EL FT -E FS Public Challenge 

Ques tions and answers to date 

Last updated 26 June 2009 

Q1: In the overview you are mentioning that the benchmark will review "the comparative 

accuracy of image-only searches, image+minutiae searches, and image+extended feature 

searches." We fully agree on this approach. Yet the different latent datasets do not seem to

correspond to such tests. For instance, does the L2 dataset correspond to image+minutiae, or is

it minutiae alone? [Q1a] Our recommendation is image+minutiae, which is state of the art

today. What is the purpose of L4 (EFS without the image)? [Q1b]

A1a: The wording was changed to make the latent subtest more explicit: L2 dataset refers

to “image with EFTS-LFFS features (fields 9.014-9.023)”; the additional L5 refers to

“EFTS-LFFS features alone” 

A1b: There are three justifications for the latent subtests without images in the public

challenge. Including these subtests in the public challenge does not necessarily indicate

that the full ELFT-EFS evaluations should include these subtests: the public challenge

results may be used in these cases to indicate whether further evaluations are necessary. 

o At the workshop, the participants on the vendor panels indicated that

image+feature searches are more accurate than feature searches. This is a

commonly accepted assumption, but there is not publicly available evaluation data

to support the assumption. 

o In some operational cases, including the image in transactions is problematic due

to bandwidth. Users in these cases need to understand the accuracy impact of these

restrictions. 

o There is some interest in whether EFS may be used as the basis for a standard

fingerprint template (without the image), and what the impact on accuracy may be

in that case. 

Q2: Will the second evaluation (SDK) be on the same grounds as ELFT07 Phase II, regarding

coding/matching speed and SDK interface?

A2: The ELFT-EFS evaluation will be based on lessons learned from ELFT07 Phase II, and

both throughput speed and SDK interface are being reviewed. We expect that ELFT-EFS

speed requirements will be faster than ELFT07 Phase II. 

Q3: Do you have any idea for test conditions (especially processing time restriction for latent

enrollment, for exemplar enrollment and for matching)?

A3: (see A2) We are soliciting input from the participants in the Public Challenge for

these time limits: 

o Exemplar enrollment (set of 10 rolls) 

o Exemplar enrollment (set of unsegmented slaps) 

o Latent matching 

Q4: Can you clarify the required format of results (score files)?

A4: See the ELFT-EFS Public Challenge Test Plan. 

Q5: We would appreciate you including in the document a disclaimer strictly limiting the use

of the SDK to ELFT-EFS testing. That is something we had discussed with NIST in previous

NIST tests and it is very important to us.

A5: We will, and are discussing specific wording now. 

Q6: Can you just download the test sets, perform your own tests and send no results at all

(without being notated in any report)?

A6: If you intend to participate in the public challenge, we will give you an ID/Password

to download the public challenge data. If you do so we request that you return results

from some or all of the public challenge subtests. The public challenge data will be made 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

public after the completion of the ELFT-EFS Public Challenge. If you want only want the

data for internal testing, please wait until then. If you intend to participate but for some

reason are unable to return results, you will not be penalized: the participants (including

participants who do not return results) will remain anonymous: they will not be listed by

name, nor have specific results attributed to them. 

Q7: I would like to confirm test condition regarding L2 and L3: - L2 - image with EFTS-LFFS

features ( fields 9.014-9.023) - L3 - image with EFS features (fields 9.300-9.373) I assume that we

can use features (EFTS-LFFS or EFS) when we encode latent from image. For example, we can

use manually-encoded direction data (if available) to extract ridge from image. Am I correct?

A7: Yes, both the image and the manually-encoded features may be used in this case. For

example, automatic feature extraction from the latent image could be performed (as in

your example) using information from the provided manually-encoded features, or not.

Note that it has been asserted by several AFIS vendors that their operational systems

receive both the image and the manually-encoded features (and it is assumed that the

image is somehow utilized in addition the provided features). In contrast, the FBI IAFIS

system is thought to ignore the image when image+minutiae are provided, so for 

systems such as IAFIS which operate in either image-only or feature-only search modes,

L2 or L5 would likely produce the same results. 

