To solve the problem of limited documentation and example code available on the subject of biometric - PowerPoint PPT Presentation

About This Presentation
Title:

To solve the problem of limited documentation and example code available on the subject of biometric

Description:

Two basic types of minutia points. Line ending Line branching ... Basic Text editor or Development IDE. Hex editor. Image manipulation program ... – PowerPoint PPT presentation

Number of Views:40
Avg rating:3.0/5.0
Slides: 14
Provided by: shivan2
Category:

less

Transcript and Presenter's Notes

Title: To solve the problem of limited documentation and example code available on the subject of biometric


1
(No Transcript)
2
  • To solve the problem of limited documentation and
    example code available on the subject of
    biometrics.
  • Research that is done in this field can not
    directly be used in an application the
    programmer must develop the code themselves using
    the research as a guide.

3
(No Transcript)
4
  • Problems associated with commercial SDKs
    (Software Development Kits)
  • Fingerprints are matching by comparing minutia
    points
  • Two basic types of minutia points

Line ending Line branching
  • Fingerprint verification vs fingerprint
    recognition
  • Verification systems need to have more accuracy
  • Recognition system must be able to process many
    prints quickly

This project is a verification system
5
  • C\C Compiler
  • Basic Text editor or Development IDE
  • Hex editor
  • Image manipulation program

6
(No Transcript)
7
Edge Detection with Logarithm Algorithm
8
Thinning with Skeletierungs Algorithm
Breaks found
Final rewritten thin
9
Match Part 1 Shifting
  • Move the verifying print vertically and
    horizontal to find the spot were the most
    pixels line up. A true match will have a certain
    percentage line up.

Lines up Does not line up
10
Match Part 2 Minutia Matching
Line Branching
Line Ending
11
My data has shown that this system is not 100
accurate, but no prints that were not suppose to
pass did. With a little bit of tuning the
accuracy of the system can be easily improved.
Also most of the goals for the project have been
met, with the exception of speed. As for speed, a
revision of Thin() and Match_Part1() are required
to optimize these functions. Unfortunately
smudged prints still cannot be matched without
further correction of the images. Overall the
project was a success and continued work will
only improve upon it.
12
  • Image manipulation including scaling and
    rotation
  • Faster Thinning
  • Faster Matching Part1
  • Design Embedded System
  • Correction of smudged and other imperfections in
    images

13
R. Haralick and L. Shapiro Computer and Robot
Vision, Vol 1, Addison-Wesley Publishing
Company, 1992. A. Jain and S. Pankanti
Automated Fingerprint Indentification and
Imageing Systems, Dept. of Comp. Sci. and Eng.,
Michigan State University, 1996. A. Jain, S.
Prabhakar and J. Wang Minutia Verification and
Classification for Fingerprint Matching, Dept.
Of Comp. Sci. and Eng., Michigan State
Unversity. D. Verna Machine Vision,
Prentice-Hall, 1991.
Write a Comment
User Comments (0)
About PowerShow.com