CN112435170B - Tunnel vault image splicing method - Google Patents
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- CN112435170B CN112435170B CN202011415199.6A CN202011415199A CN112435170B CN 112435170 B CN112435170 B CN 112435170B CN 202011415199 A CN202011415199 A CN 202011415199A CN 112435170 B CN112435170 B CN 112435170B
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- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000005286 illumination Methods 0.000 claims abstract description 19
- 238000010008 shearing Methods 0.000 claims abstract description 13
- 238000012937 correction Methods 0.000 claims abstract description 12
- 238000013507 mapping Methods 0.000 claims abstract description 11
- 230000001186 cumulative effect Effects 0.000 claims description 8
- PXFBZOLANLWPMH-UHFFFAOYSA-N 16-Epiaffinine Natural products C1C(C2=CC=CC=C2N2)=C2C(=O)CC2C(=CC)CN(C)C1C2CO PXFBZOLANLWPMH-UHFFFAOYSA-N 0.000 claims description 7
- 230000009466 transformation Effects 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 abstract description 3
- 238000006243 chemical reaction Methods 0.000 abstract description 3
- 238000012545 processing Methods 0.000 abstract description 3
- 238000001514 detection method Methods 0.000 description 12
- 238000004458 analytical method Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
- G06T3/4038—Image mosaicing, e.g. composing plane images from plane sub-images
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/14—Transformations for image registration, e.g. adjusting or mapping for alignment of images
- G06T3/153—Transformations for image registration, e.g. adjusting or mapping for alignment of images using elastic snapping
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/40—Image enhancement or restoration using histogram techniques
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Abstract
The application discloses a tunnel vault image splicing method, which comprises the following steps: uniformly acquiring a tunnel vault image along the tunnel direction; adopting a histogram equalization algorithm to perform illumination compensation on the tunnel vault image; performing image shearing correction on the tunnel vault image subjected to illumination compensation; and splicing the images subjected to the shearing correction by adopting position mapping to obtain a spliced tunnel vault plane image. Through the scheme, the method has the advantages of simple logic, less calculation workload, reliable conversion and the like, and has high practical value and popularization value in the technical field of tunnel image processing.
Description
Technical Field
The application relates to the technical field of tunnel image processing, in particular to a tunnel vault image splicing method.
Background
In tunnels such as subways and railways, due to the influence of external force, vibration and other factors, the tunnels may be cracked, water seepage and other phenomena, and the tunnels are required to be periodically detected according to the requirements of operation regulations so as to observe whether tunnel dome segments are cracked, damaged and leaked, and especially the subways are important. At present, the tunnel detection in China mainly adopts a manual detection means, which is time-consuming, labor-consuming and low in efficiency;
in addition, some intelligent equipment in the prior art is provided with cameras for automatic acquisition, but the accuracy requirement of a tunnel on image acquisition is very high, for example, subway tunnel detection specifications require that the apparent crack width of a detected duct piece reaches 0.1mm, and high requirements are provided for the resolution of the cameras, so that the existing intelligent equipment adopts a method of stacking hardware, a plurality of (generally 6-8) high-resolution linear arrays or area array cameras are carried at a time, each camera is responsible for shooting pictures of a certain direction of the tunnel duct piece, and the plurality of cameras work simultaneously to achieve the purpose. However, the scheme has more loaded equipment, is heavy, has high cost and does not meet the requirement of quick assembly and disassembly of track equipment. For example, the patent application number is 201811228215.3, the Chinese application patent with the name of "a subway tunnel appearance detection method" and the patent application number is 201910387411.3, the Chinese application patent with the name of "a subway tunnel structure comprehensive detection vehicle" are provided, and a plurality of linear array cameras or area array cameras are mounted on both technologies, so that the same problems exist.
Based on the above situation, the applicant specially puts forward a chinese patent application number of 202010138111.4, named "a tunnel track inspection robot", and a rotary driving motor, a conductive slip ring, a camera, a light source bracket and a dome camera are arranged on a dome collection assembly, and the rotation is adopted to collect images of a tunnel.
However, in the photographs acquired in this way, since the tunnel dome has a circular arc shape and the robot is equipped with a line camera, the robot rotates continuously, scans the tunnel dome image, and advances itself along the track. A subway tunnel appearance detection method, a subway tunnel structure comprehensive detection vehicle and an image shot by a tunnel track detection robot are curved surface images. However, in the image stitching and detection analysis, a planar image is required.
Therefore, there is an urgent need to provide a tunnel dome image stitching method that is simple in logic, has little calculation effort, and is reliable in conversion.
