CN114495131A - Method and device for detecting form line of seismic acquisition data form - Google Patents
Method and device for detecting form line of seismic acquisition data form Download PDFInfo
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Abstract
The invention discloses a method and a device for detecting a table line of a seismic acquisition data table, which comprise the following steps: acquiring a tabular image A of drilling data; preprocessing the form image A to obtain a form image B; carrying out image projection operation on the table image B to obtain a projection value; dividing the projection value into a longitudinal scope and a transverse scope through a division scope; respectively acquiring a horizontal table line image C and a vertical table line image D from the longitudinal scope and the transverse scope through mathematical morphology operation; adding the horizontal table line image C and the vertical table line image D to obtain a table line image E; and processing the interference lines of the table line image E to obtain a table line image F. By adopting the table line detection method based on mathematical morphology, the structural elements can be selected dynamically in a self-adaptive manner, the false detection of the table lines is reduced, the detection result is more complete and accurate, and an important basis is provided for subsequent cell content identification.
Description
Technical Field
The invention belongs to the technical field of intelligent identification of earthquake acquisition data form images, and particularly relates to a form line detection method and device for an earthquake acquisition data form.
Background
In recent years, the geophysical exploration industry and the field seismic acquisition technology are rapidly developed, the application of the computer information technology in the field seismic acquisition process is more and more extensive, and drilling data acquired in field construction need to be manually input into a spreadsheet by an operator so that subsequent researchers can analyze and process the acquired data. However, with the continuous expansion of the earthquake acquisition scale and the continuous increase of the acquired data quantity, the defect of the manual data entry mode is increasingly shown, the efficiency of the manual data entry mode is low, the error rate is high, and the subsequent production efficiency is seriously influenced; in order to solve the problem that the management and the production application of the earthquake acquisition data are disjointed, the automatic identification and entry of the table image of the earthquake acquisition data are a very effective solution, and the detection of the table line is the key of the automatic identification and entry of the table image.
The form lines divide the whole form image into different areas, which is an important basis for image layout analysis and identification information structuring processing, so that the study on form line detection is very important.
At present, a run-length smoothing-based table line detection method and a mathematical morphology-based table line detection method are generally adopted for detecting table lines of a table image, the run-length smoothing-based table line detection algorithm is easily interfered by non-table area straight lines when extracting straight lines, so that excessive useless information is extracted, the mathematical morphology-based table line detection method has a good effect, the selection of structural elements in mathematical morphology plays a critical role in table line extraction and directly influences the quality of detection results, the structural elements of a general mathematical morphology method are determined by the width and height of a single character in a table, however, because the table contents are characters recorded manually, the problems of adhesion and the like exist, a large error exists in calculating the width and the height of a single character, such a rough selection is prone to false detection, resulting in inaccurate content extraction of subsequent cells.
Disclosure of Invention
In view of the above, the present invention provides a table line detection method for a seismic acquisition data table, which at least solves the technical problems in the prior art that, in the process of adopting a table line detection method based on mathematical morphology, a large error exists in calculating the width and height of a single character, and a rough selection easily causes a false detection of a table line, resulting in inaccurate extraction of subsequent cell contents.
In a first aspect, an embodiment of the present invention provides a method for detecting a table line of a seismic acquisition data table, including:
acquiring a tabular image A of drilling data;
preprocessing the form image A to obtain a form image B;
performing image projection operation on the form image B to obtain a projection value;
dividing the projection values into a longitudinal scope and a transverse scope through a division scope;
respectively acquiring a horizontal table line image C and a vertical table line image D from the longitudinal scope and the transverse scope through mathematical morphology operation;
adding the horizontal table line image C and the vertical table line image D to obtain a table line image E;
and processing the interference line of the table line image E to obtain a table line image F.
Optionally, preprocessing the form image a to obtain a form image B, including:
and carrying out graying and binarization processing on the form image A to obtain a first image, and carrying out denoising and inclination correction on the first image to obtain a form image B.
Optionally, performing an image projection operation on the table image B to obtain a projection value, including: and carrying out binarization processing on the table image B to obtain a second image, and calculating the transverse and longitudinal projection values of the second image.
Optionally, dividing the projection values into a longitudinal scope and a transverse scope by dividing the scope, including:
and the projection value obtains the length of each column of unit cells and the width of each row of unit cells, the length of each column of unit cells is divided into a plurality of longitudinal action domains, and the width of each row of unit cells is divided into a plurality of transverse action domains.
