AlllDa 51=1272

NATL INST OF STANDARDS & TECH R.I.C.

All 102561 272

womns, Belinda Low/VIsual assessment o QC100 .1156 NO. 86-3409 1986 V19 C.1 NBS-P Visual Assessment of Holograms

Belinda L. Collins

U.S. DEPARTMENT OF COMMERCE

National Bureau of Standards

Center for Building Technology

Building Physics Division

Gaithersburg, MD 20899

July 1986

Sponsored by:

of Engraving and Printing

-QC- »asury Department

100

.1156

86-3409

1986

jton, DC

NBSIR 86-3409

* # * VISUAL ASSESSMENT OF HOLOGRAMS

NBS

RESEARCH

INFORMATION CENTER

Cluoo

. ua

tip,

mu

Belinda L. Collins

U.S. DEPARTMENT OF COMMERCE

National Bureau of Standards

Center for Building Technology

Building Physics Division

Gaithersburg. MD 20899

July 1986

Sponsored by:

Bureau of Engraving and Printing

U.S. Treasury Department

Washington, DC

U.S. DEPARTMENT OF COMMERCE. Malcolm Baldrige. Secretary

NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Director

Abstract

At the request of the Bureau of Engraving and Printing, NBS

performed an assessment of the effectiveness of holograms

intended for use as security devices on banknotes. Five

holograms containing different portraits and counters were

hotstamped on banknote currency of five different denominations.

A total of 66 notes were studied. Fifty of these banknotes were

subjected to one of five wear tests - chemical soak, laundering,

one crumple, two crumple, and four crumple. Another six notes

contained counterfeited holograms, while the final ten notes

remained in the pristine condition. Thirty observers then

participated in a visual performance experiment with the 66

banknotes in which they detected the image, counter, and seal in

each hologram, matched the holographic image and counter to the

portrait and counter on the note, rated the quality of each

hologram, and indicated if it were genuine or counterfeit. The

results indicated that wear adversely affected the performance of

the holograms, with all wear conditions except chemical soak

resulting in significantly poorer performance than the pristine

condition, well below the criterion of 80 percent accuracy.

Correlations with a physical measure of hologram quality,

diffraction efficiency, were strongest for the rated quality

measures, and were above 0.80 for image data. The data indicate

strongly that the holograms studied could not pass the standard

wear tests that conventional banknote currency regularly does.

Keywords:

Banknotes; counterfeit; currency; detection;

identification; optically variable devices; wear

iii

holog ram;
FOREWORD

This report is one of a series documenting the results of NBS

research in support of Bureau of Engraving and Printing Contract

No. V-0283-09, entitled " Not ic eab i 1 i ty of Features of Secure

Documents"

.

January 1986

The report

to July 1986.

summarizes research conducted from

ACK NOWL EDGEME NT S

We wish to acknowledge with special thanks the interest,

cooperation, and encouragement of the sponsor's Technical Project

Officer, Ms. Barbara A. Vaudreuil,

Development Division, Office of Research

as well as that of Mr. John Mercer

Division

.

Manager, Research and

and Technical Services,

Manager, Product Assurance

IV
Table of Contents

ABSTRACT iii

FOREWORD iv

ACKNOWLEDGEMENTS iv

LIST OF TABLES vi

LIST OF FIGURES vii

1. INTRODUCTION 1

1.1 General Experimental Design 1

1.2 Rationale 1

2. APPROACH 2

2.1 Observers 2

2.2 Stimuli 2

2.3 Procedure 3

2.4 Data Analysis 6

3. RESULTS 7

3.1 Summary Data 7

3.2 Wear Condition Data 11

3.3 Individual Observer Responses 16

3.4 Comparison With Physical Measurements 18

4. DISCUSSION AND CONCLUSIONS 22

5. RECOMMENDATIONS 24

6. REFERENCES 25

APPENDIX A 26

v
LIST OF TABLES

Page

Table 1. Identification of samples 4

Table 2. Instructions to observers 5

Table 3. Summary data of overall hologram performance 8

Table 4. Summary wear condition data 13

Table 5. Tabulated observer data 17

Table 6. Matrix of correlation coefficients between physical

and visual performance measures 20

Appendix A

Table 1A. Physical measurement data 31

Table 2A . Comparison of physical measurement data with visual

performance data 34

vi
LIST OF FIGURES

gags

Figure la. Percentage of correct detection of the three

holographic elements, image, denomination counter,

and seal as a function of wear condition. Data for

image detection are given first, followed by the

denomination and seal data 25

Figure 2a. Percentage of correct matches between hologram

image and note portrait, and hologram denomination counter and note denomination counter for

all notes as a function of wear condition.

Data for the image match are given first followed

by the data for the denomination match 26

Figure 3a. Mean ratings of hologram quality as a function of

wear condition. The first entry in a wear

condition refers to matched notes; the second to

mismatched notes 27

Figure 4a. Percentage of notes rated as genuine as a function

of wear condition. The first entry in a wear

condition refers to matched notes; the second to

mismatched notes 23

vn

1. Introduction

At the request of the Bureau of Engraving and Printing (BEP) , the

National Bureau of Standards (NBS) conducted a study at BEP to

evaluate the visibility and general effectiveness of holograms

intended for use on paper currency. The study was intended to

assess the visibility and recognizability of proposed holograms

for notes in five different denominations which had been

subjected to standard wear tests. Results from a parallel study

which provided physical measures of the optical characteristics

of the holograms were also compared with the visual performance

results from the present study.

1.1 General Experimental Design

Five different holograms were used in the evaluation. Each

hologram contained three elements: an image, a denomination

counter, and a Federal Reserve Seal. The hologram image and

counter were designed to match the banknote portrait and counter

for each denomination. The holograms were hotstamped on a series

of banknotes, to the left of the portrait, replacing the current

Federal Reserve Seal.

A total of 66 notes were used in the study. Fifty of these were

subjected to one of five wear tests - chemical soak (30 min in

ethanol), laundering, one crumple, two crumple, and four crumple,

while another ten notes remained in the pristine condition. Six

additional notes contained counterfeited holograms.

The wear tests are standard ones used by BEP to test currency

fitness (See BEP Test Method RT-86-01,02, and 03). Since

banknotes which pass these wear tests are considered fit for

circulation, it was of interest to determine if the notes with

holograms would also be "fit." For holograms, a reasonable

criterion for "fitness" appears to be that the three elements can

be detected, and that the holographic image and denomination

counter can be matched with the portrait and denomination counter

on the note by at least 80% of the observers, for notes subjected

to any wear condition.

1.2 Rationale

The present study was designed to be an evaluation of visual

performance with holograms intended for eventual use on

banknotes. In addition, it was designed so that visual

performance data could be compared with physical measurement data

for the same set of banknotes. The goal of this latter

comparison was to predict the visual effectiveness of holograms

for a given wear condition as a function of optical measurements.

The study used some of the methodologies developed by Collins

(1985) in an earlier assessment of the visual effectiveness of

Optically Variable Devices (OVD's)

.

1
2. Approach

2.1 Observers

A total of 30 observers participated. This number was large

enough to allow meaningful statistical comparisons, yet small

enough to allow rapid data acquisition and analysis. The

observers were employees of the Bureau of Engraving and Printing,

and included 15 males and 15 females in a variety of job

classifications. No observer had worked with the materials prior

to the experiment.

2.2 Stimuli

The stimuli included 5 conventionally produced holograms and 3

"counterfeited" holograms. Each hologram was 16mm in diameter.

The conventionally produced holograms included an image, seal and

denomination counter for each denomination, as follows:

o Lincoln, Federal Reserve Seal (FRS) , and 5; o Hamilton, FRS, and 10;

o Jackson, FRS, and 20;

o Grant, FRS, and 50;

o Franklin, FRS, and 100.

The counterfeited hologram, made by a non-commercial process,

included the following combinations:

o Lincoln, FRS, 5; o Hamilton, FRS, 10;

o Franklin, FRS, 100.

The counterfeit holograms were golden rather than silver in

color, but were about the sarnie size as the "genuine" hologram.

The intent of using holograms as a cue for genuineness is that

the user should be able to match the elements (image and

denomination) to the same elements on the note itself. Thus, a $5 note would have the Lincoln hologram with a 5 and a seal. An

important goal of the present experiment was to determine if

observers could match the hologram to the note. To control for

random guessing, half the notes were mismatched; that is, the

hologram elements did not match those of the banknote. The

mismatch was achieved by hotstamping the holograms on the wrong

denomination. This meant that the image and the counter agreed

within the hologram but not with the engraving on the note.

Thus, the hologram containing Franklin and 100, for example, war

hotstamped onto $5, $10, $20 and $50 banknotes. As a result,

there was no situation in which the images matched but the

counters did not match (or vice versa)

.

2
A total of 66 notes was used, of which 6 contained counterfeited

holograms. Half the notes (33) were mismatched, including the

counterfeits. Ten notes, five matched and five mismatched, were

used for each wear condition - laundered, chemical soak, one

crumple, two crumple, and four crumple. Ten notes remained in

the pristine condition. Only one example of a mismatch was

included for each denomination in each wear condition to reduce

the sample size to a manageable number. Care was taken,

however, to include mismatched notes with all five holograms in

each wear condition (but not all twenty-five possible

mismatches) . Table 1 identifies the notes used in the study.

2.3 Procedure

Each observer individually viewed all 66 notes. The observers

were seated at a table covered with a neutral gray surface. Two

fluorescent luminaires were above the table, one to either side

of the observers. An illuminance of about 70 fc (700 lux) was

maintained on the desk surface. Observers were given the

instructions (see Table 2) to read. They were then given two

pristine matching notes, a $10 and a $50, to examine, and asked

to report what they saw. They were reminded to look for the

three elements, and to match the image and counter. In addition,

they were told that the two notes were excellent examples of

genuine good condition notes. Observers were not given specific

criteria by which to judge genuineness but instead were allowed

to develop their own criteria - which unfortunately resulted in

some inconsistency.

Once the experiment started, an observer picked up each note,

tilted it from side to side and back and forth, gave his/her

responses, and handed the note back to the experimenter.

Seven different responses were obtained. The first three

concerned the detectability of the three holographic elements:

the image, denomination counter, and seal. The fourth and fifth

involved a match between the hologram image and note portrait,

and a match between the hologram counter and note counter. The

sixth response was a rating of hologram quality using a sevenpoint scale, while the seventh was a judgement of hologram

genuineness

.

Observers were given sufficient time to view each note and

respond completely. The experiment typically took 40 to 60

minutes to complete. While this was obviously much longer than

any normal currency transaction, it was intended to elicit as

much information as possible about each note.

The notes were randomized prior to each viewing session with one

constraint; namely, observers always began with note #1, a

pristine matching $5 note. This provided an observer further

information about good quality notes.

3
Table 1. Identification of Samples

Matched Mismatched

Wear Denom ID Number Denom ID Number

Condition

Pristine 5 1 5 w/100 1 34

10 2 10 w/20 35

20 3 20 w/50 36

50 4 50 w/5 37

100 5 100 w/10 38

Laundered 5 6 5 w/50 39

10 7 10 w/5 40

20 8 20 w/10 41

50 9 50 w/100 42

100 10 100 w/20 43

Chem Soak 5 11 5 w/10 44

10 12 10 w/20 45

20 13 20 w/5 46

50 14 50 w/100 47

100 15 100 w/50 48

One Crumple 5 16 5 w/50 49

10 17 10 w/5 50

20 18 20 w/100 51

50 19 50 w/10 52

100 20 100 w/20 53

Two Crumple 5 21 5 w/100 54

10 22 10 w/5 55

20 23 20 w/50 56

50 24 50 w/20 57

100 25 100 w/10 58

Four Crumple 5 26 5 w/20 59

10 27 10 w/5 60

20 28 20 w/10 61

50 29 50 w/5 62

100 30 100 w/50 63

Counterfeit 5 31 5 w/10 64

10 32 10 w/5 65

100 33 20 w/100 66

1 The first number refers to the note denomination ; the second

the hologram denomination.

to

4
Table 2. Instructions to Observers

The U.S. Treasury is considering using holograms on banknotes.

The hologram is used to reinforce elements of the note. It

contains an image of the same person shown in the note portrait,

a counter for the denomination, and the Federal Reserve seal. To

assess the effectiveness of holograms, the Treasury has printed

up a set of banknotes with holograms on different denominations

in different wear conditions for use in the present experiment.

There are five denominations: $5, $10, $20, $50, an $100. Each

denomination has a holographic image corresponding to the

portrait. Thus, the $5 note has both a portrait of Abraham

Lincoln and a holographic image of Lincoln. In addition, each

hologram has a counter (in this case, 5), and a Federal Reserve

Seal as well as the image. Thus, there are three elements to

each hologram - image, counter, and seal. Here are some examples

of banknotes in good condition with the proper holograms

attached

.

In this experiment, you will see a series of banknotes with

holograms located to the left of the portrait. These banknotes

are in different wear conditions, making it harder to see the

elements in the hologram. In addition, the images and counters

in some of the holograms do not match the note's portrait and

counter. These holograms are considered to be mismatched. Some

are even counterfeited.

We are interested in determining if you can see the elements in

the holograms on the banknotes, and can match them with the

portrait and counter printed on the note. To do this, please

pick up the banknote and look at it briefly. To see the elements

in the hologram, you will need to tilt the note in different

directions - back and forth, and up and down. You need to look

only at the front of the note, since there are no holograms on

the rear.

After you have examined the note, please give me several pieces

of information. First please tell me if you saw anything in the

hologram. You should see an image, a counter, and a Federal

Reserve seal. Secondly, please tell me if the hologram matches

the note; and if it does match, what matches. The image should

match the portrait, and the counter should match the four

counters at the edges of the note. Third, please rate the

quality of the hologram using a scale of 1 to 7. In this scale a

1 would mean that the hologram was clear and contained all three

elements (image, counter and seal) , while a 7 would mean that no

elements or pieces of elements were visible. Finally, please

indicate if the hologram is genuine or counterfeited. When you

have finished, please hand the note to me.

There will be a total of 66 notes in all. The experiment should

take about 45 minutes. Do you have any questions?

5
2.4 Data analysis procedure

Following completion of data collection, the data were entered

into a spreadsheet program. Responses for each of the seven data

types (image; denomination and seal detection; image and

denomination counter match; counter; rated quality; and

judgements of genuineness) were then tabulated for each banknote

and observer.

The detection data were tabulated in two separate analyses. The

first was the detection of an element, while the second was the

order in which each element was mentioned. This latter analysis

was intended to give some indication of which elements were seen

(or, at least mentioned) first. The matching data were tabulated

in terms of correct response, no response, or error (incorrect

matching response) . A distribution of quality ratings was also

tabulated for each note and wear condition. Finally, the

frequency of "genuine" responses was tabulated for each note.

Means, standard deviations and

were then calculated for the

statistical program was used to

such as chi square and correlat

mean ratings of hologram quality

different responses. A separate

calculate statistical comparisons

ion coefficients.

6
3. Results

3.1 Summary Data

Table 3 presents summary frequency and percentage data for

hologram performance in four categories - detection accuracy

(table 3a) , matching accuracy (table 3b) , rated quality (table

3c) , and judgements of genuineness (table 3d) . Results are given

for the 33 matching notes, the 33 mismatched notes, and the

combined 66 notes. Appendix A presents four figures summarizing

the data for hologram performance.

The first set of entries (table 3a) presents data for the

detectability of the image, denomination, and seal. As noted

earlier, two types of data were tabulated: detectability of an

element (Yes and No entries in table 3); and order of detection.

The latter category refers to the order in which each element was

mentioned by the observer and is represented by 1, 2, 3 or See in

table 3. (The See category represents cases in which observers

indicated seeing everything, without mentioning the order in

which they saw specific elements.) The Yes category then

combines the 1, 2, 3, and See responses, while the No category

represents only those times when observers did not see an

element. The number of No's thus provides information on the

failure to detect a particular element.

Inspection of the Yes and No data given in table 3a indicates

that the denomination counter in the hologram was detected more

frequently than the seal or the image (69 percent vs 58 percent)

.

These data also demonstrate that observers failed to detect each

holographic element more than 30 percent of the time.

The data recorded for order of detection indicate clearly that

the denomination was mentioned first, the image second, and the

seal third. Thus, as can be seen from the n combined n columns,

the denomination was mentioned first by 39 percent of the

observers and second by 23 percent, while the image was mentioned

first by 23 percent of the observers, and second by 26 percent.

The seal was mentioned first by only 14 percent, but third by 29

percent. The pattern of responses for detection order was similar

for both matched and mismatched bills.

A chi square analysis was performed to assess the differences in

the distribution of detection responses for order, excluding the

no response category (Natrella, 1966) . This analysis revealed

that the detection order was significantly different (p < . 0 0 1

)

for the image vs denomination, for image vs seal, and for

denomination vs seal comparisons. A second analysis revealed no

difference in overall detection accuracy (number of Yes responses

vs No responses) between matched and mismatched notes for either

image or denomination data.

7
Table 3. Summary Data of Overall Hologram Performance

Table 3a. Order of Detection

Image

Matched Mismatched Combined

Freq Percent Freq Percent Freq Percent

Detection 1 245 24.75 1 203 20.51 1 448 22.63

Order 2 233 23.54 2 285 28.79 2 518 26.16

3 79 7.98 3 75 7.58 3 154 7.78

SEE 32 3.23 SEE 4 0.40 SEE 36 1.82

TOTAL YES 589 59.49 YES 567 57.272 YES 1156 58.38

NO 401 40.50 NO 423 42.727 NO 824 41.62

Denomination

Matched Mismatched Combined

Freq Percent Freq Percent Freq Percent

Detection 1 340 34.34 1 431 43.54 1 771 38.94

Order 2 242 24.44 2 225 22.73 2 467 23.59

3 56 5.66 3 35 3.54 3 91 4.60

SEE 33 3.33 SEE 5 0.51 SEE 38 1.92

TOTAL YES 671 67 .77 YES 696 70.303 YES 1367 69.04

NO 319 32.55 NO 294 30.00 NO 613 30.96

Seal

Matched Mismatched Comb ined

Freq Percent Freq Pe rcent Freq Pe rcent

Detection 1 153 15.45 1 129 13.03 1 282 14.24

Order 2 129 13.03 2 137 13.84 2 266 13.43

3 257 25.96 3 311 31.41 3 568 28.69

SEE 37 3.74 SEE 8 0.81 SEE 45 2.27

TOTAL YES 576 58.18 YES 585 59.090 YES 1161 58.64

NO 414 42.24 NO 405 41.33 NO 819 41.36

8
Table 3b. Portrait and Denomination Matching

Image Data

Matched Mismatched Combined

Freq Percent Freq Percent Freq Percent

None 445 44.95 None 452 45.66 None 897 45.30

Corr. 481 48.59 Corr

.

