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Dealing with dry fingerprints

In the winter in South Korea, the temperature falls, and it becomes windy, consequently the humidity in the air drops. As a result, your skin becomes dry, leading to the oils and moisture in it to dry. Therefore, in winter, even correctly touching the surface of a fingerprint sensor with your fingertip can generate a dry fingerprint, which cannot be properly recognised.

In addition to being affected by seasonality, dry fingerprints can also easily occur in geographically dry regions, such as South Africa, Australia, and the Middle East. The occurrence of dry fingerprints is also very dependent on the individual’s occupation and age. For example, dry fingerprints can occur with people who are required to frequently disinfect their hands at work, such as doctors and workers who handle wood, leather or metal, as well as with elderly people and people with dry skin (Xerosis).

When a dry fingerprint occurs, the person’s fingertip hasn’t properly come in contact with the surface of the fingerprint sensor, and as a result, a blurry fingerprint image is generated. A blurry image of a fingerprint makes it more difficult to extract the fingerprint’s minutiae and is more likely to result in the extraction of false minutiae. Therefore, dry fingerprints eventually lead to a higher false rejection rate (FRR).

Even when there is a dry fingerprint problem, you can temporarily eschew it by blowing on your hands or applying hand cream to the fingers before going through the fingerprint authentication process. Nonetheless, such a measure is not a fundamental solution and therefore cannot guarantee the proper performance of fingerprint recognition. Suprema’s latest fingerprint sensor and algorithm can resolve such problems altogether.

Comparison of matching algorithms

Unlike the ordinary fingerprint matching algorithm, with Suprema’s fingerprint matching algorithm, inputted fingerprint images are analysed first by the Conformance Decision Engine (CDE), instead of sending them directly to the pre-processing stage. This Conformance Decision Engine (CDE) helps you obtain the correct fingerprint images even if fingerprints have been inputted in the wrong manner, by identifying instances such as when the fingerprint inputted has been produced by rubbing the surface of the fingerprint sensor with the fingertip. In addition, the acquired fingerprint images are analysed based on deep learning technology and subsequently go through the algorithm optimisation stage. This enables far faster provision of feedback to the user without having to go through the matching stage, because the fingerprint images are analysed in advance, prior to the image pre-processing stage.

Suprema’s fingerprint matching algorithm makes it possible to obtain high-quality fingerprint images since it effectively controls the fingerprint sensor and algorithm based on the CDE, and for that reason it is also excellent at eliminating false minutiae. Equipped with optimised algorithms and computation performance, all Suprema products can complete fingerprint matching in less than a second, even for dry fingerprints, and demonstrate effective and reliable fingerprint matching performance in a variety of environments.

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