CN112017114B - Method and system for splicing full images of half images in tunnel detection - Google Patents
Method and system for splicing full images of half images in tunnel detection Download PDFInfo
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Abstract
The invention relates to a method and a system for splicing full images of half images in tunnel detection, wherein the method comprises the following steps: detecting and matching characteristic points of the overlapping areas of the two half images spliced according to a set interval along the radial direction to obtain matching characteristic points of the half images; according to the matching characteristic points of the half images, obtaining the matching characteristic points of each picture in the radial direction by a linear interpolation method; taking radial coordinates of each picture in one half image as a reference, and carrying out radial coordinate matching of each picture contained in the two half images; and correspondingly splicing each picture contained in the two half images according to the matching characteristic points. The images acquired by the front and rear times of the tunnel measuring vehicle are spliced together, the overall view of the tunnel surface is restored, and the technical problems of registration, deformation elimination and the like caused by different acquisition time, acquisition visual angles and vehicle speed of the images to be spliced of the tunnel are solved.
Description
Technical Field
The invention relates to the technical field of tunnel detection, in particular to a method and a system for splicing full images of half images in tunnel detection.
Background
Image stitching is a technique of stitching several images (possibly obtained at different times, from different viewing angles or from different sensors) with overlapping portions into one large seamless high resolution image.
Because the tunnel measuring vehicle can only run in one direction in the tunnel, the acquisition of the influence of the whole tunnel needs to be acquired twice in order to ensure the definition and accuracy of the acquired image. In this case, in order to generate a large-scale tunnel full view image, the full view stitching of the tunnel images involves stitching problems of inconsistent numbers of two acquired images in the same area, and inconsistent deformation of the overlapped area images caused by different time, different view angles and different vehicle speeds.
How to splice a large tunnel face image completely is a technical problem to be solved urgently by the skilled person.
Disclosure of Invention
Aiming at the technical problems in the prior art, the invention provides a method for splicing full images by half images in tunnel detection, which solves the technical problems of registration, deformation elimination and the like caused by different acquisition time, acquisition visual angle and vehicle speed of images to be spliced in tunnels in the prior art.
The technical scheme for solving the technical problems is as follows: the method for splicing full images by using half images detected by a tunnel comprises a plurality of pictures arranged along a radial direction, wherein the radial direction is the advancing direction of a tunnel measuring vehicle in the tunnel;
the method comprises the following steps:
step 1, detecting and matching feature points of overlapping areas of two half images spliced according to a set interval along a radial direction to obtain matched feature points of the half images;
step 2, obtaining the matching characteristic points of each picture in the radial direction by a linear interpolation method according to the matching characteristic points of the half images;
step 3, performing radial coordinate matching of each picture contained in the two half images by taking radial coordinates of each picture in one half image as a reference;
and 4, correspondingly splicing each picture contained in the two half images according to the matching characteristic points.
A system for splicing full images by half images detected by a tunnel, wherein the half images comprise a plurality of pictures arranged along a radial direction, and the radial direction is the advancing direction of a tunnel measuring vehicle in the tunnel;
the system comprises:
the matching characteristic point detection screening module detects and matches characteristic points of the overlapping areas of the two half images spliced according to a set interval along the radial direction to obtain matching characteristic points of the half images;
the matching characteristic point determining module is used for obtaining the matching characteristic point of each picture in the radial direction through a linear interpolation method according to the matching characteristic point of the half picture;
the radial matching module is used for matching radial coordinates of each picture contained in the two half images by taking the radial coordinates of each picture in one half image as a reference;
and the splicing module is used for correspondingly splicing each picture contained in the two half images according to the matching characteristic points.