524 52.93 Corr. 1005 50.76

Error 64 6.46 Error 14 1.41 Error 78 3.94

Denomination Data

Matched Mismatched Combined

Freq Percent Freq Percent Freq Percent

None 350 35.35 None 315 31.82 None 665 33.59

Corr

.

619 62.53 Corr

.

667 67.37 Corr

.

1286 64.95

Error 21 2.12 Error 8 0.81 Error 29 1.46

Combined Image <and Denomination Data

Total 85 8.59 Total 22 2.22 Total 107 5.40

Errors - Errors - Errors

Matched Mismatched

Notes Notes

Table 3c. Judgements of Rated Quality

Rating Frequency

Matched Mismatched Combined

Rate

.

Freq Percent Rate

.

Freq Percent Rate

.

Freq Percent

0 0 0.00 0 0 0.00 0 0 0.00

1 138 13.94 1 86 8.69 1 224 11.31

2 62 6.26 2 80 8.08 2 142 7.17

3 42 4.24 3 43 4.34 3 85 4.29

4 60 6.06 4 45 4.55 4 105 5.30

5 133 13.43 5 125 12.63 5 258 13.03

6 206 20.81 6 209 21.11 6 415 20.96

7 349 35.25 7 402 40.61 7 751 37.93

Mean 5.02 Mean 5.30 Mean 5.16

Table 3d. Judgements of Genuineness

Frequency

Matched Mismatched Combined

Freq Percent Freq Percent Freq Percent

None 12 1.21 None 9 0.91 None 21 1.06

Gen

.

508 51.31 Gen

.

291 29.39 Gen

.

799 40.35

Count 470 47.47 Count 690 69.70 Count 1160 58.59
The next entries in table 3, Portrait and Denomination Matching

(table 3b), present data on the observers' ability to match the

holographic image and counter to the note portrait and counter.

Here, the data are presented in terms of no response (none),

correct response (indicating correctly that a match or mismatch

existed) and error (incorrect match). As with the detection

data, more people gave no response to the image (45 percent) than

to the counter (34 percent) . In addition, observers made the largest number of errors

(incorrect match/mismatch) for the matched images, with this type

of error occurring 64 times. Interestingly, thirty of these

mismatch errors occurred with $100 notes, with only 5-7 errors

occurring for each of the other denominations. While this

increase in errors may have occurred because observers were

unfamiliar with $100 notes, this seems unlikely since the

mismatch errors occurred primarily for the case in which the

hologram and portrait images matched. Unfamiliarity with $100

notes should have increased the error rate for the mismatched

$100 notes as well. It seems more likely that the Franklin

hologram was not as good a representation of the Franklin

portrait as it should have been, and that observers actually had

difficulty in matching the two.

The chi square analysis was used to compare the differences in

the frequency of correct response between matched and mismatched

notes. This comparison was significant for both the image and

the denomination match data (p < . 0 0 1 ) . As noted earlier,

observers made more matching errors, but not more detection

errors, with the matched notes.

The third entry in table 3 (table 3c) presents data on the

ratings of hologram quality. Observers rated the quality of each

hologram on a scale of 1 to 7, where 1 meant high quality and 7

meant poor quality. The holograms generally received ratings of

5 or above, (with a mean rating of 5.16) indicating that

observers considered them to be poor quality. Holograms on

matched notes received more ratings of 1 (13.9 vs 8.7 percent)

but fewer ratings of 7 (35.2 vs 40.6 percent), thus suggesting

that observers considered the matched notes to be of higher

quality

.

The fourth entry in table 3 (table 3d) presents the judgements of

hologram genuineness. Although only 9 percent of the notes (a

total of six) actually contained counterfeited holograms,

observers considered that 59 percent of the notes were

counterfeit. While they clearly considered mismatched bills to

be counterfeit (70 vs 30 percent), they also considered 48

percent of the matched bills to be counterfeit. There was some

tendency for observers to report that notes were counterfeit

because of obvious wear in either the hologram or the paper. A

few observers also mentioned the gold color and greater thickness

10
of the true counterfeits with some asking if these were merely a

different type of experimental hologram. While the experiment

was not really successful in identifying actual counterfeit

holograms, it did indicate that the observers had real

reservations about both the quality and genuineness of the

holograms (particularly after subjection to the different wear

tests) . It also indicated that observers correctly used a

mismatch between the holographic image and portrait elements as

an indicator of counterfeitedness

.

3.2 Wear Condition Data

Table 4 presents summary percentage data (from the thirty

observers) for each note in each condition - pristine, laundered,

chemical soak, one crumple, two crumple, four crumple, and

counterfeit. In this table, each note is identified by an

arbitrary note number and denomination. Wear conditions are

grouped together. The first five entries are for matched notes

while the second five are for mismatched notes. Means and

standard deviations are presented for each wear condition.

The first entries in table 4 present the percentage of correct

detections of the image, denomination, and seal for each note.

The correct detection category was obtained by combining the 1,

2, 3 and See detection responses. The next entries present the

data for correct matches for both image and denomination. The

percentage of genuine judgements for each note is given next,

followed by the mean rating of hologram quality.

Examination of Table 4 reveals nearly perfect identification and

match performance for the pristine condition with low standard

deviations. The mean of the mean rating data is also lowindicating these holograms were generally seen as good quality.

Although the number of pristine notes termed "genuine" is the

highest for any wear condition, the standard deviation is also

high - due to the observers' tendency to consider mismatched

notes counterfeit. Performance was generally similar for the

chemically soaked notes.

The other four wear conditions, laundering and crumpling (one,

two, and four times), seriously degraded the observers' ability

to detect and match the hologram elements. For these wear

conditions, the percentage of matching the hologram image

correctly ranged from 0 to 25 percent, while the accuracy of

matching the counter correctly ranged from 9 to 33 percent. In

fact, for the four crumple condition, no observer correctly

matched any image. Holograms in these wear conditions also

received high mean ratings (above 6.0) - indicating poor quality.

Data for these four wear conditions indicate that wear impaired

the effectiveness of the holograms, with mean percentages of

accurately detecting and matching elements below 75 percent.

11
Comparison of the performance for the "counterfeit" notes (given

in the last entry in table 4) with that for notes in the pristine

and chemically soaked conditions reveals that the frequency of

correct detection was much lower for the seal than for either the

image or the denomination data (41 percent vs 88 percent) . This

difference suggests that the observers had serious problems with

some of the counterfeited hologram seals. Although the match

data for the counterfeit notes are similar to the data for the

pristine and chemically soaked notes, the counterfeit notes

received a higher mean rating, indicating that observers

considered them to be of poorer quality. In addition, they were

termed genuine less frequently than notes in any other wear

condition. In fact, the mismatched counterfeits were considered

genuine by only 13-17 percent of the 30 observers. Clearly,

observers considered these six holograms to be both poor quality

and counterfeit.

The chi square statistic was used to compare differences in the

distribution of responses as a function of wear condition. Data

for the pristine condition were compared with those for each wear

condition (chemical soak, laundered, one crumple, two crumple,

and four crumple, as well as the counterfeits) . The comparisons

between each wear condition were made for the following data

types - image detection, image match, denomination detection,

denomination match, seal detection, and judgements of

genuineness. All comparisons were significant (p <.05) with two

exceptions. In no case was the comparison of pristine with

chemical soak significant. In addition, comparison of the data

for the counterfeit condition with those for the pristine

condition was not significant for either image or denomination

detection

.

The data were also compared with the 80 percent acceptance

criterion suggested by Collins (1985) . Inspection of table 4 reveals that the mean percentages for the detection and matching

data failed to meet this criterion for the laundered, one

crumple, two crumple and four crumple conditions. These

comparisons reinforce the contention that wear adversely affects

the observer's ability to use holograms effectively. Only the

chemical soak did not degrade the hologram - and this because a mild chemical soak (30-min in ethanol) was included in the

testing program. Other chemical soaks normally included in the

BEP wear tests had destroyed the hologram so effectively that any

visual performance assessment appeared meaningless.

