fingerprint – Page 5

Baby Steps Toward Order of Magnitude Increases in Fingerprint Resolution

(Part of the biometric product marketing expert series)

For many years, the baseline for high-quality capture of fingerprint and palm print images has been to use a resolution of 500 pixels per inch. Or maybe 512 pixels per inch. Whatever.

The crime scene (latent) folks weren’t always satisfied with this, so they pushed to capture latent fingerprint and latent palm print images at 1000 pixels per inch. Pardon me, 1024.

But beyond this, the resolution of captured prints hasn’t really changed in decades. I’m sure some people have been capturing prints at 2000 (2048) pixels per inch, but there aren’t massive automated biometric identification systems that fully support this resolution from end to end.

But that may be changing.

One important truth about infant fingerprints

For about as long as latent examiners have pursued 1000 ppi print capture, people outside of the criminal justice arena have been looking at fingerprints for a very different purpose.

Our normal civil fingerprint processes require us to identify people via fingerprints beginning at the age of 18, or perhaps at the age of 12.

But gow do we identify people in those first 12 years?

More specifically, can we identify someone via their fingerprints at birth, and then authenticate them as an adult by comparing to those original prints?

It’s a dream, but many have pursued this dream. Dr. Anil Jain at Michigan State University has pursued this for years, and co-authored a 2014 paper on the topic.

Given that children, as well as the adults, in low income countries typically do not have any form of identification documents which can be used for this purpose [vaccination], we address the following question: can fingerprints be effectively used to recognize children from birth to 4 years? We have collected 1,600 fingerprint images (500 ppi) of 20 infants and toddlers captured over a 30-day period in East Lansing, Michigan and 420 fingerprints of 70 infants and toddlers at two different health clinics in Benin, West Africa.

At the time, it probably made sense to use 500 pixel per inch scanners to capture the prints, since developing countries don’t have a lot of money to throw around on expensive 1000 ppi scanners. But the use of regular scanners runs counter to a very important truth about infants and their fingerprints. Are you sitting down?

Because infants are smaller than adults, infant fingerprints are smaller than adult fingerprints.

Think about it. The standard FBI fingerprint card assumes that a rolled fingerprint occupies 1.6 inches x 1.5 inches of space. If you were to roll an infant fingerprint, it would occupy much less than that. Heck, I don’t even know if an infant’s entire FINGER is 1.6 inches long.

So the capture device is obtaining these teeny tiny ridges, and these teeny tiny ridge endings, and these teeny tiny bifurcations. Or trying to. And if those second-level details can’t be captured, then you’re not going to get the minutiae, and your fingerprint matching is going to fail.

So a decade later, researchers today are adopting a newer approach, according to a Biometric Update summary of an ID4Africa webinar. (This particular portion is at the very end of the webinar, at around the 2 hour 40 minute mark.)

A video presentation from Judge Lidia Maejima of the Court of Justice of Parana, Brazil introduced the emerging legal framework for biometric identification of infants. Her representative Felipe Hay explained how researchers in Brazil developed 5,000 dpi scanners, he says, which accurately record the minutiae of infants’ fingerprints.

Did you capture that? We’re moving from five hundred pixels per inch to FIVE THOUSAND pixels per inch. (Or maybe 5120.) Whether even that resolution is capable of capturing infant fingerprint detail remains to be seen.

And as Dr. Joseph Atick noted, all this research is still in its…um…infancy. We won’t know for years whether the algorithms can truly match infant fingerprints to child or adult fingerprints.

By the way, when talking about digital images, Adobe notes that the correct term is pixels per inch, not dots per inch. DPI specifically refers to printer resolution, which is appropriate when you’re printing a fingerprint card but not when you’re displaying an image on a screen.

(Image from From https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.500-290e3.pdf )

Biometric Update: Thales wins $21m contract for Switzerland’s AFIS

Notable. I don’t know if IDEMIA provides the current Swiss AFIS (it used to), but Thales has locked this up for a long time.

Thales wins $21m contract for Switzerland’s AFIS

Biometric Update, https://www.biometricupdate.com/202503/thales-wins-21m-contract-for-switzerlands-afis

Metal Injection Attack: The Ozzy Version

In my previous blog post about a fingerprint biometric security metal injection attack, I said:

“This metal injection attack isn’t from an Ozzy Osbourne video…”

Well, now there IS an Ozzy Osbourne video about the metal injection attack. The reel is on Instagram.

