When failure
to match is
not an option
Innovative new technology for accurate
matching of low-quality fingerprints
India Partners
• Anaxee Technologies Pvt. Ltd.
• Mobile: +91-96300 20005
• Email: govind@anaxeetech.com
• Web: www.anaxeetech.com
• Contact Person: Govind Agrawal
Overview
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About us
Technology
Products & features
Performance & evaluations
Summary
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Warwick Warp
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Incorporated Jan 2006.
Spin out from the Image
Processing Group, Department of
Computer Science, University of
Warwick.
Offices at Venture Centre,
Warwick Science Park, Coventry,
UK.
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Technology
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Objective is to increase the accuracy of
fingerprint matching.
Technical problem is fingerprint variation
and associated low quality issues; partial
prints, background interference, scars,
smudges, scratches, wear & tear, age &
occupation, linear & elastic distortion.
Increasing accuracy by dealing with
fingerprint quality issues is important;
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Opens up new applications where there
is a higher proportion of low quality
fingerprints.
• High Proportion of Manual Labor
• Latent/Forensic Applications
• Mobile Applications
• Military Applications
Technology
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Innovative technology uses a new model based statistical approach to
overcome many of these problems.
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New approach features;
• Intrinsic mathematical representation of the
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ridge flow structure.
Produces “idealized” fingerprint images that
preserve distinctive features
Specific model for semi-permanent features
e.g. scars or scratches
Capable of modeling partial prints
Models low contrast and smudged images
Products & Features
Warwick Warps’ business is the development and
licensing of software technology for biometrics
applications.
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Evaluation and Benchmarks-by Quality
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NFIQ tests before and after show the
improvement produced by the technology.
NFIQ Quality Score Before and After
WW Processing NIST SD29
100%
NFIQ 5
90%
80%
70%
90% to 10%
NFIQ 4
60%
NFIQ 3
50%
40%
NFIQ 2
30%
20%
NFIQ 1
10%
0%
Before
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After
Evaluation and Benchmarks-Civil
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NPL (National Physical Laboratory, UK)
independent benchmark – WW technology
equals market leaders.
NPL Benchmark Against Leading
AFIS Vendors
Warwick Warp
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Evaluation and Benchmarks-Civil
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NPL (National Physical Laboratory, UK)
independent benchmark – WW technology
equals market leaders.
NIST (National Institute for Science and
Technology, US) independent benchmark
places WW technology in top tier.
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NIST Benchmark Against Leading
AFIS Vendors (0.1% FAR)
Rank Company
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
Cogent
NEC
Warwick Warp
BioKey
Tiger IT
L1
Sagem
Motorola
Neurotech
Sonateq
Identix
Thales
Biolink
Eastern Golden Finger
USFIS
AVG
0.999375
0.998825
0.998775
0.998675
0.998625
0.99845
0.998275
0.997875
0.997875
0.997775
0.997475
0.996400
0.993575
0.987725
0.924025
Evaluation and Benchmarks-by Quality
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NFIQ tests before and after show the
improvement produced by the technology.
Independent commercial evaluations –
performance gap widens as proportion of
low quality fingerprints increases.
Error % Comparison by NFIQ
Classification
8.00%
7.00%
6.00%
Error %
5.00%
4.00%
3.00%
2.00%
1.00%
0.00%
All
WW
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NFIQ=4,5
AFIS
Evaluation and Benchmarks-Latent
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NIST ELFT-EFS public challenge
• Latent product development started
in Apr 2009
• Submitted to NIST in July 2009
• Latest Version features significant
improvements
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Technology
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Innovative technology uses a new model based statistical approach to
overcome many of these problems.
New approach features;
• Intrinsic mathematical representation of the
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Confidential
ridge flow structure.
Produces “idealized” fingerprint images that
preserve distinctive features
Technology
•
Innovative technology uses a new model based statistical approach to
overcome many of these problems.
•
New approach features;
• Intrinsic mathematical representation of the
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•
Confidential
ridge flow structure.
Produces “idealized” fingerprint images that
preserve distinctive features
Specific model for semi-permanent features
e.g. scars or scratches
Technology
•
Innovative technology uses a new model based statistical approach to
overcome many of these problems.
•
New approach features;
• Intrinsic mathematical representation of the
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•
•
Confidential
ridge flow structure.
Produces “idealized” fingerprint images that
preserve distinctive features
Specific model for semi-permanent features
e.g. scars or scratches
Capable of modeling partial prints
Technology
Confidential
Other Examples
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Other Examples
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Other Examples
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Other Examples
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Real life deployments
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MoD contracts – Latent/AFIS SDK
Mission Critical Humanitarian projects – AFIS/Latent SDK
30+ construction sites for work force management – Livescan SDK
Passport control project – Enrollment/AFIS SDK
Auto capture for a major hardware manufacturer – Enrollment SDK
Web-based payment authorisation – Livescan SDK
Mobile AFIS screening project – Latent SDK, Livescan SDK
To Name a few:
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1. Major European Passport control
2. Mission Critical humanitarian project in Affica
3. Ministry of Defence in the UK
4. Mobile AFIS in CHINA
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Performance parameters: Accuracy, Speed
(Matching/Extraction), memory/space requirements.
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Accuracy, see the datasheet, also refer to NIST PFT tests
http://biometrics.nist.gov/cs_links/PFT/tables2f_040510.pdf (Letter: 2E)
Speed: 1:1 matching 4,500 per second per processor core (Intel >2.6GHz)
Template size: between 1-2KB
Memory for the program: >50MB
Technical support during integration of SDK
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Email, phone support from the UK headoffice
Field support provided by Anaxee Technologies
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Methods for license activation on server (during
testing & benchmarking).
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Licence key and online or offline activation
Licensing Model
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Per node lock licence or enrolled users
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Interoperability with various sensors
(optical/capacitive/multispectral etc.).
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Support all sensors providing images in all major formats such as raw,
png, jpeg, gif, bmp, wsq
Interoperability with various extractors (client
side)
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Any MINEX compatible extractors
Compatibility with various devices
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Support any device in X86 architecture with Windows / Linux OS
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Support for Iris
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Can be supplied through our partner Smartsensor Ltd if required
Sample code for JAVA functions related to
Verification, Identification, extractor, Quality
test, segmentation.
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Currently supports only C++, .NET, but JAVA interface can be supplied if
required
Support for various image formats in the ISO
FIR during feature extraction.
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Support raw, wsq, png, jpeg, bmp, gif
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Compliance to various standards.
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Minex (ANSI/NIST 378) Compatable, ISO 19794-4
Scaling requirements for 1 Million
authentications per hour.
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On an Intel based (>2.6GHz) dual core machine,
assuming template extraction for prob images are performed at client side,
WW matching SDK can handle >32 million authentication (1:1) requests.
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Summary
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New innovative technical approach –
accurate, fast and highly scalable.
Top tier AFIS accuracy performance benchmarked by NPL and NIST
Market leading matching accuracy of
low quality fingerprints.
Technology complementary to other
conventional image processing
approaches
Confidential
Thank You
UK
• Li Wang
• CEO, Warwick Warp
Confidential
India Partners
• Anaxee Technologies Pvt. Ltd.
• Mobile: +91-96300 20005
• Email: govind@anaxeetech.com
• Web: www.anaxeetech.com
• Contact Person: Govind Agrawal