12
Table 4. Summary Wear Condition Data

Pristine

Correct Detection Correct Match Genuine Rated

Image Denom Seal Image Denom Judgement Quality

NOTE DN Percent Percent Percent Percent Percent Percent Mean

MCH 1 5 100.0 100.0 100.0 100.0 96.7 90.0 1.67

2 10 100.0 100.0 100.0 100.0 100.0 100.0 1.27

3 20 100.0 100.0 96.7 96.7 100.0 86.7 1.97

4 50 100.0 100.0 100.0 100.0 100.0 96.7 1.23

5 100 100.0 100.0 100.0 83.3 96.7 86.7 1.73

MIS 34 5 100.0 100.0 100.0 100.0 100.0 50.0 2.23

35 10 100.0 100.0 90.0 93.3 100.0 46.7 3.27

36 20 100.0 100.0 100.0 100.0 100.0 53.3 2.30

37 50 100.0 100.0 100.0 100.0 100.0 40.0 2.43

38 100 100.0 100.0 96.7 96.7 100.0 46.7 2.43

MEAN 100.0 100.0 96.7 96.7 96.7 66.7 2.053

ST. DEV. 0.00 0.00 3.07 5.04 1.33 22.87 0.58

Laundered

Percent Percent Percent Percent Percent Percent Mean

MCH 6 5 83.3 6.7 0.0 63.3 6.7 63.3 6.27

7 10 90.0 100.0 6.7 73.3 93.3 33.3 5.60

8 20 63.3 23.3 10.0 26.7 13.3 23.3 6.57

9 50 46.7 43.3 13.3 20.0 26.7 23.3 6.70

10 100 86.7 100.0 33.3 53.3 96.7 50.0 5.60

MIS 39 5 66.7 60.0 26.7 16.7 3.3 30.0 6.13

40 10 73.3 63.3 10.0 0.0 0.0 20.0 6.20

41 20 63.3 36.7 3.3 0.0 3.3 16.7 6.67

42 50 60.0 83.3 36.7 0.0 0.0 20.0 6.30

43 100 100.0 100.0 53.3 0.0 0.0 23.3 5.47

MEAN 73.3 60.0 19.3 25.3 24.3 30.3 6.151

ST. DEV. 15.49 32.15 16.45 26.84 36.18 14.26 0.43

Chemical Soak

Percent Percent Percent Percent Percent Percent Mean

MCH 11 5 100.0 100.0 100.0 90.0 100.0 93.3 2.93

12 10 100.0 100.0 100.0 90.0 93.3 86.7 3.07

13 20 100.0 100.0 56.7 96.7 100.0 50.0 4.00

14 50 100.0 100.0 100.0 100.0 100.0 76.7 3.33

15 100 100.0 100.0 100.0 73.3 96.7 83.3 2.93

MIS 44 5 100.0 100.0 83.3 100.0 100.0 36.7 4.00

45 10 100.0 100.0 83.3 93.3 96.7 33.3 4.10

46 20 100.0 100.0 100.0 100.0 100.0 43.3 3.97

47 50 100.0 100.0 100.0 96.7 100.0 40.0 2.47

48 100 100.0 100.0 96.7 100.0 100.0 33.3 3.27

MEAN 100.0 100.0 90.0 93.3 96.7 56.7 3.407

ST. DEV. 0.00 0.00 13.43 7.86 2.21 23.10 0.55

13
5

10

20

50

100

5

10

20

50

100

5

10

20

50

100

5

10

20

50

100

5

10

20

50

100

5

10

20

50

100

One Crumple

Correct Detection Correct Match Genuine Rated

Image Denom Seal Image Denom Judgement Quality

Percent Percent Percent Percent Percent Percent Mean

60.0 50.0 90.0 53.3 46.7 56.7 5.67

50.0 66.7 86.7 33.3 66.7 50.0 5.90

26.7 83.3 50.0 6.7 80.0 50.0 6.03

46.7 86.7 83.3 40.0 80.0 63.3 5.87

80.0 60.0 60.0 53.3 50.0 53.3 5.80

10.0 100.0 90.0 0.0 30.0 30.0 6.07

13.3 33.3 90.0 0.0 0.0 26.7 6.23

10.0 20.0 26.7 3.3 0.0 23.3 6.77

30.0 100.0 83.3 0.0 3.3 30.0 6.03

76.7 100.0 63.3 6.7 0.0 30.0 5.97

40.3 70.0 70.0 19.7 33.3 40.0 6.034

25.05 27.41 20.50 21.52 31.80 13.92 0.29

Two Crumple

Percent Percent Percent Percent Percent Percent Mean

10.0 26.7 70.0 0.0 23.3 30.0 6.40

3.3 83.3 66.7 10.0 66.7 40.0 6.10

16.7 43.3 36.7 13.3 43.3 30.0 6.27

16.7 20.0 66.7 10.0 16.7 30.0 6.37

6.7 70.0 56.7 6.7 50.0 40.0 6.37

20.0 60.0 83.3 0.0 0.0 26.7 6.27

3.3 26.7 73.3 0.0 3.3 26.7 6.60

16.7 90.0 63.3 0.0 3.3 33.3 6.10

30.0 100.0 63.3 3.3 0.0 20.0 6.27

30.0 50.0 66.7 0.0 3.3 20.0 6.53

15.3 56.7 63.3 4.3 21.0 29.7 6.328

9.21 26.93 11.47 4.96 22.95 6.57 0.15

Four Crumple

Percent Percent Percent Percent Percent Percent Mean

3.3 36.7 50.0 0.0 30.0 40.0 6.53

0.0 6.7 6.7 0.0 6.7 23.3 7.00

3.3 23.3 10.0 0.0 23.3 26.7 6.83

6.7 13.3 6.7 0.0 6.7 36.7 6.97

13.3 43.3 50.0 0.0 20.0 26.7 6.60

0.0 0.0 0.0 0.0 0.0 26.7 7.00

0.0 0.0 0.0 0.0 0.0 26.7 7.00

3.3 0.0 16.7 0.0 0.0 20.0 7.00

3.3 16.7 10.0 0.0 3.3 26.7 6.93

0.0 3.3 13.3 0.0 0.0 26.7 6.93

3.3 14.3 16.3 0.0 9.0 28.0 6.879

3.94 14.91 17.54 0.00 10.65 5.62 0.17

14
Counterfeited Holograms

Correct Detection

Image Denom Seal

Percent Percent Percent

MCH 31 5 83.3 83.3 36.7

32 10 76.7 76.7 0.0

33 100 90.0 90.0 83.3

MIS 64 5 90.0 90.0 6.7

65 10 93.3 90.0 36.7

66 20 96.7 96.7 83.3

MEAN 88.3 87.8 41.1

ST. DEV. 6.60 6.29 32.87

Correct Match Genuine Rated

Image Denom Judgement Quality

Percent Percent Percent Mean

76.7 80.0 30.0 5.70

56.7 96.7 20.0 6.03

76.7 90.0 33.3 4.63

90.0 90.0 13.3 5.97

93.3 90.0 13.3 5.87

86.7 96.7 16.7 5.23

80.0 90.6 21.1 5.5716

12.17 5.58 7.86 0.50

15
3.3 Individual Observer Responses

The frequency of responses for each observer was tabulated for

data on detection and matching accuracy, ratings, and judgments

of genuineness. Table 5 summarizes these data for each observer

(identified with an arbitrary identifier and a short job

classification title). Means and standard deviations are given

below each column of entries.

Inspection of the data in Table 5 reveals that observers varied

in the frequency with which they detected individual elements of

the hologram. The degree of variability as measured by the

standard deviation was similar for image and denomination

detection (6.0 to 6.7) but larger for seal detection (9.61). The

variability in the matching data was highest for the image match

with four observers making 5 or more errors for the image match

condition, and only one making as many as 5 errors for the

denomination match category.

The variability among observers was greatest for the data on

judgements of genuineness, which had a mean of 26.6 but a standard deviation of 15.7 - and a range of 6 to 55. This

variability most likely reflects differences between observers in

criteria for genuineness. This idea is reinforced by the smaller

variability seen in the data for rated quality. These data had a standard deviation of 0.49 for the seven point scale, and a mean

rating of 5.15, with no mean rating below 4.15 for any observer.

Observers seemed to have less trouble determining sample quality,

than they did sample genuineness.

The data given by the observers do not appear to relate to their

job classification in any obvious way. Although two of the

observers who made substantial errors were clerks (observers 3 and 29), two other clerks (11 and 28) made very few errors. A

management analyst and a secretary (observers 9 and 21) both made

no mismatch errors while a highly trained currency examiner (23)

made several such errors, suggesting that experience with paper

currency may not increase initial ability to use holograms

accurately. Since no observer had had previous experience with

these holograms, their performance may not be atypical of that to

be expected from the general public.

16
Table 5. Individual observer data

Observer Detection

Accuracy

Matching Errors

Matched Mismatched

Quality

Judgements

NO. Job Class. Image Denom Seal Image Denom Image Denom Rating Real

1 Chemist 36 45 45 4 1 0 0 5.48 20

2 Secretary 36 46 43 1 5 0 4 4.30 13

3 Clerk 40 43 34 6 4 1 1 5.13 26

4 Carpenter 28 36 22 3 3 0 0 5.34 20

5 Div. Mgr. 45 53 51 0 0 0 1 5.22 27

6 Mgt . Anal. 35 42 35 1 0 3 0 5.71 42

7 Security 26 33 16 3 0 0 0 5.71 24

8 Security 36 45 40 1 1 1 1 4.98 8

9 Mgt. Anal. 49 52 48 0 0 0 0 4.45 28

10 Secretary 37 37 25 2 1 1 0 5.86 11

11 Clerk/typ

.

34 51 44 1 0 0 0 5.12 16

12 Maint Form. 46 55 44 5 1 1 1 4.86 38

13 Maint worke 33 33 18 1 0 1 0 5.50 9

14 Prod. Secur 36 47 42 0 0 0 0 4.98 54

15 Engineer 35 59 44 2 1 1 1 4.87 23

16 Elect .Eng

.

45 52 46 1 0 0 1 5.36 54

17 QA Spec

.

42 42 31 4 2 0 0 5.86 12

18 Press Mach. 46 49 48 3 1 0 0 4.83 55

19 Lab Tech. 30 35 24 4 2 0 0 5.83 6

20 Machinist 42 48 43 0 0 1 0 4.83 25

21 Secretary 36 45 41 0 0 0 0 5.25 10

22 Police 41 44 39 5 0 0 0 5.80 13

23 M .Cur .Exam 50 44 42 1 1 2 0 4.46 46

24 Chemist 42 54 50 3 1 1 0 4.66 47

25 Budg .Off

.

47 55 50 3 0 0 1 4.71 24

26 Exam. Form. 32 39 29 1 0 0 0 5.81 8

27 Chemist 41 49 49 3 0 0 0 4.15 52

28 Prod. Clerk 33 41 41 0 0 1 0 4.90 27

29 Prod. Clerk 39 51 42 6 2 0 0 5.15 15

30 Admin Asst. 38 42 35 1 0 0 1 5.56 46

Mean 38 .53 45 .57 38 .70 2 .17 0 .87 0.47 0 .40 5.16 26 . St. Dev. 6 .01 6 .75 9 .62 1 .83 1 .26 0.72 0 .80 0.49 15.

