CN108416839B - Three-dimensional reconstruction method and system for contour line of multiple X-ray rotating images - Google Patents
Three-dimensional reconstruction method and system for contour line of multiple X-ray rotating images Download PDFInfo
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Abstract
The embodiment of the application discloses a three-dimensional reconstruction method and a three-dimensional reconstruction system for contour lines of a plurality of X-ray rotating images, wherein a first two-dimensional matrix corresponding to the contour line of a target image is determined according to the contour line of the target image; sequentially storing contour points in the first two-dimensional matrix by using an orthogonal-priority 8-neighborhood traversal tracking method to obtain a second two-dimensional matrix; acquiring contour point coordinate sets of the target image contour lines at different angles according to the target image contour lines at different angles and the second two-dimensional matrixes corresponding to the target image contour lines at different angles; matching corresponding points in the contour point coordinate set to obtain corresponding point coordinates of the rotating image of the target image; and (4) reversely solving the coordinates of the corresponding points of the rotating image by using the coordinate transformation matrix of the rotating image points to obtain the three-dimensional coordinates of the contour points corresponding to the contour lines of the target image. By means of an orthogonal-priority 8-neighborhood traversal tracking method and a pixel point equipartition interpolation method, coordinate information of contour points is more comprehensive, and misdiagnosis is reduced.
Description
Technical Field
The application relates to the technical field of digital image recognition, in particular to a three-dimensional reconstruction method and a three-dimensional reconstruction system for contour lines of a plurality of X-ray rotating images.
Background
The X-ray detection technology of the power equipment is successfully applied to nondestructive detection of numerous power transformation equipment, such as GIS, a dry-type transformer, a voltage current transformer, a closing resistor, a breaker, an isolating switch, a load switch and the like.
The existing X-ray detection technology for the power equipment comprises the steps of firstly, carrying out digital image processing on an X-ray image, and segmenting a background and the power equipment in the image; and then, obtaining a contour curve of the power equipment under a two-dimensional plane coordinate by using an edge detection technology, and finally, analyzing and diagnosing the fault of the equipment by a professional technician through observing the contour line of the equipment.
However, in practical engineering, most of the workpieces to be detected have the characteristics of irregular external structures, complex and diversified internal structures and uneven workpiece thicknesses, so that the two-dimensional profile curve of the power equipment obtained directly through image processing contains too little information. Technicians only rely on experience to directly analyze and judge the detection workpiece by observing the two-dimensional outline of the image, so that misdiagnosis is easy to occur, and the detection efficiency is low. In order to solve the problem, a three-dimensional reconstruction method and a three-dimensional reconstruction system for contour lines of a plurality of X-ray rotation images are provided.
Disclosure of Invention
The application provides a three-dimensional reconstruction method and a three-dimensional reconstruction system for contour lines of a plurality of X-ray rotating images, which are used for solving the problem of low detection efficiency in the prior art.
In order to solve the above problems, the present application provides the following technical solutions:
the application provides a three-dimensional reconstruction method for contour lines of a plurality of X-ray rotation images, which comprises the following steps:
determining a first two-dimensional matrix corresponding to the contour line of the target image according to the obtained contour line of the target image;
sequentially storing contour points in the first two-dimensional matrix by using an orthogonal-priority 8-neighborhood traversal tracking method to obtain a second two-dimensional matrix;
acquiring contour point coordinate sets of the target image contour lines at different angles according to the target image contour lines at different angles and the second two-dimensional matrixes corresponding to the target image contour lines at different angles;
matching corresponding points in the contour point coordinate set to obtain corresponding point coordinates of the rotating image of the target image;
and (4) reversely solving the coordinates of the corresponding points of the rotating image by using the coordinate transformation matrix of the rotating image points to obtain the three-dimensional coordinates of the contour points corresponding to the contour lines of the target image.
