Biological feature extraction model training method and image segmentation method

A biometric and model training technology, applied in the computer field, can solve the problems of low biometric accuracy and high labor cost, and achieve the effects of strong expression ability, reduced labor cost, and improved accuracy

Pending Publication Date: 2022-08-09
BEIJING KUANGSHI TECH +1
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present application proposes a biological feature extraction model training method and an image segmentation method to solve the technical problems in the prior art that the human cost of training the biological feature extraction model is high and the accuracy of biological feature extraction is low

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
  • Biological feature extraction model training method and image segmentation method
  • Biological feature extraction model training method and image segmentation method
  • Biological feature extraction model training method and image segmentation method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] The present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the related invention, but not to limit the invention. In addition, it should be noted that, for the convenience of description, only the parts related to the related invention are shown in the drawings.

[0023] It should be noted that the embodiments in the present application and the features of the embodiments may be combined with each other in the case of no conflict. The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0024] It should be pointed out that all the actions of obtaining signals, information or data in this application are carried out under the premise of complying with the corresponding data protection regulations and policies of the local ...

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 embodiment of the invention discloses a biological feature extraction model training method and an image segmentation method. The method comprises the following steps: performing data enhancement processing of fixed pixel point positions on each first image in an image set containing target biological characteristics to obtain a second image corresponding to each first image; carrying out data enhancement processing of pixel point position transformation on each second image to obtain a third image corresponding to each first image; and combining each first image and the corresponding second image into a positive sample pair, combining each first image and the corresponding third image into a negative sample pair, and training a neural network based on the obtained positive sample pair and negative sample pair to obtain a biological feature extraction model. According to the embodiment, the human cost of training the biological feature extraction model is reduced, and the accuracy of biological feature extraction is improved.

Description

technical field [0001] The embodiments of the present application relate to the field of computer technology, and in particular, to a method for training a biological feature extraction model and a method for image segmentation. Background technique [0002] With the development of computer technology, image segmentation technology has been widely used in the field of computer vision. In an image recognition scenario, it is usually necessary to perform image segmentation on the image to crop out the biometric area in the image, so as to improve the accuracy of subsequent biometric recognition. [0003] In the prior art, a biometric extraction model or an image segmentation model can be trained by manually labeling the training data. This method needs to label a large amount of data, so the labor cost is high. At the same time, due to the existence of labeling errors, biometrics have a weak ability to express texture details, so the accuracy of biometrics extraction is low....

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): G06V10/774G06T7/10G06V10/40G06V40/10
CPCG06V10/774G06V40/10G06V10/40G06T7/10G06T2207/10004
Inventor 周世豪
Owner BEIJING KUANGSHI 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