Total Number of Notes = 66

17
3.4 Comparison with Physical Measurements

As with the data given by Collins (1S85) - the visual performance

data were compared with physical measurement data. Carter and

Huber (1985) and Carter and Golden (1986) developed an optical

evaluation method for measuring the physical quality of

holographic images. The technique consists of shining a laser at

a hologram and measuring the light diffracted from the image

along a plane of incidence. Carter and Golden used the term

"diffraction efficiency" to describe the diffracted light.

Initially, only specular reflections are observed as the source

is moved through the plane, and then at subsequent specific

angles, light is diffracted from the images encoded in the

hologram. This results in discrete peaks for the image and the

seal, with clearly distinguishable maxima and minima for pristine

holograms. The maxima and minima can be ratioed to provide a summary measure of "diffraction efficiency".

Carter and Golden measured each of the sixty-six holograms used

in the present experiment, as well as five examples of pristine

holograms for each denomination. These data were examined to

determine the maxima and minima for all in; ages and seals.

Initially, two diffraction angles were selected for each hologram

denomination giving the following arrangement:

Image Seal

$5 56° Maximum 45° Minimum 28° Max imum 16° Minimum

$10 55° Max imum 44° Minimum 27° Maximum 16° Minimum

$20 49° Maximum 38° Minimum 27° Max imum 20° Minimum

$50 55° Maximum 44° Minimum 26° Max imum 18° Min imum

$100 59° Maximum 46° Minimum 36° Maximum 21° Minimum

These ang les reflect the scattering ang le in degrees from

normal to the measurement plane. The dependent variable is the

Percentage of incident intensity diffracted (and measured)

.

Carter and Golden (1986) for a fuller description of the

Procedures used.

The incident intensity was determined for each of the angles

selected above for each denomination. The procedure worked well

for all wear conditions except chemical soak, where the peaks

often shifted. Here, the actual angles of maximum and minimur.

incidence were used to determine intensity, rather than the

preset angle, to select physical data for comparison with the

visual performance data.

Table 1A of the Appendix presents the maxima, minima, and

diffraction ratio data as well as the angles of maximum and

minimum incidence for the image and the seal for each note,

the pristine condition, the angular diffraction pattern shows two

sharp peaks for each hologram - one for the image and one for the

seal. Changes in the amplitude of the peaks and in the

18
diffraction ratio had been shown to correlate with changes in

visual performance for holograms on banknote currency (Mercer,

1985) . Examination of table 1A reveals that diffraction ratios for the

image ranged from 6.74 to 37.50 for pristine notes, and from 3.00

to 9.25 for chemically soaked notes. The ratios were generally at

or below 1.00 for all other conditions, including counterfeit.

Although the counterfeit holograms are included in this table,

they were excluded from subsequent comparison with the visual

performance data because they are not diffraction gratings and

can not be measured adequately by Carter and Golden's procedure.

The visual performance data given in table 4 were compared with

the physical data from table 1A. Table 2A of the Appendix

tabulates both the visual performance measures and the physical

data. Using these data, correlation coefficients were calculated

for a matrix. This matrix, given in table 6, contains

correlations between image identification (Image) , image match

(Imatch), quality rating (Rate), judgements of genuineness

(Real), image diffraction ratio (Iratio), image diffraction

maximum (Imax), image diffraction minimum (Imin), seal

identification (Seal) , seal diffraction ratio (Sratio) , seal

diffraction maximum (Smax) , seal diffraction minimum (Smin) , denomination identification (Denom) , and denomination match

(Dmatch) . The six diffraction measures refer to the physical

measurement data; the seven other measures refer to the visual

performance measures.

Inspection of the correlation coefficients given in table 6

reveals a close correlation between several visual performance

measures, as might be expected. The closest correlations are

between image detection and image match (0.97) and denomination

detection and match (0.99). Other close correlations are found

between the rating data and the detection and match data (-0.73

to -0.87). Judgements of genuineness ("real") are closely

correlated only with the rating data (-0.79).

The correlations between the visual and physical measurement data

are highest for the rated quality data. Thus, the range of

correlation coefficients between the ratings and the image

diffraction data is from -0.78 to -0.82.

On the other hand, the correlation coefficient between the data

for seal detection and seal diffraction ratio is much lower,

0.40. The correlations are equally low for the other visual

§

erformance measures - image detection, image match, denomination

etection, denomination match, seal detection, and judgements of

genuineness (with a range of 0.47 to 0.67). Thus, as with the

earlier set of data, the largest correlation coefficient occurs

between the data for rated quality and for the image diffraction

ratio. This can be interpreted as indicating that observers

19
Table 6. Matrix of correlation coefficients between physical

and visual performance measures

Variable

IMAGE

IMAGE 1.000

I MATCH 0.966

RATE -0.820

REAL 0.576

IRATIO 0.576

I MMAX 0.601

I MMIN -0.620

SEAL 0.517

S RAT 1

0

0.402

SMAX 0.264

SMIN -0.381

DENOM 0 .736

DMATCH 0 .763

IRATIO IMMAX

IMAGE 0.576 0.601

I MATCH 0.646 0.660

RATE -0.822 -0 .780

REAL 0.669 0.591

IRATIO 1.000 0.876

IMMAX 0.876 1.000

I MM IN -0.682 -0.567

SEAL 0.531 0.511

SRATIO 0.696 0 .700

SMAX 0.573 0.693

SMIN -0.447 -0.406

DENOM 0.472 0.494

DMATCH 0.505 0.523

SMAX SMIN

IMAGE 0.264 -0.381

I MATCH 0.277 -0.437

RATE -0.449 0.521

REAL 0.433 -0.293

IRATIO 0.573 -0.447

IMMAX 0.693 -0.406

I MMIN -0.191 0.600

SEAL 0.283 -0.306

SRATIO 0.823 -0.356

SMAX 1.000 - 0.111

SMIN - 0.111 1.000

DENOM 0.256 -0.242

DMATCH 0.286 -0.286

Correlation Matrix

I MATCH RATE REAL

0,966 -0.820 0.576

1.000 -0.874 0.586

-0.874 1.000 -0.786

0.586 -0 .786 1.000

0.646 -0.822 0.669

0.660 -0 .780 0.591

-0.711 0 .787 -0.580

0.586 -C .760 0.618

0.449 -0.624 0.472

0.277 -0.449 0.433

-0.437 0.521 -0.293

0.752 -0 .731 0.532

0.789 -0.764 0.545

I MM IN SEAL SRATIO

-0.620 0.517 0.402

-0.711 0.586 0.449

0 .787 -0 .760 -0.624

-0.580 0.618 0.472

-0.682 0.531 0.696

-0.567 0.511 0.700

1.000 -0.552 -0.461

-0.552 1.000 0.401

-0.481 0.401 1.000

-0.191 0.283 0.823

0.600 -0.306 -0.356

-0.428 0 .725 0.333

-0.485 0 .731 0.358

DENOM DMATCH

0.736 0 .763

0 .752 0.789

-0.731 -0.764

0.532 0.545

0.472 0.505

0.494 0.523

-0.428 -0.485

0 .725 0 .731

0.333 0.358

0.256 0.268

-0.242 -0.286

1.000 0.990

0.990 1.000

20
relied primarily on attributes of the image quality in making

their overall judgements of hologram quality, and that their

judgements concurred with the diffraction data for evaluating the

physical quality of the hologram.

Although the correlations between the physical and performance

data are lower in the present report than in the earlier report

(Mercer, 1985), this finding is not unexpected in view of the

larger number of holograms compared (60 vs 21) , and the physical

variability in the holograms themselves. For example, the

maximum and minimum diffraction angles varied by as much as 10°

between denominations for both the image and the seal for

pristine conditions and was even greater for the chemically

soaked notes. In addition, the measurement technique used by

Carter and Golden assesses holograms in only one viewing plane:

observers can move the hologram through an infinite number of

planes to maximize their likelihood of detecting the images. As

a result, their performance was often better than might have been

expected from the physical measurement data.

As in the previous study, it appears that diffraction ratios of

less than 1.0 are associated with decreased visual performance.

For such ratios the percentage of correct detections and matches

decreases, while the mean quality rating increases (indicating

poorer quality) , as can be seen from inspection of Table 2A.

Ratios below 1.0 can be interpreted as meaning that either no

peak occurred or that background noise (scattering) was high

enough to mask the peak. Visual performance appears to be

somewhat better than might be predicted from the diffraction

measurements in that ratios close to 1.0 are associated with

reasonable accuracy - suggesting that observers were able to move

the hologram in space to maximize any image/denomination/seal

information. Nevertheless, ratios around 1.0 are typically

associated with ratings of poor quality, indicating that

observers did not consider these holograms to be effective. As a

result, a diffraction ratio of 1.0 or less could be used as a

physical criterion for rejecting holograms, although further

research should be done to establish the best criterion for

rejection

.

21
4. Discussion and Conclusions

The data obtained in the present study on the effectiveness of

holograms on banknotes indicate that wear adversely affects an

observer's ability to detect holographic elements and match them

to banknote elements. Although some wear conditions were less

detrimental than others, the degrading effects of v/ear were

significant even for the one crumple condition. In addition,

laundering, a commonly occurring consumer abuse, destroyed the

ability to match the denomination on 8 of the 10 laundered notes.