“Metal Injection Attack” Instagram reel.

Metal Injection Attack: Bypassing Biometric Fingerprint Security

(Image from LockPickingLawyer YouTube video)

This metal injection attack isn’t from an Ozzy Osbourne video, but from a video made by an expert lock picker in 2019 against a biometric gun safe.

The biometric gun safe is supposed to deny access to a person whose fingerprint biometrics aren’t registered (and who doesn’t have the other two access methods). But as Hackaday explains:

“(T)he back of the front panel (which is inside the safe) has a small button. When this button is pressed, the device will be instructed to register a new fingerprint. The security of that system depends on this button being inaccessible while the safe is closed. Unfortunately it’s placed poorly and all it takes is a thin piece of metal slid through the thin opening between the door and the rest of the safe. One press, and the (closed) safe is instructed to register and trust a new fingerprint.”

Biometric protection is of no use if you can bypass the biometrics.

But was the safe (subsequently withdrawn from Amazon) over promising? The Firearm Blog asserts that we shouldn’t have expected much.

“To be fair, cheap safes like this really are to keep kids, visitors, etc from accessing your guns. Any determined person will be able to break into these budget priced sheet metal safes….”

But still the ease at bypassing the biometric protection is deemed “inexcusable.”

So how can you detect this injection attack? One given suggestion: only allow the new biometric registration control to work when the safe is open (meaning that an authorized user has presumably opened the safe). When the safe is closed, insertion of a thin piece of metal shouldn’t allow biometric registration.

For other discussions of injection attack detection, see these posts: one, two.

By the way, this is why I believe passwords will never die. If you want a cheap way to lock something, just use a combination. No need to take DNA samples or anything.

Oh, and a disclosure: I used Google Gemini to research this post. Not that it really helped.

Clean Fast Contactless Biometrics

(Image from DW)

The COVID-19 pandemic may be a fading memory, but contactless biometrics remains popular.

Back in the 1980s, you had to touch something to get the then-new “livescan” machines to capture your fingerprints. While you no longer had messy ink-stained fingers, you still had to put your fingers on a surface that a bunch of other people had touched. What if they had the flu? Or AIDS (the health scare of that decade)?

As we began to see facial recognition in the 1990s and early 2000s, one advantage of that biometric modality was that it was CONTACTLESS. Unlike fingerprints, you didn’t have to press your face against a surface.

From https://www.youtube.com/watch?v=4XhWFHKWCSE.

But then fingerprints also became contactless after someone asked an unusual question in 2004.

“Actually this effort launched before that, as there were efforts in 2004 and following years to capture a complete set of fingerprints within 15 seconds…”

This WAS an unusual question, considering that it took a minute or more to capture inked prints or livescan prints. And the government expected this to happen in 15 seconds?

A decade later several companies were pursuing this in conjunction with NIST. There were two solutions: dedicated kiosks such as MorphoWave from my then-employer MorphoTrak, and solutions that used a standard smartphone camera such as SlapShot from Sciometrics and Integrated Biometrics.

Slide 10 from the NIST presentation posted at https://www.nist.gov/system/files/documents/2016/12/14/iai_2016-nist_contactless_fingerprints-distro-20160811.pdf.

The, um, upshot is that now contactless fingerprint and face capture are both a thing. Contactless capture provides speed, and even the impossible 15 second capture target was blown away.

Fingers and faces can be captured “on the move” in airports, border crossings, stadiums, and university lunchrooms and other educational facilities.

Perhaps Iris and voice can be considered contactless and fast.

But even “rapid” DNA isn’t that rapid.

Adherence Does NOT Require 100% Compliance

(Green and red medicine bottle image from Google Gemini)

As many of you know, I spend the majority of my time in identity/biometrics, where in some cases a 99% accuracy rate is considered woefully inadequate. Imagine if your bank had a million customers and 10,000 of them couldn’t login…or 10,000 fraudsters COULD log in. The bank would throw a fit with its biometric vendor.

So perhaps my experience resulted in…um, bias when I wrote the following in my recent post on adherence and identity:

“Let’s say you are told to take 4 pills a day for 7 days, and the pharmacy gives you a prescription for 28 pills. A week later all the pills are gone.

“Does this demonstrate patient adherence to health instructions?”

Perhaps you spotted the implicit assumption that taking 28 of 28 pills (100%} constitutes adherence, while taking 27 of 28 pills (96.4%} constitutes NON-adherence.

