What’s fingerprint classification?

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Fingerprint classification is the division of fingerprints into rough categories to make them easier to match with existing records in a system. This was critical at a time when investigators had to rely on paper files for fingerprint matching and needed a way to quickly narrow down the options when comparing fingerprints from a scene to those on file. Today’s electronic systems make comparisons easier and more reliable, but fingerprint classification can still be important to investigators.

Fingerprints occur when people leave behind skin oils and other residues after handling something. Friction ridges on fingers are very distinctive and the chance of having the same pattern as another living person is very low. Even identical twins have different fingerprints. Researchers studying the patterns of friction ridges on fingertips have identified several broad classes based on the shapes they find.

One is the spiral, where an isolated dot appears in the middle of the fingerprint. This is a relatively rare type of fingerprint. Bows are another example, including both regular and tent bows. Finally, people may have what’s known as a looped pattern, where the fabric wraps to the left or right. An investigator looking at a series of fingerprints can quickly determine whether they are arcs, rings or whorls.

Fingerprint classification allows for further categorization within each broad category. Investigators can determine the direction of patterns in friction ridges and can note any special features. Sometimes people can have very marked fingers, leading to the destruction of the original fingerprint pattern and the need to match the marks left by the scars. Fingerprint classification systems can assign numerical values ​​to different types of patterns, allowing people to invent numerical codes to help them quickly find similar fingerprints on files.

Students learning the history of fingerprints can do an exercise where they take fingerprints from each other and learn about the fingerprint classification system. They can study comparison samples in textbooks to learn more about different models and subtypes. While investigators today rely primarily on computer systems to make matches, they can also compare fingerprints manually, looking for distinctive pattern characteristics to determine whether a crime scene sample matches an archived reference, such as the fingerprints of a a known criminal or suspect. A random review can also help an investigator rule someone out; if a crime scene’s fingerprints are arcuate and a suspect has swirls, for example, the investigator knows that his fingerprints won’t match those at the scene.

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