Advances in Stand-off Biometrics

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1 Advances in Stand-off Biometrics Behnam (Ben) Bavarian, President and CEO AFIS and Biometrics Consulting Inc AFIS and Biometrics Consulting Inc. The developments in this presentation is supported by the DHS Science and Technology Contract No. NBCHC All trademarks, brands and names are property of their respective owners and are protected by US and international copyright and trademark laws. Biometrics 2011 Exhibition and Conference London, United Kingdom October 19, 2011

2 Project Objectives Build a prototype system for identifying subjects on the stand-off and on the move minimize human/sensor interaction unobtrusive detection and recognition of people on the move; Use COTS Camera/Sensors no biometric sensors for the portal. Use multiple biometric samples multiple types iris, face and fingerprints and multiple samples of each type - and combine/fuse for incremental, cumulative and highly reliable identification; Enrolments done with existing biometric sensors and processes; 2 Scenario testing: Use the system to test various new sensors, various scenarios, and user interactions at the portal; 2 2

3 Biometrics Identification on the Move System (BIMS) 3 BIMS is a system solution built with multiple commercial off the shelf cameras and sensors for capturing fingerprints, iris and face photos in an entrance and/or hallway with the software to process the information and provide detection, tracking and identification of the individuals entering the portal. The key innovations include: real-time capture and processing of large number of high resolution DSLR camera images object detection, image segmentation image enhancement feature extraction; search and match of the captured biometric samples against the large background database, incremental identification based on the progressive data capture in split seconds while the subject is walking through the portal; and multiple biometric fusion for highly reliable identification. 3 3

4 BIMS Portal Lab prototype set up Multiple Sensor Unit Kinect Range Camera Face camera Array Iris camera Fingerprint on the Move (FoM) 4

5 The steps to the final prototype BIMS portal 5 Photon-X Sensor; Northrop Grumman IR&D on stand-off biometrics; Digital transition 60+ mega pixel camera DSLR COTS cameras XBOX Kinect video and range sensor. 5

6 Multiple Sensor Unit Multiple Face and Iris Capture 6

7 Multiple Sensor Unit Multiple Face and Iris Capture 7

8 Biometric Sample Examples Sample images captured by the BIMS Face /Iris Camera Array 8 7

9 Biometrics ( Face / Iris) Capture High resolution Camera Capture & analysis leading to final prototype design Segment the left and right irises obtained 200 to 250 pixels diameter iris images 9

10 Iris biometric Standard iris images are captured at NIR and requires 120 to 200 pixels diameter. Tested and analyzed: NIR NIR Visible NIR Visible - visible 10

11 Iris individualization? What is the scientific basis for uniqueness of irises? Scientific and forensic analysis of the iris individualization is practically non-existing! What are the distinguishing characters and features which is yours and different from the person next to you? 11 Large scale testing has shown that iris matching with good quality samples is as good as fingerprint matching.

12 Standoff Iris Processing and matching 12 Segment the left and right irises obtained 200 to 250 pixels diameter iris images Auto detect iris, process and extract templates Carry match analysis Left and right eyes - Sample of 10x10 segmented iris match scores

13 Iris automated processing issues Specular light confuses the segmentation algorithm 13 Color map and occlusion confuses the segmentation algorithm

14 Why the average match scores for left eye is half of those for right eye? Histogram analysis of the image 14

15 Sample iris images from Canon 5D DSLR: 15

16 Match score distribution for iris recognition Results from our lab testing 16

17 Can we make identification with non-contact hand scan processing? 17

18 Sample Cropped and Pre-Processed Images 18

19 Can we make identification with non-contact hand scan processing? DSLR Camera set up 19

20 Hand scan processing steps second set up Pre-processing Image Binarization Post-processing Finger-palm segmentation 20

21 Sample ink and livescan fingerprints from the background database 21

22 22 Sample Images with Their Corresponding Gray-Scale, Binarized and Skeletonized Images and detected minutia

23 Right Thumb Finger! 23

24 Can we make identification with non-contact hand scan processing? 24 Segment the fingerprints obtained 750 ppi image Interpolate to 500 ppi Map to gray scale image Use standard processing to detect the ridge flow and extract the minutiae Fingerprint match report Top 7 respondents Search Id: 4029f2 Case 1, Right hand index finger Search Print Number Minutiae: 123 Rank ID Candidate # of Minutiae Match Score f f f f f f f

25 Summary results for fingerprint match score analysis Histogram of matching scores and non-matching scores, Flat captures, without thumb 25

26 Summary results for fingerprint match score analysis Histogram of matching scores and non-matching scores, Rolled captures, without thumb 26