Tain’t so, Sherlock, as Philip Morisky pointed out in a comment on my LinkedIn post on adherence and identity. He said, in part:

“…the threshold at 80% means that even if you do not have access to the medication for 6 out of 30 days, you are still considered adherent.”

Morisky presumably knows what he’s talking about, since he works for a company called…adherence. And Philip’s father, Dr. Donald Morisky, developed the Morisky Medication Adherence Scale (MMAS) for medication self-reporting.

But what of this 80% threshold?

It’s commonly cited…like the statement that 30% of crime scene latent prints come from palms.

But the 80% adherence threshold is not universally accepted, as this National Library of Medicine study notes.

“Based on Haynes’s early empirical definition of sufficient adherence to antihypertensive medications as taking ≥80% of medication, many researchers used this threshold to distinguish adherent from non-adherent patients. However, we propose that different diseases, medications and patient’s characteristics influence the cut-off point of the adherence rate above which the clinical outcome is satisfactory (thereafter medication adherence threshold).”

This particular study concluded that…more research is needed.

“…we cannot reject or confirm the validity of the historical 80% threshold. Nevertheless, the 80% threshold was clearly questioned as a general standard.”

Despite the questions about the 80% threshold, Philip Morisky’s basic point remains: you don’t have to take 100% of your medications to be considered adherent from a health perspective.

But I still maintain that for critically important medications, the IDENTITY of the person taking them needs to be known at a level very close to 100%.

Friction is Bad

Some time ago I read a story (which may or may not have been true) about an employer who called multiple job applicants to the office for a morning interview. As time passed and the employer didn’t interview anyone, some of the applicants got tired of waiting and left. At the end of the day, only one applicant remained. That applicant got the job.

The person who told the story thought that it demonstrated that perseverance pays off.
Most of the readers thought that it demonstrated that the employer was a jerk and that the work environment was probably toxic.

If this were to happen in real life, the employer would paradoxically lose out on the BEST candidates who had better things to do than sit around an office all day.

Why?

Because people avoid friction. If job applicants can obtain jobs without playing silly games, they will.

Friction is bad.

Waiting room in an airport. — Waiting room image by User:Mattes – Own work, Public Domain, https://commons.wikimedia.org/w/index.php?curid=1732601.

The evolution of fingerprint capture

When I started in the biometric industry 30 years ago, many police agencies were capturing fingerprints by putting ink on a person’s fingers and rolling/slapping the prints on a card.

FBI fingerprint card. — From Certifix, https://store.certifixlivescan.com/products/criminal-fingerprint-record-card.

That was messy and time-consuming, so companies like Digital Biometrics and Identix developed “livescan” devices, which did not require ANY ink and which let police agencies capture fingerprints by rolling/slapping the prints on a glass platen. This process could require a minute or two for the livescan operator to capture all fourteen images.

That’s a long time.

As I’ve previously noted, it was TOO long for some people in the federal government, who began asking in 2004 if technology could capture a complete set of fingerprints in 15 seconds.

20 years later, we can capture fingerprints (at least 8 of them) in a couple of seconds.

How?

By avoiding friction. Rather than forcing people to place their fingerprints on a card or a platen, “contactless” technology lets the “wave” (or “fly”) their fingers over a capture device, or hold their fingerprints in front of a smartphone camera.

Friction is bad.

The sound of silence

Despite what lyricists say, silence is NOT your old friend.

When a prospect wants to find out about your biometric solution, how does silence help you?

Let’s say that a prospect hears that MegaCorp offers a biometric solution, but MegaCorp’s blog and social media haven’t posted anything lately.

What are the chances that the prospect will search far and wide to find out about MegaCorp’s biometric solution?

Actually, the chances are better that the prospect won’t search at all, and will turn to the competitors who are NOT silent.

Blogging benefits: 55% more website visitors, 67% more leads, 13x more likely to enjoy positive ROI, 92% acquire customers.

Are you going to look for the information that is easily available, or the information that is hard to obtain?

Friction is bad.

Eating my own wildebeest food

I’m trying to reduce friction in Bredemarket’s own practices.

While I still use landing pages for some thing that require further explanation for some prospects, I’m trying to avoid them in some instances.

I’m working on a marketing campaign for a client, and my first “draft 0.5” of the campaign was loaded with friction.