Q8: I understand that this test condition does not support some operational procedures such

as: 1) To launch latent matching using image only 2) To launch latent matching with manually

encoded data when 1) did not retune Positive Hit 3) To fuse scores of 1) and 2) and to

reproduce candidates However, this accuracy can be simulated from the results (scores) of L1

and L4 (or L5). Therefore, additional test is not necessary. [L1: image only L4: EFS features

alone L5: EFTS-LFFS features alone]

A8: Generation of performance results based on fusion (conditional or otherwise) of

candidate lists is an option that we may pursue. 

Q9: Released (already provided) latent data do contain some of the EFS features (fields 9.300-

9.373). However, they do not seem to contain any of EFTS-LFFS features (fields 9.014-9.023).

Please let me know your intention: 

a) Do you intend us (participants) to use latent data on SD27? [i.e. the “ideal” feature markup

that was based on both the latent and exemplar] I do not think it is good idea because minutia

positions are different, i.e. it is difficult to compare advantage of EFS (additional) features

against EFTS-LFFS features. 

b) Do you intend us (participants) to use only minutia data (position, direction) on EFS

features (fields 9.300-9.373). I think it is better idea than method a). However, I am afraid if it

would create unnecessary confusion. For example, how can we determine file name of 

candidate (score) files? 

c) Do you intend release separate latent data files which have EFTS-LFFS features (fields

9.014-9.023) and which are actually copy of the part of EFS features (fields 9.300-9.373). I would

like to recommend this method. 

A9: EFS is a deliberate superset of the IAFIS/EFTS/LFFS fields. The final version of the

latent data will have IAFIS/EFTS/LFFS features that were automatically extracted from

the EFS features. [i.e. C is correct.] 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Q10: We are having problems extracting the following WSQ images:. 

EFS_PC_500ppi_MatedExemplarsREVISED/E078A.AN2 record 03 

EFS_PC_500ppi_MatedExemplarsREVISED/E078C.AN2 record 06 

EFS_PC_500ppi_MatedExemplarsREVISED/E078C.AN2 record 08 

EFS_PC_500ppi_MatedExemplarsREVISED/E078D.AN2 record 02 

EFS_PC_500ppi_MatedExemplarsREVISED/E078D.AN2 record 04 

EFS_PC_500ppi_MatedExemplarsREVISED/E078D.AN2 record 05 

EFS_PC_500ppi_MatedExemplarsREVISED/E078E.AN2 record 05 

EFS_PC_500ppi_MatedExemplarsREVISED/E078F.AN2 record 01 

EFS_PC_500ppi_MatedExemplarsREVISED/E078F.AN2 record 02 

EFS_PC_500ppi_MatedExemplarsREVISED/E078F.AN2 record 03 

EFS_PC_500ppi_MatedExemplarsREVISED/E078F.AN2 record 09 

EFS_PC_500ppi_MatedExemplarsREVISED/E078H.AN2 record 06 

EFS_PC_500ppi_MatedExemplarsREVISED/E078I.AN2 record 01 

EFS_PC_500ppi_MatedExemplarsREVISED/E078I.AN2 record 04 

EFS_PC_500ppi_MatedExemplarsREVISED/E078I.AN2 record 06 

EFS_PC_500ppi_MatedExemplarsREVISED/E078I.AN2 record 09 

Provided as part of ULW tools 'ANSINISTViewer.exe' also crashes extracting these images.

Could you check mentioned files and confirm if there is an error in WSQ packaging or the

error is on our side ? 

A10: Some participants have had difficulty in opening a few of the WSQ files (partial list

above). The problem turned out to be nonstandard use of comments within the WSQ

data, which causes problems for some but not all WSQ decoders. 

There should not be a reason to download files unless you have a problem reading the

affected files. 

In case you are having problems, we have removed all WSQ comments from all files in

EFS_PC_500ppi_MatedExemplars. The zipfile: 

EFS_PC_500ppi_MatedExemplars20090527.zip

replaces the zipfile

EFS_PC_500ppi_MatedExemplarsREVISED.zip. 

Again, there should be no reason to download the data again unless this problem is

affecting you. 

