# Presentation: 016396

## Iris Recognition Device Usability as Observed in Comparative Testing

*The International Workshop on Usability and Biometrics*
*24 June 2008*
*Michael Thieme*
*Director of Special Projects *
*International Biometric Group*
- _[mthieme@biometricgroup.com](mailto:mthieme@biometricgroup.com)_* *

*Copyright © 2008**International Biometric Group*

## Topics

- Iris recognition capture device landscape
- Application-specific usability
- Special considerations in mobile collection
- Evaluating usability through scenario testing
- Usability-related performance test results
- Observations on iris usability
- Potential research areas

## About International Biometric Group

- International Biometric Group, LLC
- Founded 1996; 40 employees
- Staff in New York, DC Metro, San Francisco
- Technology-neutral, vendor-independent
- Biometric systems integration
- Design, develop, implement biometric identification systems
- From mobile data collection to large-scale matching
- Biometric R&D and evaluation
- 10+ years of biometric R&D and evaluation expertise
- Conducted $5m+ in USG-funded biometric R&D
- Biometric consulting
- SMEs for USG agencies: DHS, Executive Branch, IC
- Insight into biometric vendors, industry landscape
- Hands-on experience with all biometric technologies

## Iris Recognition Testing Experience

- Comparative Biometric Testing (1998-present)
- Tested Panasonic AuthentiCam, LG2200, IrisGuard, JIRIS
- Standardized scenario test methodology applicable to fingerprint, face, voice, signature, hand, vein
- First test effort to measure and report false non-match and failure-to-enroll rates for iris recognition
- DHS Independent Testing of Iris Recognition Technology (2004-2005)
- Collected approximately 120,000 irises, conducted 2b matches
- First test to evaluate interoperability across multiple iris devices
- First test to measure statistically significant false match rates
- Currently performing operational testing for tactical field deployments of iris recognition devices (GWOT)
- Factors: usability, data quality

## Iris Recognition Capture Device Landscape

- Considerable variation across iris recognition devices
- Single vs. dual-iris imagers
- Simultaneous vs. serial capture
- User-adjusted vs. auto-adjusting
- Fixed-focal length vs. auto-focus
- Volumetric range
- Audio and visual prompts
- Single-capture enrollment vs. multi-capture enrollment
- Arguably greater inter-device variation than in any other modality

## Application-Specific Usability

- Registered traveler
- Educated, tech-savvy, motivated users; low habituation; low throughput demands
- Perception of invasiveness not tolerable
- High-end access control
- Motivated, habituated users; rapid throughput required
- Device must be calibrated for fast capture
- Benefits issuance / immigration control (Pak / UAE)
- Low habituation, limited familiarity with technology; motivation may be questionable; can be invasive
- Deployer may deploy head brace or other harness
- Mobile population control
- Similar to preceding, with addition of environmental challenges (see discussion below); perceived invasiveness may be the point

## Special Considerations in Mobile Collection

- Mobile iris collection a dynamic area
- ~1m irises collected through BAT
- Adds the operator as a variable
- What prompts are most instructive to an operator?
- Does the operator have two hands free?
- How close is too close?
- Tactile vs. distance-based devices

## Measuring Usability in Scenario Testing  

- Performance metrics applicable to usability
- Failure to enroll / failure to acquire rate
- Transaction time
- False non-match rate
- These are indirect measures of usability, conflated with other factors
- Challenge: how to habituate users in a highly compressed test timeframe, while still allowing for device-to-device differentiation
- More training penalizes easy-to-use devices; less training penalizes difficult-to-use devices
- Can run multiple, sequential recognition transactions to drive muscle memory in test subjects

## Usability and Transaction Duration

## Usability and FTE / Non-Match Errors

## FTA by Age Range

| LG IrisAccess 3000 | Age Range | Recognition Attempts | Recognition Attempts with No Sample Acquired | FTA |
| --- | --- | --- | --- | --- |
| Total | 18-35 | 15930 | 760 | 4.77% |
|  | 36-50 | 10598 | 415 | 3.92% |
|  | 51-65 | 3666 | 247 | 6.74% |
|  |  |  |  |  |
| OKI 
IRISPASS-WG | Age Range | Recognition Attempts | Recognition Attempts with No Sample Acquired | FTA |
| Total | 18-35 | 15890 | 407 | 2.56% |
|  | 36-50 | 10552 | 356 | 3.37% |
|  | 51-65 | 3707 | 171 | 4.61% |
|  |  |  |  |  |
| Panasonic
 BM-ET300 | Age Range | Recognition Attempts | Recognition Attempts with No Sample Acquired | FTA |
| Total | 18-35 | 15930 | 363 | 2.28% |
|  | 36-50 | 10602 | 371 | 3.50% |
|  | 51-65 | 3690 | 259 | 7.02% |

## Observations on Iris Usability

- Iris recognition trails most other biometrics in terms of usability, but improvement is continual
- Dual-iris “mirror” imagers are problematic
- Adjustment for stronger eyes lead to misalignment, looking with wrong eye – leads to failures or off-axis captures
- Difficult to develop an interface intuitive for non-engineers
- Primary value is in reducing sequencing errors, not simplifying capture
- Older users have more difficulty interacting with devices
- Vision? Technology exposure? Other factors...
- Substantial progress has been made in “vicinity” capture
- User stands in specified area, looks in general direction of imager; no explicit alignment
- Attempt to eliminate problem of initial orientation (distance from device, where to look)

## Potential Research Areas

- Enrollment / recognition through multiple, lower-quality video frames
- Addressing dominant and weak eyes
- Correcting sequence errors
- Usability as a function of operator skills (mobile)

## Contact

- Michael Thieme
- _[mthieme@biometricgroup.com](mailto:mthieme@biometricgroup.com)_
- 212-809-9491 (NY Office)
- 917-375-8206 (Mobile)