Optionally, sequentially storing the contour points in the first two-dimensional matrix by using an orthogonal-first 8-neighborhood traversal tracking method to obtain a second two-dimensional matrix, including:
determining a first two-dimensional matrix starting point O;
according to a first two-dimensional matrix
Sequentially searching contour points around the starting point O in the medium numbering sequence;
and sequentially storing the obtained contour points of the contour lines with different angles to obtain a second two-dimensional matrix.
Optionally, obtaining a contour point coordinate set of the target image contour lines at different angles according to the target image contour lines at different angles and the second two-dimensional matrices corresponding to the target image contour lines at different angles includes:
acquiring a starting point and an end point of a target image contour line at different angles according to the second two-dimensional matrix;
and acquiring contour point coordinate sets of the target image contour lines at different angles according to the acquired starting points and the end points of the target image contour lines at different angles.
Optionally, matching corresponding points in the contour point coordinate set to obtain corresponding point coordinates of the rotated image of the target image, including:
counting the number of longitudinal pixel points of the contour point coordinate set to obtain the number of the longitudinal pixel points of the image, and finding out a maximum value;
counting the number of longitudinal transverse pixels on each layer of the corresponding contour line in the contour point coordinate set according to the trend of the contour line of the target image in sequence to obtain a third two-dimensional matrix;
acquiring the maximum value of each row of the third two-dimensional matrix;
and equally dividing and matching the abscissa of the target image contour line at different angles under the same ordinate according to the maximum value to obtain a fourth two-dimensional matrix.
Optionally, the third two-dimensional matrix is a matrix for recording the number of pixel points of the same contour line of different images under the same vertical coordinate; and the fourth two-dimensional matrix is a matrix which records different images and matches corresponding points of the same contour line.
A three-dimensional reconstruction method and a system for contour lines of a plurality of X-ray rotation images comprise the following steps:
the first acquisition module is used for determining a first two-dimensional matrix corresponding to the contour line of the target image according to the acquired contour line of the target image;
the second acquisition module is used for sequentially storing the contour points in the first two-dimensional matrix acquired by the first acquisition module by using an orthogonal-priority 8-neighborhood traversal tracking method to acquire a second two-dimensional matrix;
the third acquisition module is used for acquiring contour point coordinate sets of the target image contour lines at different angles according to the target image contour lines at different angles and the second two-dimensional matrix acquired by the second acquisition module corresponding to the target image contour lines at different angles;
the matching module is used for matching corresponding points in the contour point coordinate set acquired by the third acquisition module to acquire the coordinates of corresponding points of the rotating image of the target image;
and the solving module is used for reversely solving the coordinates of the corresponding points of the rotating image acquired by the matching module by using the coordinate transformation matrix of the rotating image points to acquire the three-dimensional coordinates of the contour points corresponding to the contour lines of the target image.
Optionally, the second obtaining module includes:
the first determining unit is used for determining a starting point of the first two-dimensional matrix acquired by the first acquiring module;
the searching unit is used for searching contour points around the first determining unit according to the serial number sequence in the first two-dimensional matrix acquired by the first acquiring module;
and the first acquisition unit is used for sequentially storing the acquired searching units of the contour lines of different angles to acquire a second two-dimensional matrix.
Optionally, the third obtaining module includes:
the second determining unit is used for acquiring the starting point and the end point of the target image contour line at different angles according to the first acquiring unit;
and the second acquisition unit is used for acquiring the contour point coordinate set of the target image contour line with different angles according to the second determination unit.
Optionally, the matching module comprises:
the third determining unit is used for counting the number of the longitudinal pixel points of the second acquiring unit, acquiring the number of the longitudinal pixel points of the image and finding out a maximum value;
the third obtaining unit is used for sequentially counting the number of longitudinal transverse pixels on each layer of the target image contour line corresponding to the third determining unit according to the trend of the target image contour line to obtain a third two-dimensional matrix;
a fourth acquiring unit configured to acquire a maximum value of each line of the third acquiring unit;
and the matching unit is used for performing equipartition matching on the abscissa of the target image contour line at different angles under the same ordinate according to the maximum value of the fourth acquisition unit to obtain a fourth two-dimensional matrix.