The beneficial effects of the invention are as follows: according to the method for splicing the full-frame images of the half-frame images for tunnel detection, images acquired by the front and rear of the tunnel measuring vehicle are spliced together, the overall view of the tunnel surface is restored, the technical problems of registration, deformation elimination and the like caused by different acquisition time, acquisition visual angles and vehicle speed of the images to be spliced of the tunnel are solved, the definition of the section images of the spliced tunnel is high, the section images obtained by splicing can be synthesized into the section images with large visual fields for automatically extracting tunnel defects, and the size of the actual defect distribution range can be calculated directly according to pixel resolution due to high splicing accuracy, so that the dangerous grade of the defects is estimated. The invention can greatly save manpower and improve the detection efficiency of tunnel defects.
On the basis of the technical scheme, the invention can be improved as follows.
Further, the step 1 includes:
step 101, detecting and matching feature points according to set intervals;
step 102, screening the characteristic points through a Law algorithm to obtain excellent characteristic points;
and 103, calculating the slope of each pair of matched excellent characteristic points, establishing groups of each slope range according to the set interval, and selecting a pair of matched characteristic points in the group with the largest number of the excellent characteristic points as the matched characteristic points of the half image.
Further, in the step 101, an Open CV algorithm is adopted to detect and match the feature points:
detecting the characteristic points by using a FAST algorithm, and constructing the characteristic point description operator by using an ORB algorithm;
and matching the characteristic points by using a FLANN algorithm.
Further, the process of performing radial coordinate matching of each of the two images in step 3 includes:
step 301, calculating a ratio k of radial coordinate differences between the adjacent matching feature points on one side and the adjacent matching feature points on the other side by taking the adjacent matching feature points of the half image obtained in the step 1 as a unit, and determining that the radial length of each picture on one side where the adjacent matching feature points are located is k times of the original length of the picture;
step 302, cutting and merging each picture on one side according to the radial length of each picture on the one side, so that the proportion of the matching feature points of each picture on one side to the upper edge and the lower edge of the picture on which the matching feature points are positioned is the same as that on the other side;
step 303, performing radial expansion and contraction on each picture on one side to make the radial lengths of the pictures on two sides identical.
Further, before the step 4 performs corresponding splicing on each picture, the method includes: and carrying out trapezoidal deformation on the corresponding pictures on the two sides according to the transverse coordinate difference of the radially adjacent matching characteristic points.
Further, the step 4 of performing trapezoidal deformation includes:
step 401, calculating the ratio k of the difference between the lateral coordinates and the difference between the radial coordinates of the adjacent matching feature points on both sides, using the adjacent matching feature points of the half image obtained in step 1 as a unit 1 And k 2 ；
Step 402, calculate d 1 And d 2 Wherein x is 1 ＝k 1 y 1 +d 1 ，x 2 ＝k 2 y 2 +d 2 ，(x 1 ，y 1 ) Coordinates of matching feature points of the picture for which trapezoidal deformation is performed for one side, (x) 2 ，y 2 ) Coordinates of matching feature points of the picture subjected to trapezoidal deformation on the other side;
step 403, performing trapezoidal deformation according to the transverse lengths of the upper edge and the lower edge of the picture with trapezoidal deformation at two sides, wherein:
x left upper part ＝k 1 y Upper part +d 1 ，x Lower left ＝k 1 y Lower part(s) +d 1 ；
x Upper right ＝k 2 y Upper part +d 2 ，x Lower right ＝k 2 y Lower part(s) +d 2 ；
x Left upper part And x Lower left The transverse length x of the upper edge and the lower edge of the picture with one side carrying out trapezoidal deformation respectively Upper right And x Lower right The lateral lengths of the upper edge and the lower edge of the picture which are respectively trapezoidal deformed at the other side, y Upper part And y Lower part(s) Radial coordinates of the upper and lower sides of the picture subjected to trapezoidal deformation are respectively given.
Further, the process of performing corresponding stitching on each picture in the step 4 includes: cutting out repeated parts according to the coordinates of the matched characteristic points, and correcting the numerical value of transverse cutting according to the empirical numerical value during cutting;
and correspondingly splicing the pictures, and stretching the spliced pictures into the width with the same transverse width as the first full-width picture of the tunnel.
