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Banking Locker Security Arpana Shree Department of MCA Mount Carmel Coll Bangalore

Banking locker security using Image processing

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Banking locker security using Image processing.This ppt elaborates on to detect human face using image processing.

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Page 1: Banking locker security using Image processing

Banking Locker Security

Arpana Shree

Department of MCA

Mount Carmel College

Bangalore

Page 2: Banking locker security using Image processing

Agenda

• Draw back of current technology

• Problem analysis model

• About hidden image scanner

• Algorithm overview

• Conclusion

Page 3: Banking locker security using Image processing

What goes wrong???

• Theft can take variety of forms

- Insider

- Outsider

Page 4: Banking locker security using Image processing

AnalysisAnalysis

Problem Analysis Model

Problem DomainProblem Domain

SolutionSolution

Page 5: Banking locker security using Image processing

Problem Domain

• Draw Back of alarm & CCTV technology- Locker not secured

• Draw Back of RFID technology- Passwords Hacking

Page 6: Banking locker security using Image processing

SolutionSolution

Problem DomainProblem Domain

Analysis

AnalysisAnalysis

Page 7: Banking locker security using Image processing

Analyzing the problem

• Usage of security tokens– Hardware/software

• Usage of 2FA

• Image scanning technology - Current trend being implemented

Page 8: Banking locker security using Image processing

SolutionSolution

Problem DomainProblem Domain AnalysisAnalysis

Solution

Page 9: Banking locker security using Image processing

Image scanning technology

• Uses a scanner

• Hidden scanner is being fixed

• Theft may not be aware of the hidden Scanner

• Face detection algorithm is used

Page 10: Banking locker security using Image processing

Example

Tiger

Page 11: Banking locker security using Image processing

Face detection algorithm

Cb Part of the input image (fig-1)

Cr Part of the input image (fig-2)

Page 12: Banking locker security using Image processing

The likely hood of the skin regions (fig-3)

Likelihood=exp[-0.5(X-M) c^-1 (X-M)]

whereX=P(r,b)^T

M=Mean value of X C=Covariance of X

Page 13: Banking locker security using Image processing

Image after thresholding

(fig-4)

Using adaptive threshold the Skin regions are highlighted effectively

Page 14: Banking locker security using Image processing

Template face used to verify the existence of face in skin region (fig-5)

Face boundary for the given image (fig-6)

Page 15: Banking locker security using Image processing

Continued

• The detected face is given as a input as a dimension 100X100 to Eigen face recognition system.

• The output will be of the dimension 100X1

Page 16: Banking locker security using Image processing

Conclusion

• Image scanner implementation in banking locker security reduces 75% of hacking

• One of the emerging trend in IT industry

• Implemented in abroad Countries

Page 17: Banking locker security using Image processing

Government website navigation page

www.clerk.house.gov/member_info/cong.aspx

Page 18: Banking locker security using Image processing

THANK YOU!!!