According to the technical scheme, the application provides a three-dimensional reconstruction method and a three-dimensional reconstruction system for contour lines of a plurality of X-ray rotation images, and the method comprises the following specific steps: firstly, determining a first two-dimensional matrix corresponding to a target image contour line according to the obtained target image contour line; secondly, sequentially storing contour points in the first two-dimensional matrix by using an orthogonal-priority 8-neighborhood traversal tracking method to obtain a second two-dimensional matrix; thirdly, acquiring contour point coordinate sets of contour lines of the target image at different angles according to the contour curves of the target image at different angles and a second two-dimensional matrix corresponding to the contour curves of the target image at different angles; then, matching corresponding points in the contour point coordinate sets of the contour curves with different angles to obtain corresponding point coordinates of the rotating image of the target image; and finally, reversely solving the coordinates of the corresponding points by using the coordinate transformation matrix of the rotating image points to obtain the three-dimensional coordinates of the contour points corresponding to the contour lines of the target image. After the edge detection is carried out on the X-ray image, the contour points are stored by using an orthogonal-priority 8-neighborhood traversal tracking improvement algorithm, so that the sequential storage of the target contour lines is realized; and matching corresponding points of the contours of the multiple images by using a pixel point equipartition interpolation method to obtain a contour line matching matrix, and finally calculating by rotating the image coordinate change matrix to obtain the three-dimensional expression of the contour line. According to the method, through an orthogonal-priority 8-neighborhood traversal tracking improvement algorithm and a pixel point equipartition interpolation method, the contour line of the image is converted from two-dimensional coordinate representation to three-dimensional coordinate representation, so that the coordinate information of the contour point of the image is more comprehensive, the contour line is clearer, the occurrence of misdiagnosis is reduced, and the detection efficiency is improved.
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In order to more clearly explain the technical solution of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without any creative effort.
Fig. 1 is a schematic flowchart of a three-dimensional reconstruction method for a contour line of a plurality of X-ray rotational images according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart of a process for acquiring a second two-dimensional matrix according to an embodiment of the present disclosure;
fig. 3 is a schematic flowchart of a process for obtaining a contour point coordinate set of a target image contour line at different angles according to an embodiment of the present application;
fig. 4 is a schematic flow chart of corresponding point matching according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a system for three-dimensional reconstruction of a contour line of a multiple X-ray rotational image according to an embodiment of the present application.
Detailed Description
Fig. 1 is a schematic flow chart of a method for three-dimensional reconstruction of a contour line of a plurality of X-ray rotational images according to an embodiment of the present disclosure. Because the existing target image can be identified by a person after being directly processed, but the computer cannot identify the target image, the phenomenon of misdiagnosis is easy to occur when the person directly identifies equipment through the target image. In order to reduce the problem of low detection efficiency caused by the misdiagnosis phenomenon, the target image needs to be preprocessed, and then the three-dimensional coordinates of the contour line of the processed target image need to be stored. The method for preprocessing the target image and storing the three-dimensional coordinates of the contour line of the target image is a three-dimensional reconstruction method of the contour line of a plurality of X-ray rotating images. The method comprises the following steps:
s101: and determining a first two-dimensional matrix corresponding to the contour line of the target image according to the obtained contour line of the target image.
Firstly, carrying out binarization and image morphology processing on a target image; secondly, checking the image contour by using a Canny operator to obtain a contour line of the target image; and finally, storing the contour line of the target image in a two-dimensional sparse matrix. The two-dimensional sparse matrix is a first two-dimensional matrix, the row number and the column number of the matrix respectively represent the length and the width of a target image, the value of an edge point is 1 or 255, and the value of a non-edge point is 0.
S102: and sequentially storing the contour points in the first two-dimensional matrix by using an orthogonal-priority 8-neighborhood traversal tracking method to obtain a second two-dimensional matrix. Referring to fig. 2, a schematic flowchart for acquiring a second two-dimensional matrix according to an embodiment of the present disclosure is shown.