Q11: In the Test Plan you are only asking participants to report their timings, without giving

any guidelines on what a reasonable coding/matching speed should be. Participants might

choose very different timings which could hinder the final analysis. As you know the 

matching accuracy can me much improved given sufficient processing time. Do you plan on

releasing speed requirements before phase 1? 

A11: Our intent is to use all timing results obtained from the challenge problem to inform

the limits placed on future evaluations. Based on feedback from ELFT Phase II, our

current assumption for subsequent evaluations (which is subject to change based on

these results, feedback, etc.) is that the latent encode/search time limits will be 

approximately 5x faster than ELFT Phase II. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Q12: What is the purpose of having multiple exemplars for some subjects with respect to the

500ppi mated exemplars provided? How should these be treated with respect to the candidate

lists returned? 

A12: The purpose is not to evaluate “linked” multiple exemplars (i.e. combined exemplar

sets for a given subject), but rather to assess the range of performance obtained in the

best, median, and worst case across all exemplars are present. Thus, all exemplars should

be searched and the returned results (candidates) for each shall be independent. To be

specific: this challenge problem is a case in which we can explore a variety of cases in

which a given subject has five, ten, or more exemplars, and compare the results. To that

end, for a given search, we intend to show what the results would be if we ignore all

mates but a) the highest-scoring, b) the median, and c) the lowest scoring. This can give

us some insight (limited, of course by the challenge test size) into the effect of variations

between exemplars. 

Q13: How should galleries for the searches of E1, E2, E3, and E4 be constructed and searched?

A13: Before a specific exemplar subtest can be executed, an appropriate gallery must be

constructed containing both mated (foreground) and non-mated (background) exemplars

appropriate to the subtest. As stated in the Public Challenge Problem Test Plan, the

following are the Exemplar subtests: 

o E1 - 1000ppi rolled exemplars 

o E2 - 500ppi rolled exemplars 

o E3 - 1000ppi plain exemplars (unsegmented slaps) 

o E4 - 500ppi plain exemplars (unsegmented slaps) 

Therefore, these are the galleries to be used: 

o E1 - 1000ppi rolled exemplars 

o 204 mated exemplar sets from EFS_PC_1000ppi_MatedExemplars 

o 214 non-mated exemplar sets from EFS_PC_1000ppi_Nonmate_Exemplars 

o Only the Rolled prints (pos 1-10) are used from each file 

o E2 - 500ppi rolled exemplars 

o 643 mated exemplar sets from EFS_PC_500ppi_MatedExemplars 

o 214 non-mated exemplar sets from EFS_PC_500ppi_Nonmate_Exemplars 

o Only the Rolled prints (pos 1-10) are used from each file 

o E3 - 1000ppi plain exemplars (unsegmented slaps) 

o 204 mated exemplar sets from EFS_PC_1000ppi_MatedExemplars 

o 214 non-mated exemplar sets from EFS_PC_1000ppi_Nonmate_Exemplars 

o Only the Plain/Slap prints (pos 11-14) are used from each file 

o E4 - 500ppi plain exemplars (unsegmented slaps) 

o 643 mated exemplar sets from EFS_PC_500ppi_MatedExemplars 

o 214 non-mated exemplar sets from EFS_PC_500ppi_Nonmate_Exemplars 

o Only the Plain/Slap prints (pos 11-14) are used from each file 

The ordering of all exemplars within a gallery should be randomized with the matching

software unaware of the mated exemplar positions. 

Q14: It appears there are wrong IDs for some latents/exemplars: 

Latent 240.01 Hit on Exemplar 215.01 

Latent 163.07 Hit on Exemplar 181.07 

Latent 181.08 DOES NOT Hit on Exemplar 181.08

A14: The following corrections will be made: 

° Latent # 240 belongs to Subject # 215 (there is no subject 240) 

° E181 (Subject # 181) was incorrectly labeled – it should be E163. (both 500ppi and

1000ppi images). Latent 181 has no corresponding exemplar.

We will update the crossreference spreadsheet. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Q15: The exemplar L187.an2 is poorly segmented so that the rolled image for finger #2 has

problems matching the latent 187.