The beneficial effects of adopting the further scheme are as follows: after the left half corresponding image and the right half corresponding image are obtained, if obvious radial dislocation is caused by direct splicing, trapezoidal deformation is carried out on the left half corresponding image and the right half corresponding image, and then splicing is carried out, so that the continuity of the radial images is ensured.
Drawings
FIG. 1 is a flow chart of a method for splicing full images of a half image for tunnel detection provided by the invention;
FIG. 2 is a schematic diagram of a method for calculating coordinates of matching points by linear interpolation according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a method for obtaining a right image corresponding to left image content according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a trapezoidal correction method for a stitched image according to an embodiment of the present invention;
FIG. 5 is a block diagram illustrating an embodiment of a system for stitching full images together of half images for tunnel inspection according to the present invention;
fig. 6 is a schematic entity structure diagram of an electronic device according to an embodiment of the present invention.
In the drawings, the list of components represented by the various numbers is as follows:
101. the device comprises a matching characteristic point detection screening module 102, a matching characteristic point determination module 103, a radial matching module 104, a splicing module 201, a processor 202, a communication interface 203, a memory 204 and a communication bus.
Detailed Description
The principles and features of the present invention are described below with reference to the drawings, the examples are illustrated for the purpose of illustrating the invention and are not to be construed as limiting the scope of the invention.
As shown in fig. 1, a flowchart of a method for splicing full images by using half images for tunnel detection provided by the invention is shown, wherein the half images comprise a plurality of pictures arranged along a radial direction, and the radial direction is a travelling direction of a tunnel measuring vehicle in a tunnel; as can be seen from fig. 1, the method for splicing full images by half images for tunnel detection provided by the present invention includes:
and step 1, detecting and matching characteristic points of the overlapping area of the two half images spliced according to a set interval along the radial direction to obtain matching characteristic points of the half images.
And 2, obtaining the matching characteristic points of each picture in the radial direction by a linear interpolation method according to the matching characteristic points of the half picture.
According to the running speed of the vehicle, the original half-image is basically an independent picture along each meter along the radial direction, as shown in fig. 2, which is a schematic diagram of a method for calculating coordinates of matching points by linear interpolation, wherein the linear interpolation is to approximate an original function by using a straight line of two points, and the matching characteristic points of each independent picture are obtained by using a linear interpolation method according to the matching characteristic points of the left half-image and the right half-image obtained in the step 1.
And 3, carrying out radial coordinate matching of each picture contained in the two half images by taking the radial coordinates of each picture in one half image as a reference.
And 4, correspondingly splicing each picture contained in the two half images according to the matched characteristic points.
According to the method for splicing the full-frame images of the half-frame images for tunnel detection, images acquired by the front and rear of the tunnel measuring vehicle are spliced together, the overall view of the tunnel surface is restored, the technical problems of registration, deformation elimination and the like caused by different acquisition time, acquisition visual angles and vehicle speed of the images to be spliced of the tunnel are solved, the definition of the section images of the spliced tunnel is high, the section images obtained by splicing can be synthesized into the section images with large visual fields for automatically extracting tunnel defects, and the size of the actual defect distribution range can be calculated directly according to pixel resolution due to high splicing accuracy, so that the dangerous grade of the defects is estimated. The invention can greatly save manpower and improve the detection efficiency of tunnel defects.
Example 1
Embodiment 1 provided by the present invention is an embodiment of a method for splicing full images of a half image for tunnel detection, where the embodiment includes:
and step 1, detecting and matching characteristic points of the overlapping area of the two half images spliced according to a set interval along the radial direction to obtain matching characteristic points of the half images.
Preferably, step 1 comprises:
step 101, detecting and matching the feature points according to the set interval.
The set interval is flexibly set according to the detected tunnel length and efficiency requirements, and can be 5 meters or 10 meters, for example.
Further, the Open CV algorithm is adopted to detect and match the characteristic points:
and detecting characteristic points by using a FAST algorithm, and constructing a characteristic point description operator by using an ORB algorithm.