The only wear condition which did not adversely affect

performance was the 30 minute soak in ethanol - a relatively

innocuous chemical test. As in the previous study (Collins,

19 85 ) , performance was particularly poor for the Franklin

hologram with observers making many more matching response errors

for it than for any other hologram.

The data presented in section 3 do not support the hypothesis

that holograms can pass the same wear tests that banknote

currency does. The effect of even minimal wear, exemplified by

the one crumple test, is to reduce matching accuracy - the

critical performance attribute for holograms - well below the 80

percent criterion set forth in the previous report. While the

accuracy of matching images for notes in the pristine condition

is 96.7 percent, it drops to 19.7 percent for the one crumple

condition. By the four crumple condition, observers fail to match

any image accurately; and only match denominations with a accuracy of 9 percent. Yet, conventional banknote currency is

considered acceptable after 32 crumples.

The only conditions in which either detection frequency or

matching accuracy are above 80 percent correct are the pristine

and chemical soak conditions. It should be noted that overall

performance would have been much poorer had a more stringent

chemical soak condition than a 30-min soak in ethanol been used.

Some test soaks with chemicals such as acetone or sodium

hydroxide had obliterated the holograms so completely that they

could not be included in the present experiment.

As a result, it is reasonable to conclude that the particula: set

of holograms studied did not adequately withstand even minimal

wear tests.

The data obtained in the present study further suggest that use

of a holographic image of a portrait as an indicator of

genuineness was not particularly successful. Observers made many

more errors matching the image to the portrait than they did for

the counter. In addition, they detected both the image and t. h« seal less frequently than the counter.

The fact that observers made many more matching errors (85 vs 22)

for matched notes than for mismatched notes suggests they had

22
some difficulty in determining if the holographic image really

represented the same person as the note portrait. Further

support for this idea is given by the fact that observers made

errors 2.6 times more frequently for the image match than for the

denomination match. These data suggest that it may be easier to

tell that two denominations are the same than that two images

match

.

The observers also made a much greater number of errors for the

Franklin hologram - portrait combination. They had far more

trouble determining that the two Franklins matched than they did

for all other images/portraits combined. The converse was not

true - observers did not claim the Franklin hologram matched a different portrait. This finding reinforces the need to ensure

the fidelity of the holographic image relative to that of the

portrait, since informal examination of the hologram suggested

that it really did not look like the Franklin portrait. In

addition, the physical diffraction ratios were lower for

Franklin, even in the pristine condition. The problems with the

Franklin hologram also suggest that the quality of the image in

the hologram needs to be a particularly accurate representation

of the portrait if observers are to use holograms successfully as

a counterfeit deterrent. Otherwise, the hologram becomes a poor

quality counterfeit of the portrait - effectively degrading the

effectiveness of both portrait and hologram.

The data further suggest that observers used unanticipated

criteria for genuineness. Ideally, they should have considered

only the six "fake" holograms as counterfeit. The data indicate

clearly, however, that they considered a mismatch between

hologram and note elements to be a major indicator of a

counterfeit note - the original reason for using holograms as a counterfeit deterrent. Observers also tended to consider worn

notes, particularly those in which elements could not be matched,

to be counterfeit. A similar tendency to consider worn bills as

counterfeit was found in a report on counterfeit currency

(Collins, Mayerson, and Worthey, 1985). In the present report,

the mean percentage of indicating notes as genuine drop from a high of 66.7 percent for pristine to 30.3 and 28.0 percent for

notes in the laundered and four crumple conditions, respectively.

Nonetheless, the counterfeited holograms were seen as counterfeit

far more frequently than any other group of notes, with the

mismatched "fake" notes having a very low rate of acceptance as

genuine (around 15 percent)

.

The data reinforce the conclusion from the previous report

(Collins, 1985) that wear seriously degrades the performance of

holograms relative to the rest of the note. As with the OVDS'

s

studied in that report, the holograms studied here failed wear

tests that normal banknote currency easily passes.

23
5. Recommendations

Based on the data obtained in the present report and in the

previous report (Collins, 1985), the five holograms studied

should not be used on banknotes. All have consistently failed

visual performance tests related to detection, identification,

and matching when subjected to even minimal wear. Furthermore,

they are consistently given low ratings for quality and are not

considered genuine once they are no longer in the pristine

condition

.

The improvements made in the holograms between July 1585 and

January 1986 did not improve their performance on visual

performance tests. Rather, the newer holograms could not be

accurately matched with other note elements even in the one

crumple condition. Contrary to expectations, the detectability

of the holographic image was even poorer than that of the

denomination counter. This suggests that it is more difficult to

develop readily detectable holographic images of faces than of

numerals - an idea reinforced by the greater number of errors

made for the Franklin holographic image. Observers also had more

trouble matching the images - successfully making matches in only

51 percent of the notes. The holograms, particularly the

holographic images, thus appear to be difficult to use as an

indicator of currency genuineness after being subjected to any

wear test. In addition, once subjected to the various wear:

tests, they were rated as being of poor quality - a rating which

correlated closely with physical measurements of diffraction

efficiency. As a result, holograms do not appear to be an

effective tool for ensuring visual detection of counterfeit paper

currency

.

Finally, it should be remembered that the observers, while not

familiar with holograms, were relatively young and skilled

workers. Although they had had no training with holograms, as

employees of the Bureau of Engraving and Printing, they may have

had somewhat greater exposure to banknote currency. Yet,

although the variability between the BEP observers was larger, it

did not appear to be related to their job description or apparent

familiarity with paper currency. Nevertheless, performance could

reasonably be expected to be even poorer with oidei, less

skilled, or handicapped observers.

Consequently, the use of the holograms as they are presently

designed cannot be recommended for use as a counterfeit deterrent

on paper currency.

24
6. References

Bureau of Engraving and Printing. BEP Test Method RT-86-01,

Crumple Test. BEP Test Method RT-86-02, Chemical Resistance.

BEP Test Method RT-86-03, Laundering.

Carter, W.H. & Golden, J.P. Measurements of Wear in Optically

Variable Devices. Washington, D.C. Naval Research Laboratory

Report 8992, June 1986.

Carter, W.H., & Huber, V. Measurements of Wear in Optically

Variable Devices. Letter Report from the Naval Research

Laboratory to the Bureau of Engraving and Printing, June 1985.

Collins, B.L. Visual Assessment of Optically Variable Devices.

Letter Report from the National Bureau of Standards to the Bureau

of Engraving and Printing, July, 1985.

Collins, B.L., Mayerson, S., Worthey, J.A. Not iceability of

Features of Secure Documents. Gaithersburg, MD., National Bureau

of Standards, NBSIR 85-3160, July 1985.

Mercer. J.W. Evaluation of Holographic OVDs. Internal Memorandum

to E.L. Graminski, Bureau of Engraving and Printing, July 1985.

Natrella, M. Experimental Statistics . Washington D.C., National

Bureau of Standards, Handbook 91, 1963.

25
Appendix A

Figures Depicting Visual Performance Data

Physical Measurement Data

1 Tables Containing

26
Legend

PM refers to pristine matched; PMIS to pristine mismatched; LM to

laundered matched; LMIS to laundered mismatched; CSM to chemical

soak matched; CSMIS to chemical soak mismatched; 1XM to one

crumple matched; 1XMIS to one crumple mismatched; 2XM to two

crumple matched; 2XMIS to two crumple mismatched; 4XM to four

crumple matched; 4XMIS to four crumple mismatched; CM to

counterfeit matched; and CMIS to counterfeit mismatched.

MAG El, DENOM e:a l_ d eti" e: ction

1 DO

130

ao

7-0

eo

50

-4-0 30

20

1 O

O

x x.

k

%

x

1 xlv

x

T PMIS

CEZ

— xxlv

x'

fS

X 'V X V

X' VXfx,.

s r

.

X' "0

:> Xx;

4n

x

J3

X V

X' V

X S.

xs.

x V

X- s.

X" V

X S

X' S

PM U-vl L_M IS CSM CSM IS 1 X M 1 XMI S 2X M2 XMI

WE-ifi CONDITION — MATCHED Ae. Ml SMATCH ED

I MAGE r-TTJ DEMCM SE

4XM4XMIS CM CMIS

CH El EAi.

Figure la. Percentage of correct detection of the three

holographic elements, image, denomination counter, and seal as a function of wear condition. Data for image detection are given

first, followed by the denomination and seal data.

27
Legend

PM refers to pristine matched; PMIS to pristine mismatched; LM to

laundered matched; LMIS to laundered mismatched; CSM to chemical

soak matched; CSMIS to chemical soak mismatched; 1XM to one

crumple matched; 1XMIS to one crumple mismatched; 2X1! to two

crumple matched; 2XMIS to two crumple mismatched; 4XM to four

crumple matched; 4XMIS to four crumple mismatched; CM to

counterfeit matched; and CMIS to counterfeit mismatched.

M AO E ,

. C- EhJ O M M ATC I—1 1 M-\

L:.‘

1. 1-1

i:c::

lit::: OC

U..I

n.s- grE

r.iJC u_i Cl

I r_;i o

3 Cl a o

? O

s a

s o

4-0

3 O

2 O

1 O

P js — U- -Livy EAR_ OO N DlTI ON —

IZZ2D

D Ac K -1 1 :3 f ‘.1 C H£['

DE N'M

Figure 2a. Percentage of correct matches between hoiogra~ image

and note portrait and hologram denomination counter and note

denomination counter for all notes as a function of we a l condition. Data for the image match are given first followed by

the data for the denomination match.

