Training method of fingerprint repair model, fingerprint identification method, medium and equipment

A technology for repairing models and training methods, applied in character and pattern recognition, acquiring/arranging fingerprints/palmprints, neural learning methods, etc., can solve the problem of low accuracy of fingerprint repairing models, simplify training difficulty, and improve training speed , the effect of improving the accuracy

Pending Publication Date: 2022-02-11
BOE TECH GRP CO LTD
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present disclosure is to provide a training method for a fingerprint restoration model, a fingerprint identification method, a computer-readable storage medium, and an electronic device, thereby overcoming at least to a certain extent the accuracy of the fingerprint restoration model caused by the limitations and defects of related technologies. lower degree problem

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
  • Training method of fingerprint repair model, fingerprint identification method, medium and equipment
  • Training method of fingerprint repair model, fingerprint identification method, medium and equipment
  • Training method of fingerprint repair model, fingerprint identification method, medium and equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0074] Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided in order to give a thorough understanding of embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific details being omitted, or other methods, components, devices, steps, etc. may be adopted. In other instances, well-known technical solution...

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 relates to a training method of a fingerprint repair model, a fingerprint identification method, a medium and equipment, which relate to the technical field of machine learning. The method comprises the following steps of obtaining a first standard fingerprint, and inputting the first standard fingerprint into a preset dry fingerprint generation model to obtain a first simulated dry fingerprint, extracting a first local fingerprint feature of the first simulated dry fingerprint by using a first feature extraction model, and performing fingerprint repair on the first simulated dry fingerprint by using the first local fingerprint feature to obtain a first output result, and constructing a first loss function according to the first output result and the first standard fingerprint, and adjusting parameters in the first feature extraction model by using the first loss function to obtain a fingerprint repair model. The accuracy of the fingerprint repair model is improved.

Description

technical field [0001] Embodiments of the present disclosure relate to the technical field of machine learning, and in particular, relate to a training method of a fingerprint restoration model, a fingerprint identification method, a computer-readable storage medium, and an electronic device. Background technique [0002] Fingerprint identification technology is a relatively mature identity information identification technology, and is widely used in public security and personal information protection and other fields. In the field of fingerprint recognition, due to the partial loss of texture information of dry fingerprints, which cannot be repaired by classical image processing methods, the recognition accuracy of dry fingerprints is low. [0003] Existing training methods for fingerprint repair models can be implemented through deep learning technology; among them, deep learning technology is a popular technical field in the field of image processing at present, and can a...

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 Applications(China)
IPC IPC(8): G06V40/12G06V10/44G06V10/764G06V10/82G06V30/19G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/047G06N3/045G06F18/2415G06F18/241
Inventor 陈冠男孙梦笛
Owner BOE TECH GRP CO LTD
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