Disclosure of Invention
The application aims to provide a tunnel vault image splicing method, which adopts the following technical scheme:
a tunnel vault image stitching method comprising the steps of:
adopting a rotary linear array camera to uniformly acquire a tunnel vault image along the tunnel direction;
adopting a histogram equalization algorithm to perform illumination compensation on the tunnel vault image;
performing image shearing correction on the tunnel vault image subjected to illumination compensation;
and splicing the images subjected to the shearing correction by adopting position mapping to obtain a spliced tunnel vault plane image.
Further, the illumination compensation of the tunnel vault image by using a histogram equalization algorithm comprises the following steps:
global histogram equalization is performed on any tunnel dome image, and the input image and the output image satisfy the following formulas:
where k represents a gray value, H represents a height of the image, W represents a width of the image, hist O (k) A cumulative histogram representing the output image;
the gray level P of the input image and the gray level q of the output image are calculated, which satisfy the following formula:
wherein hist is I (k) Representing a cumulative histogram of the input image.
Further, the image shearing correction is carried out on the tunnel vault image after illumination compensation, and the method comprises the following steps:
affine transformation is carried out on the tunnel vault image after illumination compensation, and the expression is as follows:
where I denotes the illumination-compensated tunnel dome image, I' denotes the affine-derived image,for the angle offset in the y-direction of the image, +.>The degree of shear in the x direction; the X direction is perpendicular to the acquisition direction, namely the height direction of the image; the Y direction refers to the direction along the tunnel acquisition, i.e. the width direction of the image.
Further, the position mapping stitching is adopted for the image after the shearing correction, and the method comprises the following steps:
reading the corrected image, and marking to obtain a plurality of wave peaks;
selecting data between a first wave crest and a last wave crest in the plurality of wave crests and data of the first wave crest;
and (5) adopting position mapping and splicing to obtain a tunnel vault plane image.
Further, the reading of the corrected image and marking to obtain a plurality of peaks includes the following steps:
reading N images acquired by a camera, and marking the image storage time of the ith image as T i Adjacent images have a time interval D i ；
Drawing a waveform chart with an image sequence number as an abscissa and a graph storing time interval as an ordinate;
if the time interval D i If the data is larger than a preset threshold dT, marking the data as a peak and marking the data as F i ＝1；
If the time interval D i If the data is smaller than or equal to a preset threshold dT, marking the data as non-peak and marking the data as F i ＝0。
Further, the method for obtaining the tunnel vault plane image by adopting the position mapping and splicing comprises the following steps:
tiling the images to be spliced along the acquisition direction;
obtaining a circle with the largest quantity of the shot images of the camera rotating for one circle;
traversing the image to obtain the number dIndex of adjacent peak intervals i The expression is:
dIndex i ＝P k -P k-1
wherein P is k An image index representing a kth peak; p (P) k-1 An image index representing the kth-1 peak;
obtaining the maximum value of the index, wherein the expression is as follows:
iCircle＝max(dIndex i )
obtaining a row-column index value of any image to be spliced, wherein the expression is as follows:
ColIdx i ＝PeakCnt
RowIdx i ＝j-PeakIdx
wherein PeakCnt represents the number of peaks, peakIdx represents the index value corresponding to the peak; the value of j is the same as the index value corresponding to the wave crest;
the pixel position of any image is obtained, and the expression is as follows:
x i ＝ColIdx i *W
y i ＝RowIdx i *H
w represents the width of the image and H represents the height of the image.
Compared with the prior art, the application has the following beneficial effects:
(1) The application skillfully adopts the rotary linear array camera to collect the images of the tunnel vault, and solves the technical problem that the investment of the traditional tunnel detection stacking camera detection equipment is large; therefore, the application can realize that one camera detects and splices the apparent images of the tunnel segment.
(2) The curved surface is projected to the plane by adopting the position mapping method, so that the detection and analysis are more accurate;
(3) The application corrects the image deformation caused by the rotation and the forward movement of the rotary camera in an affine transformation mode, and carries out image shearing correction on the tunnel vault image after illumination compensation, and has the advantages that: the deformation caused by the rotation and the forward movement of the rotary camera can be corrected simply, efficiently and accurately, so that the image is more close to reality.
(4) The application adopts a histogram equalization algorithm to carry out illumination compensation on the tunnel vault image, and aims to eliminate the influence caused by the change of illumination conditions or the difference of sensing curves of imaging equipment, so that the histogram is in a uniformly distributed form. The application can enhance the contrast of the image and improve the quality of the image by carrying out histogram equalization treatment on the image;
in conclusion, the method has the advantages of simple logic, less calculation workload, reliable conversion and the like, and has high practical value and popularization value in the technical field of tunnel image processing.
Drawings
For a clearer description of the technical solutions of the embodiments of the present application, the drawings to be used in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope of protection, and other related drawings may be obtained according to these drawings without the need of inventive effort for a person skilled in the art.
