Check patentability & draft patents in minutes with Patsnap Eureka AI!

Deep learning-based fingerprint texture extraction method, system and device and storage medium

A texture extraction and deep learning technology, applied in instruments, biological neural network models, character and pattern recognition, etc., can solve the problems of poor fingerprint recognition, fuzzy fingerprints, contamination, etc., to improve accuracy and improve texture extraction capabilities. Effect

Pending Publication Date: 2021-08-10
GRG BAKING EQUIP CO LTD
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, although the traditional method can obtain a high recognition rate on high-quality fingerprint images, in practical applications, the fingerprints may be blurred, damaged, and stained during the process of collecting fingerprints, which makes the traditional method very difficult to recognize. It is difficult to extract the complete fingerprint texture, making the fingerprint recognition effect very poor
Especially in the case of severe fingerprint damage, the traditional method cannot restore the fingerprint texture at all, so that the accuracy of fingerprint recognition cannot be improved.

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
  • Deep learning-based fingerprint texture extraction method, system and device and storage medium
  • Deep learning-based fingerprint texture extraction method, system and device and storage medium
  • Deep learning-based fingerprint texture extraction method, system and device and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] This embodiment provides a fingerprint texture extraction method based on deep learning. The method of this embodiment can extract fingerprint textures in various situations very well, and can greatly improve the accuracy of fingerprint recognition.

[0054] Such as figure 1 As shown, the fingerprint texture extraction method of this embodiment specifically includes the following steps:

[0055] Step S1: Obtain the fingerprint image, and preprocess the fingerprint image so that the size of the fingerprint image meets the input requirements of the fingerprint texture extraction model;

[0056] Step S2: Input the preprocessed fingerprint image into the fingerprint texture extraction model to output the texture map;

[0057] Step S3: Cutting the output texture map to obtain a texture map that matches the size of the original fingerprint image.

[0058] Among them, the fingerprint image can be obtained through the Internet or fingerprint collection equipment. Since the co...

Embodiment 2

[0081] This embodiment provides a fingerprint texture extraction system based on deep learning, which implements the fingerprint texture extraction method based on deep learning described in Embodiment 1, such as Figure 8 As shown, the fingerprint texture extraction system of the present embodiment at least includes the following modules:

[0082] The preprocessing module is used to preprocess the obtained fingerprint image so that the size of the fingerprint image meets the input requirements of the fingerprint texture extraction model;

[0083] The model analysis module is used for inputting the fingerprint image after preprocessing into the fingerprint texture extraction model to output the texture map;

[0084] The post-processing module is used for cropping the output texture map to obtain a texture map matching the size of the original fingerprint image.

Embodiment 3

[0086] This embodiment provides a fingerprint texture extraction device, including:

[0087] program;

[0088] a memory for storing the program;

[0089] The processor is configured to load the program to execute the fingerprint texture extraction method based on deep learning described in Embodiment 1.

[0090] In addition, this embodiment also provides a storage medium, which stores a program, and is characterized in that, when the program is executed by a processor, the method for extracting fingerprint texture based on deep learning as described above is implemented.

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 deep learning-based fingerprint texture extraction method, system and device and a storage medium, and the method specifically comprises the following steps: S1, obtaining a fingerprint image, and carrying out the preprocessing of the fingerprint image, so as to enable the size of the fingerprint image to meet the input requirements of a fingerprint texture extraction model; s2, inputting the preprocessed fingerprint image into a fingerprint texture extraction model to output a texture image; and S3, cutting the output texture image to obtain a texture image conforming to the size of the original fingerprint image. Through the method, fingerprint textures under various conditions can be well extracted, and the accuracy of fingerprint identification can be greatly improved.

Description

technical field [0001] The present invention relates to the technical field of fingerprint identification, in particular to a deep learning-based fingerprint texture extraction method, system, device and storage medium. Background technique [0002] In the continuous development of the information society, people urgently need more reliable identification technology for identity authentication, and the use of biometrics for identity authentication has become a current craze. Among them, fingerprint recognition is widely recognized and applied because of its convenience and reliability. The traditional fingerprint identification method is to extract the ridge texture map of the fingerprint first, and then extract the feature points based on the texture map and do matching to find the similarity. Among them, fingerprint texture extraction is a very important link, which directly affects the accuracy of subsequent feature point extraction and matching. [0003] However, altho...

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): G06K9/00G06K9/34G06K9/62G06N3/04
CPCG06N3/04G06V40/1359G06V30/153G06F18/253
Inventor 周小龙黄跃珍王锟孙燕廖梓豪
Owner GRG BAKING EQUIP CO LTD
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com