Fingerprint matching method and fingerprint matching implementation mode

Abstract

The invention relates to a fingerprint identification and verification method. Specifically, a fingerprint matching method and a fingerprint matching implementation mode comprise that fingerprints are turned into a standardized frame ( with unified regulations), wherein the frame is used for inputting, matching and storing a fingerprint template. The fingerprint matching method and the fingerprint matching implementation mode are an image processing method, can remove liner deformation and elastic deformation in an image, and turn a group of two-dimension digital images into a structural framework with the unified regulations. The invention further provides an image processing method for fingerprint image matching. According to the fingerprint matching method and the fingerprint matching implementation mode, the structure of the typical framework is involved, detection of sweat pore characteristics from the fingerprint image is involved, nonlinearity calibration of the elastic deformation is involved, an input program is involved, and a matching program is involved.

Description

technical field [0001] The invention relates to a fingerprint identification and verification method. Specifically, the present invention turns fingerprints into a standardized framework (a framework with a unified specification), which is used to enter, match and store fingerprint templates. technical background [0002] The fingerprint is characterized by its smooth fingerprint ridges and valleys, and its characteristics are reflected in the position, interval, shape and tiny details of these ridges and valleys. The detail is the tail end and fork of the ridge. [0003] Traditionally, fingerprints have been widely adopted in the field of biometrics. The structure and distinction of fingerprints has been known since the early 20th century (see Handbook of Fingerprint Recognition, D. Maltoni, et al, Springer 2003). Fingerprint science is based on three basic principles: [0004] 1. For different fingerprints, the ridges and grooves of the individual's epidermis have diff...

AI Technical Summary

Problems solved by technology

[0032] 1. The fingerprint scanning area of ​​the query fingerprint is different from that of the template fingerprint

[0033] 2. Non-repeatable contact of the finger with the scanner due to manual operation or accidental contact that temporarily changes the structure of the fingerprint ridges

[0034] 3. Different skin and environmental factors can cause low contrast and / or image noise in the image, these factors include: dry skin, sweating, dust, humidity, residue on the glass surface of the scanning device, etc.

[0035] 4. There will be errors and artifacts during feature extraction, ridge detection and reduction

However, although the analysis of the third layer greatly increases the accuracy rate, this analysis also requires high-resolution scanning

Given the high density of sweat pores, consistent feature extraction and correlation between fingerprints is difficult to obtain

The need for high-resolution scanning (above 1000dpi) prevents widespread use of tertiary analysis

Images