Optionally, the acquiring the horizontal table line image C and the vertical table line image D by mathematical morphology operation for the longitudinal scope and the lateral scope respectively includes:
performing mathematical morphology closed operation of self-adaptive selection of structural elements on the longitudinal scope to obtain the horizontal form line image C; performing mathematical morphology closed operation of self-adaptive selection of structural elements on the transverse scope to obtain the vertical form image D;
wherein, the calculation formula of the image C with the horizontal form line obtained by the longitudinal scope through the mathematical morphology closed operation of the self-adaptive selection structural element is as follows:
X_i＝αh_i
wherein, X _ i is the value of the structural element of each row, alpha is 0.8-0.9, and h _ i is the length of the unit cell of the ith column.
Optionally, processing the interference line of the form line image E to obtain a form line image F includes:
filling a part of black areas in the form line image E, removing white areas, detecting horizontal lines and vertical lines in the form line image E based on a mathematical morphology operation method to obtain interference lines, and removing the interference lines to obtain a form line image F.
Optionally, denoising and tilt correcting the first image to obtain a form image B includes:
applying a median filtering algorithm to the first image, and saving the edge information of the table line while denoising;
extracting image edge information of the denoised first image by adopting a Canny edge detection method;
acquiring a contour area of the form frame by using a contour detection method;
and acquiring the angle between the rectangle and the horizontal line of the form frame, and rotating the form frame according to the angle to acquire a form image B.
Optionally, the partitioning the vertical scope comprises:
sorting the projection values of each column according to the longitudinal projection values to obtain N longitudinal table lines;
according to the projection value of each longitudinal table line, finding out the points of the projection value in a certain threshold value range in a certain neighborhood position range, wherein the adjacent points form the width of each longitudinal table line;
calculating the length of each column of cells according to the position of the table line and the width of the table line;
dividing the longitudinal scope according to the length of each row of cells;
the calculation formula for calculating the length of each row of cells is as follows:
TW_i＝d_i-d_(i-1)-W_i
where TW _ i is the cell length of the ith column, d _ i is the last pixel point position of the list gridline, d _ (i-1) is the last pixel point of the previous list gridline, and W _ i is the width of the current list gridline.
Optionally, the removing of the interference line includes:
calculating the number of black connected domain pixel points in the table line image E, and if the number is smaller than a set threshold value, carrying out white filling; calculating the number of white connected domain pixels, and if the number is smaller than a set threshold value, rejecting the white connected domain pixels;
carrying out corrosion operation on the table line image E to obtain a table line image F;
wherein, the formula of the corrosion calculation for removing the horizontal interference line is as follows:
wherein the content of the first and second substances,
representing corrosion operations, K being a composite structureElement, K ═ K1, K2]Let k1 be 1 x 3 and the data elements all be the structuring elements of 1, and k2 be the table vertical structuring elements of the corresponding lateral scope.
In a second aspect, an embodiment of the present invention further provides a table line detection apparatus for a seismic acquisition data table, including:
the image module is used for acquiring a table image A of the drilling data;
the processing module is used for preprocessing the form image A to obtain a form image B;
the image projection module is used for carrying out image projection operation on the table image B to obtain a projection value;
a scope division module which divides the projection values into a longitudinal scope and a transverse scope;
the operation module is used for respectively acquiring a horizontal table line image C and a vertical table line image D from the longitudinal scope and the transverse scope through mathematical morphology operation;
the repairing module is used for adding the horizontal table line image C and the vertical table line image D to obtain a table line image E;
and the interference line processing module is used for processing the interference lines of the table line image E to obtain a table line image F.
The invention has the beneficial effects that:
according to the invention, the table image is divided into a plurality of action domains, and the structural elements can be adaptively and dynamically selected in the process of adopting the table line detection method based on mathematical morphology operation, so that the false detection of the table lines is reduced, the detection result is more complete and accurate, and an important basis is provided for the subsequent cell content identification.
Additional features and advantages of the invention will be set forth in the detailed description which follows.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing in more detail exemplary embodiments thereof with reference to the attached drawings, in which like reference numerals generally represent like parts throughout.
FIG. 1 is a flow chart of a method for detecting a form line of a seismic acquisition data form according to a first embodiment of the invention;
FIG. 2 is a diagram of an input picture according to a first embodiment of the present invention;
FIG. 3 is a schematic cross-line drawing of a table obtained by the prior art in accordance with the present invention;
FIG. 4 is a schematic cross-line representation of a table obtained using the present invention;
FIG. 5 is a table line diagram of a test according to an embodiment of the present invention.
