CN116342635A - Crack contour extraction method in geological mapping - Google Patents

Crack contour extraction method in geological mapping Download PDF

Info

Publication number
CN116342635A
CN116342635A CN202310600933.3A CN202310600933A CN116342635A CN 116342635 A CN116342635 A CN 116342635A CN 202310600933 A CN202310600933 A CN 202310600933A CN 116342635 A CN116342635 A CN 116342635A
Authority
CN
China
Prior art keywords
enhancement
pixel point
gray
value
crack
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202310600933.3A
Other languages
Chinese (zh)
Other versions
CN116342635B (en
Inventor
崔珂伟
高吉青
王鹏飞
王利
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
First Geological Brigade of Shandong Provincial Bureau of Geology and Mineral Resources of First Geological and Mineral Exploration Institute of Shandong Province
Original Assignee
First Geological Brigade of Shandong Provincial Bureau of Geology and Mineral Resources of First Geological and Mineral Exploration Institute of Shandong Province
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by First Geological Brigade of Shandong Provincial Bureau of Geology and Mineral Resources of First Geological and Mineral Exploration Institute of Shandong Province filed Critical First Geological Brigade of Shandong Provincial Bureau of Geology and Mineral Resources of First Geological and Mineral Exploration Institute of Shandong Province
Priority to CN202310600933.3A priority Critical patent/CN116342635B/en
Publication of CN116342635A publication Critical patent/CN116342635A/en
Application granted granted Critical
Publication of CN116342635B publication Critical patent/CN116342635B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/13—Edge 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/30—Assessment of water resources

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Image Processing (AREA)

Abstract

The invention relates to the technical field of image processing, in particular to a crack contour extraction method in geological mapping, which comprises the following steps: the method comprises the steps of collecting geological crack images, obtaining enhancement coefficients of each pixel according to a gray value mean value of a window where each pixel is located and a gray value of each pixel, obtaining enhancement degrees of each pixel, obtaining base numbers of the pixels in logarithmic enhancement and indexes in exponential enhancement according to the enhancement degrees in a self-adaptive mode, obtaining logarithmic enhancement gray values and exponential enhancement gray values, obtaining final enhancement gray of the pixels by combining the logarithmic enhancement gray values and the exponential enhancement gray values, further obtaining enhancement images, and extracting crack contours according to the enhancement images. According to the invention, the enhancement degree of each pixel point is combined to enhance each pixel point, so that the gray value difference between the geological surface area and the pixel point of the crack area is large, and the crack contour extracted according to the enhanced image is kept relatively more complete.

