Every day that passes, we see different technological advancement that are more appealing than what we are used to, something that gives us an assurance that the future would even be better and greater with more technological devices to smile about. The idea of using fingerprints in the identification of individuals and the development of the first classification study was first developed by a British Surgeon, Dr. Henry Faulds.
He would then write to Charles Darwin seeking his input in the matter. But Darwin was unable to help and forwarded the information to Sir. Francis Galton who helped improve Dr. Fauld’s ideology and classification technology after studying over 8,000 fingerprints.
He would then introduce this concept to the rest of the world in his book, Fingerprints, published in 1892. Sonae then different institutions, with law enforcement agencies, technology companies, and scientists, have picked up from where Galton left and developed into the modern fingerprint technology. Improvements to the biometrics technology as well as the development of different fingerprint devices have allowed for better understanding of the fingerprint technology.
The technology has helped different parties learn of the different fingerprint patterns, their identification process and appreciate the strengths and weaknesses of the approach.
Understanding how fingerprinting works
For decades, particularly before the computerization era, fingerprint professionals fought hard to come up with a unique identifying base for the different fingerprints. Accurate identification of the different patterns that make Fingerprints unique would go a long way in influencing the development of fingerprint devices that maximize on capturing these all-important parts.
Years of researching this biometrics and the fast adoption of technology have helped industry players identify the different parts of all prints and their contributions to making every individual’s fingerprints unique. These rely heavily on the fingerprint lines and curves, also known as ridges, and include:
Crossover: This refers to the point on the print where two ridges cross each other or intersect. Experts and fingerprint devices often factor in the size, shape, and location of the crossover points when comparing prints.
Core: This refers to the center or the point of origin of the fingerprints. The size shape and location of the core also plays a critical role in matching fingerprints as it helps determine the type of thus fingerprint thus narrowing the search.
Island: This refers to a small ridge in between two spaces that appear as a dot. It also influences the shape of the uniqueness of a print.
Ridge ending: Fingerprint ridges and curves don’t necessarily start and stop at the edge of the finger. Most originate and wind up deep inside the face of a print. Ridge end, therefore, refers to the end of a line curve.
Delta: This refers to the space between two didges. While most are often blank, islands may appear on some.
Different fingerprint patterns
Note that fingerprints have over time emerged as one of the most accurate forms of identification based on the fact that no two individuals can have matching prints.
A lifetime of research further proved that Fingerprints can be broadly categorized into three patterns, loop, whorl, arch, and composites. These patterns solely depend on the position and location of the fingerprint core.
This represents the most popular fingerprint pattern with close to 65% of all Americans estimated to possess this fingerprint scan. It derives the name Loop based on the fact that the ridges here enter the finger from one side, form a curve and exit on the same side. You should, however, note that Loops only make backward turns but don’t twist. Its sub-categories include:
Radial Loop: These are referred to as radial loops based on the fact that the ridges appear to flow towards the radial bone. They appear to originate from the index finger and flowing towards the thumb.
Ulnar Loop: This also derives its name from the fact that its ridges appear to be flowing towards the ulnar bone of the hand. They appear to originate from the thumb flowing towards the index finger.
With over 30 percent of the human population donning the whorl type fingerprint patterns, this type of prints can be said to be the second most populous fingerprints. Unlike the loop patterns that originate from the edge of the finger, whorl prints have the ridges and curves forming a center point on the finger. The different types of whorls include:
Plain whorl: refers to finger ID pattern where the ridges make a single circular or spiral turn around a circular, spiral or oval core.
Double whorl: Refers to a scenario where the prints appear as two distinct patterns forming on two different cores.
Accidental whorl: Refers to a fingerprint pattern that features one form of whorl pattern and one other print formation except for plain arch.
This features one of an uncommon fingerprint pattern with only 5 percent of the human population estimated to have an arch print pattern. It derives its name from the fact that ridges here appear to originate from one end of the finger and form a curve before exiting on the other end. There are different types of arch prints that include the following:
Plain arch: Biometrics of a plain arch print pattern show the ridges entering the impression from one side, forming a plain wave by raising at the middle of the print before exiting on the other end.
Tented Arch: These are similar to the plain arch safe for the fact that their waves at the center of the print have a higher rise that forms a definite angle. They may also have two or more ridges at the center that help form an up thrust for the tented arch.
Most of these fingerprint classification patterns were developed by Henry Faulds. Modern fingerprint technology that involves a deeper understanding of these patterns through the use of biometrics and even the introduction of fingerprint devices has only served to affirm the effectiveness of these patterns in allowing for accurate identification and verification of persons.