Tag Archives: fingerprint

“Absolute Match,” A Relative Failure

Here is the latest public domain hit, the AFIS-inspired “Absolute Match.” If Google Lyria could, um, accurately pronounce “bifurcation” and “minutiae,” perhaps I could have done more with this. At least it got “ridge ending” right.

Absolute Match.

And of course characterizing a match as “absolute” is outdated in the post-NAS 2009 world.

So forget about the music. But if you need WORDS to market your biometric friction ridge product to hungry prospects, turn to a leading biometric product marketing consultant. Bredemarket can help.

Stop losing prospects! Use Bredemarket content for tech marketers

Today’s Acronyms Are NIST, FRIF, TE, E1N, and ROC

ROC (previously known as Rank One Computing) posted this about its latest resukts in the NIST Friction Ridge Image and Features Technology Evaluation Exemplar One-to-Many (FRIF TE E1N) evaluation.

“ROC’s performance in the NIST FRIF TE E1N evaluation, including #1 global ranking in Class B slap fingerprints, a critical capture format for high-scale civil and government identity programs, proves that American technology can now lead at the highest levels of global biometric performance….

“The NIST Friction Ridge Image and Features Technology Evaluation Exemplar One-to-Many evaluation, known as NIST FRIF TE E1N, evaluates one-to-many fingerprint identification at massive scale, testing how accurately algorithms can identify a subject from large enrollment repositories. Across the evaluation, ROC delivered top-tier performance in every category tested, including Class A, Class B, and Class C. “

As with every NIST biometric test, FRIF yields a massive amount of data. Just looking at the Class B slap data alone, here is what you can find, showing the top 7 entries out of 12 for the Class B Left Slap FNIR (another acronym: false negativce identification rate) at rank less than or equal to 10. Even this view excludes all other slap data and all other ranking data (1, 2, and 5).

(Data captured Friday, May 29, 2026 and may become outdated when new algorithms are tested.)

National Institute of Standards and Technology.

With this massive wealth of data, just about every vendor probably performed well in something, which is why ROC took the time to point out why Class B slap results are important.

“ROC’s most significant milestone came in Class B slap fingerprints. This performance is especially important for high-scale ABIS environments, including national ID programs, border management, civil enrollment, and high-stakes criminal justice workflows, where handling immense scale without sacrificing accuracy is mandatory.”

Although ROC may be the only entity trumpeting May results, other vendors have promotede earlier NIST FRIF TE E1N achievements, including IDEMIA, Identy.IO, Innovatrics, and Neurotechnology.

But they’re foreign. (As is Thales Group, for those keeping score.)

Dry To The Bone

You’re not gonna hear this song about dry fingerprint ridges on Top 40 radio. But for a select few biometric product marketers, it highlights a critically important issue.

“Dry To The Bone #1.” Google Lyria.

Why?

Because dry fingerprint ridges, while not a common worry among the general populace, ARE a concern among law enforcement, homeland security, financial institution, and other professionals who depend on high-quality friction ridge capture to solve crimes and identify people.

And these people desperately need products that accurately capture fingerprints in challenging conditions.

And the product vendors need to communicate their product benefits to potential vendors. (Whoops, I mean prospects.)

That’s where Bredemarket comes to save the day.

Not with music.

“Tracing the Ridge.” Google Lyria.

(Thankfully.)

Through Bredemarket, I work with you to develop the customer-focused, benefits-oriented words that move your prospects toward your fingerprint capture solution.

If you want prospects to buy your identity product, schedule a free meeting with the biometric product marketing expert.

Stop losing prospects! Use Bredemarket content for tech marketers
Stop losing prospects!

And…I couldn’t resist one more.

“Dry To The Bone #2.” Google Lyria.

How Do You Talk About the Product “Plumbing”?

There are a variety of hungry people (target audiences) who look at your product marketing content. And they all have different needs.

  • When talking about an elegant water fountain, some readers only care that the fountain works.
  • Other readers want to know HOW it works. Issues such as support and maintenance are critically important to these folks, but matter little to the first group who simply wants a working fountain.

If you are forced to speak to both target audiences in a single piece of content, how do you do it?

Very carefully.

My preference is to discuss the high-level benefits at the beginning of the content, and save the more technical uptime details and/or feature lists for later in the narrative.

Unless you are ONLY speaking to technical folks, leading with the “plumbing” kills your content. Someone who wants their police agency to solve more burglaries will fall asleep at a mention of 1000 pixels per inch fingerprint resolution or NIST-compliant lower palm print image dimensions.

Stay light, and only go deep to buttress your lightness.

My Favorite Line I Wrote Today

From my post this morning on Advent International, Amadeus, and IDEMIA Public Security.

“Plan C became to split IDEMIA into three chunks—biometric product marketing experts call this a “trifurcation”—and sell the three chunks individually.”

Now I have never officially written about trifurcations, but if you saw my post on bifurcations you can probably figure out trifurcations also.

From NIST.

Master Keys for Fingerprints and Voices

I swear I’ve written about “MasterPrints” before, but I can’t find any such article. Maybe I just discussed it internally at IDEMIA when I worked there in 2018.

“Generative adversarial network produces a “universal fingerprint” that will unlock many smartphones“

“Researchers at NYU and U Michigan have published a paper explaining how they used a pair of machine-learning systems to develop a “universal fingerprint” that can fool the lowest-security fingerprint sensors 76% of the time (it is less effective against higher-security sensors).

“The researchers used “generative adversarial networks” (GAN) to develop their attack: this technique uses a pair of machine learning systems, a “generator” which tries to fool a “discriminator,” to produce a kind of dialectical back-and-forth in that creates fakes that are harder and harder to detect.”

While this happened over seven years ago and is probably harder to implement with today’s technology, I was reminded of this when I ran across this Biometric Update article.

“Voice morphing attack blends identities to bypass voice biometrics: study“

“A new research paper explores a signal-level approach to voice morphing attacks that exposes vulnerabilities in biometric voice recognition systems.

“The abstract describes Time-domain Voice Identity Morphing (TD-VIM) as “a novel approach for voice-based biometric morphing” which “enables the blending of voice characteristics from two distinct identities at the signal level.” TD-VIM allows for seamless voice morphing directly in the time domain, allowing “identity blending without any embeddings from the backbone, or reference text.””

So it, um, sounds like we not only have MasterPrints, but also MasterVoices.