What is the principle of fingerprint recognition technology?

The principle of fingerprint recognition technology is based on the unique texture characteristics of each person's finger skin surface. It is mainly divided into three steps: 1. Collect the fingerprint image of the user's finger through a sensor or camera; 2. Use an image processing algorithm to Fingerprint details are extracted and enhanced; 3. After fingerprint collection and extraction, the system will generate a template for reference, that is, the feature vector of the fingerprint.

# Operating system for this tutorial: Windows 10 system, Dell G3 computer.

The principle of fingerprint recognition technology is based on the unique texture characteristics of each person's finger skin surface. It is mainly divided into three steps: collection, extraction and matching.

1. Collection: First, collect the fingerprint image of the user's finger through a sensor or camera. This can be done by touching the sensor surface directly, or using optical or pulsed means for non-contact acquisition. The sensor records the details of the fingerprint image, including features such as fine lines, sweat pores and grooves.

2. Extraction: In the collected fingerprint images, the fingerprint details are extracted and enhanced through image processing algorithms. These algorithms can detect and track feature points in fingerprint images, such as the bifurcations, intersections, and ends of fine lines. Through these feature points, a digital representation called a "feature vector" is generated, which is used for subsequent comparison and identification.

3. Matching: After fingerprint collection and extraction, the system will generate a template for reference, that is, the feature vector of the fingerprint. When the user attempts identification again, the system will collect their fingerprint image and extract its feature vector. Then, the user's feature vector is compared with all templates stored in the system. The comparison process usually uses algorithms to calculate the similarity between feature vectors. If the similarity reaches the preset threshold, the fingerprint matching is considered successful and the user's identity is identified.

The principle of fingerprint identification technology is based on the non-replicability and stability of fingerprints. Since each person's fingerprint pattern is unique, it can be used as a credential for identity verification. In addition, fingerprints remain relatively stable across time and age, and are not affected by external conditions such as cuts, abrasions or contamination. This makes fingerprint recognition a reliable and secure biometric technology that is widely used in various fields, such as mobile phone unlocking, access control systems, and forensic science.

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