Detailed Description
Preferred embodiments of the present invention will be described in more detail below. While the following describes preferred embodiments of the present invention, it should be understood that the present invention may be embodied in various forms and should not be limited by the embodiments set forth herein.
In a first aspect, an embodiment of the present invention provides a method for detecting a table line of a seismic acquisition data table, including:
acquiring a tabular image A of drilling data;
preprocessing the form image A to obtain a form image B;
specifically, graying and binarization processing are performed on the form image A to obtain a first image, and denoising and inclination correction are performed on the first image to obtain a form image B.
Specifically, denoising and tilt correcting the first image to obtain a form image B includes:
applying a median filtering algorithm to the first image, and saving the edge information of the table line while denoising;
extracting image edge information of the denoised first image by adopting a Canny edge detection method;
acquiring a contour area of the form frame by using a contour detection method;
and acquiring the angle between the rectangle and the horizontal line of the form frame, and rotating the form frame according to the angle to acquire a form image B.
Performing image projection operation on the form image B to obtain a projection value;
specifically, the form image B is subjected to binarization processing to obtain a second image, and the horizontal and vertical projection values of the second image are calculated.
Dividing the projection values into a longitudinal scope and a transverse scope through a division scope;
specifically, the projection value obtains the length of each column of unit cells and the width of each row of unit cells, the length of each column of unit cells is divided into a plurality of longitudinal scope of action, and the width of each row of unit cells is divided into a plurality of transverse scope of action.
Specifically, the dividing the vertical scope includes:
sorting the projection values of each column according to the longitudinal projection values to obtain N longitudinal table lines;
according to the projection value of each longitudinal table line, finding out the points of the projection value in a certain threshold value range in a certain neighborhood position range, wherein the adjacent points form the width of each longitudinal table line;
calculating the length of each column of cells according to the position of the table line and the width of the table line;
dividing the longitudinal scope according to the length of each row of cells;
the calculation formula for calculating the length of each row of cells is as follows:
TW_i＝d_i-d_(i-1)-W_i
where TW _ i is the cell length of the ith column, d _ i is the last pixel point position of the list gridline, d _ (i-1) is the last pixel point of the previous list gridline, and W _ i is the width of the current list gridline. Calculating the table width per row is also such a method, but the conversion from column calculations to row calculations is not repeated here.
Respectively acquiring a horizontal table line image C and a vertical table line image D for the longitudinal scope and the transverse scope through mathematical morphology operation;
specifically, performing mathematical morphology closed operation of adaptively selecting structural elements on the longitudinal scope to obtain the horizontal form line image C; performing mathematical morphology closed operation of self-adaptive selection of structural elements on the transverse scope to obtain the vertical form image D;
wherein, the calculation formula of the image C with the horizontal form line obtained by the longitudinal scope through the mathematical morphology closed operation of the self-adaptive selection structural element is as follows:
X_i＝αh_i
wherein, X _ i is the value of the structural element of each row, alpha is 0.8-0.9, and h _ i is the length of the unit cell of the ith column.
The calculation method of the horizontal scope is the same as that of the vertical scope, and is not described herein again.
Adding the horizontal table line image C and the vertical table line image D to obtain a table line image E;
and processing the interference line of the table line image E to obtain a table line image F.
Specifically, a part of black areas in the form line image E are filled, white areas are removed, horizontal lines and vertical lines in the form line image E are detected based on a mathematical morphology operation method, interference lines are obtained, the interference lines are removed, and a form line image F is obtained.
Specifically, the removing of the interference line includes:
calculating the number of black connected domain pixel points in the table line image E, and if the number is smaller than a set threshold value, carrying out white filling; and (4) calculating the number of the white connected domain pixel points, and rejecting the white connected domain pixel points if the number of the white connected domain pixel points is less than a set threshold value, wherein the threshold value is set according to actual needs.
Carrying out corrosion operation on the table line image E to obtain a table line image F;
wherein the etching operation comprises:
performing corrosion calculation on the table line image E to obtain a table line image F;
wherein, the formula of the corrosion calculation for removing the horizontal interference line is as follows:
wherein the content of the first and second substances,
represents corrosion operation, K is a complex structural element, K ═ K1, K2]Let k1 be 1 x 3 and the data elements all be the structuring elements of 1, and k2 be the table vertical structuring elements of the corresponding lateral scope.
