The Secrets Behind Fingerprint Scanning: Exploring the Accuracy of Visual Fingerprint Recognition
When you start your day, how do you unlock your phone? Do you enter a password, rely on facial recognition, or simply place your finger on your phone, eagerly awaiting that magical moment when it automatically unlocks?
Fingerprints stand out as the most widely used biometric today! This form of biometric authentication finds application in smartphone and tablet security, financial transactions, identity verification, attendance systems, and healthcare.
In my attempt to replicate fingerprint scanning, I opted for a more manual approach — testing my ability to recognize fingerprints visually, bypassing technology. For this experiment, I studied fingerprints from my mother, sister, and two friends.
Biometric scanners identify fingerprints based on details like the delta, curves, and other unique features. In my experiment, I aim to differentiate between fingerprints by analyzing these distinctive characteristics. First, I’ll gather information on all the fingerprints, and then I’ll test my recognition skills by identifying a fingerprint without prior knowledge of the owner.
Stage 1: Undestanding Fingerprint Characterisitcs
Firstly, to ensure a common understanding, fingerprints are distinguished by their orientations, core, and delta. While every fingerprint exhibits these three characteristics, the variation in their placement and size allows biometric scanners to distinctly differentiate between individuals.
Orientations denote the direction of the fingerprint ridges. In the example provided, the predominant orientation is from the top left to the bottom right. It’s important to note that each fingerprint may have multiple orientations, with some flowing in circular or oval patterns, referred to as the core or whorl.
The core exhibits a loop-like appearance in the fingerprint. The location of the core varies among individuals, with some having it at the bottom and others at the top. Another crucial fingerprint characteristic is the delta, identified as a triangle-like shape where the ridge orientations change direction.
Now, you might wonder if these characteristics are the sole means of fingerprint identification. The answer is no. While these three traits are the most significant and user-friendly, scanners can utilize additional details for recognition. For instance, scanners may use bifurcation, a ridge characteristic where a friction ridge splits into two, with the ridges on either side diverging to accommodate it.
Stage 2: Taking Fingerprints and Anaylzing Them
To start the actual replicate, I took my sister and my own coloured-fingerprints two times to analyze them separately.
Analyzing the first fingerprint, my sister’s:
Firstly, upon analyzing the core or whorl of the fingerprint, it’s evident that my sister’s fingerprint features a small core situated at the bottom-center of her finger. Moving to the delta, hers is slightly lower and to the right of the core. Notably, her delta is small and lacks a full triangle shape — it appears as if a side is missing.
Examining the main orientation of her fingerprint, it flows evenly above the core, imitating the core’s shape and straightening towards the tip of her finger. While she has numerous bifurcations, I’ve highlighted one of the more obvious and clear bifurcations for reference.
Analyzing the second fingerprint, mine’s:
Firstly, examining the core or whorl of the fingerprint reveals a notable difference — I have a larger core compared to my sister’s, and mine is situated in the middle of my finger. Moving to the delta, it becomes evident that mine is both farther from the core and to the right. Upon closer inspection, my delta is larger and forms a complete triangle.
Further analysis unveils two primary orientations on my fingerprint. One flows directly and evenly above the core, mirroring its shape. The second orientation follows the first but starts leaning to the right as it straightens out. From the fingertip, this orientation progresses from the top right to the bottom left, eventually becoming equal on both sides.
The bifurcation is a noteworthy feature, especially in comparing my sister’s and my fingerprints. A significant difference arises — while my sister’s bifurcation splits from the direction of her fingertips to her palm, mine splits from the direction of my palm to my fingertips. This distinction could be valuable in identifying fingerprints in Stage 3.
Stage 3: Recognizing a Unnamed Fingerprint
At this stage, I shuffled the second set of fingerprints that I obtained earlier and chose a random one to analyze and recognize who it belongs to.
I began by examining the core or whorl as I’ve done in my previous analyses. It struck me that, despite the small size, the core was oriented differently — it was facing upwards, unlike my sister’s, which lies horizontally. This discrepancy indicates that this fingerprint is likely mine.
Moving on, I focused on the delta of the fingerprint. I observed a full triangle shape, positioned a bit farther from the core. Comparing this to my sister’s fingerprint, hers has a delta closer to the core and isn’t a complete triangle, whereas mine is a full triangle and located further from the core. This reinforces my hypothesis that this fingerprint belongs to me.
Additionally, I studied the orientation and noticed that the majority of the fingerprint flows from the top right to the bottom right, with an eventual equal flow above the core. Contrasting this with my sister’s, her orientation flows evenly from the core to her fingertips, while mine goes from top to bottom at the fingertip. This observation further supports my conclusion that this fingerprint is mine.
Lastly, upon scrutinizing the bifurcations, I noted that both highlighted bifurcations split from the palm toward the fingertip. We had previously established that my sister’s bifurcation splits from the fingertip to the palm, while mine does the opposite — from palm to fingertip. This confirmed that the fingerprint in question is indeed mine.
Finishing Up My Replicate
This experiment tested the accuracy of recognizing different fingerprints through visual analysis. I focused on key features such as cores, deltas, orientations, and bifurcations during the replicate. The results indicate that these distinctive characteristics are indeed reliable indicators for identifying unique fingerprints.
The differences observed in core placement, delta shapes, and orientation patterns helps support the hypothesis that each individual’s fingerprint is distinct. This replicate has driven the fact that the intricate details of each finger is what make each fingerprint truly unique.