A15: You are correct. L187.an2 (both 500 and 1000ppi) is poorly segmented -- we received

the data this way, and unfortunately this represents a real-world occurrence. Note that

the second 500ppi exemplar set (L187A.an2) does not have this problem. 

Q16: There is no exemplar for subject 253.

A16: There is no 1000ppi exemplar for subject 253. Note there is an exemplar (E253A.an2)

at 500ppi. 

Q17: The following exemplars are missing from the datasets (column 2 of “EFS-PC_Xref.txt”)

for both resolutions.: 

Latent_Image_Number Subject 

L038 38 

L059 59 

L081 81 

L085 85 

L101 101 

L117 117 

L118 118 

L119 118 

L127 101 

L163 163 (see Q14) 

L240 240 (see Q14) 

L251 251 

L254 254 

A17: Yes, this is consistent with section 2 of "ELFT-EFS-PC_Readme_2009-05-20.pdf".

There are 12 latents corresponding to 10 unique subjects without an exemplar mate

available at either resolution (500 or 1000 ppi): 

° L038 

° L059 

° L081 

° L085 

° L101 

° L117 

° L118 

° L119 

° L127 

°

°

L181 (not L163 – see Q14) 

L251 

° L254 

Note: As stated in Q16, one latent (L253) has one 500ppi exemplar mate (E253A), but no

1000ppi exemplars.

Therefore, when searched against the 1000ppi gallery there are 13 latent searches which

cannot be mated, and 12 searches which cannot be mated against the 500ppi gallery. 

Q18: The mate-images at 500 PPI appear to be slightly blocky. Was the 

compression/decompression done correctly? (For example, most of the images in 

\EFS_PC_500ppi_Exemplars_full3\). However, the 1000 PPI images appear to be much better.

A18: The 1000ppi images were scanned and compressed by NIST. With the 500ppi 

images, there are two sources: 

° The 500ppi images without a suffix (e.g. E002.an2, E003.an2) are the same images

as the 1000ppi images (reduced by pixel sampling, not pixel averaging), and

were compressed by NIST 

° The 500ppi images with a suffix (e.g. E003A.an2, E005L.an2) were obtained from

various sources, and the compression methods used were outside of NIST’s

control. For good or bad, these are representative of reality. Note that 

recompression is not possible without further increasing artifacts. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Q19: About the L1- image (only) test set... Some of the latents have multiple images in them —

so, processing and matching the whole image may not be very meaningful (e.g., ID's 56, 57, 58, 

etc.). If one were to use the masks from the other sets — which one to use (the Juried one 

perhaps?)

A19: As several people discussed in the NIST latent workshop, there are multiple

definitions for image-only searching, and multiple scenarios for use. Among these:

A. Automated searching of latent images without human preprocessing (i.e. image

only, no region of interest) 

B. Automated searching of latent images with minimal human preprocessing (i.e.

image only, region of interest and orientation marked)

There are operational needs for both processes. For the public challenge dataset, we

decided not to further increase complexity by adding another latent subtest: the L1 test is

just for the image (A), not ancillary information (B). For the actual evaluation, we plan to

run subtests for both image only and image+region of interest. 

Q20: Regarding the Answer to Question 19 of the last FAQ of June 3rd 2009. It seems to me

that for the matching of the latent images in set L1, no "human interaction" with the images is

allowed whatsoever. By "Human Interaction" I mean manually editing the minutiae of a given

image, including the manual definition of a Region of Interest. Is my understanding correct?

A20: Yes, you are correct. For L1, the intent is image-only searches without any manually 

created additional information (e.g. region of interest). The idea with L1 is to measure

how well the software is able to perform image-only matching without any human

assistance. 

Q21: Finger No. for plain exemplars (unsegmented slaps) (E3 and E4) in the candidate lists. I

am assuming that we shall record 1-10 (Finger Pos.) based on segmented data for the Finger

No. instead of 11-14. Am I correct? 

A21: Correct. 

Q22: For the submission method of the public challenge results, I am assuming that I can send

our results over e-mail after encryption. Am I correct?