28
Legend

PRIS refers to pristine

chemically soaked notes;

crumpled notes; 4X to four

notes

.

notes; LD to laundered notes: CS to

IX to one crumpled notes; 2X to two

crumpled notes; and CTF to counterfeit

RATED QUALITY OF I—I O I O O' FR A. fvl 23

W EAR CONDITION — WCHED As MISt/IATCHED matched MisivtATCH

Figure 3a. Mean ratings of hologram quality as a function

wear condition. The first entry in a wear condition refers

matched notes; the second to mismatched notes.

of

to

29
Legend

PHIS refers to pristine notes; LD to laundered notes: CS to

chemically soaked notes; IX to one crumpled notes; 2X to two

crumpled notes; 4X to four crumpled notes; and CTF to counterfeit

notes .

Ij.J

ijip:

usai dii fT

L.-> -<L El

L

r

Jl.tj

L> G t : M El NT O F~ H O O G R: A. M G t. f J U I r J E I r J

1 o o

£3 Cl a o

7' O s o

5 O

4- O

3 r_l S O

1 ClO

WE.aft CON DITlON MATC HE D

K-t* Tj -i t : d 3c f -i i ar uacHin f mi smat c h

Figure 4a. Percentage of notes rated as

wear condition. The first entry in a matched notes; the second to mismatched

genuine as a function

wear condition refers

notes

.

o f

to

30
Table 1A. Physical Measurement Data - Diffraction Response

IMAGE SEAL

ANGLE/ ANGLE ANGLE/ ANGLE/

NOTE MAX DEGRE MIN DEGREE RATIO MAX DEGREE MIN DEGRE RATIO

AVE 5 0.081 56 0.003 45 27.00 0.054 28 0.005 16 10.80

iAVE 10 0.069 55 0.003 44 23.00 0.043 27 0.005 16 8.60

AVE 20 0.119 49 0.005 38 26.44 0.042 27 0.006 20 7 .00

AVE 50 0.163 55 0.005 44 32.60 0.034 26 0.006 18 5.67

AVE 100 0.069 59 0.003 46 27.60 0.052 36 0.003 21 17.33

Imean 27 .328 9.88

PRISTINE

|

MATCHED NOTES

I'TN1D5 0.070 56 0.004 45 19.91 0.045 28 0.008 16 5.65

ITN2D10 0.075 55 0.002 44 37 .50 0.033 27 0.004 16 8.25

TN3D20 0.147 49 0.005 38 32.67 0.067 27 0.011 16 6.38

TN4D50 0.188 55 0.006 44 31.33 0.188 26 0.006 18 31.33

ITN5D100 0.065 59 0.004 46 16.25 0.067 36 0.005 21 13.40

'MEAN 27.532 13.002

LAUNDERED

TN6D5 0.012 56 0.014 45 0.86 0.022 28 0.041 16 0.54

TN7D10 0.012 55 0.013 44 0.92 0.023 27 0.041 16 0.56

TN8D20 0.020 49 0.020 38 1.00 0.028 27 0.045 20 0.62

TN9D50 0.034 55 0.038 44 0.89 0.049 26 0.072 18 0.68

TN10D100 0.011 59 0.013 46 0.85 0.015 36 0.034 21 0.44

MEAN 0.9042 0.5683

CHEMICAL SOAK

TN11D5 0.031 55 0.007 41 4.43 0.019 28 0.013 21 1.46

TN12D10 0.025 54 0.007 42 3.57 0.016 27 0.013 22 1.23

TN13D20 0.076 49 0.009 38 8.44 0.022 27 0.012 22 1.83

TN14D50 0.049 55 0.012 39 4.08 0.018 26 0.017 21 1.06

TN15D100 0.033 58 0.011 45 3.00 0.043 35 0.014 26 3.07

MEAN 4.7055 1.7311

ONE CRUMPLE

TN16D5 0.015 56 0.013 45 1.15 0.023 26 0.015 22 1.50

TN17D10 0.012 55 0.012 44 1.00 0.034 20 0.027 16 1.24

TN18D20 0.015 49 0.023 38 0.65 0.026 27 0.032 20 0.81

TN19D50 0.020 55 0.020 44 1.00 0.036 26 0.184 18 0.20

TN20D100 0.015 56 0.012 45 1.25 0.012 36 0.024 21 0.50

MEAN 1.0112 0.8497

31
TWO CRUMPLE

TN21D5 0 .010 56 0.016 45 0.59 0.021 28 0.034 16 C .63

TN22D10 0.011 55 0.014 44 0.81 0.030 27 0.034 16 0.88

TN23D20 0.015 49 0.020 38 0 .75 0.027 27 0 .041 20 0.67

TN24D50 0.016 55 0.019 44 0.84 0.020 26 0.032 18 0.62

TN25D1C 0 0.018 56 0.018 45 1.00 0.018 36 0.043 21 0.42

MEAN 0.8001 0.6426

FOUR CRUMPLE

TN26D5 0.012 56 0.015 45 0.80 0.020 28 0.027 16 0.73

TN27D10 0.012 55 0.013 44 0.92 0.024 27 0.045 16 0.53

TN28D20 0.014 49 0.018 38 0.78 0 .022 27 0.022 20 1.00

TN29D50 0.013 55 0.016 44 0.81 0.025 26 0.025 18 1.00

TN30D100 0.015 56 0.018 45 0.81 0.003 36 0.047 21 0.07

MEAN 0.8237 0.6665

COUNTERFEIT

TN31D5 0.003 56 0.003 45 1.00 0.004 28 0.010 16 0.35

TN32D10 0.004 55 0.003 44 1.33 0.005 27 0.009 16 0.56

TN33D100 0.003 56 0.002 45 1.50 0 .003 36 0.006 21 0.55

MEAN 1.2777 0.4836

MISMATCHED NOTES

PRISTINE

TN34D5-10C 0.058 58 0.003 45 19.17 0.054 36 0.005 21 11.91

TN35D10-20 0.090 49 0.005 38 18.00 0.019 27 0 .006 20 3.17

TN36D20-50 0.095 55 0.005 42 19.00 0.020 26 0.007 18 2.86

TN37D5C-5 0.062 56 0.004 45 15.50 0.048 28 0.002 16 24 .00

TN38D100-1C 0.047 55 0.007 44 6 .74 0.025 27 0.014 22 1 .76

MEAN 15.681 8.7384

LAUNDERED

TN3SD5-50 0.025 55 0.019 44 1.32 0.023 26 0 .036 18 0.64

TN40D10-5 0.013 56 0.015 45 0.87 0.024 28 0 .054 16 0.44

TM41D20-10 0.014 55 0.016 44 0.84 0.027 27 0.044 16 0.61

TN42D50-100 0.014 56 0.015 45 0.95 0 .015 36 0.027 21 0.56

TN43D10 0-2C 0.017 49 0.016 38 1.06 0 .019 27 0.024 20 0.77

MEAN 1.0080 0.6046

CHEMICAL SOAK

TN44D5-1C 0.030 55 0.005 40 6.00 0.014 27 0.012 22 1 TN45D10-20 0.089 50 0.010 38 8.90 0.040 27 0.016 20 2 50

TN46D20-5 0.037 56 0.004 40 9.25 0.016 28 0.009 20

TN47D50-10 0 0.049 59 0.007 45 7.54 0.048 36 0.007 21 6 .79

TN48D100-50 0.088 55 0.010 44 9.25 0.021 26 0.013 20 6 v

MEAN 8.1882

M
ONE CRUMPLE

TN49D5-50 0.014 55 0.021 44 0.67 0.041 26 0.057 18 0.72

TN50D10-5 0.013 56 0.014 45 0.93 0.018 28 0.031 16 0.58

TN51D20-100 0.013 56 0.013 45 1.00 0.016 36 0.024 21 0.67

TN52D50-10 0.012 55 0.023 44 0.52 0.031 27 0.027 16 1.15

TN53D10-20 0.016 49 0.024 38 0.68 0.039 27 0.041 20 0.95

MEAN 0 .7595 0.8131

TWO CRUMPLE

TN54D5-100 0.012 56 0.013 45 0.92 0.014 36 0.046 21 0.30

TN55D10-5 0.014 56 0.016 45 0.88 0.027 28 0.037 16 0 .73

TN56D20-50 0.018 55 0.021 44 0.86 0.019 26 0.025 18 0.76

TN57D50-20 0.015 49 0.018 38 0.83 0.030 27 0.032 20 0.95

TN58D100-10 0.010 55 0.018 44 0.56 0.042 27 0.065 16 0.65

MEAN 0.8088 0.6778

FOUR CRUMPLE

TN59D5-20 0.014 49 0.018 38 0.78 0.022 27 0.036 20 0.61

TN60D10-5 0.011 56 0.014 45 0.79 0.022 28 0.026 16 0.85

TN61D20-10 0.012 55 0.014 44 0.82 0.020 28 0.024 16 0.85

TN62D50-5 0.012 56 0.017 45 0.73 0.026 28 0.038 16 0.68

TN63D100-50 0.014 55 0.017 44 0.82 0.022 26 0.030 18 0.72

MEAN 0.7871 0.7418

COUNTERFEIT

TN64D5-10 0.003 55 0.002 44 1.50 0.004 27 0.007 16 0.57

TN65D10-5 0.003 56 0.002 45 2.00 0.004 28 0.007 16 0.57

TN66D20-100 0.004 56 0.002 45 1.75 0.004 36 0.005 21 0.80

I MEAN 1.75 0.6476
Table 2A . Comparison of Physical Measurement Data with Visual

