unconstrained fingerprint recognition fully touchless 3 d system ieee

Toward Unconstrained Fingerprint Recognition:a Fully Touchless 3-D System

Based on Two Views on the Move

By,Sinisha George S2 MTech CS

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OVERVIEW• Problem Statement• Introduction• Related works• Proposed method• Experimental Results• Conclusion• References

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PROBLEM STATEMENT

• Require contact of the finger with any acquisition surface

• Require constrained and highly cooperative acquisition methods.

• Low usability, user acceptance and presence of distortions, less robust to dust and dirt , hygiene issues.

INTRODUCTION• Fingerprints are one of many forms of biometrics

used to identify individuals and verify their identity.• fully touchless fingerprint recognition system based

on the computation of three-dimensional models. • Models from two view image captured during

movement• less-constrained biometrics aim at using samples

captured–Contactless, higher distance, Natural light

conditions, On the move

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RELATED WORKS

A) Two dimensional system

Structured light

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RELATED WORKS

• Three dimensional system

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PROPOSED SYSTEM

BIOMETRIC RECOGNITION PROCESS

1) Acquisition2) Three-dimensional fingerprint reconstruction3) Computation of touch-compatible images4) Template computation5) Matching

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BIOMETRIC RECOGNITION PROCESS(cont.)

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1. CONTACTLESS ACQISITION

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CONTACTLESS ACQISITION(Cont.)

Fig : Rotations of the finger with respect to the optical centre of Camera A.

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CONTACTLESS ACQISITION(Cont.)

Examples of images in Dataset B captured with exaggerate finger orientations: (a) leftward yaw rotation; (b) counter clockwise roll rotation; (c)downward pitch rotation; (d) rightward yaw rotation; (e) clockwise roll rotation; (f) upward pitch rotation.

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2. THREE-DIMENSIONAL FINGERPRINT RECONSTRUCTION

1) Image pre-processing;2) Segmentation;3) Extraction and matching of the reference points;4) Refinement of the pairs of corresponding points;5) Three-dimensional surface computation and

image wrapping.

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2.1 IMAGE PREPROCESSING

• Details of the ridge pattern are Particularly visible in the green channel of the RGB color Space of the captured images

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2.2 SEGMENTATION

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2.3 EXTRACTION AND MATCHING OF THE REFERENCE POINTS

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2.3 EXTRACTION AND MATCHING OF THE REFERENCE POINTS(CONT.)

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2.4 REFINEMENT OF THE PAIRS OF CORRESPONDING POINTS

• To obtain smooth and accurate representation of the finger surface

• Applying thin plate spline to the set of corresponding points.

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2.5 THREE-DIMENSIONAL SURFACE COMPUTATION AND IMAGE WRAPPING.

• Creates a three-dimensional model MA as the depth map corresponding to the view of Camera A.

• Triangulation

• Linear interpolation– Mp, Mz

Fig: dense three-dimensional model with a superimposed texture image obtained by the proposed method

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3. COMPUTATION OF TOUCH-COMPATIBLE IMAGES

• Enhancemento background subtractionoNonlinear equalization(logarithm)o Butterworth low-pass filter

• Two dimensional mapping– Enrolment

oCompensate for rotationsoComputation of NR rotations

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3. COMPUTATION OF TOUCH-COMPATIBLE IMAGES(cont.)

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4.TEMPLATE COMPUTATION

• Neurotechnology veriFinger– Commercial feature extractor – Compute template T– Properly identifies the coordinates– Designed for touch-based images.

Fig: a binary image and minutia coordinates obtained using the proposed system and the software Verifinger

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5. MATCHING

• In the verification phase computes a single minutiae template Tf .

• Matching score represents the similarity of the fresh template with a multi-template.

• Te score is computed as,

• Match(.) – matching function ,performed using nuerotechnology verifinger software

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EXPERIMENTAL RESULTS

a) Data sets descriptionb)  Accuracy of 3D reconstruction c) Recognition performance d) User acceptability e) Interoperability 

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EXPERIMENTAL SETUP

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A) DATA SETS DESCRIPTION

Touchless - one session. 2368 samples. 10 fingers, 30 volunteers, 8 acquisitions per finger.

Touchless - two sessions 2368 samples 10 fingers, 15 volunteers, 16 acquisitions per finger. - 8acquisitions one year, 8 acquisition subsequent year .

Touchless - misplaced fingers 1200 samples 2 fingers (index), 30 volunteers, 20 acquisitions per finger

Touch-based One session Two sessions 

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B) ACCURACY OF 3D RECONSTRUCTION

• point clouds describing the three-dimensional shape of the finger and the corresponding dense three-dimensional models with superimposed texture images• Average error 0.03mm

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C) RECOGNITION PERFORMANCE

• ROC curves representing the accuracy of the proposed touchless system under standard operating conditions (Dataset). •The results represent different numbers of three-dimensional rotations NR performed during the enrolment step.• Every test included 5, 605, 056 identity comparisons. •The configuration that yielded the best accuracy was NR = 9, with EER = 0.03%.

Table: Accuracy of the proposed biometric system using samples acquired under standard operating conditions (dataset A).

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D) USER ACCEPTABILITY

• Survey performed using questionnaires.• Results show preference towards contactless

recognition.

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G) OVERVIEW OF THE DIFFERENT TECHNOLOGIES

Aspect Touch -based Touchless

accuracy EER=0.06% EER=0.03%

Usability medium High

User acceptance Medium High

Privacy Data protection techniques Data protection techniques

Speed Template extraction + matching

3D reconstruction + template extraction +matching

Cost 10$ to 5000$ 10$ to 5000$

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CONCLUSIONS

– Systems based on two-dimensional samples can be used

in low-cost applications, but the samples present distortions.

– Systems based on three-dimensional samples can obtain comparable accuracy with respect to traditional systems

– Touchless systems are characterized by higher usability, user acceptance, less constrained.

– Robust to uncontrolled environmental illumination.– Tolerate wide range of finger orientations.

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REFERENCES[[1] D. Maltoni, D. Maio, A. K. Jain, and S. Prabhakar, Handbook ofFingerprint Recognition, 2nd ed. Springer Publishing Company,Incorporated, 2009.[2] R. Donida Labati and F. Scotti, “Fingerprint,” in Encyclopedia ofCryptography and Security (2nd ed.), H. van Tilborg and S. Jajodia,Eds. Springer, 2011, pp. 460 – 465.[3] R. Donida Labati, V. Piuri, and F. Scotti, Touchless FingerprintBiometrics, ser. Series in Security, Privacy and Trust. CRC Press,2015.[4] G. Parziale, “Touchless fingerprinting technology,” in Advances inBiometrics, N. K. Ratha and V. Govindaraju, Eds. Springer London,2008, pp. 25–48.

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Verifinger S/W

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Minutiae

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Charge-coupled devices

Morphological opening operator

Morphological filling

Epipolar lines