A22: Please put all of the candidate lists for each subtest in a separate zipfile, named

<vendor>_L#xE#.zip, emailed to latent-efs@nist.gov using zip encryption and the 

password used for https://tsf.noblis.org/download/ELFT-EFS-PC/. 

° For example, if Vendor FOO is providing results for all tests, then 20 zipfiles will

be provided: FOO_L1xE1.zip, FOO_L1xE2.zip, [...], FOO_L5xE4.zip. 

° The zipfiles can be encrypted using any of these common encryption methods

(listed in descending encryption strength): 256-bit AES, 128-bit AES, Zip 2.0. 

Q23: A question came up today that relates to the sequestered test and your goals for the

testing: There are several different sub-tests to this EFS test, and some problems may be better

solved with different approaches. For instance the minutiae extractor used for the gallery

exemplars may differ for image-only lights out (L1) tests compared to the other tests. This is

fine when we are just submitting results since we could enroll different gallery templates for

each sub-test. However, for the sequestered test, this would require you to perform different

enrollments for the different scenarios tested. Should we constrain our approach to a single

enrollment, or in the sequestered test will we have the option to enroll different templates for

the different types of tests?

A23: In the sequestered test, there will only be a single opportunity for enrollment.

However, the “template” that results from that enrollment may in practice be a superset

of different special-purpose templates from your point of view. When you provide

feedback and recommendations at the end of the Public Challenge, you may wish to

revisit the template size and/or enrollment speed implications of this in your comments. 

Q24: Please note that the files containing EFS features (sets L3 and L4) cannot be opened

using ULW 5.6. When is the version available?

A24: ULW Beta release 5.6.8 may be downloaded from the following site: 

https://tsf.noblis.org/download/ELFT-EFS-PC/ULW_568.zip [Access requires the 

UserID and password (case sensitive) that we sent to you previously.] This version of

ULW is intended for EFS testing and should not be used for operational work. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Q25: Can you please clarify how you intend to calculate rank statistics when there exists more

than 1 exemplar for a latent? There are generally 2 ways: take only the highest exemplar rank

or use all exemplars from the same finger separately (ignoring each other) in calculating the

rank statistics. The first method would reflect the ‘hit rate’ and would allow pooling of the 

gallery (exemplar) data. The other method would reflect the accuracy if a database deduplication was needed or would better reflect the effect of removing one of the exemplars.

A25: For rank-based analysis against the 1000ppi galleries (E1/E3), the rank-based 

analyses will consists of a CMC over ranks 1-100 for all searches having a mate in the

gallery.

For rank-based analysis against the 500ppi galleries (E2/E4), many subjects have 

multiple exemplars per subject, and therefore CMC/rank-based analysis must use a

specialized approach. For the 500ppi exemplars, there will be 4 rank-based analyses:

Baseline Identification Rate (Comparable to 1000ppi Results)

This models a scenario where the gallery retains a single encounter, specifically

that corresponding to the 1000 ppi gallery. Results will be scored as if only the 

one corresponding impression were retained for each subject_finger. All 

additional exemplars per-subject beyond those used for the 1000ppi gallery will

be discarded from the candidate lists before computing the mate rank. Note that

the 500ppi images without a suffix (e.g. E002.an2, E003.an2) are the baseline

images – subsampled versions of the 1000ppi images.

Identification Rate with Multiple Encounters: BEST RANK

This models an operational scenario where the gallery retains multiple

encounters and matchers return candidate lists of subjects. Results will be scored

as if only one impression were retained for each subject_finger. The highest

scoring mate and the highest scoring non-mates will be retained with all other

candidates discarded from the candidate list before computing the mate rank.

Identification Rate with Multiple Encounters: BEST NFIQ

This models an operational scenario where the gallery retains a single encounter

based on highest NFIQ score. Results will be scored as if only one impression

were retained for each subject_finger. The “best” impression by NFIQ for each

subject_finger (breaking ties arbitrarily) will be retained, with all others 

discarded from the candidate list before computing the mate rank.