The process of removing the vertical interference lines is similar to the above, except that K1 is 3 × 1 in K, and the data elements all have values of 1, and K2 is the table horizontal structure element corresponding to the vertical scope.
According to the invention, the projection value is divided into the longitudinal scope and the transverse scope by dividing the scope, the influence of structural elements is fully considered, the extracted table line is more accurate and complete, the accuracy after table reconstruction is improved, and the method has important significance for subsequent cell extraction and cell content identification.
Furthermore, the form line detection of the seismic acquisition data form is carried out by a morphology-based method, so that structural elements can be selected in a self-adaptive manner, the influence of the form type is avoided, and the universality is good.
In a second aspect, an embodiment of the present invention further provides a table line detection apparatus for a seismic acquisition data table, including:
the image module is used for acquiring a table image A of the drilling data;
the processing module is used for preprocessing the form image A to obtain a form image B;
the image projection module is used for carrying out image projection operation on the table image B to obtain a projection value;
a scope division module which divides the projection values into a longitudinal scope and a transverse scope;
the operation module is used for respectively acquiring a horizontal table line image C and a vertical table line image D from the longitudinal scope and the transverse scope through mathematical morphology operation;
the repairing module is used for adding the horizontal table line image C and the vertical table line image D to obtain a table line image E;
and the interference line processing module is used for processing the interference lines of the table line image E to obtain a table line image F.
The first embodiment is as follows:
referring to fig. 1, a drilling data table image of the Shanghe area is selected for specific description, and a table line detection method for a seismic acquisition data table comprises the following steps:
s1, obtaining a tabular image A of the well drilling data
The form image a is obtained by shooting or scanning the field drilling form data by a mobile phone, as shown in fig. 2, and is input into the server.
S2, preprocessing the form image A to obtain a form image B
Carrying out image graying and binarization processing on the obtained form image A to obtain a first image, and then carrying out denoising and inclination correction on the first image to obtain a form image B;
s3, projection calculation is carried out on the form image B
Carrying out binarization processing on the corrected form image B to obtain a second image, and calculating the transverse and longitudinal projection values of the second image;
s4, dividing scope
The length of each column of unit cells and the width of each row of unit cells are obtained according to the projection value, a plurality of longitudinal action areas are divided according to the length of each column of unit cells, the width of each action area is 15% of the length of the unit cell which extends forwards and backwards from the current unit cell, the transverse action area is similar to the operation, the division is based on the fact that the width of each row of unit cells is changed, the method is easy to achieve for a person skilled in the art, and the method is not repeated herein.
S5 mathematical morphology operation
When mathematical morphology closed operation of self-adaptive selection structural elements is carried out on each longitudinal scope, the selection of the structural elements is determined by the length of the cells of the current column, and the horizontal form line image C is obtained after the closed operation; and when the mathematical morphology closed operation of self-adaptive selection of structural elements is carried out on each transverse scope, the selection of the structural elements is determined by the cell width of the current line, and a vertical form image D is obtained after the closed operation.
S6 form broken line repairing
And adding the horizontal table line image C and the vertical table line image D for reconstruction to obtain a table line image E, calculating the average width of the table lines, determining structural elements according to the average width of the table lines, and performing closing operation on the table line image E.
S7, removal of interference line
Referring to fig. 3-5, the small-area black regions in the table line image E are filled, the white regions are removed, the horizontal lines and the vertical lines are further detected by a mathematical morphology method of adaptively selecting structural elements, and the detected interference lines are removed, as can be seen from fig. 3 and 4, the table horizontal lines extracted by the technical scheme are more accurate and complete, and the accuracy after table reconstruction is greatly improved.
In this embodiment, the specific steps for denoising and image tilt correction in step S2 are as follows:
s21, a median filtering algorithm is adopted for the first binarized image, and the edge information of the table line is saved while the noise point is removed;
s22, extracting the image edge of the denoised first image by adopting a Canny-based edge detection method;
s23, obtaining all outlines in the first image by adopting an outline-based detection method, wherein the outlines comprise all character outlines, cell outlines and form frame outlines, and obtaining outline areas of the form frame through outline attributes;
and S24, acquiring the angle between the rectangle and the horizontal line of the form frame, and rotating the form frame according to the angle to acquire a form image B.
