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Latent Fingerprint Image Segmentation using Fractal Dimension Features and Weighted Extreme Learning Machine Ensemble Jude Ezeobiejesi and Bir Bhanu Center for Research in Intelligent Systems University of California, Riverside, CA 92521, USA e-mail: [email protected], [email protected] June 26,2016

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Page 1: Latent Fingerprint Image Segmentation using …vislab.ucr.edu/Biometrics16/CVPR_presentation_June_2016.pdfFigure: Sample latent fingerprints from NIST SD27:- Quality levels (a) good,

Latent Fingerprint Image Segmentation using

Fractal Dimension Features and

Weighted Extreme Learning Machine Ensemble

Jude Ezeobiejesi and Bir Bhanu

Center for Research in Intelligent Systems

University of California, Riverside, CA 92521, USA

e-mail: [email protected], [email protected]

June 26,2016

Page 2: Latent Fingerprint Image Segmentation using …vislab.ucr.edu/Biometrics16/CVPR_presentation_June_2016.pdfFigure: Sample latent fingerprints from NIST SD27:- Quality levels (a) good,

Outline Outline

Page 3: Latent Fingerprint Image Segmentation using …vislab.ucr.edu/Biometrics16/CVPR_presentation_June_2016.pdfFigure: Sample latent fingerprints from NIST SD27:- Quality levels (a) good,

Problem definitionProblem Definition

Page 4: Latent Fingerprint Image Segmentation using …vislab.ucr.edu/Biometrics16/CVPR_presentation_June_2016.pdfFigure: Sample latent fingerprints from NIST SD27:- Quality levels (a) good,

Related work Related Work

Page 5: Latent Fingerprint Image Segmentation using …vislab.ucr.edu/Biometrics16/CVPR_presentation_June_2016.pdfFigure: Sample latent fingerprints from NIST SD27:- Quality levels (a) good,

Technical approachTechnical Approach

Page 6: Latent Fingerprint Image Segmentation using …vislab.ucr.edu/Biometrics16/CVPR_presentation_June_2016.pdfFigure: Sample latent fingerprints from NIST SD27:- Quality levels (a) good,

Extreme Learning Machine(ELM)

and Weighted ELM

Extreme Learning Machine (ELM)

and Weighted ELM

Page 7: Latent Fingerprint Image Segmentation using …vislab.ucr.edu/Biometrics16/CVPR_presentation_June_2016.pdfFigure: Sample latent fingerprints from NIST SD27:- Quality levels (a) good,

Performance evaluation metricsPerformance Evaluation Metrics

Page 8: Latent Fingerprint Image Segmentation using …vislab.ucr.edu/Biometrics16/CVPR_presentation_June_2016.pdfFigure: Sample latent fingerprints from NIST SD27:- Quality levels (a) good,

Experiments – ELM hyper parameter selection

Experiments – ELM Hyper Parameter Selection

Page 9: Latent Fingerprint Image Segmentation using …vislab.ucr.edu/Biometrics16/CVPR_presentation_June_2016.pdfFigure: Sample latent fingerprints from NIST SD27:- Quality levels (a) good,

Fractal dimension (FD) features

Fractal Dimension

FD Lacunarity

Fractal Dimension (FD) Features

Page 10: Latent Fingerprint Image Segmentation using …vislab.ucr.edu/Biometrics16/CVPR_presentation_June_2016.pdfFigure: Sample latent fingerprints from NIST SD27:- Quality levels (a) good,

Experiments - setupExperiments - Setup

Page 11: Latent Fingerprint Image Segmentation using …vislab.ucr.edu/Biometrics16/CVPR_presentation_June_2016.pdfFigure: Sample latent fingerprints from NIST SD27:- Quality levels (a) good,

Results & comparison with other segmentation approaches

Results & Comparison with Other

Segmentation Approaches

Page 12: Latent Fingerprint Image Segmentation using …vislab.ucr.edu/Biometrics16/CVPR_presentation_June_2016.pdfFigure: Sample latent fingerprints from NIST SD27:- Quality levels (a) good,

Conclusions and future workConclusions and Future Work