The prospect had to open an email.
In the email, the prospect had to click on a landing page.
On the landing page, the prospect had to fill out a form to book a meeting.

Huge numbers of people drop out of the process at every step. So why not eliminate a step, and let the prospect book a meeting in a form embedded in the email?

Friction is bad.

And I’m applying this same principle to this post.

If your identity/biometric firm is desperate for content to convert prospects into paying customers, why don’t you schedule a free 30-minute meeting with Bredemarket to discuss your needs and what I can offer?

Incidentally, while I often repurpose blog content on Bredemarket’s social media channels, this post WON’T be one of them. I can’t embed a Calendly form into an Instagram or LinkedIn post.

And I can’t embed YouTube videos either.

From https://www.youtube.com/watch?v=nkUOACGtGfA.

In Case You Missed My Incessant “Biometric Product Marketing Expert” Promotion

Biometric product marketing expert.

Modalities: Finger, face, iris, voice, DNA.

Plus other factors: IDs, data.

John E. Bredehoft has worked for Incode, IDEMIA, MorphoTrak, Motorola, Printrak, and a host of Bredemarket clients.

(Some images AI-generated by Google Gemini.)

Biometric product marketing expert.

Let’s Explain the MINEX Acronyms

(Part of the biometric product marketing expert series)

Any endeavor, scientific or non-scientific, tends to generate a host of acronyms that the practitioners love to use.

For people interested in fingerprint identification, I’ve written this post to delve into some of the acronyms associated with NIST MINEX testing, including ANSI, INCITS, FIPS, and PIV.

And, of course, NIST and MINEX.

After defining what the acronyms stand for, I’ll talk about the MINEX III test. Because fingerprints are still relevant.

Common MINEX acronyms

NIST

We have to start with NIST, of course. NIST is the National Institute of Standards and Technology, part of the U.S. Department of Commerce.

NIST was involved with fingerprints before NIST even existed. Back when NIST was still the NBS (National Bureau of Standards), it issued its first fingerprint interchange standard back in 1986. I’ve previously talked about the 1993 version of the standard in this post, “When 250ppi Binary Fingerprint Images Were Acceptable.”

But let’s move on to another type of interchange.

MINEX

It’s even more important that we define MINEX, which stands for Minutiae (M) Interoperability (IN) Exchange (EX).

You’ll recall that the 1993 (and previous, and subsequent) versions of the ANSI/NIST standard included a “Type 9” to record the minutiae generated by the vendor for each fingerprint. However, each vendor generated minutiae according to its own standard. Back in 1993 Cogent had its standard, NEC its standard, Morpho its standard, and Printrak its standard.

So how do you submit Cogent minutiae to a Printrak system? There are two methods:

First, you don’t submit them at all. Just ignore the Cogent minutiae, look at the Printrak image, and use an algorithm regenerate the minutiae to the Printrak standard. While this works with high quality tenprints, it won’t work with low quality latent (crime scene) prints that require human expertise.

The second method is to either convert the Cogent minutiae to the Printrak minutiae standard, or convert both standards into a common format.

Something like ANSI INCITS 378-2009 (S2019).

So I guess we need to define two more acronyms.

ANSI

Actually, I should have defined ANSI earlier, since I’ve already referred to it when talking about the ANSI/NIST data interchange formats.

ANSI is the American National Standards Institute. Unlike NIST, which is an agency of the U.S. government, ANSI is a private entity. Here’s how it describes itself:

The American National Standards Institute (ANSI) is a private, non-profit organization that administers and coordinates the U.S. voluntary standards and conformity assessment system. Founded in 1918, the Institute works in close collaboration with stakeholders from industry and government to identify and develop standards- and conformance-based solutions to national and global priorities….

ANSI is not itself a standards developing organization. Rather, the Institute provides a framework for fair standards development and quality conformity assessment systems and continually works to safeguard their integrity.

So ANSI, rather than creating its own standards, works with outside organizations such as NIST…and INCITS.

INCITS

Now that’s an eye-catching acronym, but INCITS isn’t trying to cause trouble. Really, they’re not. Believe me.

INCITS, or the InterNational Committee for Information Technology Standards, is another private organization. It’s been around since 1961, and like NIST has been known under different names in the past.