Description

Crack contour extraction method in geological mapping
Technical Field
The invention relates to the technical field of image processing, in particular to a crack contour extraction method in geological mapping.
Background
The ground cracks are a macroscopic ground surface damage phenomenon that ground strata and soil bodies are cracked under the action of natural factors or artificial factors, cracks with certain length and width are formed on the ground, the ground cracks not only cause direct damage of various engineering buildings such as urban buildings, life line engineering, traffic, farmlands, water conservancy facilities and the like, but also damage land resources, further exacerbate land process contradiction, and cause a series of environmental problems, so that the cracks in geological images are extracted, the defects can be identified as soon as possible, and measures are taken for the defects.
Because the difference of gray values at the junction of the crack and the geological surface is not obvious, the geological crack image needs to be enhanced, the image is generally enhanced by using logarithmic enhancement or exponential enhancement at present, the same enhancement parameters are used for enhancing all pixel points in the image, the contrast at the junction of the crack area and the geological area in the enhanced image is not obvious, and the problem of edge deletion still exists when the crack contour is acquired according to the enhanced image.
Disclosure of Invention
The invention provides a crack contour extraction method in geological mapping, which aims to solve the existing problems.
The invention relates to a crack contour extraction method in geological mapping, which adopts the following technical scheme:
an embodiment of the invention provides a crack contour extraction method in geological mapping, which comprises the following steps:
collecting a geological fracture image; constructing windows by taking each pixel point in the geological fracture image as a center, and taking the average value of gray values of all the pixel points in each window as the representative gray of each window;
obtaining the enhancement coefficient of the central pixel point of each window according to the representative gray level of each window and the gray level value of the central pixel point of each window; performing linear normalization processing on the enhancement coefficients of all the pixel points to obtain the enhancement degree of each pixel point; acquiring a base number parameter of logarithmic enhancement of each pixel point according to the enhancement degree of each pixel point in the geological crack image, and acquiring a logarithmic enhancement gray value of each pixel point according to the base number parameter; acquiring index parameters of index enhancement of each pixel point according to the enhancement degree of each pixel point in the geological crack image, and acquiring an index enhancement gray value of each pixel point according to the index parameters;
acquiring a first gray level difference and a second gray level difference of each pixel point according to the gray level value, the logarithmic enhancement gray level value and the exponential enhancement gray level value of each pixel point; when the first gray level difference of the pixel point is larger than or equal to the second gray level difference, taking the logarithmic enhancement gray level value as the final enhancement gray level of the pixel point, and when the first gray level difference of the pixel point is smaller than the second gray level difference, taking the exponential enhancement gray level value as the final enhancement gray level of the pixel point;
forming an enhanced image by the final enhanced gray scale of all the pixel points; and extracting crack contours according to the enhanced images.
Preferably, the step of obtaining the enhancement coefficient of the center pixel point of each window according to the representative gray level of each window and the gray level value of the center pixel point of each window includes the following specific steps:
Figure SMS_1
wherein ,
Figure SMS_4
is->
Figure SMS_6
Enhancement coefficients for the center pixel points of the windows; />
Figure SMS_7
Is->
Figure SMS_2
Gray values of center pixel points of the windows; />
Figure SMS_5
Is->
Figure SMS_8
Representative gray scale of each window; />
Figure SMS_9
The median value of the representative gray values of all windows; />
Figure SMS_3
Is a natural constant.
Preferably, the obtaining the base number parameter of logarithmic enhancement of each pixel point according to the enhancement degree of each pixel point in the geological fracture image includes the following specific steps:
Figure SMS_10
wherein ,
Figure SMS_11
is the>
Figure SMS_12
Base parameters of the pixel points during logarithmic enhancement; />
Figure SMS_13
Is the>
Figure SMS_14
Enhancement degree of each pixel point; />
Figure SMS_15
Is a super parameter; />
Figure SMS_16
Is a natural constant.
Preferably, the step of obtaining the logarithmic enhancement gray value of each pixel point according to the base parameter includes the following specific steps:
Figure SMS_17
wherein ,
Figure SMS_20
is the>
Figure SMS_21
Logarithmic enhancement gray values of individual pixels; />
Figure SMS_23
Is the>
Figure SMS_18
Gray values of the individual pixels; />
Figure SMS_22
Is the>
Figure SMS_24
Base parameters of the pixel points during logarithmic enhancement; />
Figure SMS_25
Constant parameters that are logarithmically enhanced; />
Figure SMS_19
To round the symbol up.
Preferably, the obtaining the index parameter of the index enhancement of each pixel point according to the enhancement degree of each pixel point in the geological fracture image includes the following specific steps:
Figure SMS_26
wherein ,
Figure SMS_27
is the>
Figure SMS_28
Index parameters of the pixel points during index enhancement; />
Figure SMS_29
Is the>
Figure SMS_30
Enhancement degree of each pixel point; />
Figure SMS_31
Is a super parameter; />
Figure SMS_32
Is a natural constant.
Preferably, the obtaining the index enhanced gray value of each pixel according to the index parameter includes the following specific steps:
Figure SMS_33
wherein ,
Figure SMS_35
is the>
Figure SMS_38
An exponentially enhanced gray value of each pixel; />
Figure SMS_40
Is the>
Figure SMS_34
Gray values of the individual pixels; />