The specific process of obtaining the second two-dimensional matrix is as follows:
s1021: a first two-dimensional matrix starting point O is determined.
S1022: according to a first two-dimensional matrix
The middle number sequence sequentially searches contour points around the starting point O.
Firstly, sequentially judging whether contour points exist in four points of 1, 2, 3 and 4 in 8 adjacent domains around the point O, if so, saving the position coordinates of the contour points in the graph, setting the contour points as new starting points O, and restarting to search for new contour points by taking the point O as a starting point. If no contour point exists in the positions 1, 2, 3 and 4, sequentially judging whether contour points exist in four points 5, 6, 7 and 8 in the 8 neighborhood, if so, saving the position coordinates of the contour points in the graph, setting the contour points as new starting points, and restarting to search for new contour points by taking the contour points as the starting points. If no contour point exists in the neighborhood of 8 around the O point, the search is ended and a new search is started.
S1023: and sequentially storing the obtained contour points of the contour lines with different angles to obtain a second two-dimensional matrix.
And sequentially searching contour lines of different angles of the same target image for corresponding contour points, and storing the corresponding contour points according to the sequence to obtain a second two-dimensional matrix in which the coordinates of the contour points are stored.
When the traditional 8-neighborhood contour tracing method is used for contour searching of the curve, some points on the contour line can be missed, when the curve is required to turn around again and then search for the missing points after the clockwise searching is finished, the stored points are connected in sequence, and the contour line cannot be obtained. This lengthens the search process, increases the workload, and reduces the work efficiency. The orthogonal priority 8-neighborhood contour tracing method can strictly search and store the coordinates of contour points according to the trend of contour lines, the omission phenomenon can not occur, the stored points are sequentially connected, the complete contour lines can be obtained, and the working efficiency is effectively improved.
S103: and acquiring contour point coordinate sets of the target image contour lines at different angles according to the target image contour lines at different angles and the second two-dimensional matrixes corresponding to the target image contour lines at different angles. Referring to fig. 3, a schematic flow chart of acquiring a contour point coordinate set of a target image contour line at different angles according to an embodiment of the present application is provided.
The specific process of obtaining the contour point coordinate set of the target image contour line at different angles is as follows:
s1031: and acquiring the starting point and the end point of the target image contour line at different angles according to the second two-dimensional matrix.
Firstly, selecting a target image contour line on a picture, and marking the starting point and the end point of the contour line; secondly, selecting points between the starting point and the end point to obtain a point coordinate set of the contour line of the target image; and finally, selecting a starting point and an end point which represent the contour line of the same target image on the target images at different angles.
S1032: and acquiring contour point coordinate sets of the target image contour lines at different angles according to the acquired starting points and the end points of the target image contour lines at different angles.
And finding the coordinates of the starting point and the end point of the obtained target image contour line with different angles in a second two-dimensional matrix, selecting points between the starting point and the end point, and forming the selected points into a set to obtain a point coordinate set of the selected contour line.
S104: and matching corresponding points in the contour point coordinate set to obtain corresponding point coordinates of the rotating image of the target image. Referring to fig. 4, a schematic flow chart of corresponding point matching provided in the embodiment of the present application is shown.
The concrete process of corresponding point matching:
s1041: and counting the number of longitudinal pixel points of the contour point coordinate set to obtain the number of the longitudinal pixel points of the image, and finding out a maximum value.
S1042: and counting the number of longitudinal transverse pixels on each layer of the corresponding contour line in the contour point coordinate set according to the trend of the contour line of the target image in sequence to obtain a third two-dimensional matrix.
And the third two-dimensional matrix records the number of pixel points of the same contour line of different images under the same coordinate.
S1043: the maximum value of each row of the third two-dimensional matrix is obtained.
S1044: and equally dividing and matching the abscissa of the target image contour line at different angles under the same ordinate according to the maximum value to obtain a fourth two-dimensional matrix.
And the fourth two-dimensional matrix records a matrix after corresponding points of the same contour line of different images are matched.
