When failure to match is not an option

When failure to match is not an optionInnovative 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

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Overview

• About us• Technology • Products & features• Performance & evaluations• Summary

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Warwick Warp

• 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

• 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;• 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

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Technology

• Innovative technology uses a new model based statistical approach to overcome many of these problems.

• New approach features;• Intrinsic mathematical representation of the

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

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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

• NFIQ tests before and after show the improvement produced by the technology.

NFIQ Quality Score Before and After WW Processing NIST SD29

90% to 10%

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Evaluation and Benchmarks-Civil

• NPL (National Physical Laboratory, UK) independent benchmark – WW technology equals market leaders.

Warwick Warp

NPL Benchmark Against Leading AFIS Vendors

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Evaluation and Benchmarks-Civil

• 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.

NIST Benchmark Against Leading AFIS Vendors (0.1% FAR)

Rank Company AVG

1 Cogent 0.9993752 NEC 0.9988253 Warwick Warp 0.9987754 BioKey 0.9986755 Tiger IT 0.9986256 L1 0.998457 Sagem 0.9982758 Motorola 0.9978759 Neurotech 0.99787510 Sonateq 0.99777511 Identix 0.99747512 Thales 0.99640013 Biolink 0.99357514 Eastern Golden Finger 0.98772515 USFIS 0.924025

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Evaluation and Benchmarks-by Quality

• 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

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Evaluation and Benchmarks-Latent

• 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

• Innovative technology uses a new model based statistical approach to overcome many of these problems.

• New approach features;• Intrinsic mathematical representation of the

ridge flow structure.• Produces “idealized” fingerprint images that

preserve distinctive features

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Technology

• Innovative technology uses a new model based statistical approach to overcome many of these problems.

• New approach features;• Intrinsic mathematical representation of the

ridge flow structure.• Produces “idealized” fingerprint images that

preserve distinctive features • Specific model for semi-permanent features

e.g. scars or scratches

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Technology

• Innovative technology uses a new model based statistical approach to overcome many of these problems.

• New approach features;• Intrinsic mathematical representation of the

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

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Technology

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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

• 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:

• 1. Major European Passport control 2. Mission Critical humanitarian project in Affica3. Ministry of Defence in the UK4. Mobile AFIS in CHINA

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Performance parameters: Accuracy, Speed (Matching/Extraction), memory/space requirements.

• 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

• 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).

• Licence key and online or offline activation

Licensing Model

• Per node lock licence or enrolled users

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Interoperability with various sensors (optical/capacitive/multispectral etc.).

• Support all sensors providing images in all major formats such as raw, png, jpeg, gif, bmp, wsq

Interoperability with various extractors (client side)

• Any MINEX compatible extractors

Compatibility with various devices

• Support any device in X86 architecture with Windows / Linux OS

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Support for Iris• Can be supplied through our partner Smartsensor Ltd if required

Sample code for JAVA functions related to Verification, Identification, extractor, Quality test, segmentation. • 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. • Support raw, wsq, png, jpeg, bmp, gif

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Compliance to various standards. • Minex (ANSI/NIST 378) Compatable, ISO 19794-4

Scaling requirements for 1 Million authentications per hour.

• 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

• 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

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Thank YouThank You

India Partners• Anaxee Technologies Pvt. Ltd.• Mobile: +91-96300 20005• Email: govind@anaxeetech.com• Web: www.anaxeetech.com• Contact Person: Govind Agrawal

UK• Li Wang• CEO, Warwick Warp