a new approach to signature verification digital data acquisition pen n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
A New Approach to Signature Verification: Digital Data Acquisition Pen PowerPoint Presentation
Download Presentation
A New Approach to Signature Verification: Digital Data Acquisition Pen

Loading in 2 Seconds...

play fullscreen
1 / 19

A New Approach to Signature Verification: Digital Data Acquisition Pen - PowerPoint PPT Presentation


  • 80 Views
  • Uploaded on

A New Approach to Signature Verification: Digital Data Acquisition Pen. Ondřej Rohlík. rohlik@kiv.zcu.cz Department of Computer Science and Engineering University of West Bohemia in Pilsen. Outline. pen – pictures, construction signals – description application areas

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'A New Approach to Signature Verification: Digital Data Acquisition Pen' - herman-stout


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
a new approach to signature verification digital data acquisition pen

A New Approach to Signature Verification: Digital Data Acquisition Pen

Ondřej Rohlík

rohlik@kiv.zcu.cz

Department of Computer Science and Engineering

University of West Bohemia in Pilsen

outline
Outline
  • pen – pictures, construction
  • signals – description
  • application areas
  • signature verification
  • author identification
  • results

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

the pen
The Pen

The pen was designed and constructed at Fachhochschule Regensburg

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

writing with the pen
Writing with the Pen

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

signals
Signals

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

signals1
Signals

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

application areas
Application Areas
  • signature verification
      • authentic signature or fake
  • person identification
      • which of several people
  • character/text recognition
      • replacement of keyboards and/or scanners

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

signature verification problem
Signature Verification – Problem
  • we have to classify into two classes
  • classes overlaps each other
  • we have no training data for “fakes”

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

program developed
Program Developed

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

useable features
Useable Features

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

algorithms
Algorithms

For each class C Training algorithm

For each feature f

For each pair of signatures Classes[C][i] and Classes[C][j]

Compute the difference between Classes[C][i] and Classes[C][j]

and add it to an extra variable Sum[f]

Compute mean value mean[f] and variance var[f] of each feature over

all pairs using the variable Sum[f]

Compute critical cluster coefficient using variances var[f] and weights w[f]

over all features f

For class C to be verified Recognition algorithm

For each pattern Classes[c][i]

For each feature f

Compute the difference and remember the least one over all

patterns

Sum up products of least differences and weights w[f] and compare the

sum with Critical cluster coefficient

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

signature verification results
Signature Verification – Results

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

author identification problem
Author Identification – Problem
  • samples are classified into several classes – each corresponds to one author
  • the written word is not a name (signature) but any other word – we use the same word for all authors

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

author identification problem1
Author Identification – Problem

Graphologists use many signs to characterize the personality of the author

– movement (expansion in height and in width, coordination, speed, pressure, stroke, tension, directional trend, rhythm)

– form (style, letter shapes, loops, connective forms, rhythm)

– arrangement (patterns, rhythm, line alignment, word interspaces, zonal proportions, slant, margins – top, left and right)

– signature (convergence with text, emphasis on given name or family name, placement)

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

author identification solution
Author Identification – Solution
  • classification by neural network – two-layer perceptron network
  • trained using variant of back-propagation algorithm with momentum

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

author identification results
Author Identification – Results

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

conclusion and future work
Conclusion and Future Work
  • twofold purpose of our research:
    • to improve reliability of signature verification
    • to make text recognition devices cheaper
  • result achieved so far are good but more tests must be done in order to prove that our pen and methods are useful
  • acceleration sensor is not suitable for text recognition – will be replaced by pressure sensors

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

example of signature rohl k
Example of signature – “Rohlík“

Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001