Figure SMS_37
Is the>
Figure SMS_39
Index parameters of the pixel points during index enhancement; />
Figure SMS_41
A constant parameter that is exponentially enhanced; />
Figure SMS_36
To round the symbol up.
Preferably, the step of obtaining the first gray level difference and the second gray level difference of each pixel according to the gray level value, the logarithmic enhancement gray level value and the exponential enhancement gray level value of each pixel includes the following specific steps:
taking the absolute value of the difference value between the gray value of each pixel point in the geological crack image and the logarithmic enhancement gray value as the first gray difference of each pixel point; and taking the absolute value of the difference value between the gray value of each pixel point in the geological crack image and the exponentially enhanced gray value as the second gray difference of each pixel point.
Preferably, the step of extracting the crack contour according to the enhanced image comprises the following specific steps:
and carrying out threshold segmentation on the enhanced image to obtain a binary image, carrying out connected domain analysis on the binary image, and taking the edge of the connected domain as a crack contour.
The technical scheme of the invention has the beneficial effects that: according to the method, the enhancement coefficient of each pixel point is obtained according to the gray value average value of the window where each pixel point is located and the gray value of each pixel point, the enhancement degree of each pixel point is further obtained, the base number when the pixel point carries out logarithmic enhancement and the index when the pixel point carries out index enhancement are obtained in a self-adaptive mode according to the enhancement degree, the logarithmic enhancement gray value and the index enhancement gray value are further obtained, the final enhancement gray of the pixel point is obtained by combining the logarithmic enhancement gray value and the index enhancement gray value, an enhanced image is further obtained, and the crack outline is extracted according to the enhanced image. According to the invention, the enhancement degree of each pixel point is combined to enhance each pixel point, so that the gray value difference between the geological surface area and the pixel point of the crack area is large, and the crack contour extracted according to the enhanced image is kept relatively more complete.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of steps of a method for extracting a fracture contour in geological mapping according to the present invention;
FIG. 2 is an image of a geological fracture.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following detailed description refers to specific implementation, structure, characteristics and effects of a crack contour extraction method in geological mapping according to the invention by combining the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following specifically describes a specific scheme of a fracture contour extraction method in geological mapping provided by the invention with reference to the accompanying drawings.
Referring to fig. 1, a flowchart illustrating steps of a method for extracting a fracture profile in geological mapping according to an embodiment of the present invention is shown, the method includes the following steps:
s001, collecting geological fracture images.
The camera is used to capture an image of the region where the geological fracture may exist, and the captured image is subjected to graying processing to obtain a geological fracture image for facilitating subsequent processing, as shown in fig. 2.
S002, obtaining the enhancement degree of each pixel point in the geological fracture image.
It should be noted that, under the influence of illumination, part of edges in the geological fracture image are located at the juncture of the geological surface and the fracture surface, part of edges are located at the juncture of the geological surface and the fracture shadow, the gray value difference at the juncture is less obvious due to the interference of the fracture shadow, the gray value of pixel points of the geological surface at the juncture is uneven, and the contour extracted after the adaptive threshold segmentation of the geological fracture image is inaccurate. Therefore, the geological fracture image needs to be enhanced, so that pixels belonging to the geological surface are brighter after being enhanced, and pixels belonging to the fracture area are darker after being enhanced. The pixels of the geological surface are relatively bright, the pixels of the crack area are relatively dark, and the gray values of the pixels at the junction of the geological surface and the crack area are uneven, so that the pixels at the junction of the geological surface and the crack area are required to be enhanced.
In the embodiment of the invention, each pixel point in the geological fracture image is taken as the center to be arranged
Figure SMS_42
A window of size, in the present embodiment,/-in>
Figure SMS_43
In other embodiments, the practitioner can set +.>
Figure SMS_44
Is of a size of (a) and (b). And obtaining the average value of the gray values of all pixel points in each window to be used as the representative gray of each window.
Obtaining the enhancement coefficient of the central pixel point of each window according to the representative gray level of each window:
Figure SMS_45
wherein ,
Figure SMS_72
is->
Figure SMS_75
Enhancement coefficients for the center pixel points of the windows; />
Figure SMS_78
Is->
Figure SMS_48
Gray values of center pixel points of the windows; />
Figure SMS_52
Is->
Figure SMS_56
Representative gray scale of each window; />
Figure SMS_61
The median value of the representative gray values of all windows; />
Figure SMS_70
Is a natural constant; when->
Figure SMS_73
The larger the representative gray level of the window, i.e. +.>
Figure SMS_74
The larger the average value of the gray values of all pixels in the window, the description +.>
Figure SMS_77
The more likely the pixel points in the window belong to the geological surface area, when +.>
Figure SMS_79
The smaller the representative gray level of the window, i.e. +.>
Figure SMS_81
The smaller the average value of the gray values of all pixels in the window, the description +.>
