algorithm

Training_and_testing_
of_neural_networks

3d_face_recognition

Challenges_for_face_recognition

From_2d_to_3d_face_recognition

Advantages_and_disadvantages
_of_3D_face_recognition

3d_face_matching

Matlab_program_1_
for_face_recognition

Matlab_program_2_
for_face_recognition

Matlab_program_3_
for_edge_detection

Matlab_program_4_noise_insertion

Matlab_program_4_
alphanumeric_character_detection
_and_fourior_transform

Matlab_program_5_
edge_detection_of_2_
same_alphanumeric_chars

Fourier_transform_of_2_diff

Edge_detection_cross_correlelation

Utility_of_sobel_
and_canny_for_edge_detection

Human_face_detection_conclusion

Comparison of various biometric technologies:

It is possible to understand if a human characteristic can be used for biometrics in terms of the following parameters:

 

  • Universality describes how commonly a biometric is found individually.
  • Uniqueness is how well the biometric separates individually from another.
  • Permanence measures how well a biometric resists aging.
  • Collectability ease of acquisition for measurement.
  • Performance accuracy, speed, and robustness of technology used.
  • Acceptability degree of approval of a technology.
  • Circumvention ease of use of a substitute.



 

 

 

The following table shows a comparison of existing biometric systems in terms of those parameters:

Comparison of various biometric technologies, according to A. K. Jain (H=High, M=Medium, L=Low)

Biometrics:  ↓

Universality  ↓

Uniqueness  ↓

Permanence  ↓

Collectability  ↓

Performannce  ↓

Acceptability  ↓

Circumvention*  ↓

Face

H

L

M

H

L

H

L

Fingerprint

M

H

H

M

H

M

H

Hand geometry

M

M

M

H

M

M

M

Keystrokes

L

L

L

M

L

M

M

Hand veins

M

M

M

M

M

M

H

Iris

H

H

H

M

H

L

H

Retinal scan

H

H

M

L

H

L

H

Signature

L

L

L

H

L

H

L

Voice

M

L

L

M

L

H

L

facial thermograph

H

H

L

H

M

H

H

Odor

H

H

H

L

L

M

L

DNA

H

H

H

L

H

L

L

Gait

M

L

L

H

L

H

M

Ear recognition

M

M

H

M

M

H

M

* - circumventability listed with reversed colors because low is desirable here instead of high

A. K. Jain ranks each biometric based on the categories as being either low, medium, or high. A low ranking indicates poor performance in the evaluation criterion whereas a high ranking indicates a very good performance.

 

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