Fig. 1 is a comparison of the illumination compensation of the present application.
Fig. 2 is a graph of the present application before and after image shearing correction.
FIG. 3 is a schematic diagram of a peak marking according to the present application.
Fig. 4 is a schematic diagram of an image tiling position according to the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the present application will be further described with reference to the accompanying drawings and examples, which include, but are not limited to, the following examples. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Examples
As shown in fig. 1 to 4, the present embodiment provides a tunnel vault image stitching method; the method comprises the following steps:
firstly, uniformly acquiring a tunnel vault image along a tunnel direction by adopting a rotary linear array camera;
secondly, adopting a histogram equalization algorithm to perform illumination compensation on the tunnel vault image;
(21) Global histogram equalization is performed on any tunnel dome image, and the input image and the output image satisfy the following formulas:
where k represents a gray value, H represents a height of the image, W represents a width of the image, hist O (k) A cumulative histogram representing the output image;
(22) Then, the cumulative histogram of the input image and the cumulative histogram of the output image satisfy the following relationship:
wherein, p, q E [0,255];
(23) The gray level P of the input image and the gray level q of the output image have the following correspondence,
wherein hist is I (k) Representing a cumulative histogram of the input image.
Thirdly, performing image shearing correction on the tunnel vault image subjected to illumination compensation;
affine transformation is carried out on the tunnel vault image after illumination compensation, and the expression is as follows:
where I denotes the illumination-compensated tunnel dome image, I' denotes the affine-derived image,for the angle offset in the y-direction of the image, +.>The shearing degree in the x direction is 0.04711914; the Y direction is along the tunnel acquisition direction, namely the width direction of the image; the x-direction is perpendicular to the acquisition direction, i.e. the height direction of the image.
And fourthly, splicing the images subjected to the shearing correction by adopting position mapping to obtain a spliced tunnel vault plane image. (41) Reading the corrected image, and marking to obtain a plurality of wave peaks;
reading N images acquired by a camera, and marking the image storage time of the ith image as T i In ns, the time interval between adjacent images is D i Unit ns;
D i ＝T i -T i-1 ；D O ＝0
i＝1...N
drawing a waveform chart with an image sequence number as an abscissa and a graph storing time interval as an ordinate; in this embodiment, it is apparent that the peak represents that the camera has rotated one revolution;
if the time interval D i If the data is larger than a preset threshold dT, marking the data as a peak and marking the data as F i =1; in this embodiment, the threshold dT takes on a value of 100000000;
if the time interval D i If the data is smaller than or equal to a preset threshold dT, marking the data as non-peak and marking the data as F i ＝0。
(42) Selecting data between a first wave crest and a last wave crest in the plurality of wave crests and data of the first wave crest;
(43) And (3) obtaining a tunnel vault plane image by adopting position mapping and splicing:
tiling the images to be spliced along the acquisition direction;
obtaining a circle with the largest quantity of the shot images of the camera rotating for one circle;
traversing the image to obtain the number dIndex of adjacent peak intervals i The expression is:
dIndex i ＝P k -P k-1
wherein P is k An image index representing a kth peak; p (P) k-1 An image index representing the kth-1 peak;
obtaining the maximum value of the index, wherein the expression is as follows:
iCircle＝max(dIndex i )
obtaining a row-column index value of any image to be spliced, wherein the expression is as follows:
ColIdx i ＝PeakCnt
RowIdx i ＝j-PeakIdx
wherein PeakCnt represents the number of peaks, peakIdx represents the index value corresponding to the peak; the value of j is the same as the index value corresponding to the wave crest;
the pixel position of any image is obtained, and the expression is as follows:
x i ＝ColIdx i *W
y i ＝RowIdx i *H
the (x, y, W, H) is used to represent a rectangular area to mark the pixel locations where each map should be placed in the tiled large map.
Then record (x) of figure i i ,y i W, H), where x i ，y i Respectively representing the pixel coordinates of the upper left corner of the graph;
w represents the width of the image, and H represents the height of the image; in the present embodiment, w=h=4096.
The above embodiments are only preferred embodiments of the present application and are not intended to limit the scope of the present application, but all changes made by adopting the design principle of the present application and performing non-creative work on the basis thereof shall fall within the scope of the present application.
