CN108765400A - A kind of method of different materials in differentiation section image of asphalt pavement core sample - Google Patents

A kind of method of different materials in differentiation section image of asphalt pavement core sample Download PDF

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Publication number
CN108765400A
CN108765400A CN201810508942.9A CN201810508942A CN108765400A CN 108765400 A CN108765400 A CN 108765400A CN 201810508942 A CN201810508942 A CN 201810508942A CN 108765400 A CN108765400 A CN 108765400A
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China
Prior art keywords
different materials
core sample
asphalt pavement
image
section image
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Pending
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CN201810508942.9A
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Inventor
夏晓华
岳鹏举
姚运仕
高军
陆艳辉
杨发
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Changan University
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Changan University
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Priority to CN201810508942.9A priority Critical patent/CN108765400A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/136—Segmentation; Edge detection involving thresholding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/536—Depth or shape recovery from perspective effects, e.g. by using vanishing points

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  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Quality & Reliability (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)

Abstract

The invention discloses a kind of methods of different materials in differentiation section image of asphalt pavement core sample, include the following steps：1) cross-section image of asphalt pavement core sample is displayed on the screen；2) region division is carried out to image by setting grey parameter, each region corresponds to a kind of material, adjusts grey parameter, the differentiation effect of different materials in image is displayed on the screen；3) it according to the differentiation effect shown on screen, determines optimum gradation parameter, completes the division of different materials in section image of asphalt pavement core sample.The present invention distinguishes the different materials in section image of asphalt pavement core sample by the way of human-computer interaction, easy to operate；Operating process is not related to the professional knowledge of image procossing, and operation threshold is low；Avoid thresholding method because threshold value select it is improper caused by material distinguish ineffective problem, it is high that material distinguishes accuracy.

Description

A kind of method of different materials in differentiation section image of asphalt pavement core sample
Technical field
The invention belongs to road image process fields, and in particular to different in a kind of differentiation section image of asphalt pavement core sample The method of material distinguishes the different materials in core sample cross-section image by way of human-computer interaction.
Background technology
Image segmentation is the committed step for carrying out image analysis with Objective extraction.To the cross-section image of asphalt pavement core sample into Row analysis needs to distinguish the different materials in cross-section image.Different materials in existing differentiation section image of asphalt pavement core sample Method is mostly thresholding method.Thresholding method distinguishes the different materials in image by given threshold, and the selection of threshold value is to material The differentiation effect of material has a major impact, and value is usually close with the factors such as the light exposure of illumination condition, camera when Image Acquisition Correlation is generally difficult to determine best threshold value in actual use, user is needed to have certain image procossing professional knowledge And threshold value sets experience.
Cited literature 2：
[1] image segmentation algorithms of Lu Tao, Wan Yongjing, the Yang Wei based on sparse principal component analysis and adaptive threshold selection [J] computer science, 2016,43 (7):95-100.
[2] packets asphalt pavement core sample detection method research [D] Chang'an of the auspicious based on digital image processing techniques is big It learns, 2013.
Invention content
It is an object of the invention to the problems in for the above-mentioned prior art, provide a kind of differentiation asphalt pavement core sample section The method of different materials in image determines the different materials in image by way of human-computer interaction, ensures the standard that material is distinguished True property.
To achieve the goals above, the technical solution adopted by the present invention includes step：
1) cross-section image of asphalt pavement core sample is shown；
2) region division is carried out to image by setting grey parameter, each region corresponds to a kind of material, adjustment gray scale ginseng Number, shows the differentiation effect of different materials in image；
3) it according to effect is distinguished, determines optimum gradation parameter, completes different materials in section image of asphalt pavement core sample It divides.
Preferably, the adjusting range of grey parameter is 0~255 in the step 2).
Preferably, the mode that effect is distinguished in the step 2) display is real-time display.
Preferably, lines, color or the transparency in each region are different when effect is distinguished in the step 2) display.
Preferably, grey parameter is one or more variable gray values in step 2), or one or more variable Tonal range.If grey parameter is one or more variable gray values in step 2), it is assumed that its number is n, gray value point F is not denoted as it1, f2..., fn-1, fn, meet f1≤f2≤…≤fn-1≤fn, then in image pixel value in 0~f of gray scale interval1Range Interior pixel constitutes the 1st kind of region, and pixel value is in gray scale interval f1~f2Pixel in range constitutes the 2nd kind of region ..., pixel Value is in gray scale interval fn-1~fnPixel in range constitutes n region, and pixel value is in gray scale interval fnPicture in~255 ranges Element constitutes (n+1) and plants region；If grey parameter is one or more variable tonal range in step 2), it is assumed that its number is M, tonal range are denoted as f respectively1l~f1u, f2l~f2u..., f(m-1)l~f(m-1)u, fml~fmu, meet f1l≤f1u, f2l≤ f2u..., f(m-1)l≤f(m-1)u, fml≤fmu, then these tonal ranges are 1st kind determining respectively, the 2nd kind ..., (m-1) kind, m Kind region.
The present invention has the advantages that：Section image of asphalt pavement core sample is determined by the way of human-computer interaction not Same material, it is easy to operate；Operating process is not related to the professional knowledge of image procossing, and operation threshold is low；Avoid thresholding method Because threshold value select it is improper caused by material distinguish ineffective problem, it is high that material distinguishes accuracy.
Specific implementation mode
Below by specific implementation mode, the present invention is described in further detail.
The method that the present invention distinguishes different materials in section image of asphalt pavement core sample includes the following steps：
Step 1：The cross-section image of asphalt pavement core sample is displayed on the screen；
Step 2：Region division is carried out to image by setting grey parameter, each region corresponds to a kind of material, adjustment ash Parameter is spent, on the screen by the differentiation effect real-time display of different materials in image, the adjusting range of grey parameter is 0~255, Grey parameter is adjusted by the way of dragging slider bar, and the differentiation effect of different materials in image is displayed on the screen.
Step 3：According to the differentiation effect shown on screen, optimum gradation parameter is determined, complete asphalt pavement core sample section The division of different materials in image.
Step 2 lines, color or transparency in each region when effect is distinguished in display are different.
The grey parameter of step 2 is one or more variable gray values, or one or more variable gray scale models It encloses；If grey parameter is one or more variable gray values, it is assumed that its number is n, and gray value is denoted as f respectively1, f2..., fn-1, fn, meet f1≤f2≤…≤fn-1≤fn, then in image pixel value in 0~f of gray scale interval1Pixel in range constitutes the 1st Kind region, pixel value is in gray scale interval f1~f2Pixel in range constitutes the 2nd kind of region ..., and pixel value is in gray scale interval fn-1 ~fnPixel in range constitutes n region, and pixel value is in gray scale interval fnPixel in~255 ranges constitutes (n+1) kind Region；If grey parameter is one or more variable tonal ranges in step 2, it is assumed that its number is m, tonal range difference It is denoted as f1l~f1u, f2l~f2u..., f(m-1)l~f(m-1)u, fml~fmu, meet f1l≤f1u, f2l≤f2u..., f(m-1)l≤ f(m-1)u, fml≤fmu, then these tonal ranges are 1st kind determining respectively, the 2nd kind ..., (m-1) kind, m kinds region.
The above is only the better embodiment of the present invention, is not imposed any restrictions to the present invention, every according to this hair Bright technical spirit still falls within protection domain to any simple modification, change and equivalence change made by above technical scheme Within.