27 Summary results for fingerprint match score analysis Histogram of the Flat and Rolled fingerprint match scores 27

28 Fingerprint on the Move (FoM) Next generation of identification and authentication product using the non-contact scan of the palmar area of the hand with high resolution COTS camera and automatically getting the information needed ( fingerprints and palmprint minutiae templates) to carry out the one to one verification and one to many identification task. The product concept is like the barcode scanners on the check-out counters in the supermarket. The surface of your hand is your unique "barcode" and our product will do the capture and process and match automatically

29 Fingerprint on the Move (FoM) 29 16

30 FoM Biometric Samples 30

31 Video Clips from BIMS MSU and FoM 31

32 BIMS by-products Mobile Biometrics Identification on the move system (M-BIMS) 32 M-BIMS or Mobile BIMS is the web-based identification product which we have developed on the Andriod smart phone. The application runs on your mobile phone and captures pictures from fingerprints and face and sends to a secure sever ( our Server in our lab) and process and extract the features and carry out a one to one match to verify your identity. This app may be used as the highly secure access entry for many use cases on the smart phone such as - access your personal data on the phone and carry out mobile commerce / banking / financial transaction with your phone

33 Mobile Biometrics Identification on the move system (M-BIMS) Phone Camera Finger/ Face Detection Focus Judgment Pre-processing Smartphone GUI for iden/verif results Internet Database Feature/Matchi ng Server Your-Fingerprint- Your-Unique-Barcode 21

34 Sample images from HTC Incredible II smart phone 8Mpixel Camera: 34

35 Sample images from HTC Incredible II smart phone 8Mpixel Camera: 35

36 BIMS by-products Hand-Match IDentification (HaMID) Stand off access control without using any fingerprint readers on the access door. The product uses very high resolution digital back camera to capture the hand image from 4 to 6 feet away process and authenticate to provide the access for the person

37 Final Project outcome inventory Biometrics Identification on the Move System (BIMS) Fingerprint on the Move (FOM) identification device Hand-Match Identification (HaMID) Mobile-BIMS Your-Fingerprint-Your-Barcod(C) Scanner Multiple Biometric Match and Fusion Services - This software package product is a complete backend services for multiple biometric identification which is scalable via multiple servers or blade servers or as deployed in the cloud server farm. It includes our commercially available fusion engine. Multiple biometric enrollment application - This is a complete software package frontend for capturing demographic and biometric data for enrollment for face, finger, palm and iris biometrics. The output record is in the standard data exchange format which can be used by any biometric backend system in the market. 37 Biometrics on Cloud Testing Framework Large scale implementation of biometrics identification on scalable server farm, deploying 100s to 1000s servers to carry out test and parameter tuning. 37

38 The project inventory Operational capabilities 38 In addition to prototype products or product solution concepts we have: The approved IRB(Internal Review Board) process which guarantees data privacy/protection for human subject test and evaluation in place; Project resources (veteran biometrics experts with 20+ years of hands on experience in product development and biometric ID system delivery) to carry the biometrics research and development work tasks and access to very large number of volunteer subjects for test and evaluation; Identification portal with scalable match and fusion services utilizing multiple algorithms and multiple biometric modality; 38

39 Concluding Remarks 39 Successful conclusion of Project with working prototype products, software and extensive testing and analysis reports on stand-off biometrics. All software products developed under the contract are license free for US Federal Government and collaborating foreign government agencies. We are looking for Phase III support for field test and commercial productization. On Technical side: Improve the ergonomics; Improve Biometric samples image quality capture; Improve samples image processing and enhancement

40 Thank you Contact: AFIS and Biometrics Consulting Inc. 896 Dove Street, 3rd Floor Newport Beach, California Phone: Fax:

41 Author Biography Behnam (Ben) Bavarian Dr. Bavarian is one of the pioneers and industry leading authority in the field of Biometric Identification with over 26 years of R&D and management experience in industry and academics. He founded the AFIS and Biometrics Consulting Inc. in 2007, providing independent subject matter expert consulting and strategic management services in Biometrics Identification Industry. The company has successfully completed more than two dozen contracts in the last three years. Prior to ABC Inc. Dr. Bavarian was the Vice President of Motorola Biometrics, where he led the business turn around and four fold increase in Sales by directing the development of the industry leading Automated Biometric Identification System products with over 100 large scale deployments. 41 Before moving to the industry in 1992, Dr. Bavarian was a professor in the Department of Electrical and Computer Engineering at the University of California, Irvine, where he conducted original research in image processing, computer vision, intelligent systems and published over 120 technical papers and received several awards for outstanding research and distinguished teaching. Dr. Behnam (Ben) Bavarian received his Ph.D. in Electrical and Computer Engineering from The Ohio State University, Columbus Ohio in 1984.

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