Back in 2004, INCITS worked with ANSI (and NIST, who created samples) to develop three standards: one for finger images (ANSI INCITS 381-2004), one for face recognition (ANSI INCITS 385-2004), and one for finger minutiae (ANSI INCITS 378-2004, superseded by ANSI INCITS 378-2009 (S2019)).

From https://webstore.ansi.org/standards/incits/incits3782009s2019.

When entities used this vendor-agnostic minutiae format, then minutiae from any vendor could in theory be interchanged with those from any other vendor.

This came in handy when the FIPS was developed for PIV. Ah, two more acronyms.

FIPS and PIV

One year after the three ANSI INCITS standards were released, this happened (the acronyms are defined in the text):

Federal Information Processing Standard (FIPS) 201 entitled Personal Identity Verification of Federal Employees and Contractors establishes a standard for a Personal Identity Verification (PIV) system (Standard) that meets the control and security objectives of Homeland Security Presidential Directive-12 (HSPD-12). It is based on secure and reliable forms of identity credentials issued by the Federal Government to its employees and contractors. These credentials are used by mechanisms that authenticate individuals who require access to federally controlled facilities, information systems, and applications. This Standard addresses requirements for initial identity proofing, infrastructure to support interoperability of identity credentials, and accreditation of organizations issuing PIV credentials.

From the General Services Administration.

So the PIV, defined by a FIPS, based upon an ANSI INCITS standard, defined a way for multiple entities to create and support fingerprint minutiae that were interoperable.

But how do we KNOW that they are interoperable?

Let’s go back to NIST and MINEX.

Testing interoperability

So NIST ended up in charge of figuring out whether these interoperable minutiae were truly interoperable, and whether minutiae generated by a Cogent system could be used by a Printrak system. Of course, by the time MINEX testing began Printrak no longer existed, and a few years later Cogent wouldn’t exist either.

You can read the whole history of MINEX testing here, but for now I’m going to skip ahead to MINEX III (which occurred many years after MINEX04, but who’s counting?).

Like some other NIST tests we’ve seen before, vendors and other entities submit their algorithms, and NIST does the testing itself.
In this case, all submitters include a template generation algorithm, and optionally can include a template matching algorithm.
Then NIST tests each algorithm against every other algorithm. So the “innovatrics+0020” template generator is tested against itself, and is also tested against the “morpho+0115” algorithm, and all the other algorithms.

NIST then performs its calculations and comes up with summary values of interoperability, which can be sliced and diced a few different ways for both template generators and template matchers.

From NIST. Top 10 template generators (*Ascending “Pooled 2 Fingers FNMR @ FMR≤10^-2“*) as of July 29, 2024.

And this test, like some others, is an ongoing test, so perhaps in a few months someone will beat Innovatrics for the top pooled 2 fingers spot.

Are fingerprints still relevant?

And entities WILL continue to submit to the MINEX III test. While a number of identity/biometric professionals (frankly, including myself) seem to focus on faces rather than fingerprints, fingers still play a vital role in biometric identification, verification, and authentication.

Fingerprints are clearly a 21st century tool.

Even if one vendor continues its obsession with 1970s crime fighters.

And no, I’m NOT going to explain what the acronym FAP means. This post has too many acronyms already (TMAA).

When 250ppi Binary Fingerprint Images Were Acceptable

(Part of the biometric product marketing expert series)

I remember the first computer I ever owned: a Macintosh Plus with a hard disk with a whopping 20 megabytes of storage space. And that hard disk held ALL my files, with room to spare.

For sake of comparison, the video at the end of this blog post would fill up three-quarters of that old hard drive. Not that the Mac would have any way to play that video.

That Mac is now literally a museum piece.

By Tmarki – Own work, Public Domain, https://commons.wikimedia.org/w/index.php?curid=8058630.

And its 20 megabyte hard disk illustrates the limitations of those days. File storage was a precious commodity in the 1980s and 1990s, and we therefore accepted images that we wouldn’t even think about accepting today.

This affected the ways in which entities exchanged biometric information.

The 1993 ANSI/NIST standard

The ANSI/NIST standard for biometric data interchange has gone through several iterations over the years, beginning in 1986 when NIST didn’t even exist (it was called the National Bureau of Standards in those days).

From https://csrc.nist.gov/nist-cyber-history.

Fingerprints only

When I began working for Printrak in 1994, the image interchange standard in effect was ANSI/NIST-CSL 1-1993, the “Data Format for the Interchange of Fingerprint Information.”