And (5) carrying out feature point matching by using a FLANN algorithm.
And 102, screening the characteristic points through a Law algorithm to obtain excellent characteristic points.
After the feature points are detected and matched according to the set interval, the number of the obtained feature points is relatively large, so that the method adopts the Law algorithm to screen the feature points.
Step 103, calculating the slope of each pair of matched excellent characteristic points, establishing groups of slope ranges according to the set intervals, and selecting a pair of matched characteristic points in the small group with the largest number of excellent characteristic points as matched characteristic points of the half image.
The number of the feature points after screening is still large, further screening can be performed by detecting slopes between the matched feature points, if more slopes belong to a small group with a slope range, a pair of matched feature points are selected from the small group to serve as matched feature points of the half image, and the slope setting interval can be flexibly set according to practical situations, for example, can be set to be 0.01.
And 2, obtaining the matching characteristic points of each picture in the radial direction by a linear interpolation method according to the matching characteristic points of the half picture.
And 3, carrying out radial coordinate matching of each picture contained in the two half images by taking the radial coordinates of each picture in one half image as a reference.
Preferably, as shown in fig. 3, a schematic diagram of a method for obtaining a right image corresponding to a left image content according to an embodiment of the present invention is shown, and as can be seen from fig. 3, a process for performing radial coordinate matching of each picture included in two half images in step 3 includes:
step 301, calculating the ratio k of the radial coordinate differences of the adjacent matching feature points on one side and the other side by taking the adjacent matching feature points of the half image obtained in step 1 as a unit, and determining that the radial length of each picture on one side where the adjacent matching feature points are located is k times of the original length of the picture.
Step 302, cutting and merging each picture on one side according to the radial length of each picture on the one side, so that the proportion of the matching feature points of each picture on one side to the upper edge and the lower edge of the picture on which the matching feature points are located is the same as that on the other side.
Step 303, performing radial expansion and contraction on each picture on one side to make the radial lengths of the pictures on two sides identical.
In the embodiment shown in fig. 2 and 3 in combination with fig. 2 and 3, each picture has a radial length of 2000 mm, a lateral length of 10000 mm, the zero point being the upper right corner of the left image and the upper left corner of the right image.
The coordinates of adjacent matching feature points A and B of the left half image are (x) Left 1 ，y Left 1 ) And (x) Left 2 ，y Left 2 ) The coordinates of adjacent matching feature points C and D of the right half image are (x Right 1 ，y Right 1 ) And (x) Right 2 ，y Right 2 ) When the right picture is cut according to the left picture:
can be calculated to obtainThe radial length of each picture on the right side is 2000k when cutting is carried out, and the ratio of the matching characteristic points of each picture to the distances between the upper edge and the lower edge of the picture after cutting and splicing is ensured to be the same.
And 4, correspondingly splicing each picture contained in the two half images according to the matched characteristic points.
Preferably, as shown in fig. 4, which is a schematic diagram of a method for correcting a trapezoid of a stitched image according to an embodiment of the present invention, as can be seen from fig. 4, before the step 4 of stitching each picture correspondingly, the method includes: and carrying out trapezoidal deformation on the corresponding pictures on the two sides according to the transverse coordinate difference of the radially adjacent matching characteristic points.
The process of performing trapezoidal deformation includes:
step 401, calculating the ratio k of the lateral coordinate difference value and the radial coordinate difference value of the adjacent matching feature points on both sides by taking the adjacent matching feature points of the half image obtained in step 1 as a unit 1 And k 2 。
Step 402, calculate d 1 And d 2 Wherein x is 1 ＝k 1 y 1 +d 1 ，x 2 ＝k 2 y 2 +d 2 ，(x 1 ，y 1 ) Coordinates of matching feature points of the picture for which trapezoidal deformation is performed for one side, (x) 2 ，y 2 ) Coordinates of matching feature points of the picture subjected to trapezoidal deformation for the other side.