Figure SMS_83
The more likely the pixel points in the window belong to the crack region, when +.>
Figure SMS_85
The representative gray level of the windows is in the middle, i.e. the closer the representative gray level is to the median of the representative gray values of all windows +.>
Figure SMS_57
Description of the->
Figure SMS_62
In a windowThe more likely the pixel point is at the junction of the earth surface and the crack; the gray value of the crack region is smaller if +.>
Figure SMS_65
When the window is a crack region, < ->
Figure SMS_68
Representative gray scale +.>
Figure SMS_47
The large probability is smaller than the median of the representative gray values of all windows +.>
Figure SMS_50
，/>
Figure SMS_53
Negative number->
Figure SMS_55
Positive number, at this time->
Figure SMS_49
Larger due to->
Figure SMS_58
Is [0,1]Numbers within the range when the index of the same is +.>
Figure SMS_63
The larger the corresponding +.>
Figure SMS_66
The smaller is at this point->
Figure SMS_69
The enhancement coefficient of the central pixel point of each window is smaller; the grey value of the geological surface area is larger, if +.>
Figure SMS_80
The>
Figure SMS_82
Representative gray scale +.>
Figure SMS_86
The large probability is larger than the median +.of the representative gray values of all windows>
Figure SMS_54
，/>
Figure SMS_59
Is positive in number and is added with->
Figure SMS_60
Negative number, at this point->
Figure SMS_64
Smaller due to->
Figure SMS_67
Is [0,1]Numbers within the range when the index of the same is +.>
Figure SMS_71
The smaller the corresponding +.>
Figure SMS_76
The larger is at this point->
Figure SMS_84
The enhancement coefficient of the central pixel point of each window is larger; for the pixel points at the edges of the ground surface and the cracks, the representative gray level of the corresponding window is in the middle, so +.>
Figure SMS_46
The value of (2) tends to 0, possibly positive or negative, and +.>
Figure SMS_51
The enhancement coefficient of the center pixel point of the corresponding window is dependent on the gray value of the center pixel point, the larger the enhancement coefficient when the gray value is larger, and the smaller the enhancement coefficient when the gray value is smaller.
The enhancement coefficient of the central pixel point of each window, namely the enhancement coefficient of each pixel point in the geological fracture image is obtained, the enhancement coefficients of all the pixel points in the geological fracture image are subjected to linear normalization processing, and the enhancement coefficients after linear normalization are called enhancement degrees.
Thus, the enhancement degree of each pixel point in the geological fracture image is obtained. It should be noted that, in the embodiment of the present invention, a window is set for each pixel, and the enhancement degree of the central pixel is obtained by combining the average value of the pixels in the window and the gray value of the central pixel, so that the enhancement degrees of the pixels possibly located in different areas are different, and the subsequent adaptive enhancement effect according to the enhancement degree of each pixel is better.
S003, obtaining an enhanced image according to the enhancement degree of each pixel point in the geological crack image.
It should be noted that, common image enhancement methods have logarithmic enhancement and exponential enhancement. The embodiment of the invention needs to be brighter for the pixels belonging to the geological surface area and darker for the pixels belonging to the crack area. Since the logarithmic enhancement function has a convex nature, as the base in the logarithmic enhancement function increases, the originally brighter pixels in the image become brighter, as well as the originally darker pixels. Therefore, the logarithmic enhancement has better enhancement effect on pixels in the geological surface area, and the enhancement effect is not expected for pixels in the crack area. In the exponential enhancement, when the exponent in the exponential enhancement algorithm is greater than 1, the function of the exponential enhancement has a concave property, and as the exponent in the function of the exponential enhancement increases, the originally darker pixels in the image become darker, and the originally lighter pixels also become darker. Therefore, the exponential enhancement has better enhancement effect for the pixels in the crack area, and the enhancement effect is not expected for the pixels in the geological surface area. Therefore, the embodiment of the invention combines the enhancement degree to carry out logarithmic enhancement and exponential enhancement on each pixel point, and selects the optimal enhancement result of each pixel point as the final enhancement gray value of each pixel point, so that the contrast between the geological surface area and the crack area is more obvious, and the crack profile obtained according to the enhanced image is more accurate.
In the embodiment of the invention, the logarithmic enhancement gray value of each pixel point is obtained according to the enhancement degree of each pixel point in the geological crack image:
Figure SMS_87
Figure SMS_88
wherein ,
Figure SMS_99
is the>
Figure SMS_90
Logarithmic enhancement gray values of individual pixels; />
Figure SMS_96
Is the>
Figure SMS_101
Gray values of the individual pixels; />
Figure SMS_104
Is the>
Figure SMS_105
Base parameters of the pixel points during logarithmic enhancement; />
Figure SMS_108
Is the>
Figure SMS_97
Enhancement degree of each pixel point; />
Figure SMS_100
Is super-parametric due to->
Figure SMS_89
The value range of (2) is [0,1 ]]If directly used/>
Figure SMS_93
Obtaining base parameters->
Figure SMS_91
The base parameters of all pixels when logarithmic enhancement is performed are small, so that the enhancement effect of the pixels belonging to the geological surface area is not obvious, and the base parameters are super-parameters +>
Figure SMS_94
For->
Figure SMS_102
Enlarging to increase the base number of the logarithmic enhancement of the pixel points with large enhancement degree and ensure that the pixel points of the geological surface area are brighter, wherein the base number is +.>
Figure SMS_107
In other embodiments, the practitioner can set the superparameter ++according to the actual implementation>