Identification Rate with Multiple Encounters: RANDOM

This models a scenario where the gallery retains a single encounter selected at

random. Multiple lists of one impression (selected at random) per subject will be

created. Results will be scored as if only one impression were retained for each

subject corresponding to the impression in each list. Multiple overlayed CMCs

will be generated, one per list, for each subtest. The aggregate of these multiple

CMCs will show the variation in accuracy due to different exemplars. 

Q26: In the L3 set, print L006G, all three markups have orientation direction = 19, and

uncertainty = 16, which I thought was rather remarkable for that latent. (Q26a) I was surprised

that humans could specify these numbers so accurately (I assume the examiners sort of 

guessed the orientation). Also, since the default value of u = 15, it is remarkable that the value

of u = 16 was even specified. (Q26b)

A26a: During the initial markup for this dataset, the examiners did not mark the 

orientation. When the images were juried, the orientation was marked and that 

orientation was pushed to the other markups. Therefore for many of the images in the

public challenge dataset, all three markups have the same orientation.

A26b: The orientation and uncertainty were determined graphically by mouse dragging –

the examiners dragged a line to indicate upright, and dragged a mirrored pair of lines to

indicate uncertainty. The examiners did not type in the numbers. 

Q27: Regarding field 9.308 (RQM): 6 valid values (quality codes) are defined (0 through 5) but

only 2 bits are allocated, which are not enough for representation of 6 values. How would this

be resolved? 

A27: It appears that you are referring to the EFS draft 0.2 or earlier, which had the issue

you mention for one format. In EFS 0.3 and 0.4, field 9.308 can use the formats specified

infield 9.309, Uncompressed or Run-Length Encoded. The data for the ELFT-EFS 

evaluation will use the Uncompressed format for simplicity, which uses one character 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

per grid cell. The current specification can be obtained from 

http://fingerprint.nist.gov/standard/cdeffs/ 

Q28: It is stated in “Public Challenge Problem Test Plan’ (04/18/09) that “... participants will 

remain anonymous in the results”. Can you please confirm this?

A28: The results for the Public Challenge will be anonymous: they will not indicate the

participants’ names. Participants are not prohibited from disclosing their results from the

Public Challenge. 

Q29: In the Public Challenge dataset, a few of the cells for the ridge flow (9.310) seem to be off.

An example of marked extended data with 'off' value: L3\L002G_JURIED_NP.lffs, Row 54 ,

25th block orientation is 0x5A=90, and 26th block orientation is 0x16=22. The difference of

these two angles is 90-22=68. It is in an area where ridges go smoothly. There is no data for the

24th block while the orientation for the 23th block is 45. 

A29: The ridge flow values were extracted from the ridge tracing. The tracing in the cell

mentioned in your example has a small downward bend, which resulted in the ridge

flow angle you note. The algorithm currently used is based on the current cell direction,

without using a larger window, which results in sensitivity to local changes. In 

discussions among CDEFFS (in 2006), the committee considered and rejected 

recommending/requiring a specific window size for determining ridge flow. One 

implication of using a small window size is that the consumer of the ridge flow data may

choose to blur the data (effectively applying a larger window after the fact), but has the

option of choosing the window size to use. 

Q30: Your 06/05 email mentions a ‘public challenge report’(again, the participants will remain

anonymous in the report) that is to be made public. Is this still the plan? If yes, when would it

be available? 

A30: Yes. We intend to make draft results available to the participants by the end of July,

before we accept the latent matcher SDKs for Evaluation #1. 

Q31: Our understanding is that a technology provider can participate in public challenge but

opt to not participate in evaluation #1. Is this correct? If so, does the provider have to inform

NIST about their withdrawing before a certain deadline to remain anonymous?

A31: You may participate in the Public Challenge and not participate in Evaluation #1.

Public challenge anonymity is not related to participation in Evaluation #1. 

Q32: Our understanding is that data in fields 9.310 and 9.372 are not marked manually but

generated by software. Is this correct? If yes, (1) can you please let us know what software is

used to generate the data? and (2) Are there any other fields that are not marked manually?

A32: The skeletonized image (9.372) WAS marked manually. The ridge flow map (9.310)

was generated from the skeleton using the ULW libraries — the ridge flow map is the

only field that was generated by software rather than direct human markup.