Smart fingerprint lock fingerprint recognition system introduced four modules

Smart Fingerprint Fingerprint Identification System Module 1: Fingerprint Image Compression

Large-capacity fingerprint databases must be compressed and stored to reduce storage space. The main methods include JPEG, WSQ, EZW and so on.

Smart Fingerprint Fingerprint Identification System II: Fingerprint Image Processing

Including fingerprint area detection, image quality judgment, pattern and frequency estimation, image enhancement, fingerprint image binarization and refinement. Pre-processing refers to the processing of fingerprint images containing noise and pseudo-features using a certain algorithm to make the structure of the ridge lines clear and the feature information prominent. Its purpose is to improve the quality of fingerprint images and improve the accuracy of feature extraction. In general, the preprocessing process includes normalization, image segmentation, enhancement, binarization, and refinement, but depending on the specific situation, the preprocessing steps are also not the same.

Smart Fingerprint Fingerprint Identification System Module 3: Fingerprint Feature Extraction

Fingerprint feature extraction: Extracts fingerprint feature point information (endpoints, bifurcation points, etc.) from preprocessed images. The information mainly includes parameters such as type, coordinates, and direction. The detailed features in fingerprints usually include endpoints, bifurcation points, isolated points, short bifurcations, rings, and so on. The ridge end point and the bifurcation point have the most chance, the most stable, and easy to obtain in the fingerprint. These two types of feature points can match the fingerprint features: the degree of similarity between the feature extraction results and the stored feature templates is calculated.

Smart Fingerprint Fingerprint Identification System Module 4: Fingerprint Matching

Fingerprint matching is to compare the characteristics of fingerprints collected in the field with those stored in the fingerprint database to determine whether they belong to the same fingerprint. There are two ways to compare fingerprints:

1) One-to-one comparison: According to the user ID, the user fingerprint to be compared is retrieved from the fingerprint database, and then compared with the newly acquired fingerprint;

2) One-to-many alignment: The newly acquired fingerprint and all fingerprints in the fingerprint library are compared one by one.

The application of fingerprint identification technology in the field of access control, test conditions, identification, and safe deposit boxes in China is relatively mature, while the application of other products is still relatively small. However, with the development of fingerprint recognition technology, the application range of fingerprint identification is very wide, and the price is low, more and more users accept this technology. The application of fingerprint recognition in attendance and access control will continue to expand.