Figure SMS_95
Is a value of (2); />
Figure SMS_98
Is a natural constant; />
Figure SMS_103
For the logarithmic enhancement of the constant parameters, in the examples of the invention +.>
Figure SMS_106
In other embodiments, the implementation personnel can be set according to the actual implementation situation; />
Figure SMS_92
Rounding up the symbol; when the enhancement degree is more than 0, the pixel is more likely to belong to the crack region, and in the logarithmic enhancement, the pixel does not need excessive enhancement, so the base parameter of the function of the logarithmic enhancement corresponding to the pixel is smaller, and the logarithmic enhancement gray value after enhancementThe original gray value has smaller difference: when the enhancement degree is more 1, it means that the pixel point is more likely to belong to the geological surface area, and in the logarithmic enhancement, the pixel point needs to be enhanced to become brighter, so that the larger the base parameter of the function of the logarithmic enhancement corresponding to the pixel point is, the larger the logarithmic enhancement gray value after enhancement is compared with the original gray value.
Acquiring an exponential enhancement gray value of each pixel point according to the enhancement degree of each pixel point in the geological crack image:
Figure SMS_109
Figure SMS_110
wherein ,
Figure SMS_119
is the>
Figure SMS_113
An exponentially enhanced gray value of each pixel; />
Figure SMS_116
Is the>
Figure SMS_121
Gray values of the individual pixels; />
Figure SMS_125
Is the>
Figure SMS_127
Index parameters of the pixel points during index enhancement; />
Figure SMS_128
Is the>
Figure SMS_120
Individual pixelsThe degree of enhancement of the dots; />
Figure SMS_122
Is super-parametric due to->
Figure SMS_111
The value range of (2) is [0,1 ]]If directly use->
Figure SMS_115
Acquisition of index parameter->
Figure SMS_114
The index parameters of all pixels during the index enhancement are smaller, so that the enhancement effect of the pixels belonging to the crack region is not obvious, and the super parameters are adopted>
Figure SMS_118
For->
Figure SMS_123
Enlarging the index of the pixel points with small enhancement degree to ensure that the pixel points in the crack area are darker when the index of the pixel points with small enhancement degree is enhanced, wherein the index is +.>
Figure SMS_126
In other embodiments, the practitioner can set the superparameter ++according to the actual implementation>
Figure SMS_117
Is a value of (2); />
Figure SMS_124
Is a natural constant; />
Figure SMS_129
For exponentially increasing constant parameters, in the present examples +.>
Figure SMS_130
In other embodiments, the implementation personnel can be set according to the actual implementation situation; />
Figure SMS_112
Rounding up the symbol; when the enhancement degree is more than 0, it means that the pixel is more likely to belong to the crack region, and in the exponential enhancement, the pixel needs to be enhanced, so that the pixel is darker, so that the exponential parameter of the exponential enhancement corresponding to the pixel is larger, and the exponential enhancement gray value after enhancement is smaller than the original gray value: when the enhancement degree is more 1, it means that the pixel point is more likely to belong to the geological surface area, and in the exponential enhancement, the pixel point is less required to be enhanced, so that the index enhancement gray value corresponding to the pixel point is smaller than the original gray value, and the difference between the enhanced exponential enhancement gray value and the original gray value is smaller.
And acquiring the absolute value of the difference value between the logarithmic enhancement gray value and the original gray value of each pixel point in the geological crack image as the first gray difference of each pixel point. And acquiring an absolute value of a difference value between the index enhanced gray value and the original gray value of each pixel point in the geological crack image, and taking the absolute value as a second gray difference of each pixel point. When the first gray level difference of the pixel point is larger than or equal to the second gray level difference, the logarithmic enhancement gray level value is used as the final enhancement gray level of the pixel point, and when the first gray level difference of the pixel point is smaller than the second gray level difference, the exponential enhancement gray level value is used as the final enhancement gray level of the pixel point.
Thus, the final enhancement gray of each pixel point is obtained. The final enhanced gray scale of all pixels in the geologic crack image constitutes an enhanced image.
Thus, an enhanced image is acquired.
S004, acquiring crack contours according to the enhanced images.
And (3) carrying out Ojin threshold segmentation on the enhanced image to obtain a binary image, and carrying out connected domain analysis on the binary image to obtain the edge of the connected domain, namely the crack contour.
Through the steps, the extraction of the crack outline is completed.
According to the embodiment of the invention, the enhancement coefficient of each pixel point is obtained according to the gray value average value of the window where each pixel point is located and the gray value of each pixel point, so that the enhancement degree of each pixel point is obtained, the base number of the pixel point when carrying out logarithmic enhancement and the index of the pixel point when carrying out index enhancement are obtained in a self-adaptive mode according to the enhancement degree, the logarithmic enhancement gray value and the index enhancement gray value are obtained, the final enhancement gray of the pixel point is obtained by combining the logarithmic enhancement gray value and the index enhancement gray value, an enhanced image is further obtained, and the crack outline is extracted according to the enhanced image. According to the invention, the enhancement degree of each pixel point is combined to enhance each pixel point, so that the gray value difference between the geological surface area and the pixel point of the crack area is large, and the crack contour extracted according to the enhanced image is kept relatively more complete.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.

