Multi-source fingerprint image fusion method based on convolution sparse representation

A fingerprint image, sparse representation technology, applied in the field of fingerprint recognition, can solve the problem of fingerprints that cannot be recognized and matched, and achieve the effect of improving quality

Active Publication Date: 2020-09-15
ZHEJIANG UNIV OF TECH
View PDF6 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the situation that the existing external fingerprints cannot be identified and matched due to wear and scratches, the present invention proposes a multi-source fingerprint image fusion method based on convolutional sparse representation. By

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
  • Multi-source fingerprint image fusion method based on convolution sparse representation
  • Multi-source fingerprint image fusion method based on convolution sparse representation
  • Multi-source fingerprint image fusion method based on convolution sparse representation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] The present invention will be further described below in conjunction with accompanying drawing and embodiment:

[0041] see figure 1 and figure 2 , a multi-source fingerprint image fusion method based on convolutional sparse representation, including the following steps:

[0042] 1) adopting the sparse coding based on the convolution sparse morphological component analysis model to obtain the cartoon component and the sparse coefficient map of the texture component of the fingerprint image; including the following steps:

[0043] (11) Sparse coding using a morphological component analysis model based on convolutional sparse representation, where the model is defined as:

[0044]

[0045] Among them, S is the whole image, d m,c and d m,t Two sets of dictionary filters representing the sparse representation (SR) of the cartoon component and the texture component respectively, which are independently pre-learned from the cartoon image and the texture image using th...

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 discloses a multi-source fingerprint image fusion method based on convolution sparse representation. The method comprises the following steps: 1) obtaining pre-registered internal and external fingerprint images, and obtaining a sparse coefficient graph of cartoon and texture parts of the fingerprint images through employing the sparse coding of a morphological part analysis model based on convolution sparse; 2) determining a weight adding mode according to the value of the fingerprint image quality evaluation index direction determinacy, and adding the weight adding mode into cartoon and texture parts of the two source fingerprint images; and 3) respectively fusing the cartoon and texture parts of the two source fingerprint images by adopting a convolution sparse representation-based fusion method, obtaining a fusion coefficient graph of the cartoon and texture parts according to a weighted average rule, and reconstructing the fusion coefficient graph of the two parts toobtain a fused fingerprint image. According to the algorithm, more fingerprint details, textures and edge information can be reserved, regions with better quality of two source fingerprint images aresaved, and a fused fingerprint image with higher quality is obtained.

Description

technical field [0001] The invention relates to the field of fingerprint identification, in particular to a multi-source fingerprint image fusion method based on convolution sparse representation. Background technique [0002] Because of the uniqueness, permanence, and ease of collection of fingerprints, fingerprint identification features have become the most widely used biometric identification features for personal identification; currently the most used in identification applications are epidermis fingerprints, which are what the human eye can detect. The external fingerprints of the fingertip skin can be seen, because the fingertip skin exists on the surface of the skin and is easily affected by the external environment. When the skin on the fingertip surface is polluted by stains and sweat, etc., or is subjected to abrasion and scratches, it will cause irreparable damage. When the fingerprint is damaged, the texture structure of the fingerprint will be destroyed, and t...

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
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06T7/40
CPCG06T7/40G06V40/1335G06V40/1347G06V10/513G06V10/40G06F18/251Y02T10/40
Inventor 王海霞崔静静梁荣华陈朋刘义鹏蒋莉
Owner ZHEJIANG UNIV OF TECH
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap