Gradient background digital X-ray image defect automatic identification method

An automatic identification and X-ray technology, applied in image enhancement, image analysis, image data processing, etc., to achieve high recognition efficiency, improve signal-to-noise ratio, and reduce interference

Active Publication Date: 2019-08-02
CHINA WEAPON SCI ACADEMY NINGBO BRANCH
View PDF4 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide an automatic identification method for digital X-ray image defects with reduced noise interference and a gradient background with high detection accuracy in view of the current state of the art

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
  • Gradient background digital X-ray image defect automatic identification method
  • Gradient background digital X-ray image defect automatic identification method
  • Gradient background digital X-ray image defect automatic identification method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0048] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0049] A digital X-ray image defect automatic identification method with gradient background, comprising the following steps:

[0050] Step 1. Manufacture a ladder-shaped comparison test block that is consistent with the material of the workpiece to be inspected by mechanical processing, and the thickness of each step of the comparison test block changes gradually, wherein the maximum thickness of the comparison test block is greater than or equal to the thickness of the workpiece to be inspected The maximum thickness and the minimum thickness are less than or equal to the minimum thickness of the inspected workpiece; the number of steps of the comparison test block is greater than or equal to 5. In this embodiment, a gradient background is formed after DR scanning through the gradually changing ladder-shaped inspected workpiece and the compari...

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 gradient background digital X-ray image defect automatic identification method. The method comprises steps of scanning the detected workpiece and the step-shaped reference block through digital X-ray imaging, selecting an area image where steps with different penetration thicknesses are located in the DR image of the reference block, and calculating corresponding image gray value mean values under different penetration thicknesses, standard deviation and quantum noise probability density functions; calculating a noise theoretical summary density function and a noiseactual probability density function in a local area of any point by using a detection area in the DR image of the detected workpiece, and replacing the numerical value of the point with the sum of absolute values of differences between the noise theoretical summary density function and the noise actual probability density function to form a new image; by using the same method, realizing numericalvalue replacement of all points in the detection area, and forming a new detection image of the detected workpiece; and automatically detecting a new detection image of the detected workpiece by adopting a threshold segmentation method. According to the method, the interference of noise on small defects is reduced, the small defects can be automatically identified, and the identification accuracyand precision are high.

Description

technical field [0001] The invention relates to the field of image detection, in particular to an automatic identification method for digital X-ray image defects with gradient background. Background technique [0002] As one of the five conventional non-destructive testing technologies, X-ray inspection technology has the advantages of intuitive imaging, accurate quantification, positioning and qualitative, and can be archived and reviewed. As a result, the cost of use is high, it is not environmentally friendly, and the preservation, information management and transmission of film images have great limitations. In order to make up for the deficiencies of the film method, digital X-ray imaging technology came into being. Its principle is to irradiate the inspected workpiece through ray, and the attenuated ray photons are received by the scintillator, and the visible fluorescence is generated by the excitation transition effect, which is transformed by the detector. It is 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
IPC IPC(8): G06T7/00G01N23/04
CPCG06T7/0004G01N23/04G06T2207/10116G06T2207/30164G01N2223/03G01N2223/1016G01N2223/401G01N2223/646
Inventor 齐子诚倪培君唐盛明马兰付康左欣郑颖郭智敏李红伟余琼
Owner CHINA WEAPON SCI ACADEMY NINGBO BRANCH
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