Claims (8)

1. A crack contour extraction method in geological mapping is characterized by comprising the following steps:
collecting a geological fracture image; constructing windows by taking each pixel point in the geological fracture image as a center, and taking the average value of gray values of all the pixel points in each window as the representative gray of each window;
obtaining the enhancement coefficient of the central pixel point of each window according to the representative gray level of each window and the gray level value of the central pixel point of each window; performing linear normalization processing on the enhancement coefficients of all the pixel points to obtain the enhancement degree of each pixel point; acquiring a base number parameter of logarithmic enhancement of each pixel point according to the enhancement degree of each pixel point in the geological crack image, and acquiring a logarithmic enhancement gray value of each pixel point according to the base number parameter; acquiring index parameters of index enhancement of each pixel point according to the enhancement degree of each pixel point in the geological crack image, and acquiring an index enhancement gray value of each pixel point according to the index parameters;
acquiring a first gray level difference and a second gray level difference of each pixel point according to the gray level value, the logarithmic enhancement gray level value and the exponential enhancement gray level value of each pixel point; when the first gray level difference of the pixel point is larger than or equal to the second gray level difference, taking the logarithmic enhancement gray level value as the final enhancement gray level of the pixel point, and when the first gray level difference of the pixel point is smaller than the second gray level difference, taking the exponential enhancement gray level value as the final enhancement gray level of the pixel point;
forming an enhanced image by the final enhanced gray scale of all the pixel points; and extracting crack contours according to the enhanced images.
2. The method for extracting a crack contour in geological mapping according to claim 1, wherein the step of obtaining the enhancement coefficient of the center pixel point of each window according to the representative gray level of each window and the gray level value of the center pixel point of each window comprises the following specific steps:
Figure QLYQS_1
wherein ,
Figure QLYQS_4
is->
Figure QLYQS_6
Enhancement coefficients for the center pixel points of the windows; />
Figure QLYQS_8
Is->
Figure QLYQS_3
Gray values of center pixel points of the windows; />
Figure QLYQS_5
Is->
Figure QLYQS_7
Representative gray scale of each window; />
Figure QLYQS_9
For representative grey values of all windowsA median value; />
Figure QLYQS_2
Is a natural constant.
3. The method for extracting a fracture contour in geological mapping according to claim 1, wherein the step of obtaining the base parameter of logarithmic enhancement of each pixel point according to the enhancement degree of each pixel point in the geological fracture image comprises the following specific steps:
Figure QLYQS_10
wherein ,
Figure QLYQS_11
is the>
Figure QLYQS_12
Base parameters of the pixel points during logarithmic enhancement; />
Figure QLYQS_13
Is the>
Figure QLYQS_14
Enhancement degree of each pixel point; />
Figure QLYQS_15
Is a super parameter; />
Figure QLYQS_16
Is a natural constant.
4. The method for extracting the contour of the crack in the geological mapping according to claim 1, wherein the step of obtaining the logarithmic enhancement gray value of each pixel point according to the base parameter comprises the following specific steps:
Figure QLYQS_17
wherein ,
Figure QLYQS_20
is the>
Figure QLYQS_21
Logarithmic enhancement gray values of individual pixels; />
Figure QLYQS_23
Is the>
Figure QLYQS_18
Gray values of the individual pixels; />
Figure QLYQS_22
Is the>
Figure QLYQS_24
Base parameters of the pixel points during logarithmic enhancement; />
Figure QLYQS_25
Constant parameters that are logarithmically enhanced; />
Figure QLYQS_19
To round the symbol up.
5. The method for extracting a fracture contour in geological mapping according to claim 1, wherein the step of obtaining the index parameter of the index enhancement of each pixel point according to the enhancement degree of each pixel point in the geological fracture image comprises the following specific steps:
Figure QLYQS_26
wherein ,
Figure QLYQS_27
is the>
Figure QLYQS_28
Index parameters of the pixel points during index enhancement; />
Figure QLYQS_29
Is the>
Figure QLYQS_30
Enhancement degree of each pixel point; />
Figure QLYQS_31
Is a super parameter; />
Figure QLYQS_32
Is a natural constant.
6. The method for extracting a crack contour in geological mapping according to claim 1, wherein the step of obtaining the index enhanced gray value of each pixel point according to the index parameter comprises the following specific steps:
Figure QLYQS_33
wherein ,
Figure QLYQS_34
is the>
Figure QLYQS_38
An exponentially enhanced gray value of each pixel; />
Figure QLYQS_39
Is the>
Figure QLYQS_36
Gray values of the individual pixels; />
Figure QLYQS_37
Is the>
Figure QLYQS_40
Index parameters of the pixel points during index enhancement; />
Figure QLYQS_41
A constant parameter that is exponentially enhanced; />
Figure QLYQS_35
To round the symbol up.
7. The method for extracting a crack contour in geological mapping according to claim 1, wherein the step of obtaining the first gray level difference and the second gray level difference of each pixel point according to the gray level value, the logarithmically enhanced gray level value and the exponentially enhanced gray level value of each pixel point comprises the following specific steps:
taking the absolute value of the difference value between the gray value of each pixel point in the geological crack image and the logarithmic enhancement gray value as the first gray difference of each pixel point; and taking the absolute value of the difference value between the gray value of each pixel point in the geological crack image and the exponentially enhanced gray value as the second gray difference of each pixel point.
8. The method for extracting the crack contour in the geological mapping according to claim 1, wherein the step of extracting the crack contour according to the enhanced image comprises the following specific steps:
and carrying out threshold segmentation on the enhanced image to obtain a binary image, carrying out connected domain analysis on the binary image, and taking the edge of the connected domain as a crack contour.
CN202310600933.3A 2023-05-26 2023-05-26 Crack contour extraction method in geological mapping Active CN116342635B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310600933.3A CN116342635B (en) 2023-05-26 2023-05-26 Crack contour extraction method in geological mapping