The existing corresponding point matching method can accurately match limited points in a plurality of rotating images, and cannot accurately match corresponding line segments in the plurality of rotating images, so that a three-dimensional model constructed by the result has deviation. In order to reduce the occurrence of the deviation, the method uses a pixel uniform interpolation contour point matching method to match corresponding points of the same target image contour line at different angles. The probability of deviation of the three-dimensional model constructed by the result is reduced, the recognition degree of the image is further improved, and the working efficiency is further improved.
S105: and (4) reversely solving the coordinates of the corresponding points of the rotating image by using the coordinate transformation matrix of the rotating image points to obtain the three-dimensional coordinates of the contour points corresponding to the contour lines of the target image.
And (3) capturing the contour line of a section of target image on different images, obtaining a contour line matching matrix by storing the coordinates of the contour line and matching the corresponding points of the contour line, and calculating the three-dimensional expression of the contour line by rotating the image coordinate change matrix. And the correctness of the two-dimensional coordinate storage of the contour line and the matching of the corresponding points is verified, the occurrence of misdiagnosis is reduced, and the working efficiency is improved.
As can be seen from the foregoing embodiments, the present application provides a method for three-dimensional reconstruction of a contour line of a multiple X-ray rotational image. The method comprises the following specific steps: firstly, determining a first two-dimensional matrix corresponding to a target image contour line according to the obtained target image contour line; secondly, sequentially storing contour points in the first two-dimensional matrix by using an orthogonal-priority 8-neighborhood traversal tracking method to obtain a second two-dimensional matrix; thirdly, acquiring contour point coordinate sets of the target image contour lines at different angles according to the target image contour lines at different angles and the second two-dimensional matrix corresponding to the target image contour lines at different angles; then, matching corresponding points in the contour point coordinate set of the target image contour line at different angles to obtain corresponding point coordinates of the rotating image of the target image; and finally, reversely solving the coordinates of the corresponding points by using the coordinate transformation matrix of the rotating image points to obtain the three-dimensional coordinates of the contour points corresponding to the contour lines of the target image. After the edge detection is carried out on the X-ray image, the contour points are stored by using an orthogonal-priority 8-neighborhood traversal tracking improvement algorithm, so that the sequential storage of the target contour lines is realized; and matching corresponding points of the contours of the multiple images by using a pixel point equipartition interpolation method to obtain a contour line matching matrix, and finally calculating by rotating the image coordinate change matrix to obtain the three-dimensional expression of the contour line. According to the method, through an orthogonal-priority 8-neighborhood traversal tracking improvement algorithm and a pixel point equipartition interpolation method, the contour line of the image is converted from two-dimensional coordinate representation to three-dimensional coordinate representation, so that the coordinate information of the contour point of the image is more comprehensive, the contour line is clearer, the occurrence of misdiagnosis is reduced, and the detection efficiency is improved.
Corresponding to the method for three-dimensional reconstruction of the contour line of the multiple X-ray rotated images provided by the present application, the present application also provides a system for three-dimensional reconstruction of the contour line of the multiple X-ray rotated images, and referring to fig. 5, a schematic structural diagram of the system for three-dimensional reconstruction of the contour line of the multiple X-ray rotated images provided by the embodiment of the present application is provided. As shown in fig. 5, the system includes: the device comprises a first acquisition module, a second acquisition module, a third acquisition module, a matching module and a solving module. The first acquisition module is used for determining a first two-dimensional matrix corresponding to the contour line of the target image according to the acquired contour line of the target image; the second acquisition module is used for sequentially storing the contour points in the first two-dimensional matrix acquired by the first acquisition module by using an orthogonal-priority 8-neighborhood traversal tracking method to acquire a second two-dimensional matrix; the third acquisition module is used for acquiring contour point coordinate sets of the target image contour lines at different angles according to the target image contour lines at different angles and the second two-dimensional matrix acquired by the second acquisition module corresponding to the target image contour lines at different angles; the matching module is used for matching corresponding points in the contour point coordinate set acquired by the third acquisition module to acquire the coordinates of corresponding points of the rotating image of the target image; and the solving module is used for reversely solving the coordinates of the corresponding points of the rotating image acquired by the matching module by using the coordinate transformation matrix of the rotating image points to acquire the three-dimensional coordinates of the contour points corresponding to the contour lines of the target image.