Performance Data

Note Image Imatch Rate Real I ratio Immax Immin Srat io Smax Smin Seal

1 1.00 1.00 1.67 0.90 19.91 0.070 0.004 5.65 0.045 0.008 1.00

2 1.00 1.00 1.27 1.00 37.50 0.075 0.002 8.25 0.033 0.004 1.00

3 1.00 0.97 1.97 0.87 32.67 0.147 0.005 6.38 0.067 0.011 0.97

4 1.00 1.00 1.23 0.97 31.33 0.188 0.006 31.33 0.188 0.006 1.00

5 1.00 0.83 1.73 0.87 16.25 0.065 0.004 13.40 0.067 0 .005 1.00

6 0.83 0.63 6.27 0.33 0.86 0.012 0.014 0.54 0.022 0.041 0.00

7 0.90 0.73 5.60 0.33 0.92 0.012 0.013 0.56 0.023 0.041 0 .07

8 0.63 0.27 6.57 0.23 1.00 0.020 0.020 0.62 0.028 0.045 0.10

9 0.47 0.20 6.70 0.23 0.89 0.034 0.038 0.68 0.049 0.072 0.13

10 0.87 0.53 5.60 0.50 0.85 0.011 0.013 0.44 0.015 0.034 0.33

11 1.00 0.90 2,93 0.93 3.63 0.029 0.008 1.12 0.019 0.017 1.00

12 1,00 0.90 2.67 0.87 3.13 0 .025 0.008 0.80 0.016 0 .020 1.00

13 1,00 0.97 4.00 0.50 8.44 0.076 0.009 1.69 0.022 0.013 0.57

14 1.00 1.00 3.33 0 .77 3.06 0.049 0.016 0.82 0.018 0.022 0.93

15 1.00 0.73 2.93 0.83 2.82 0.031 0.011 2.47 0.042 0.017 1.00

16 0.60 0.53 5.67 0.57 1.15 0.015 0.013 0.50 0.016 0.032 0.90

17 0.50 0.33 5.70 0.50 1.00 0.012 0.012 0.70 0.019 0.027 0.87

18 0.27 0.07 6.03 0.50 0.65 0.015 0.023 0.81 0.026 0.032 0.50

19 0.47 0.40 5.87 0.63 1.00 0.020 0.020 0.20 0 .036 0.184 0.83

20 0.80 0.53 5.80 0.53 1.25 0.015 0.012 0.50 0.012 0.024 0.60

21 0.10 0.00 6.40 0.30 0 .59 0.010 0.016 0.63 C .021 0.034 0.70

22 0.03 0.10 6.10 0.40 0.81 0.011 0.014 0.88 0.030 0.034 0.67

23 0.17 0.13 6.27 0.30 0 .75 0.015 0.020 0.67 C .027 0.041 0.37

24 0.17 0.10 6.37 0.30 0.84 0.016 0 .019 0.62 C .020 0.032 0.67

25 0.07 0.07 6.37 0.40 1.00 0.018 0.018 0.42 0.018 0.043 0.57

26 0.03 0.00 6.53 C .40 0.80 0.012 0.015 0.73 0.020 0.027 0.50

27 0.00 0.00 7.00 0.23 0.92 0.012 0.013 0.53 C .024 0.045 0.07

28 0.03 0.00 6.83 0.27 0 .78 0.014 0.018 1.00 0.022 0.022 0.10

29 0.07 0.00 6.97 0.37 0.81 0.013 0.016 1.00 0 .025 0.025 0 .07

30 0.13 0.00 6.60 0.27 0.81 0.015 0.018 0.07 0.003 0.047 0.50

34
Note Image Imatch Rate Real Iratio Immax Immin Sratio Smax Smin Seal

34 1.00 1.00 2.23 0.50 11.67 0.035 0.003 11.91 0.054 0.005 1.00

35 1.00 0.93 3.27 0.47 18.00 0.090 0.005 3.17 0.019 0.006 0.90

36 1.00 1.00 2.30 0.53 11.88 0.095 0.008 2.86 0.020 0.007 1.00

37 1.00 1.00 2.43 0.40 15.50 0.062 0.004 24.00 0.048 0.002 1.00

38 1.00 1.00 2.43 0.47 6.29 0.044 0.007 1.10 0.023 0.021 0.97

39 0.67 0.30 6.13 0.30 1.32 0.025 0.019 0.64 0.023 0.036 0.27

40 0.73 0.70 6.20 0.20 0.87 0.013 0.015 0.44 0.024 0.054 0.10 41 0.63 0.47 6.67 0.17 0.84 0.014 0.016 0.61 0.027 0.044 0.03 42 0.60 0.60 6.30 0.20 0.95 0.014 0.015 0.56 0.015 0.027 0 .37

43 1.00 1.00 5.47 0.23 1.06 0.017 0.016 0.77 0.019 0.024 0.53

44 1.00 1.00 4.00 0.37 4.29 0.030 0.007 0.82 0.014 0.017 0.83

45 1.00 0.93 4.10 0.33 8.80 0.088 0.010 2.50 0.040 0.016 0.83 46 1.00 1.00 3.10 0.43 5.69 0.037 0.007 1.33 0.016 0.012 1.00

47 1.00 0.97 2.47 0.40 6.00 0.039 0.007 6.79 0.048 0.007 1.00 48 1.00 1.00 3.27 0.33 9.25 0.088 0.010 1.51 0.021 0.014 0.97

49 0.10 0.10 5.87 0.30 0.67 0.014 0.021 0.72 0.041 0.057 0.90

50 0.13 0.10 6.23 0.27 0.93 0.013 0.014 0.58 0.018 0.031 0.90

51 0.10 0.07 6.77 0.23 1.00 0.013 0.013 0.67 0.016 0.024 0.27

52 0.30 0.33 6.03 0.30 0.52 0.012 0.023 1.15 0.031 0.027 0.83

53 0 .77 0.53 5.97 0.30 0.68 0.016 0.024 0.95 0.039 0.041 0.63

54 0.20 0.17 6.27 0.27 0.92 0.012 0.013 0.30 0.014 0.046 0.83

55 0.03 0.07 6.60 0.27 0.88 0.014 0.016 0.73 0.027 0.037 0 .73

56 0.17 0.20 6.10 0.33 0.86 0.018 0.021 0.76 0.019 0.025 0.63

57 0.30 0.10 6.27 0.20 0.83 0.015 0.018 0.95 0.030 0.032 0.63 58 0.30 0.13 6.53 0.20 0.56 0.010 0.018 0.65 0.042 0.065 0.67

59 0.00 0.00 7.00 0.27 0.78 0.014 0.018 0.61 0.022 0.036 0.00

60 0.00 0.00 7.00 0.27 0.79 0.011 0.014 0.85 0.022 0.026 0.00 61 0.03 0.07 7.00 0.20 0.82 0.012 0.014 0.85 0.020 0.024 0.17

62

r 0.03 0.00 6.93 0.27 0.73 0.012 0.017 0.68 0.026 0.038 0.10

63 0.00 0.00 6.93 0.27 0.82 0.014 0.017 0.72 0.022 0.030 0.13

35
.
NBS-H4A (REV. 2«ec) U.S.'DEPT. OF COMM.

BIBLIOGRAPHIC DATA

SHEET (See instructions)

1. PUBLICATION OR

REPORT NO.

NBSIR 86-3409

2. Performing Organ. Report No. 3. Publication Date

JULY 1986

4. TITLE AND SUBTITLE

Visual Assessment of Holograms

5. AUTHOR(S)

Belinda L. Collins

6. PERFORMING ORGANIZATION (If joint or other than NBS. see instructions)

national bureau of standards

DEPARTMENT OF COMMERCE

WASHINGTON, O.C. 20234

7. Contract/Grant No.

8. Type of Report & Period Covered

9. SPONSORING ORGANIZATION NAME AND COMPLETE ADDRESS (Street. City. State , ZIP)

Bureau of Engraving and Printing

Department of the Treasury

Washington, D.C. 20228

10. SUPPLEMENTARY NOTES

| | Document describes a computer program; SF-185, FIPS Software Summary, is attached.

11. ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant

bibliography or literature survey, mention it here)

At the request of the Bureau of Engraving and Printing, NBS performed an

assessment of the effectiveness of holograms intended for use as security

devices on banknotes. Five holograms containing different portraits and

counters were hotstamped on banknote currency of five different

denominations. Each of the sixty-six banknotes, including 6

counterfeited holograms were then subjected to one of six wear testspristine, chemical soak, laundering, one crumple, two crumple, and four

crumple. Thirty observers then participated in a visual performance

experiment in which they detected the image, counter, and seal in each

hologram, matched the image and counter to the portrait and counter on

the note, rated the quality of each hologram, and indicated if it were

genuine or counterfeit. The results indicated that wear adversely

affected the performance of the holograms, with all wear conditions

except chemical soak resulting in significantly poorer performance than

the pristine condition, well below the criterion of 80 percent accuracy.

Correlations with a physical measure of hologram quality, diffraction

efficiency, were strongest for the rated quality measures, and were above

0.80 for image data. The data indicate strongly that the holograms

studied could not pass standard wear tests that conventional banknote

currency rpgul arl v dnps . 12. KEY WORDS (Six to twelve entries ; alphabetical order; capitalize only proper names; and separate key words by semicolons)

Banknotes; counterfeit; currency; detection; hologram; identification;

optically variable devices; wear

13. AVAILABILITY

| | Unlimited

X^For Official Distribution. Do Not Release to NTIS

| | Order From Superintendent of Documents, U.S. Government Printing Office, Washington, D.C.

20402.

| | Order From National Technical Information Service (NTIS), Springfield, VA. 2216 I

14. NO. OF

PRINTED PAGES

15. Price