Yes, FINGERPRINT information. No faces. No scars/marks/tattoos. signatures, voice recordings, dental/oral data, irises, DNA, or even palm prints. Oh, and no XML-formatted interchange either. Just fingerprints.

No logical record type 99, or even type 10

Back in 1993, there were only 9 logical record types.

From https://www.nist.gov/system/files/documents/2021/02/03/ansi-nist-csl_1-1993.pdf

For purposes of this post I’m going to focus on logical record types 3 through 6 and explain what they mean.

Type 3, Fingerprint image data (low-resolution grayscale).
Type 4, Fingerprint image data (high-resolution grayscale).
Type 5, Fingerprint image data (low-resolution binary).
Type 6, Fingerprint image data (high-resolution binary).

Image resolution in the 1993 standard

In the 1993 version of the ANSI/NIST standard:

“Low-resolution” was defined in standard section 5.2 as “9.84 p/mm +/- 0.10 p/mm (250 p/in +/- 2.5 p/in),” or 250 pixels per inch (250ppi).
The “high-resolution” definition in sections 5.1 and 5.2 was twice that, or “19.69 p/mm +/- 20 p/mm (500 p/in +/- 5 p/in.”
While you could transmit at these resolutions, the standard still mandated that you actually scan the fingerprints at the “high-resolution” 500 pixels per inch (500ppi) value.

Incidentally, this brings up an important point. The series of ANSI/NIST standards are not focused on STORAGE of data. They are focused on INTERCHANGE of data. They only provided a method for Printrak system users to exchange data with automated fingerprint identification systems (AFIS) from NEC, Morpho, Cogent, and other fingerprint system providers. Just interchange. Nothing more.

Binary and grayscale data in the 1993 standard

Now let’s get back to Types 3 through 6 and note that you were able to exchange binary fingerprint images.

Yup, straight black and white images.

The original uploader was CountingPine at English Wikipedia. – Transferred from en.wikipedia to Commons., CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=90286557.

Why the heck would fingerprint experts tolerate a system that transmitted binary images that latent fingerprint examiners considered practically useless?

Because they had to.

Storage and transmission constraints in 1993

Two technological constraints adversely affected the interchange of fingerprint data in 1993:

Storage space. As mentioned above, storage space was limited and expensive in the 1980s and the 1990s. Not everyone could afford to store detailed grayscale images with (standard section 4.2) “eight bits (256 gray levels)” of data. Can you imagine storing TEN ENTIRE FINGERS with that detail, at an astronomical 500 pixels per inch?
Transmission speed. There was another limitation enforced by the modems of the data. Did I mention that the ANSI/NIST standard was an INTERCHANGE standard? Well, you couldn’t always interchange your data via the huge 1.44 megabyte floppy disks of the day. Sometimes you had to pull your your trusty 14.4k or 28.8k modem and send the images over the telephone. Did you want to spend the time sending those huge grayscale images over the phone line?

Sound effects not included. By Wilton Ramon de Carvalho Machado – Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=3572726.

So as a workaround, the ANSI/NIST standard allowed users to interchange binary (black and white) images to save disk space and modem transmission time.

And we were all delighted with the capabilities of the 1993 ANSI/NIST standard.

Until we weren’t.

The 2015 ANSI/NIST standard

The current standard, ANSI/NIST-ITL 1-2011 Update 2015, supports a myriad of biometric types. For fingerprints (and palm prints), the focus is on grayscale images: binary image Type 5 and Type 6 are deprecated in the current standard, and low-resolution Type 3 grayscale images are also deprecated. Even Type 4 is shunned by most people in favor of new friction ridge image types in which the former “high resolution” is now the lowest resolution that anyone supports:

Excludes record types 20-22, 98, and 99. From https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.500-290e3.pdf

Type 13, Variable-resolution latent friction ridge image.
Type 14, Variable-resolution fingerprint image.
Type 15, Variable-resolution palm print image.

We’ve come a long way.

Now that you’ve read this whole thing, I’ll share my video which covers everything in 25 seconds.

Fade to gray.

By the time I upload this video to Instagram, I’ll probably use Instagram’s music facilities to add this song as background music.

And note that the band name is spelled Visage with one I, not Viisage with two I’s. (Now part of IDEMIA, along with Printrak.)
But the spelling inaccuracy is not surpring. The band can’t spell “gray” either.

From https://www.youtube.com/watch?v=eZHk4RwIp_g.