Fingerprint recognition using matlab

 

Table Of Contents


  • <p> </p><p>Acknowledgement – – – .. &nbsp;2 </p><p>

Chapter ONE

INTRODUCTION

  • &nbsp; – – – – &nbsp;6 </p><p><b>
  • 1.1INTRODUCTION &nbsp; – – . &nbsp;7 </b></p><p>
  • 1.2Biometrics &nbsp; – – – – &nbsp;8 </p><p>
  • 1.3Biometrics Authentication Techniques &nbsp; – . &nbsp;8 </p><p>
  • 1.4How Biometric Technologies Work &nbsp; – – . &nbsp;8 </p><p>1.
  • 4.1Enrollment &nbsp; – – .. &nbsp;9 </p><p>1.
  • 4.2Verification &nbsp; – – – – .. &nbsp;10 </p><p>1.
  • 4.3Identification &nbsp; – – – – .. &nbsp;10 </p><p>1.
  • 4.4Matches Are Based on Threshold Settings &nbsp; – .. &nbsp;11 </p><p>
  • 1.5Leading Biometric Technologies &nbsp; – – – &nbsp;12 </p><p>
  • 1.6Fingerprints as a Biometric &nbsp; – – – – .. &nbsp;13 </p><p>1.
  • 6.1Fingerprint Representation &nbsp; – – – . &nbsp;14 </p><p>1.
  • 6.2Minutiae &nbsp; – – – &nbsp;14 </p><p><b>

Chapter TWO

LITERATURE REVIEW

  • </b>&nbsp;Motivation for the project &nbsp; – – &nbsp;16 </p><p>
  • 2.1Problem Definition &nbsp; – – – – &nbsp;17 </p><p>
  • 2.2Motivation for the Project &nbsp; – – &nbsp;18 </p><p>
  • 2.3About the Project &nbsp; – – – – .. &nbsp;18 </p><p><b>

Chapter THREE

SYSTEM DESIGN AND IMPLEMENTATION

  • </b>System design – – . &nbsp;20 </p><p>
  • 2.1System Level Design &nbsp; – – – . &nbsp;21 </p><p>
  • 2.2Algorithm Level Design &nbsp; – – .. &nbsp;22 </p><p><b>

Chapter FOUR

SYSTEM TESTING AND EVALUATION

  • </b>&nbsp;Fingerprint image preprocessing &nbsp; – – – . &nbsp;24 </p><p>
  • 4.1Fingerprint Image Enhancement – – .. &nbsp;25 </p><p>4.
  • 1.1Histogram Equalization: &nbsp; – – – – &nbsp;26 </p><p>4.
  • 1.2Fingerprint Enhancement by Fourier Transform &nbsp; – – .. &nbsp;28 </p><p>
  • 4.2Fingerprint Image Binarization &nbsp; – – – .. &nbsp;30 </p><p>
  • 4.3Fingerprint Image Segmentation (orientation flow estimate) – – – – .. &nbsp;32 </p><p>4.
  • 3.1Block direction estimation – – – .. &nbsp;32 </p><p>3.
  • 3.2ROI extraction by Morphological operation – .. &nbsp;34 </p><p><b>

Chapter FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS

  • </b>Minutiae extraction &nbsp; – – – – . &nbsp;36 </p><p>
  • 5.1Fingerprint Ridge Thinning – – – – .. &nbsp;37 </p><p>
  • 5.2Minutia Marking &nbsp; – – – – &nbsp;39 </p><p><b>Chapter six: </b>Minutiae post-processing &nbsp; – – – &nbsp;42 </p><p>False Minutia Removal &nbsp; – – – .. &nbsp;43 </p><p><b>Chapter seven: </b>Minutiae match &nbsp; – – . &nbsp;46 </p><p>
  • 6.1Alignment Stage – – – – &nbsp;48 </p><p>
  • 6.2Match Stage &nbsp; – – – . &nbsp;50 </p><p><b>Chapter eight:</b>&nbsp;System evaluation and conclusion &nbsp; – – &nbsp;51 </p><p>
  • 8.1Evaluation of the system – – .. &nbsp;52 </p><p>
  • 8.2Conclusion &nbsp; – – – . &nbsp;54 </p><p><b>Appendix – – – &nbsp;55 </b></p><p><b>REFERENCES – – – – . &nbsp;74</b></p> <br><p></p>

Project Abstract

<p> Human fingerprints are rich in details called minutiae, which can be used as identification marks for fingerprint verification. The goal of this project is to develop a complete system for fingerprint verification through extracting and matching minutiae. To achieve good &nbsp;minutiae extraction in fingerprints with varying quality, preprocessing in form of image enhancement and binarization is first applied on fingerprints before they are evaluated. Many methods have been combined to build a minutia extractor and a minutia matcher. Minutia-marking with false minutiae removal methods are &nbsp;used in the work. An alignment-based elastic matching algorithm has been developed for minutia matching. This algorithm is capable of finding the correspondences between input minutia pattern and the stored template minutia pattern without resorting to exhaustive search. Performance of the developed system is then evaluated on a database with fingerprints from different people. &nbsp; <br></p>

Project Overview

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