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Fingerprint identification method based on density chart model

A technology of fingerprint identification and density map, which is applied in character and pattern recognition, instruments, computer parts, etc., and can solve problems such as unsatisfactory improvement effects, application obstacles, and large storage space

Inactive Publication Date: 2005-03-16
TSINGHUA UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Among all available patents or published documents, those that are closer to the thinking of the present invention are: (A.K.Jain, S.Prabhakar, L.Hong and S.Pankanti. Filterbank-basedfingerprint matching.IEEE Trans.on Image Processing, Vol.9, 2000, PP: 846-859) uses multi-filter responses to encode, and uses these codes as features for fingerprint recognition, in (A.Ross, S.Prabhakar, and A.K.Jain.Fingerprint matching using minutiae and texture features.Proc.ICIP 2001,Vol.3,Greece,Oct 2001,pp 282-285) adopts a code similar to the above idea plus detail point information for fingerprint recognition, and has achieved certain results, but the problem is It requires a very large storage space, causing obstacles to application
The improvement effect is not very ideal

Method used

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  • Fingerprint identification method based on density chart model
  • Fingerprint identification method based on density chart model
  • Fingerprint identification method based on density chart model

Examples

Experimental program
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Embodiment Construction

[0181] Our invention can be implemented on ordinary PC computers, and there is no requirement for the operating system.

[0182] The fingerprint recognition algorithm based on multi-features is described in detail below. The main steps in the feature extraction stage include: effective area extraction, direction field estimation, image processing and enhancement, minutiae point extraction, and density map feature extraction; the main steps in the feature comparison or recognition stage include: minutiae point comparison, density map comparison, Decision Fusion. Among them, each step of effective area extraction, direction field estimation, image processing and enhancement, minutiae extraction and minutiae comparison can be carried out by traditional methods. Each step is introduced one by one below. Refer to Figure 1 for the overall flow chart, and Figure 2 introduces the results of each part of the entire process through a specific example.

[0183] Feature extraction:

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Abstract

The invention relates to a fingerprint identification method based on the density diagram model, which belongs to the fingerprint identification technique field. Its characteristic is shown as the following. The method combines the conventional detail point characteristic with the effective region characteristic and the density diagram characteristic to give the fingerprint identification characteristic. At the same time, combines the density diagram comparison result with the conventional detail point comparison result to improve the identification rate. The method is applicable with a little increment of the needed memory spaces. It is more suitable to identify the poor quality fingerprints.

Description

technical field [0001] The invention relates to the technical field of fingerprint recognition, in particular to a technology for simultaneously fusing fingerprint density map features and minutiae features for recognition. Background technique [0002] In modern society, the requirement for fast, effective and automatic personal identification is increasingly urgent. Security of important departments, border control, immigration inspection, entry and exit of confidential or valuables storage places, prevention of credit card fraud, network security, etc. all require reliable identification. personal identification. In the basis of identity verification, keys and certificates may be lost, stolen or copied, and passwords are easily forgotten, confused or peeped, and biometrics (including fingerprints, faces, hand shapes, handwritten signatures, irises, etc.) Inherent attributes of human beings, they do not appear in the above situation, so they become the most ideal basis fo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
Inventor 周杰万定锐
Owner TSINGHUA UNIV
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