Step 403, performing trapezoidal deformation according to the transverse lengths of the upper edge and the lower edge of the picture with trapezoidal deformation at two sides, wherein:
x left upper part ＝k 1 y Upper part +d 1 ，x Lower left ＝k 1 y Lower part(s) +d 1 ；
x Upper right ＝k 2 y Upper part +d 2 ，x Lower right ＝k 2 y Lower part(s) +d 2 。
x Left upper part And x Lower left The transverse length x of the upper edge and the lower edge of the picture with one side carrying out trapezoidal deformation respectively Upper right And x Lower right The lateral lengths of the upper edge and the lower edge of the picture which are respectively trapezoidal deformed at the other side, y Upper part And y Lower part(s) Radial coordinates of the upper and lower sides of the picture subjected to trapezoidal deformation are respectively given.
The transverse coordinates are coordinates in the direction perpendicular to the radial direction, after the left half corresponding image and the right half corresponding image are obtained, if the direct stitching can cause obvious radial dislocation, the left half corresponding image and the right half corresponding image are stitched after trapezoidal deformation, so that the continuity of the radial images is ensured.
Preferably, the process of correspondingly splicing each picture in the step 4 includes: and cutting out repeated parts according to the coordinates of the matched feature points, and then correspondingly splicing the pictures.
Specifically, the value of the transverse cut is corrected based on the empirical value at the time of cutting.
And stretching the spliced pictures into the width with the same transverse width as the first full-width picture of the tunnel after splicing.
Example 2
The embodiment 2 provided by the invention is an embodiment of a system for splicing full images by a half image of tunnel detection, wherein the half image comprises a plurality of pictures arranged along a radial direction, and the radial direction is the advancing direction of a tunnel measuring vehicle in a tunnel; fig. 5 is a block diagram of an embodiment of a system for splicing full images of half images for tunnel detection according to the present invention, and as can be seen from fig. 5, the system includes: the device comprises a matching characteristic point detection screening module 101, a matching characteristic point determination module 102, a radial matching module 103 and a splicing module 104.
The matching feature point detection and screening module 101 detects and matches feature points of the overlapping area of the two half images spliced according to a set interval along the radial direction, and obtains matching feature points of the half images.
The matching feature point determining module 102 obtains the matching feature point of each picture in the radial direction by a linear interpolation method according to the matching feature point of the half picture.
The radial matching module 103 performs radial coordinate matching of each picture included in the two half images with reference to the radial coordinates of each picture in the half image on one side.
And the splicing module 104 correspondingly splices each picture contained in the two half images according to the matched characteristic points.
Fig. 6 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention, where, as shown in fig. 6, the electronic device may include: the processor 201, the communication interface 202, the memory 203 and the communication bus 204, wherein the processor 201, the communication interface 202 and the memory 203 complete communication with each other through the communication bus 204. The processor 201 may invoke a computer program stored in the memory 203 and executable on the processor 201 to perform the method for stitching full images from half-images for tunnel detection provided in the above embodiments, for example, including: step 1, detecting and matching characteristic points of overlapping areas of two half images spliced according to a set interval along a radial direction to obtain matching characteristic points of the half images; step 2, obtaining matching characteristic points of each picture in the radial direction by a linear interpolation method according to the matching characteristic points of the half picture; step 3, taking radial coordinates of each picture in one half image as a reference, and carrying out radial coordinate matching of each picture contained in the two half images; and 4, correspondingly splicing each picture contained in the two half images according to the matched characteristic points.
The embodiments of the present invention further provide a non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, is implemented to perform the method for stitching full images with half image for tunnel detection provided in the above embodiments, for example, including: step 1, detecting and matching characteristic points of overlapping areas of two half images spliced according to a set interval along a radial direction to obtain matching characteristic points of the half images; step 2, obtaining matching characteristic points of each picture in the radial direction by a linear interpolation method according to the matching characteristic points of the half picture; step 3, taking radial coordinates of each picture in one half image as a reference, and carrying out radial coordinate matching of each picture contained in the two half images; and 4, correspondingly splicing each picture contained in the two half images according to the matched characteristic points.
The foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the invention are intended to be included within the scope of the invention.
Claims (7)
1. The method for splicing full images by using half images detected by a tunnel comprises a plurality of pictures arranged along a radial direction, wherein the radial direction is the advancing direction of a tunnel measuring vehicle in the tunnel;
characterized in that the method comprises:
step 1, detecting and matching feature points of overlapping areas of two half images spliced according to a set interval along a radial direction to obtain matched feature points of the half images;
step 2, obtaining the matching characteristic points of each picture in the radial direction by a linear interpolation method according to the matching characteristic points of the half images;
step 3, performing radial coordinate matching of each picture contained in the two half images by taking radial coordinates of each picture in one half image as a reference;
step 4, corresponding splicing is carried out on each picture contained in the two half images according to the matching characteristic points;
the process of performing radial coordinate matching of each picture included in the two half images in the step 3 includes:
step 301, calculating a ratio k of radial coordinate differences between the adjacent matching feature points on one side and the adjacent matching feature points on the other side by taking the adjacent matching feature points of the half image obtained in the step 1 as a unit, and determining that the radial length of each picture on one side where the adjacent matching feature points are located is k times of the original length of the picture;
step 302, cutting and merging each picture on one side according to the radial length of each picture on the one side, so that the proportion of the matching feature points of each picture on one side to the upper edge and the lower edge of the picture on which the matching feature points are positioned is the same as that on the other side;
step 303, performing radial expansion and contraction on each picture on one side to enable the radial lengths of the pictures on two sides to be the same;
before the step 4 of correspondingly splicing each picture, the method comprises the following steps: trapezoidal deformation is carried out on the corresponding pictures on the two sides according to the transverse coordinate difference of the adjacent matching characteristic points;
the step 4 of performing trapezoidal deformation includes:
step 401, calculating the ratio k of the difference between the lateral coordinates and the difference between the radial coordinates of the adjacent matching feature points on both sides, using the adjacent matching feature points of the half image obtained in step 1 as a unit 1 And k 2 ；
Step 402, calculate d 1 And d 2 Wherein x is 1 ＝k 1 y 1 +d 1 ，x 2 ＝k 2 y 2 +d 2 ，(x 1 ，y 1 ) Coordinates of matching feature points of the picture for which trapezoidal deformation is performed for one side, (x) 2 ，y 2 ) Coordinates of matching feature points of the picture subjected to trapezoidal deformation on the other side;
step 403, performing trapezoidal deformation according to the transverse lengths of the upper edge and the lower edge of the picture with trapezoidal deformation at two sides, wherein:
x left upper part ＝k 1 y Upper part +d 1 ，x Lower left ＝k 1 y Lower part(s) +d 1 ；
x Upper right ＝k 2 y Upper part +d 2 ，x Lower right ＝k 2 y Lower part(s) +d 2 ；
x Left upper part And x Lower left The transverse length x of the upper edge and the lower edge of the picture with one side carrying out trapezoidal deformation respectively Upper right And x Lower right The lateral lengths of the upper edge and the lower edge of the picture which are respectively trapezoidal deformed at the other side, y Upper part And y Lower part(s) Radial coordinates of the upper and lower sides of the picture subjected to trapezoidal deformation are respectively given.
2. The method according to claim 1, wherein the step 1 comprises:
step 101, detecting and matching feature points according to set intervals;
step 102, screening the characteristic points through a Law algorithm to obtain excellent characteristic points;
and 103, calculating the slope of each pair of matched excellent characteristic points, establishing groups of each slope range according to the set interval, and selecting a pair of matched characteristic points in the group with the largest number of the excellent characteristic points as the matched characteristic points of the half image.
3. The method according to claim 2, wherein the detecting and matching of the feature points are performed in step 101 using an Open CV algorithm:
detecting the characteristic points by using a FAST algorithm, and constructing the characteristic point description operator by using an ORB algorithm;
and matching the characteristic points by using a FLANN algorithm.
