Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Image processing method, target recognition model training method and target recognition method

An image processing and target recognition technology, applied in the field of target recognition, can solve problems such as affecting the identification of geological defects, and achieve the effect of improving accuracy, accuracy and efficiency

Active Publication Date: 2020-10-16
CHINA TIESIJU CIVIL ENG GRP CO LTD +1
View PDF6 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Aiming at the problem that the radar spectrum in the existing tunnel geological defect detection has a large number of stripes and noise points, which greatly affects the identification of geological defects, the present invention provides an image processing method, a target recognition model training method and a target recognition method , used to identify geological defects in the radar spectrum

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
  • Image processing method, target recognition model training method and target recognition method
  • Image processing method, target recognition model training method and target recognition method
  • Image processing method, target recognition model training method and target recognition method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0056] Such as figure 1 and Figure 4 As shown, combined with the formation principle of the tunnel geological radar scanning spectrum and the characteristics of large differences in gradient information in different states, before the geological defect identification, the feature enhancement processing of the image is carried out first. The edge features, texture features and structural features are enhanced. The extraction and enhancement of these three features can be promoted side by side without any order. The following will introduce the extraction of edge features, texture features and structural features respectively.

[0057] When extracting the edge features of the image to be processed, the gradient transformation algorithm is used, and the obtained gradient prior graph is named Fg, where the gradient transformation algorithm is a sobel operator, and f(x, y) is set as (x, y) on the image to be processed. y) point grayscale value, G(x) is the image grayscale value o...

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 an image processing method, and belongs to the technical field of target recognition. The method comprises the following steps: extracting edge features of a to-be-processed image to obtain a gradient prior image Fg; extracting texture features of the to-be-processed image to obtain a texture feature map Fv; extracting structural features of the to-be-processed image to obtain a structural feature graph Fs; carrying out Concat splicing on the gradient prior image Fg, the texture feature image Fv and the structure feature image Fs to obtain a multi-feature spliced imageFc; and performing convolution fusion operation on the multi-feature spliced image Fc to obtain a multi-feature fusion image Ff. According to the invention, edge feature enhancement is carried out onthe to-be-processed image and then the texture features and the structure features are fused, so that the target features in the image can be identified more accurately.

Description

technical field [0001] The invention belongs to the technical field of target recognition, and more specifically relates to an image processing method, a target recognition model training method and a target recognition method. Background technique [0002] With the development of information technology, image-based target detection technology is more and more widely used, common face recognition and vehicle obstacle recognition. Due to different application scenarios, it is difficult for the same target recognition model to be universally used in all fields that require target recognition. For example, in the construction of tunnel engineering, it is necessary to quickly and accurately detect and locate the voids and cavities that may appear inside the tunnel transverse tunnel. At present, in the method of abnormal detection of tunnel geological structure, it is mainly based on manual frame selection and mark counting from the geological radar scanning spectrum map. This k...

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): G06T7/00G06K9/46G06K9/62G06N3/04
CPCG06T7/0002G06V10/44G06N3/045G06F18/253
Inventor 刘道学耿天宝杨铭于健胡伟肖丽娜张尧尘
Owner CHINA TIESIJU CIVIL ENG GRP CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products