MAJOR PROJECT PRESENTATION

ON

PRESENTED BY :-

ABHISHEK DE & ADITYA GOENKAB.TECH 8th SEMESTERDEPARTMENT OF ELECTRONICS & COMMUNICATIONINSTITUTE OF ENGINEERING &TECHNOLOGY, ALWAR

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GUIDED BY :-

MR.RAKESH KUMAR SHARMA

HEAD OF DEPARTMENTELECTRONICS & COMMUNICATION ENGINEERING

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Fingerprint Recognition

Outline: Introduction

• Project Scope• Fingerprint Research Background

Algorithm • Overview of Approach• Detailed Design• Conclusion

WHAT IS FINGERPRINT???

Feature pattern of one finger Composed of many ridges and furrows Fingerprint recognition is done using abnormal

points on these ridges, called as ‘minutia’

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FINGERPRINT RECOGNITION

Left Loop Right Loop

Whorl Arch Tented Arch

Delta

Pore

WHY FINGERPRINT MATCHING???

Unique Scientifically Reliable Permanent

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Termination Bifurcation

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Algorithm Level Design

•Thinning

•Pixel-to-pixel matching

Minutia extraction

Preprocessing•Image Enhancement•Image Binarization•Image Segmentation

Post-processing

STEPS INVOLVED IN FINGERPRINT MATCHING

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LOADING ORIGINAL FINGERPRINT

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HISTOGRAM EQUALIZATION9

ORIGINAL IMAGE HISTOGRAM EQUALIZED IMAGE

HISTOGRAM PLOTS OF IMAGES10

HISTOGRAM OF ORIGINAL IMAGE

HISTOGRAM OF EQUALIZED IMAGE

ENHANCEMENT USING FFT

• The enhanced image after FFT has the improvements to connect some falsely broken points on ridges and to remove some spurious connections between ridges

• Formula for the calculation using Fast Fourier Transform(FFT) is :-

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BINARIZATION

• Binarization is to transform the 8-bit Gray fingerprint image to a 1-bit image with 0-value for ridges and 1-value for furrows.

• After the operation, ridges in the fingerprint are highlighted with black color while furrows are white.

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BINARIZED IMAGE

IMAGE SEGMENTATION

• The main purpose behind image segmentation is to obtain the Region of Interest (ROI)

• To extract the ROI, a two-step method is used :-STAGE 1 - Block direction estimationSTAGE 2 - ROI extraction by Morphological operations

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RIDGE DIRECTION

• Gradient values along x-direction (gx) and y-direction (gy) for each pixel of the block is calculated using ‘Sobel Filter’

• Tangent value of the block direction is estimated using the following formula :-

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tg2 = 2sin cos /(cos2 -sin2 )

DIRECTION MAP

ROI EXTRACTION USING MORPHOLOGICAL OPERATION

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Original image After close operation After open operation ROI + Bound

SEGMENTED IMAGE16

Binarized Image ROI Extracted Image

THINNING OF ROI EXTRACTED IMAGE

• Ridge Thinning is to eliminate the redundant pixels of ridges till the ridges are just one pixel wide.

• The thinned ridge map is then filtered by other three Morphological operations to remove some H breaks, isolated points and spikes.

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Thinned image

PIXEL TO PIXEL MATCHING

• The images after thinning of minutia of two different fingerprints are matched by pixel-to-pixel comparison of the two images.

• If minimum 80 % of the pixels match, then fingerprints are approximately matched.

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References

[1] Rafael C. Gonzalez, Richard E. Woods, “Digital Image Processing”,ISBN-978-81-203-3640-7, by Prentice Hall Publication, Third Edition, 2008.

[2] Rafael C. Gonzalez, Richard E. Woods,Steven L. Eddins, “Digital Image Processing Using Matlab”,ISBN-978-81-7758-898-9, by Prentice Hall Publication, Fourth Edition, 2008.

[3] Jain, A.K., Hong, L., and Bolle, R.(1997), “On-Line Fingerprint Verification,” IEEE Trans. On Pattern Anal and Machine Intell, 19(4), pp. 302-314.

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Conclusion

All the objectives of the software have been accomplished and the main aim of fingerprint recognition with image processing techniques have been achieved.

Application of fingerprint recognition techniques are widely used in forensic and biometric diagnosis.

Plethora of research related activities have also been focussed.

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QUESTIONS?????

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THANK YOU !!!!!!

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