The second acquisition module includes: the device comprises a first determining unit, a searching unit and a first acquiring unit. The first determining unit is used for determining a starting point of the first two-dimensional matrix acquired by the first acquiring module; the searching unit is used for searching contour points around the first determining unit according to the serial number sequence in the first two-dimensional matrix acquired by the first acquiring module; and the first acquisition unit is used for sequentially storing the acquired searching units of the contour lines of different angles to acquire a second two-dimensional matrix. The output end of the first acquisition module is connected with the input end of the first determination unit, the output end of the first determination unit is connected with the input end of the search unit, and the output end of the search unit is connected with the input end of the first acquisition unit. The use process comprises the following steps: the signal obtained by the first obtaining module enters the first determining unit of the second obtaining module, the signal in the first determining unit enters the searching unit through the output end, and the signal output from the searching unit reaches the first obtaining unit.
The third acquisition module includes: a second determining unit and a second acquiring unit. The second determining unit is used for acquiring the starting point and the end point of the target image contour line at different angles according to the first acquiring unit; and the second acquisition unit is used for acquiring the contour point coordinate set of the target image contour line with different angles according to the second determination unit. The output end of the first acquisition unit of the second acquisition module is connected with the input end of the second determination unit of the third acquisition module, and the output end of the second determination unit is connected with the input end of the second acquisition unit. The use process comprises the following steps: the signal output by the first acquisition unit enters a second determination unit of the third acquisition module, and the signal in the second determination unit enters a second acquisition unit through an output end.
The matching module comprises: the device comprises a third determining unit, a third acquiring unit, a fourth acquiring unit and a matching unit. The third determining unit is used for counting the number of the longitudinal pixel points of the second acquiring unit, acquiring the number of the longitudinal pixel points of the image and finding out a maximum value; the third acquisition unit is used for sequentially counting the number of longitudinal transverse pixels on each layer of the target image contour line corresponding to the third acquisition unit according to the trend of the target image contour line to obtain a third two-dimensional matrix; a fourth acquiring unit configured to acquire a maximum value of each line of the third acquiring unit; and the matching unit is used for performing equipartition matching on the abscissa of the target image contour line at different angles under the same ordinate according to the maximum value of the fourth acquisition unit to obtain a fourth two-dimensional matrix. The output end of a second acquisition unit of the third acquisition module is connected with the input end of a third determination unit of the matching module, the output end of the third determination unit is connected with the input end of the third acquisition unit, the output end of the third acquisition unit is connected with the input end of a fourth acquisition unit, the output end of the fourth acquisition unit is connected with the input end of the matching unit, and the output end of the matching unit is connected with the input end of the solving module. The use process comprises the following steps: and the signal in the matching unit enters a solving module through the output end to carry out reverse solution to obtain the three-dimensional coordinates of the contour point corresponding to the contour line of the target image.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.
