Secondary classification fusion identification method for fingerprint and finger vein bimodal identification

A technology of fingerprint recognition and secondary classification, applied in the field of pattern recognition, can solve the problem of few vein recognition features, achieve high recognition rate and improve accuracy

Inactive Publication Date: 2012-06-06
HARBIN ENG UNIV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, vein recognition has the disadvantage of few features that can be extracted

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Secondary classification fusion identification method for fingerprint and finger vein bimodal identification
  • Secondary classification fusion identification method for fingerprint and finger vein bimodal identification
  • Secondary classification fusion identification method for fingerprint and finger vein bimodal identification

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] The following examples describe the present invention in more detail:

[0023] 1 fingerprint identification

[0024] Fingerprint recognition method based on minutiae matching:

[0025] (1) First obtain the orientation map of the fingerprint image, use the orientation filtering method to enhance the image, and use the orientation information of the fingerprint, that is, the orientation map to binarize the image and refine it using the eight-neighborhood-based thinning algorithm.

[0026] (2) Then extract minutiae points, that is, endpoints and bifurcation points, and singular points, that is, center points and triangle points, from the thinned fingerprint image, and use the method of texture tracking to remove false feature points.

[0027] (3) Use the extracted center point and triangle point for registration, so that the input image and the template image are on the same standard.

[0028] (4) Perform minutiae matching operation on the registered image. The matching...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a secondary classification fusion identification method for fingerprint and finger vein bimodal identification. A fingerprint module and a vein module are used as primary classifiers, and a secondary decision module is used as a secondary classifier. The method comprises the following steps of: reading a fingerprint image and a vein image through the fingerprint module and the vein module; pre-processing the read images respectively and extracting characteristic point sets of the both; performing identification on the images respectively to obtain respective identification results, wherein the fingerprint identification adopts a detail point match-based method, and the vein identification uses an improved Hausdorff distance mode to perform identification; forming a new characteristic vector by using the extracted fingerprint and vein characteristic point sets in a characteristic series mode through the secondary decision module so as to form the secondary classifier and obtain an identification result; and finally, performing decision-level fusion on the three identification results. The method has the advantages of making full use of identification information of fingerprints and finger veins, and effectively improving the accuracy of an identification system, along with high identification rate.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition, in particular to a method for recognizing through fingerprints and finger veins. Background technique [0002] The information collected by the single-mode biometric identification system is susceptible to changes due to time, environment or other factors, and the defects of feature extraction and matching lead to an excessively high error rate, which makes the application environment have too many restrictions and each biometric It is also impossible to be universal in a true sense, and these problems are difficult to solve by simply improving the matching method. The multi-modal biometric identification can provide more sufficient identification information through the combination of multiple biometric features, which makes up for the shortcomings of single biometric authentication such as instability and high error rate, improves the recognition rate of the system, and enhances the...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00
Inventor 王科俊马慧冯伟兴李雪峰刘靖宇王晨晖
Owner HARBIN ENG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products