In this embodiment, for the scope division in S4, the specific steps are as follows:
s41, sorting the projection values of each column according to the projection values obtained by the longitudinal projection calculation result of the second image in the step S3, finding out the first N nonadjacent points, and obtaining N longitudinal table lines when the difference of the values of the N points is within a certain threshold range;
s42, finding out points with projection values within a certain threshold value range in a certain neighborhood position range according to the projection values of each longitudinal table line, wherein the adjacent points form the width of each table line;
s43, calculating the length of each column of cells according to the position of the table line and the width of the table line, wherein the calculation formula is as follows:
TW_i＝d_i-d_(i-1)-W_i
where TW _ i is the cell length of the ith column, d _ i is the last pixel point position of the list gridline, d _ (i-1) is the last pixel point of the previous list gridline, and W _ i is the width of the current list gridline. Calculating the width of each row of tables is also the method, and only the calculation is converted from column calculation to row calculation, and the detailed description is omitted;
and S44, dividing the longitudinal scope of the form image according to the length of each column of cells, and dividing the image into N-1 longitudinal scopes, wherein the width of each scope is that the current cell extends forwards and backwards by 15% of the length of the cell.
In this embodiment, for the mathematical morphology operation in S5, the specific steps are as follows:
and S51, selecting the length of the current column cell multiplied by a factor n as the size of a structural element for each longitudinal scope, wherein the calculation formula is as follows, and after all longitudinal scopes are operated, obtaining the transverse lines of all longitudinal scope tables.
X_i＝αh_i
Wherein, X _ i is the value of the structural element of each row, alpha is 0.8-0.9, and h _ i is the length of the unit cell of the ith column.
In this embodiment, for repairing the table disconnection in S6, the specific steps are as follows:
s61, calculating the average width of all the table lines;
and S62, setting the structural elements to be N × N to perform closed operation on the table image, wherein the closed operation has better connection and defect filling functions.
In this embodiment, for the interference line removal in S7, the specific steps are as follows:
s71, calculating the number of black connected domain pixels in the image, if the number of the black connected domain pixels is smaller than a set threshold, carrying out white filling, calculating the number of the white connected domain pixels, if the number of the white connected domain pixels is smaller than the set threshold, removing certain noise influence in the calculation process, and further repairing holes in the surface lines.
Wherein, the formula of the corrosion calculation for removing the horizontal interference line is as follows:
wherein the content of the first and second substances,
represents corrosion operation, K is a complex structural element, K ═ K1, K2]Let k1 be 1 x 3 and the data elements all be the structuring elements of 1, and k2 be the table vertical structuring elements of the corresponding lateral scope.
The process of removing the vertical interference lines is similar to the above, except that K1 is 3 × 1 in K, and the data elements all have values of 1, and K2 is the table horizontal structure element corresponding to the vertical scope.
The invention provides a form line detection method for a seismic acquisition data form, which divides a form image into a plurality of action domains, can adaptively and dynamically select structural elements in the process of adopting a form line detection method based on mathematical morphology, reduces false detection of form lines, enables the detection result to be more complete and accurate, and provides an important basis for subsequent cell content identification.
Example two:
a form line detection apparatus for seismic acquisition data forms, comprising the steps of:
the image module is used for acquiring a table image A of the drilling data;
the processing module is used for preprocessing the form image A to obtain a form image B;
the image projection module is used for carrying out image projection operation on the table image B to obtain a projection value;
a scope division module which divides the projection values into a longitudinal scope and a transverse scope;
the operation module is used for respectively acquiring a horizontal table line image C and a vertical table line image D from the longitudinal scope and the transverse scope through mathematical morphology operation;
the repairing module is used for adding the horizontal table line image C and the vertical table line image D to obtain a table line image E;
and the interference line processing module is used for processing the interference lines of the table line image E to obtain a table line image F.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.
Claims (10)
1. A method for form line detection for a seismic acquisition data form, comprising:
acquiring a tabular image A of drilling data;
preprocessing the form image A to obtain a form image B;
performing image projection operation on the form image B to obtain a projection value;
dividing the projection values into a longitudinal scope and a transverse scope through a division scope;
respectively acquiring a horizontal table line image C and a vertical table line image D from the longitudinal scope and the transverse scope through mathematical morphology operation;
adding the horizontal table line image C and the vertical table line image D to obtain a table line image E;
and processing the interference line of the table line image E to obtain a table line image F.
2. A method as claimed in claim 1, wherein preprocessing said form image a to obtain a form image B comprises:
and carrying out graying and binarization processing on the form image A to obtain a first image, and carrying out denoising and inclination correction on the first image to obtain a form image B.