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310600933.3A CN116342635B (en) 2023-05-26 2023-05-26 Crack contour extraction method in geological mapping

Publications (2)

Publication Number Publication Date
CN116342635A true CN116342635A (en) 2023-06-27
CN116342635B CN116342635B (en) 2023-08-08

Family

ID=86893293

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310600933.3A Active CN116342635B (en) 2023-05-26 2023-05-26 Crack contour extraction method in geological mapping

Country Status (1)

Country Link
CN (1) CN116342635B (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117152187A (en) * 2023-10-30 2023-12-01 山东中科冶金矿山机械有限公司 Crack contour extraction method in geological mapping
CN117710399A (en) * 2024-02-06 2024-03-15 山东省地质测绘院 Crack contour extraction method in geological survey based on vision

Citations (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1994013098A1 (en) * 1992-11-30 1994-06-09 Eastman Kodak Company Resolution enhancement system for binary images
US20030156762A1 (en) * 2001-10-15 2003-08-21 Jonas August Volterra filters for enhancement of contours in images
CN103048329A (en) * 2012-12-11 2013-04-17 北京恒达锦程图像技术有限公司 Pavement crack detecting method based on active contour model
CN103440657A (en) * 2013-08-27 2013-12-11 武汉大学 Method for online screening cracks of road
CN104992429A (en) * 2015-04-23 2015-10-21 北京宇航时代科技发展有限公司 Mountain crack detection method based on image local reinforcement
US20180137612A1 (en) * 2015-04-27 2018-05-17 Wuhan Wuda Zoyon Science And Technology Co., Ltd. A stepwise refinement detection method for pavement cracks
KR101932214B1 (en) * 2017-11-30 2018-12-24 한국과학기술원 Apparatus for measuring crack using image processing technology and method thereof
CN110264459A (en) * 2019-06-24 2019-09-20 江苏开放大学（江苏城市职业学院） A kind of interstices of soil characteristics information extraction method
CN110298802A (en) * 2019-06-28 2019-10-01 广东诚泰交通科技发展有限公司 Road surface crack detection method and device
CN110298816A (en) * 2019-04-26 2019-10-01 陕西师范大学 A kind of Bridge Crack detection method re-generated based on image
US20200364849A1 (en) * 2018-01-03 2020-11-19 Southeast University Method and device for automatically drawing structural cracks and precisely measuring widths thereof
CN112419250A (en) * 2020-11-13 2021-02-26 湖北工业大学 Pavement crack digital image extraction, crack repair and crack parameter calculation method
WO2021114564A1 (en) * 2019-12-10 2021-06-17 南京莱斯电子设备有限公司 Enhancement method for low-contrast infrared image
JP2021092414A (en) * 2019-12-09 2021-06-17 金川 典代 Crack extraction method
CN115063404A (en) * 2022-07-27 2022-09-16 建首(山东)钢材加工有限公司 Weathering resistant steel weld joint quality detection method based on X-ray flaw detection
US11580647B1 (en) * 2021-12-24 2023-02-14 Guangzhou University Global and local binary pattern image crack segmentation method based on robot vision
CN115861290A (en) * 2022-12-30 2023-03-28 南京林业大学 Method for detecting surface defects of skin-touch wooden door