The above-described embodiments of the apparatus and system are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
The above description is merely exemplary of the present application and is presented to enable those skilled in the art to understand and practice the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (7)
1. A three-dimensional reconstruction method for contour lines of a plurality of X-ray rotation images is characterized by comprising the following steps:
determining a first two-dimensional matrix corresponding to the contour line of the target image according to the obtained contour line of the target image;
sequentially storing the contour points in the first two-dimensional matrix by using an orthogonal-priority 8-neighborhood traversal tracking method to obtain a second two-dimensional matrix;
acquiring contour point coordinate sets of the target image contour lines at different angles according to the target image contour lines at different angles and the second two-dimensional matrixes corresponding to the target image contour lines at different angles;
matching corresponding points in the contour point coordinate set to obtain a corresponding point coordinate of a rotating image of the target image, wherein the method comprises the steps of counting the number of longitudinal pixel points of the contour point coordinate set to obtain the number of longitudinal pixel points of the image, finding out a maximum value, sequentially counting the number of longitudinal transverse pixel points on each layer of a target image contour line corresponding to the contour point coordinate set according to the trend of the target image contour line to obtain a third two-dimensional matrix, obtaining the maximum value of each line of the third two-dimensional matrix, and performing equal division matching on the horizontal coordinates of the target image contour line at different angles under the same longitudinal coordinate according to the maximum value to obtain a fourth two-dimensional matrix;
and reversely solving the coordinates of the corresponding points of the rotating image by using the coordinate transformation matrix of the rotating image points to obtain the three-dimensional coordinates of the contour points corresponding to the contour lines of the target image.
2. The method for three-dimensional reconstruction of contour lines of multiple X-ray rotational images according to claim 1, wherein said sequentially storing contour points in said first two-dimensional matrix using an orthogonal-first 8-neighborhood traversal tracking method to obtain a second two-dimensional matrix comprises:
determining a starting point O of the first two-dimensional matrix;
according to the first two-dimensional matrix
Sequentially searching contour points around the starting point O in the medium numbering sequence;
and sequentially storing the contour points of the acquired contour lines with different angles to obtain the second two-dimensional matrix.
3. The method for three-dimensional reconstruction of object contours of multiple X-ray rotational images according to claim 2, wherein the obtaining of the coordinate sets of the object points of the object image contours at different angles according to the object image contours at different angles and the second two-dimensional matrices corresponding to the object image contours at different angles comprises:
acquiring a starting point and an end point of the target image contour line at different angles according to the second two-dimensional matrix;
and acquiring contour point coordinate sets of the target image contour lines at different angles according to the acquired starting points and the acquired end points of the target image contour lines at different angles.
4. The method for three-dimensional reconstruction of contours of multiple X-ray rotated images according to claim 1, wherein the third two-dimensional matrix is a matrix recording the number of pixels of the same contour of different images under the same ordinate; and the fourth two-dimensional matrix is a matrix obtained by recording matching of corresponding points of the same contour line of different images.
5. A three-dimensional reconstruction method and a system for contour lines of a plurality of X-ray rotation images are characterized by comprising the following steps:
the first acquisition module is used for determining a first two-dimensional matrix corresponding to the contour line of the target image according to the acquired contour line of the target image;
the second acquisition module is used for sequentially storing the contour points in the first two-dimensional matrix acquired by the first acquisition module by using an orthogonal-priority 8-neighborhood traversal tracking method to acquire a second two-dimensional matrix;
the third acquisition module is used for acquiring contour point coordinate sets of the target image contour lines at different angles according to the target image contour lines at different angles and the second two-dimensional matrix acquired by the second acquisition module corresponding to the target image contour lines at different angles;
a matching module, configured to match corresponding points in the contour point coordinate set acquired by the third acquiring module to acquire coordinates of corresponding points of a rotation image of the target image, that is, a third determining unit, configured to count the number of longitudinal pixels of the second acquiring unit to acquire the number of longitudinal pixels of the image and find out a maximum value, a third acquiring unit, configured to count the number of horizontal pixels on each layer of the longitudinal direction on the contour line of the target image corresponding to the third determining unit in order according to the trend of the contour line of the target image to acquire a third two-dimensional matrix, a fourth acquiring unit, configured to determine a maximum value of each line of the third acquiring unit, and a matching unit, configured to perform equipartition matching on horizontal coordinates of the contour line of the target image at different angles under the same longitudinal coordinate according to the maximum value of the fourth acquiring unit, obtaining a fourth two-dimensional matrix;
and the solving module is used for reversely solving the coordinates of the corresponding points of the rotating image acquired by the matching module by using the coordinate transformation matrix of the rotating image points to acquire the three-dimensional coordinates of the contour points corresponding to the contour lines of the target image.