3. A method as claimed in claim 1, wherein performing an image projection operation on the table image B to obtain a projection value comprises: and carrying out binarization processing on the form image B to obtain a second image, and calculating the transverse and longitudinal projection values of the second image.
4. The method of claim 3, wherein partitioning the projection values into longitudinal and lateral scopes by partitioning the scope comprises:
and the projection value obtains the length of each column of unit cells and the width of each row of unit cells, the length of each column of unit cells is divided into a plurality of longitudinal action domains, and the width of each row of unit cells is divided into a plurality of transverse action domains.
5. The method of claim 1, wherein the obtaining of the horizontal and vertical table line images C and D by mathematical morphology operations for the longitudinal and lateral scopes respectively comprises:
performing mathematical morphology closed operation of self-adaptive selection of structural elements on the longitudinal scope to obtain the horizontal form line image C; performing mathematical morphology closed operation of self-adaptive selection of structural elements on the transverse scope to obtain the vertical form image D;
wherein, the calculation formula of the image C with the horizontal form line obtained by the longitudinal scope through the mathematical morphology closed operation of the self-adaptive selection structural element is as follows:
X_i＝αh_i
wherein, X _ i is the value of the structural element of each row, alpha is 0.8-0.9, and h _ i is the length of the unit cell of the ith column.
6. The method as claimed in claim 1, wherein the step of processing the interference lines of the form line image E to obtain a form line image F comprises:
filling a part of black areas in the form line image E, removing white areas, detecting horizontal lines and vertical lines in the form line image E based on a mathematical morphology operation method to obtain interference lines, and removing the interference lines to obtain a form line image F.
7. The method as claimed in claim 2, wherein de-noising and tilt correcting the first image to obtain a form image B comprises:
applying a median filtering algorithm to the first image, and saving the edge information of the table line while denoising;
extracting image edge information of the denoised first image by adopting a Canny edge detection method;
acquiring a contour area of the form frame by using a contour detection method;
and acquiring the angle between the rectangle and the horizontal line of the form frame, and rotating the form frame according to the angle to acquire a form image B.
8. The method of claim 4, wherein the partitioning the vertical scope comprises:
sorting the projection values of each column according to the longitudinal projection values to obtain N longitudinal table lines;
according to the projection value of each longitudinal table line, finding out the points of the projection value in a certain threshold value range in a certain neighborhood position range, wherein the adjacent points form the width of each longitudinal table line;
calculating the length of each column of cells according to the position of the table line and the width of the table line;
dividing the longitudinal scope according to the length of each column of cells;
the calculation formula for calculating the length of each row of cells is as follows:
TW_i＝d_i-d_(i-1)-W_i
where TW _ i is the cell length of the ith column, d _ i is the last pixel point position of the list gridline, d _ (i-1) is the last pixel point of the previous list gridline, and W _ i is the width of the current list gridline.
9. A method of detecting form lines in a seismic acquisition data form according to claim 6, wherein said removing of said disturbance lines comprises:
calculating the number of black connected domain pixel points in the table line image E, and if the number is smaller than a set threshold value, carrying out white filling; calculating the number of white connected domain pixels, and if the number is smaller than a set threshold value, rejecting the white connected domain pixels;
carrying out corrosion operation on the table line image E to obtain a table line image F;
wherein the etching operation comprises:
performing corrosion calculation on the table line image E to obtain a table line image F;
wherein, the formula of the corrosion calculation for removing the horizontal interference line is as follows:
wherein the content of the first and second substances,
represents corrosion operation, K is a complex structural element, K ═ K1, K2]Let k1 be 1 x 3 and the data elements all be the structuring elements of 1, and k2 be the table vertical structuring elements of the corresponding lateral scope.
10. A form line detection apparatus for seismic acquisition data forms, comprising:
the image module is used for acquiring a table image A of the drilling data;
the processing module is used for preprocessing the form image A to obtain a form image B;
the image projection module is used for carrying out image projection operation on the form image B to obtain a projection value;
a scope division module which divides the projection values into a longitudinal scope and a transverse scope;
the operation module is used for respectively acquiring a horizontal table line image C and a vertical table line image D from the longitudinal scope and the transverse scope through mathematical morphology operation;
the repairing module is used for adding the horizontal table line image C and the vertical table line image D to obtain a table line image E;
and the interference line processing module is used for processing the interference lines of the table line image E to obtain a table line image F.
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