Patent Citations (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1994013098A1 (en) * 1992-11-30 1994-06-09 Eastman Kodak Company Resolution enhancement system for binary images
US20030156762A1 (en) * 2001-10-15 2003-08-21 Jonas August Volterra filters for enhancement of contours in images
CN103048329A (en) * 2012-12-11 2013-04-17 北京恒达锦程图像技术有限公司 Pavement crack detecting method based on active contour model
CN103440657A (en) * 2013-08-27 2013-12-11 武汉大学 Method for online screening cracks of road
CN104992429A (en) * 2015-04-23 2015-10-21 北京宇航时代科技发展有限公司 Mountain crack detection method based on image local reinforcement
US20180137612A1 (en) * 2015-04-27 2018-05-17 Wuhan Wuda Zoyon Science And Technology Co., Ltd. A stepwise refinement detection method for pavement cracks
KR101932214B1 (en) * 2017-11-30 2018-12-24 한국과학기술원 Apparatus for measuring crack using image processing technology and method thereof
US20200364849A1 (en) * 2018-01-03 2020-11-19 Southeast University Method and device for automatically drawing structural cracks and precisely measuring widths thereof
CN110298816A (en) * 2019-04-26 2019-10-01 陕西师范大学 A kind of Bridge Crack detection method re-generated based on image
CN110264459A (en) * 2019-06-24 2019-09-20 江苏开放大学（江苏城市职业学院） A kind of interstices of soil characteristics information extraction method
CN110298802A (en) * 2019-06-28 2019-10-01 广东诚泰交通科技发展有限公司 Road surface crack detection method and device
JP2021092414A (en) * 2019-12-09 2021-06-17 金川 典代 Crack extraction method
WO2021114564A1 (en) * 2019-12-10 2021-06-17 南京莱斯电子设备有限公司 Enhancement method for low-contrast infrared image
CN112419250A (en) * 2020-11-13 2021-02-26 湖北工业大学 Pavement crack digital image extraction, crack repair and crack parameter calculation method
US11580647B1 (en) * 2021-12-24 2023-02-14 Guangzhou University Global and local binary pattern image crack segmentation method based on robot vision
CN115063404A (en) * 2022-07-27 2022-09-16 建首(山东)钢材加工有限公司 Weathering resistant steel weld joint quality detection method based on X-ray flaw detection
CN115861290A (en) * 2022-12-30 2023-03-28 南京林业大学 Method for detecting surface defects of skin-touch wooden door

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
刘丰年;: "路面裂缝图像局部对比度增强技术研究", 三门峡职业技术学院学报, no. 03 *
周丽军;: "基于图像增强与分水岭分割的隧道低对比度裂缝提取方法", 计算机科学, no. 1 *
姜维刚;王仲霖;潘飞;: "一种基于孔洞填充的路面裂缝识别方法", 电子技术与软件工程, no. 11 *
徐亚明;田鹏;: "一种自适应裂缝宽度的二值化方法", 大地测量与地球动力学, no. 03 *
朱其刚: "基于像素特征的路面裂缝图像自适应滤噪", 山东师范大学学报(自然科学版), no. 03 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117152187A (en) * 2023-10-30 2023-12-01 山东中科冶金矿山机械有限公司 Crack contour extraction method in geological mapping
CN117152187B (en) * 2023-10-30 2024-01-26 山东中科冶金矿山机械有限公司 Crack contour extraction method in geological mapping
CN117710399A (en) * 2024-02-06 2024-03-15 山东省地质测绘院 Crack contour extraction method in geological survey based on vision
CN117710399B (en) * 2024-02-06 2024-04-30 山东省地质测绘院 Crack contour extraction method in geological survey based on vision

Also Published As

Publication number Publication date
CN116342635B (en) 2023-08-08

Similar Documents

Publication Publication Date Title
CN116342635B (en) Crack contour extraction method in geological mapping
CN107730527A (en) A kind of highlands glade extracting method based on satellite-remote-sensing image
CN111797712B (en) Remote sensing image cloud and cloud shadow detection method based on multi-scale feature fusion network
CN109584240B (en) Landslide trailing edge crack displacement image identification method
CN107564017B (en) Method for detecting and segmenting urban high-resolution remote sensing image shadow
CN109978848B (en) Method for detecting hard exudation in fundus image based on multi-light-source color constancy model
CN103295191A (en) Multi-scale vision self-adaptation image enhancing method and evaluating method
CN110807738B (en) Blurred image non-blind restoration method based on edge image block sharpening
CN113436124B (en) Single image defogging method applied to ocean foggy environment
CN116630321B (en) Intelligent bridge health monitoring system based on artificial intelligence
CN112070717A (en) Power transmission line icing thickness detection method based on image processing
CN112529853A (en) Method and device for detecting damage of netting of underwater aquaculture net cage
CN110874825B (en) Method for extracting binary image of water trace on surface of composite insulator
CN116721121A (en) Plant phenotype color image feature extraction method
CN115660998A (en) Image defogging method based on deep learning and traditional priori knowledge fusion
CN108986079B (en) Crack extraction and optimization method for complex fracture network
CN115205713A (en) Method for recovering details of scenery color and texture in shadow area of remote sensing image of unmanned aerial vehicle
CN117152187B (en) Crack contour extraction method in geological mapping
CN112288726A (en) Method for detecting foreign matters on belt surface of underground belt conveyor
CN111091580B (en) Stumpage image segmentation method based on improved ResNet-UNet network
CN116596911A (en) Underwater planar structure sonar image crack quantification method
CN113379620B (en) Optical remote sensing satellite image cloud detection method
CN115661382A (en) Filtering method based on morphological template angle protection in three-dimensional landform reconstruction
CN109035217B (en) Quantitative evaluation method for soil body fracture based on image two-dimensional entropy
CN115719310A (en) Pretreatment method of fundus image data set and fundus image training model

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant