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Automatic Detection of

Handwriting forgery Dr. Sung-Hyuk Cha & Dr. Charlies C. Tappert

School of Computer Science & Information Systems

© S. Cha8/8/2002

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Analysis of Handwriting

Recognition Examination Personality identification(Graphology)

On-line Off-line Writer VerificationWriter Identification

Natural Writing Forgery Disguised Writing

Handwriting Analysis TaxonomyHandwriting Analysis Taxonomy

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• Background

• Differences b/w authentic handwriting & forgery

• Measure of Wrinkliness

• Automatic Forgery Detection Model

• Conclusion

OverviewOverview

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To determine the Validity of

Individuality in Handwriting

Legal MotivationLegal Motivation

Frye vs. US (1923)scientific community

Daubert vs. Merrell Dow(1993) testing,

peer review, error rates

U.S. vs. Starzecpyzel(1995)

“skilled” testimony

GE vs. Joiner (1997)

weight of evidence

Kumho vs.Carmichael(1999)

reliability standard

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Each person writes differently.

Individuality of HandwritingIndividuality of Handwriting

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(b) Forgeries of (a)

(a) Authentic handwriting samples from one writer

Authentic vs. ForgeriesAuthentic vs. Forgeries

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CSISCSIS3 Differences b/w authentic & forgery3 Differences b/w authentic & forgery

1. Shape

2. Pressure

3. Speed

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CSISCSISAngular and Magnitude Type Angular and Magnitude Type Element String Element String

Angular Magnitude

Image Stroke Direction Stroke Width

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w1 w2 w3 w4 w5 w6 w7

5 3 6 5 4 5 5

min(wi) = 3

w1

w2

w3

w4

w5

w6

w7 w8 w9 w10

4.24 4.24 4.24 4.242.83 4.24 4.24

2.83

2.83

2.83

min(wi) = 2.83

Stroke Width ExtractionStroke Width Extraction

(a) Vertical & horizontal stroke width (b) Diagonal stroke width

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CSISCSISFractal: Fractal: How Long is a Coastline? How Long is a Coastline?

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CSISCSISFractal: Fractal: How wrinkly is the Coastline of Britain? How wrinkly is the Coastline of Britain?

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(a) Number of in the boundary = 69

(b) Number of in the boundary = 32

(a) (b)

Fractal: Fractal: How wrinkly is Handwriting? How wrinkly is Handwriting?

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)2log(/.___

.___log

reslowinboundary

reshighinboundarysWrinklines

1085.1)2log(/)32

69log( sWrinklines

Fractal: Fractal: Measure of WrinklinessMeasure of Wrinkliness

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(d-e) ascender & descender

Computational FeaturesComputational Features

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(f) stroke width

(g-i) projected histogram and gradient histogram

Computational FeaturesComputational Features

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sample1 by x

),...,,( 11121

xd

xx fff ),...,,( 22221

xd

xx fff ),...,,( 11121

xd

xx fff ),...,,( 21yyy x

dxx fff

sample2 by x sample1 by x Forgery of x by y

Feature Extractor

)),(),...,,(),,(( 2121212211

xd

xd

xxxx ffdffdffd

Distance computing

)),(),...,,(),,(( 1112211

yyy xd

xd

xxxx ffdffdffd

d-dimensionalwithin-authentic-

handwritingdistance set

d-dimensionalbetween-authentic-

handwriting & forgery distance set

Automatic Forgery Detection ModelAutomatic Forgery Detection Model

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.49 .70 .71 .13 .47 .32 .21

.49 .75 .70 .26 .54 .35 .18

.49 .67 .74 .23 .48 .32 .22

.72 .33 .47 .66 .60 .42 .10

.74 .33 .48 .60 .59 .45 .10

.79 .36 .54 .60 .59 .52 .09

.30 .61 .66 .70 .71 .57 .10

.42 .72 .64 .67 .74 .53 .10

.40 .75 .67 .75 .70 .54 .11

.30 .60 .59 .66 .60 .36 .10

.32 .60 .59 .60 .59 .39 .10

.30 .66 .60 .60 .59 .34 .09

cent slant wid zone side-h bot-h grad

Feature distances

AAAAAA

FFFFFF

Truth

Inputs & TruthInputs & Truth

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Original/Forgery?

Distancecompu-tation

Feature extraction

),...,,( 21x

dxx fff

),...,,( 21y

dyy fff

),( 11yx ff

),( 22yx ff

),( yd

xd ff

Authentic sample from a known source

Handwritingsample in question

Artificial Neural NetworkArtificial Neural Network

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CSISCSISDistributions and ErrorsDistributions and Errors

between authentic & forgerydistance

within authenticdistance

forgery identified authentic

authenticidentified as

forgery

Decisionboundary

d ( , )

d ( , )

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withinclass

betweenclass 60180

Random selectionRandom selection

dichotomizer

s’-error d’-error

dichotomizer

s-error d-error

estimateestimate

Design of ExperimentDesign of Experiment

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CSISCSISConclusionConclusion

• Authentic handwriting and forgery handwritten word images were collected.

• Differences b/w authentic handwriting and forgery

• Measure of Wrinkliness

• Automatic Forgery Detection Model using the dichotomy approach.

• Further quantitative study with more samples is necessary.

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The EndThank you.

http://www.csis.pace.edu/~scha/handwriting.html