Claims (4)
1. A method for stitching a tunnel vault image, comprising the steps of:
adopting a rotary linear array camera to uniformly acquire a tunnel vault image along the tunnel direction;
adopting a histogram equalization algorithm to perform illumination compensation on the tunnel vault image;
performing image shearing correction on the tunnel vault image subjected to illumination compensation;
position mapping splicing is adopted on the sheared and corrected images, so that a spliced tunnel vault plane image is obtained;
the method for carrying out illumination compensation on the tunnel vault image by adopting a histogram equalization algorithm comprises the following steps:
global histogram equalization is performed on any tunnel dome image, and the input image and the output image satisfy the following formulas:
where k represents a gray value, H represents a height of the image, W represents a width of the image, hist O (k) A cumulative histogram representing the output image;
the gray level P of the input image and the gray level q of the output image are calculated, which satisfy the following formula:
wherein hist is I (k) A cumulative histogram representing the input image;
performing image shearing correction on the tunnel vault image after illumination compensation, comprising the following steps:
affine transformation is carried out on the tunnel vault image after illumination compensation, and the expression is as follows:
where I denotes the illumination-compensated tunnel dome image, I' denotes the affine-derived image,for the angle offset in the y-direction of the image, +.>The degree of shear in the x direction; the X direction is perpendicular to the acquisition direction, namely the height direction of the image; the Y direction refers to the direction along the tunnel acquisition, i.e. the width direction of the image.
2. A method of stitching tunnel dome images in accordance with claim 1 wherein the shear corrected images are stitched using a position map comprising the steps of:
reading the corrected image, and marking to obtain a plurality of wave peaks;
selecting data between a first wave crest and a last wave crest in the plurality of wave crests and data of the first wave crest;
and (5) adopting position mapping and splicing to obtain a tunnel vault plane image.
3. The method for splicing tunnel dome images according to claim 2, wherein the steps of reading the corrected image and marking to obtain a plurality of peaks, comprises the steps of:
reading N images acquired by a camera, and marking the image storage time of the ith image as T i Adjacent images have a time interval D i ；
Drawing a waveform chart with an image sequence number as an abscissa and a graph storing time interval as an ordinate;
if the time interval D i If the data is larger than a preset threshold dT, marking the data as a peak and marking the data as F i ＝1；
If the time interval D i If the data is smaller than or equal to a preset threshold dT, marking the data as non-peak and marking the data as F i ＝0。
4. The method for splicing the tunnel dome images according to claim 2, wherein the method for splicing the tunnel dome plane images by using the position mapping comprises the following steps:
tiling the images to be spliced along the acquisition direction;
obtaining a circle with the largest quantity of the shot images of the camera rotating for one circle;
traversing the image to obtain the number dIndex of adjacent peak intervals i The expression is:
dIndex i ＝P k -P k-1
wherein P is k An image index representing a kth peak; p (P) k-1 An image index representing the kth-1 peak;
obtaining the maximum value of the index, wherein the expression is as follows:
iCircle＝max(dIndex i )
obtaining a row-column index value of any image to be spliced, wherein the expression is as follows:
ColIdx i ＝PeakCnt
RowIdx i ＝j-PeakIdx
wherein PeakCnt represents the number of peaks, peakIdx represents the index value corresponding to the peak; the value of j is the same as the index value corresponding to the wave crest;
the pixel position of any image is obtained, and the expression is as follows:
x i ＝ColIdx i *W
y i ＝RowIdx i *H
w represents the width of the image and H represents the height of the image.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| JP2015049765A (en) * | 2013-09-03 | 2015-03-16 | 公益財団法人鉄道総合技術研究所 | Method of correcting distortion of tunnel lining surface image |
| CN109358065A (en) * | 2018-10-22 | 2019-02-19 | 湖南拓达结构监测技术有限公司 | A kind of subway tunnel appearance detecting method |
| CN109801216A (en) * | 2018-12-20 | 2019-05-24 | 武汉武大卓越科技有限责任公司 | The quick joining method of Tunnel testing image |
| CN110033407A (en) * | 2019-03-29 | 2019-07-19 | 华中科技大学 | A kind of shield tunnel surface image scaling method, joining method and splicing system |
| CN110827199A (en) * | 2019-10-29 | 2020-02-21 | 武汉大学 | Tunnel image splicing method and device based on guidance of laser range finder |
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- 2020-12-04 CN CN202011415199.6A patent/CN112435170B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2015049765A (en) * | 2013-09-03 | 2015-03-16 | 公益財団法人鉄道総合技術研究所 | Method of correcting distortion of tunnel lining surface image |
| CN109358065A (en) * | 2018-10-22 | 2019-02-19 | 湖南拓达结构监测技术有限公司 | A kind of subway tunnel appearance detecting method |
| CN109801216A (en) * | 2018-12-20 | 2019-05-24 | 武汉武大卓越科技有限责任公司 | The quick joining method of Tunnel testing image |
| CN110033407A (en) * | 2019-03-29 | 2019-07-19 | 华中科技大学 | A kind of shield tunnel surface image scaling method, joining method and splicing system |
| CN110827199A (en) * | 2019-10-29 | 2020-02-21 | 武汉大学 | Tunnel image splicing method and device based on guidance of laser range finder |
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