6. The system for three-dimensional reconstruction of contour lines of multiple X-ray rotational images according to claim 5, wherein said second obtaining module comprises:
a first determining unit, configured to determine a starting point of the first two-dimensional matrix obtained by the first obtaining module;
the searching unit is used for searching contour points around the first determining unit according to the serial number sequence in the first two-dimensional matrix acquired by the first acquiring module;
and the first acquisition unit is used for sequentially storing the acquired contour lines of different angles in the search unit to obtain a second two-dimensional matrix.
7. The system for three-dimensional reconstruction of contour lines of multiple X-ray rotational images according to claim 6, wherein said third obtaining module comprises:
the second determining unit is used for determining the starting point and the end point of the target image contour line at different angles according to the first acquiring unit;
and the second acquisition unit is used for acquiring the contour point coordinate set of the target image contour line at different angles according to the second determination unit.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101261685A (en) * | 2008-01-31 | 2008-09-10 | 浙江工业大学 | Automatic input device for cloth sample image based on image vector technology |
| CN101301207A (en) * | 2008-05-28 | 2008-11-12 | 华中科技大学 | Vascular angiography three-dimensional rebuilding method under dynamic model direction |
| CN104021568A (en) * | 2014-06-25 | 2014-09-03 | 山东大学 | Automatic registering method of visible lights and infrared images based on polygon approximation of contour |
| CN104182757A (en) * | 2013-05-22 | 2014-12-03 | 内蒙古大学 | Method of acquiring actual coverage area of measured target and device |
| CN104680127A (en) * | 2014-12-18 | 2015-06-03 | 闻泰通讯股份有限公司 | Gesture identification method and gesture identification system |
| CN105916444A (en) * | 2013-11-04 | 2016-08-31 | 苏尔吉维索公司 | Method for reconstructing a 3d image from 2d x-ray images |
| CN107389705A (en) * | 2017-07-20 | 2017-11-24 | 云南电网有限责任公司电力科学研究院 | A kind of power equipment X ray Non-Destructive Testing three-D imaging method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102004016586A1 (en) * | 2004-03-31 | 2005-11-03 | Siemens Ag | Image reconstruction device for an X-ray device and method for local 3D reconstruction of an object region |
-
2018
- 2018-03-08 CN CN201810189126.6A patent/CN108416839B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101261685A (en) * | 2008-01-31 | 2008-09-10 | 浙江工业大学 | Automatic input device for cloth sample image based on image vector technology |
| CN101301207A (en) * | 2008-05-28 | 2008-11-12 | 华中科技大学 | Vascular angiography three-dimensional rebuilding method under dynamic model direction |
| CN104182757A (en) * | 2013-05-22 | 2014-12-03 | 内蒙古大学 | Method of acquiring actual coverage area of measured target and device |
| CN105916444A (en) * | 2013-11-04 | 2016-08-31 | 苏尔吉维索公司 | Method for reconstructing a 3d image from 2d x-ray images |
| CN104021568A (en) * | 2014-06-25 | 2014-09-03 | 山东大学 | Automatic registering method of visible lights and infrared images based on polygon approximation of contour |
| CN104680127A (en) * | 2014-12-18 | 2015-06-03 | 闻泰通讯股份有限公司 | Gesture identification method and gesture identification system |
| CN107389705A (en) * | 2017-07-20 | 2017-11-24 | 云南电网有限责任公司电力科学研究院 | A kind of power equipment X ray Non-Destructive Testing three-D imaging method |
Non-Patent Citations (2)
| Title |
|---|
| 3D Shape Reconstruction of Loop Objects in X-Ray Protein Crystallography;Tilo Strutz;《IEEE/ACM Transactions on Computational Biology and Bioinformatics》;20111231;第8卷(第3期);第797-807页 * |
| 基于医学图像序列轮廓线重建三维表面的改进算法;张艳君，叶伯生，曾理湛;《计算机工程与应用》;20040531(第13期);第215-218页 * |
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