advances in iris recognition interoperable iris ... · pdf filesalient points ‐iris...
TRANSCRIPT
Advances in Iris Recognition
Interoperable Iris Recognition systems
Date 5/5/09
Agenda
How best to meet operational requirements
• Historical Overview of iris technology
• The current standard
• Market and Technological drivers
• Operational programs using the ISO standard
• Next steps in interoperability Research – IREX 2008
• Quality assessment –as an independent function
• DeFacto Standard Templates from 2Pi Algorithim
2
* IOM is a register Trademark of Sarnoff Corporation
Iris Recognition The Biology and The Technology
1. Iris is NOT the Retina 3. 512 Byte Digital Template
2. Digital Image/ Subtle Light 4. Authentication Robustness
Salient Points ‐ Iris Recognition
Then
• The first commercial iris products appeared in late 1997.
• Limited set of formidable players for the first 10 years.
• Single algorithm vs. multiple algorithms in the market.
• Restricted availability of core technology camera know how.
• More spent on litigation than collected revenue.
Now
• Many new entrants in the past 24 months for cameras and matching algorithms.
• Significant R&D in government, academia and commercially.
4
Market Drivers• General
– Need to process larger populations at a higher speed
– Minimize the probable outlier population using multiple biometrics
– The relative success of iris in theater
– Adoption of iris into the national criminal database at FBI
• Technological – Iris at a distance
– Iris in motion
– Portable iris
– Less than pristine iris image recognition
– Outdoor use
5
Iris Algorithms
• Historically the segmentation and template generation process has been a singular function.
• Image Quality assessment routines have been an integrated part of the template generation process
• Imposter distribution curves have not traditionally been made available to the research an integrator community
• There have been a limited number of commercial offerings
6
Segmented Image
Interoperable Iris Recognition
• Definition – ISO Iris Standard 19794‐6 – Rectilinear and Polar (segmented & un‐segmented) Image definitions
– Basic quality metrics for interoperable systems are defined
• A basic challenge is the size of the data as defined in the specification
����������� ��
����� ��
300 KB
16 KB
Image size reduction• Advances in the segmentation process may allow smaller images
• Polar image
8
����������� ���������� �������� �����������
� ������������������������������ ��
�������
����� ��������
Standards Activity surrounding Iris
• IREX 2008– The IREX 2008 test is designed to measure the accuracy, interoperability
of rectilinear and polar iris images formatted according to the ISO/IEC 19794‐6 standard, under JPEG and JPEG 2000 compression.
– The test itself will proceed in summer 2008, with a view toward making results available ahead of the SC 37 meeting in January 2009.
• Commercial Imager Evaluations (NIST)– Sponsor FBI
• Multiple Biometric Grand Challenge (NIST)– Low quality still images
– High and low quality video imagery
– Face and iris images taken under varying illumination conditions
– Off‐angle or occluded images
• FBI NGI
9
Programs Using the Iris Standard
• DOD ‐ Field operations with portable iris capture and recognition device– Images/Templates are exported to the BAT 4.0 field repository
– Matching using a proprietary algorithm
• US Registered Traveler– CIMS uses rectilinear image for de‐duplication
– Service providers use compressed polar image on a smart card for verification at the airport kiosk.
– Some international RT programs (Privium & Saphire ) use templates
• Border Crossings– Jordan, Oman,Qtar , Saudi Arabia, UAE
– Privium & Saphire ( use proprietary template on the smart card)
– CAN PASS (AKA Nexis Air)
10
NIST IREX 08
• IREX 08 is going to test three different compact formats of irisimages: – cropped images,
– Un segmented polar images,
– ROI (region of interest) images.
– NIST asked vendors to submit software that makes the compact formats and matches templates. But we were not required to support all three image formats. We can either support
• NIST will also test the boundary of various algorithm's performance characteristics with varied degrees of compression on iris imagesimages
11
Images from a distance
• Image matching probe vs. gallery– The image at the right successfully
matches against itself and the pristine quality enrollment image.
• The image at the right matches against itself, but not to an image with standard illumination.
12
A successful recognition image captured at 2 metersDifferent illumination
iCAPIris Capture & Analysis Platform
June 2008
LG Electronics USAIris Technology Division
iCAP
Flex™ 2
iData ISO SDK
Image ProcessingLibrary
Windows PC
SQL Database
Iris images
14
Why iCAP?– Some “Stage One” Objectives
• Provide a easy to use tool to enable the study of iris images from various commercial and prototype imagers.
• Process images of lesser than perfect quality as compared those used in commercial deployments of iris recognition technology which have traditionally expected pristine quality images.
• Initial GUI targeted at the mid level analyst which may have limited experience with iris recognition technology.
• Prepare a framework for the addition of other available iris matching algorithms.
• Work towards the separation of image quality assessment, segmentation, and template generation as discrete operation steps.
Different Illumination
• Commercial iris imagers use illumination in the IR bad from about 700 nm to 850 NM.
• IARPA Research Program ‐Use other wavelengths
15
Iris illuminated with 950 NMIris illuminated with 1550 NM
Diffused 1550 NM