Claims (6)

1. a kind of method for distinguishing different materials in section image of asphalt pavement core sample, which is characterized in that including step：
1) cross-section image of asphalt pavement core sample is shown；
2) region division is carried out to image by setting grey parameter, each region corresponds to a kind of material, adjusts grey parameter, right The differentiation effect of different materials is shown in image；
3) it according to effect is distinguished, determines optimum gradation parameter, completes the division of different materials in section image of asphalt pavement core sample.
2. the method for distinguishing different materials in section image of asphalt pavement core sample according to claim 1, it is characterised in that：Institute The adjusting range of grey parameter is 0~255 in the step 2) stated.
3. the method for distinguishing different materials in section image of asphalt pavement core sample according to claim 1, it is characterised in that：Institute The mode that effect is distinguished in the step 2) display stated is real-time display.
4. the method for distinguishing different materials in section image of asphalt pavement core sample according to claim 1, it is characterised in that：Institute Lines, color or the transparency in each region are different when effect is distinguished in the step 2) display stated.
5. the method for distinguishing different materials in section image of asphalt pavement core sample according to claim 1, it is characterised in that：Step It is rapid 2) in grey parameter be one or more variable gray value, or one or more variable tonal ranges.
6. the method for distinguishing different materials in section image of asphalt pavement core sample according to claim 5, it is characterised in that：If Grey parameter is one or more variable gray values in step 2), it is assumed that its number is n, and gray value is denoted as f respectively1, f2..., fn-1, fn, meet f1≤f2≤…≤fn-1≤fn, then in image pixel value in 0~f of gray scale interval1Pixel in range constitutes the 1st Kind region, pixel value is in gray scale interval f1~f2Pixel in range constitutes the 2nd kind of region ..., and pixel value is in gray scale interval fn-1 ~fnPixel in range constitutes n region, and pixel value is in gray scale interval fnPixel in~255 ranges constitutes (n+1) kind Region；If grey parameter is one or more variable tonal ranges in step 2), it is assumed that its number is m, tonal range difference It is denoted as f1l~f1u, f2l~f2u..., f(m-1)l~f(m-1)u, fml~fmu, meet f1l≤f1u, f2l≤f2u..., f(m-1)l≤ f(m-1)u, fml≤fmu, then these tonal ranges are 1st kind determining respectively, the 2nd kind ..., (m-1) kind, m kinds region.
CN201810508942.9A 2018-05-24 2018-05-24 A kind of method of different materials in differentiation section image of asphalt pavement core sample Pending CN108765400A (en)

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EP4414942A1 (en) * 2023-02-08 2024-08-14 infraTest Prüftechnik GmbH Automated core sample measurement

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Application publication date: 20181106