ICE Phase I test Res

Using Multiscale Vari

Multisector Metho

Hyeong In Choi

& Daniel Dae

Seoul National University IriTec
The Object of This Presenta

• Establish the bottom line performa• Investigate how enabling algorithm

accuracy

− Iris & Pupil Border Detection− Occlusion Location Estimation− Image Quality Measure

• Examine the accuracy and robustn

recognition algorithms under variocircumstances

• Study how to reject bad images in 

achieve (almost) separation

23 March 2006 ICE Phase I Test Result
Classification of Tests

Iris & Pupil

Border Detection

Occlusion Location 

Estimation Im

Type A Manual Manual Type B Automatic Manual 

Type C Automatic Manual Au

Type D Automatic Automatic Au

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Image characteristics

»Diverse image qualities

- Sharp

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Image characteristics

»Diverse image qualities

- Reasonably Sharp

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Image characteristics

»Diverse image qualities

- Reasonably Blurry

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Image characteristics

»Diverse image qualities

- Quite Blurry

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Image characteristics

»Diverse image qualities

- Side Gazing

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Image characteristics

»Diverse image qualities

- Wearing Contact Lenses

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Image characteristics

»Diverse image qualities

- Reasonably Occluded

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Image characteristics

»Diverse image qualities

- Severely Occluded

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Type A Test : 

Establishing the Bo

 Pupil/ Iris Border Detection : Manual

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Type A Test : 

Establishing the Bo

 Occlusion Location Estimation : Manual

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Type A Test : 

Establishing the Bo

 Image Selection

 Group 1: All images Group 2: All images except very blurry ones Group 3: All images except side gazing ones Group 4: All images except severely occlude Group 5: Intersection of groups 2, 3, and 4 a

those images not rejected as very 

gazing, or severely occluded

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Number of Images Rejected

Group1 Group2 Group3 Grou

Right 0958 

Left

0 23

5 14 

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Accuracy

Group1 Group2 Group3 Grou

EER 0.0018 0.0015 0.0007 0.00

VR@FAR=0.001 0.9979 0.9984 0.9995 0.99

Right Eye Image

Group1 Group2 Group3 Grou

EER 0.0054 0.0030 0.0037 0.00

VR@FAR=0.001 0.9928 0.9967 0.9951 0.99

Left Eye Image

23 March 2006 ICE Phase I Test Result
IQ ROC Curve – Right Eye I

1

2

3

4

5

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IQ ROC Curve – Left Eye im

1

2

3

4

5

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Type B Test

 Pupil/ Iris Border Detection : Automatic 

( Non-circu

 Occlusion Location Estimation : Manual Image Selection : Manual

 Group 1: All images Group 2: All images except very blurry ones Group 3: All images except side gazing ones Group 4: All images except severely occlude Group 5: Intersection of groups 2, 3, and 4 a

those images not rejected as very 

gazing, or severely occluded

23 March 2006 ICE Phase I Test Result
Number of Images Rejected

Group1 Group2 Group3 Group

Right 0958 

Left

0 23

5 14 

23 March 2006 ICE Phase I Test Result
Accuracy

Group1 Group2 Group3 Gro

EER 0.0028 0.0025 0.0008 0.0

VR@FAR=0.001 0.9963 0.9970 0.9993 0.9

Right Eye Image

Group1 Group2 Group3 Gro

EER 0.0070 0.0044 0.0056 0.0

VR@FAR=0.001 0.9910 0.9950 0.9930 0.9

Left Eye Image

23 March 2006 ICE Phase I Test Result
IQ ROC Curve – Right Eye I

1

2

3

4

5

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IQ ROC Curve – Left Eye Im

1

2

3

4

5

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Type C Test

 Pupil/ Iris Border Detection : Automatic

( Non-circu

 Occlusion Location Estimation : Manual Image Selection : Automatic by IQ Meas

 Group 1: All images regardless of the QM va Group 2: Images whose QM value >= 0 Group 3: Images whose QM value >= 1 Group 4: Right Images whose QM value >= 

Left Images whose QM value >= 7

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Number of Images Rejected

Group1 Group2 Group3 

Right

0 13 18 

Left

0 10 20 

23 March 2006 ICE Phase I Test Result
Accuracy

Group1 Group2 Group3 

EER 0.0028 0.0008 0.0007 

VR@FAR=0.001 0.9963 0.9992 0.9993 

Right Eye Image

Group1 Group2 Group3 

EER 0.0070 0.0053 0.0044 

VR@FAR=0.001 0.9910 0.9933 0.9944 

Left Eye Image

23 March 2006 ICE Phase I Test Result
IQ ROC Curve – Right Eye I

1

2

3

4

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IQ ROC Curve – Left Image

1

2

3

4

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Type D Test : Fully Automa

 Pupil/ Iris Border Detection : Automatic 

( Non-circu

 Occlusion Location Estimation : Automa Image Selection: Automatic by IQ Meas

 Group 1: All images  Group 2: Images whose QM value >= 0 Group 3: Images whose QM value >= 1 Group 4: Right Images whose QM value >= 

Left Images whose QM value >= 7

23 March 2006 ICE Phase I Test Result
Number of Images Rejected

Group1 Group2 Group3 

Right

0 13 18 

Left

0 10 20 

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Accuracy

Group1 Group2 Group

EER 0.0035 0.0016 0.001

VR@FAR=0.001 0.9953 0.9982 0.998

Right Eye Image

Group1 Group2 Group

EER 0.0069 0.0049 0.004

VR@FAR=0.001 0.9906 0.9939 0.994

Left Eye Image

23 March 2006 ICE Phase I Test Result
IQ ROC Curve – Right Eye I

1

2

3

4

23 March 2006 ICE Phase I Test Result
IQ ROC Curve – Left Eye Im

1

2

3

4

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The Conclusion

• Iritech algorithm is rather robust and qu• Automatic pupil & iris border detection h

adverse impact on accuracy

• Automatic occlusion location estimation 

adverse impact on accuracy

• Image quality has major impact on accu

− Image quality measure still has room for imp

23 March 2006 ICE Phase I Test Result
The Conclusion

• In order to improve the accuracy and rob

recognition, it is necessary to use 

− Both eye− Multiple frames− Utilize more sophisticated decision process 

simplistic single scalar quantity to describe t

23 March 2006 ICE Phase I Test Result