What is the principle of fingerprint recognition technology?

The principle of fingerprint recognition technology is to find and compare the characteristics of fingerprints on fingerprint images; fingerprint recognition technology associates a person with his fingerprints and compares his fingerprints with pre-saved fingerprints. His true identity can be verified; each person's skin texture is different in patterns, breakpoints and intersections, and is unique. Relying on this uniqueness and stability, we can create fingerprint recognition technology.

The operating environment of this tutorial: Windows 7 system, Dell G3 computer.

What is the principle of fingerprint recognition technology?

Fingerprint recognition technology matches a person with his fingerprints, and by comparing his fingerprints with pre-saved fingerprints, his true identity can be verified. Each person's skin texture (including fingerprints) is unique in patterns, breakpoints and intersections, and it is through this uniqueness and stability that we can create fingerprint recognition technology. Each person's skin texture, including fingerprints, is different in patterns, breakpoints and intersections, making it unique and unchanged throughout life.

Technical Introduction

Every person’s skin texture, including fingerprints, is different in patterns, breakpoints and intersections, which are unique and unchanged throughout life. Based on this, we can match a person with his fingerprints, and by comparing his fingerprints with pre-saved fingerprint data, we can verify his true identity. This is fingerprint identification technology.

Fingerprint recognition mainly identifies the operator or the person being operated based on the lines, detailed features and other information of human fingerprints. Thanks to modern electronic integrated manufacturing technology and fast and reliable algorithm research, it has begun to enter our daily life, and has become the most in-depth research, the most widely used, and the most mature technology in biodetection.

Working principle

Fingerprints are actually quite complicated. Unlike manual processing, many biometric technology companies do not directly store images of fingerprints. Over the years, many digital algorithms have been produced in various companies and research institutions (relevant US laws believe that fingerprint images belong to personal privacy, so fingerprint images cannot be directly stored). But fingerprint recognition algorithms ultimately boil down to finding and comparing fingerprint features on fingerprint images.

Fingerprint identification

Different from manual processing, general biometric technology companies do not directly store fingerprint images, but use different digital algorithms to map fingerprints. Find and compare fingerprint characteristics on the image. Each fingerprint has several unique and measurable feature points. Each feature point has about 5 to 7 features. Our ten fingers produce at least 4900 independently measurable features, which is enough to show that fingerprint recognition is a A more reliable identification method.

Research on Fingerprint Recognition

• Overall Features

Overall features refer to those features that can be directly identified with the human eye Observable characteristics. Including pattern shape, pattern area, core points, triangle points and number of patterns, etc.

Pattern

Based on long-term practice, fingerprint experts generally divide fingerprints into three categories based on the direction and distribution of ridges - loop, also known as bucket-shaped ), arc (arch), spiral (whorl).

Pattern area

is the area on the fingerprint that includes the overall characteristics. From this area, you can tell which type the fingerprint belongs to. Some fingerprint recognition algorithms only use the data in the pattern area, while others use the complete fingerprint obtained.

The core point

is located at the progressive center of the fingerprint pattern, which serves as a reference point when reading and comparing fingerprints. Many algorithms are based on core points, that is, they can only process and identify fingerprints with core points.

Triangle point

is located at the first bifurcation point or breakpoint starting from the core point, or at the convergence of two lines, an isolated point, a turning point, or pointing to these singular points. Triangulation points provide the starting point for counting traces of fingerprint patterns.

Number of patterns

is the number of fingerprint patterns in the pattern area. When calculating the lines of a fingerprint, the core points and the triangular points are generally connected first. The number of intersections between this connection and the lines of the fingerprint can be considered as the number of lines of the fingerprint.

• Local features

Local features refer to the characteristics of nodes on the fingerprint. These nodes with certain characteristics are called detail features or feature points. .

Two fingerprints often have the same overall characteristics, but their detailed characteristics are unlikely to be exactly the same. Fingerprint lines are not continuous, smooth and straight, but often interrupted, bifurcated or turned. These breakpoints, bifurcation points and turning points are called "feature points", and it is these feature points that provide confirmation information about the uniqueness of fingerprints. The most typical ones are end points and bifurcation points, and others include divergence points and isolated points. , ring points, short lines, etc. The parameters of the feature points include: direction (the node can move in a certain direction), curvature (describing the speed at which the direction of the texture changes), position (the position of the node is described by x/y coordinates, which can be absolute or relative to triangular points or feature points).

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