4. The method according to claim 1, wherein the process of splicing the pictures in step 4 includes: cutting out repeated parts according to the coordinates of the matched characteristic points, and correcting the numerical value of transverse cutting according to the empirical numerical value during cutting; and correspondingly splicing the pictures, and stretching the spliced pictures into the width with the same transverse width as the first full-width picture of the tunnel.
5. A system for splicing full images by half images detected by a tunnel, wherein the half images comprise a plurality of pictures arranged along a radial direction, and the radial direction is the advancing direction of a tunnel measuring vehicle in the tunnel;
characterized in that the system comprises:
the matching characteristic point detection screening module detects and matches characteristic points of the overlapping areas of the two half images spliced according to a set interval along the radial direction to obtain matching characteristic points of the half images;
the matching characteristic point determining module is used for obtaining the matching characteristic point of each picture in the radial direction through a linear interpolation method according to the matching characteristic point of the half picture;
the radial matching module is used for matching radial coordinates of each picture contained in the two half images by taking the radial coordinates of each picture in one half image as a reference;
the splicing module is used for correspondingly splicing each picture contained in the two half images according to the matching characteristic points;
the radial coordinate matching process of each picture contained in the two half images by the radial matching module comprises the following steps:
step 301, calculating a ratio k of radial coordinate differences between the adjacent matching feature points on one side and the adjacent matching feature points on the other side by taking the adjacent matching feature points of the half image obtained in the step 1 as a unit, and determining that the radial length of each picture on one side where the adjacent matching feature points are located is k times of the original length of the picture;
step 302, cutting and merging each picture on one side according to the radial length of each picture on the one side, so that the proportion of the matching feature points of each picture on one side to the upper edge and the lower edge of the picture on which the matching feature points are positioned is the same as that on the other side;
step 303, performing radial expansion and contraction on each picture on one side to enable the radial lengths of the pictures on two sides to be the same;
before the splicing module carries out corresponding splicing on each picture, the splicing module comprises: trapezoidal deformation is carried out on the corresponding pictures on the two sides according to the transverse coordinate difference of the adjacent matching characteristic points;
the trapezoidal deformation process of the splicing module comprises the following steps of:
step 401, calculating the ratio k of the difference between the lateral coordinates and the difference between the radial coordinates of the adjacent matching feature points on both sides, using the adjacent matching feature points of the half image obtained in step 1 as a unit 1 And k 2 ；
Step 402, calculate d 1 And d 2 Wherein x is 1 ＝k 1 y 1 +d 1 ，x 2 ＝k 2 y 2 +d 2 ，(x 1 ，y 1 ) Coordinates of matching feature points of the picture for which trapezoidal deformation is performed for one side, (x) 2 ，y 2 ) Coordinates of matching feature points of the picture subjected to trapezoidal deformation on the other side;
step 403, performing trapezoidal deformation according to the transverse lengths of the upper edge and the lower edge of the picture with trapezoidal deformation at two sides, wherein:
x left upper part ＝k 1 y Upper part +d 1 ，x Lower left ＝k 1 y Lower part(s) +d 1 ；
x Upper right ＝k 2 y Upper part +d 2 ，x Lower right ＝k 2 y Lower part(s) +d 2 ；
x Left upper part And x Lower left The transverse length x of the upper edge and the lower edge of the picture with one side carrying out trapezoidal deformation respectively Upper right And x Lower right The lateral lengths of the upper edge and the lower edge of the picture which are respectively trapezoidal deformed at the other side, y Upper part And y Lower part(s) Radial coordinates of the upper and lower sides of the picture subjected to trapezoidal deformation are respectively given.
6. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor performs the steps of the method of tunneling half-images stitching full images as claimed in any of claims 1 to 4.
7. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, performs the steps of the method of tunnel inspection half-image stitching full-image as claimed in any one of claims 1 to 4.
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