CN113587829B - Edge thickness measuring method and device, edge thickness measuring equipment and medium - Google Patents
Edge thickness measuring method and device, edge thickness measuring equipment and medium Download PDFInfo
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Abstract
The embodiment of the invention discloses an edge thickness measuring method, an edge thickness measuring device, edge thickness measuring equipment and a medium. The edge thickness measuring method comprises the following steps: acquiring a rotation translation matrix between a first linear array camera and a second linear array camera which are arranged on two sides of a scanning platform; shooting a material to be detected through a first linear array camera to obtain a first material depth image, fitting an initial material edge reference plane where the edge of the material to be detected is located, and determining a material edge thickness measurement interest area according to the initial material edge reference plane; switching the initial material edge reference plane from a first coordinate system to a second coordinate system according to the rotation translation matrix to obtain a target material edge reference plane; and under a second coordinate system, measuring the distance from the three-dimensional space point in the material edge thickness measurement interest area to the target material edge reference plane to be used as an edge thickness value of the material to be measured. So as to improve the measurement precision and efficiency, save the measurement cost and simplify the measurement means.
Description
Technical Field
The embodiment of the invention relates to the technical field of machine vision detection, in particular to an edge thickness measuring method and device, edge thickness measuring equipment and medium.
Background
The 3C industry refers to the information home appliance industry which integrates and applies three major technical products of computers, communication and consumer electronics, and the 3C industry has very wide application on copper sheets and simultaneously controls the quality of the copper sheets. Taking the thickness of the copper sheet as an example, in the production process of electronic equipment such as a mobile phone and the like, whether the thickness of the edge of the copper sheet meets the requirement (the general required precision range is within +/-0.03 mm) strictly limits the heat dissipation effect of the back of the middle frame of the mobile phone, and if the copper sheet is too thick, the copper sheet can not be put into or arch, and if the copper sheet is too thin, the heat conduction effect is poor. Therefore, to ensure the dimensional accuracy of the thickness of the edge of the copper sheet, the copper sheet needs to be detected at proper time.
At present, the traditional copper sheet edge thickness detection method is to manually measure by a vernier caliper, but the manual measurement can cause measurement errors due to various uncertain factors, so that the requirements of modern industry on the efficiency, precision and the like of a measurement process cannot be met, and meanwhile, the labor cost and the management cost of a factory are increased. In addition, the thickness of the copper sheet edge can also be measured in a non-contact mode, for example, a line white light confocal technology, a laser displacement meter, a 3D profile measuring instrument and the like are used for measuring, and although the measuring mode can meet the requirement of the dimensional accuracy of the copper sheet edge thickness, the cost and the complexity of measuring equipment are increased at the same time.
Disclosure of Invention
The embodiment of the invention provides an edge thickness measuring method, an edge thickness measuring device and a medium, so that the measuring precision and efficiency are improved, the measuring cost is saved, and the measuring means are simplified.
In a first aspect, an embodiment of the present invention provides an edge thickness measurement method, including:
acquiring a rigid transformation relation between a first linear array camera and a second linear array camera coordinate system which are arranged on two sides of a scanning platform, wherein the rigid transformation relation is represented by a rotation translation matrix between the first coordinate system where the first linear array camera is positioned and the second coordinate system where the second linear array camera is positioned;
after placing a material to be tested on the scanning platform, starting the scanning platform to move, and respectively shooting the material to be tested through the first linear array camera and the second linear array camera to correspondingly obtain a first material depth image and a second material depth image of the material to be tested;
fitting an initial material edge reference plane where the material edge to be measured is located according to the first material depth image, and determining a material edge thickness measurement interest area according to the initial material edge reference plane, wherein a coordinate system of the initial material edge reference plane is the first coordinate system;
Switching the coordinate system of the initial material edge reference plane from the first coordinate system to the second coordinate system according to the rotation translation matrix to obtain a target material edge reference plane, wherein the coordinate system of the target material edge reference plane is the second coordinate system;
and under the second coordinate system, measuring the distance from the three-dimensional space point in the interest area to the target material edge reference plane in the corresponding material edge thickness measurement interest area in the second material depth image, and taking the distance as the edge thickness value of the material to be measured.
In a second aspect, an embodiment of the present invention further provides an edge thickness measurement apparatus, including:
the rigid transformation relation determining module is used for obtaining rigid transformation relation between the first linear array camera and the second linear array camera coordinate systems arranged on two sides of the scanning platform, and the rigid transformation relation is represented by a rotation translation matrix between the first coordinate system where the first linear array camera is located and the second coordinate system where the second linear array camera is located;
the depth image acquisition module is used for starting the scanning platform to move after the material to be detected is placed on the scanning platform, and shooting the material to be detected through the first linear array camera and the second linear array camera respectively to correspondingly obtain a first material depth image and a second material depth image of the material to be detected;
The plane fitting module is used for fitting an initial material edge reference plane where the material edge to be measured is located according to the first material depth image, determining a material edge thickness measurement interest area according to the initial material edge reference plane, and the coordinate system of the initial material edge reference plane is the first coordinate system;
the coordinate system conversion module is used for switching the coordinate system of the initial material edge reference plane from the first coordinate system to the second coordinate system according to the rotation translation matrix to obtain a target material edge reference plane, wherein the coordinate system of the target material edge reference plane is the second coordinate system;
and the edge thickness value determining module is used for measuring the distance from the three-dimensional space point in the interest area to the edge reference plane of the target material, which is measured by the corresponding material edge thickness in the second material depth image, in the second coordinate system, and taking the distance as the edge thickness value of the material to be measured.
In a third aspect, an embodiment of the present invention further provides an edge thickness measurement apparatus, including:
a first line camera and a second line camera;
a scanning platform;
One or more processors;
a storage means for storing a plurality of programs,
the at least one of the plurality of programs, when executed by the one or more processors, cause the one or more processors to implement an edge thickness measurement method provided by an embodiment of the first aspect of the present invention.
In a fourth aspect, embodiments of the present invention further provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements an edge thickness measurement method provided by an embodiment of the first aspect of the present invention.
According to the technical scheme, the rigid transformation relation between the first linear array camera and the second linear array camera arranged on two sides of the scanning platform is obtained, and the rigid transformation relation is represented by a rotation translation matrix between the first coordinate system where the first linear array camera is located and the second coordinate system where the second linear array camera is located; after placing a material to be tested on a scanning platform, starting the scanning platform to move, and respectively shooting the material to be tested through a first linear array camera and a second linear array camera to correspondingly obtain a first material depth image and a second material depth image of the material to be tested; fitting an initial material edge reference plane where the material edge to be measured is located according to the first material depth image, and determining a material edge thickness measurement interest area according to the initial material edge reference plane, wherein the coordinate system of the initial material edge reference plane is a first coordinate system; switching a coordinate system of an initial material edge reference plane from a first coordinate system to a second coordinate system according to the rotation translation matrix to obtain a target material edge reference plane, wherein the coordinate system of the target material edge reference plane is the second coordinate system; and under a second coordinate system, measuring the distance from the three-dimensional space point in the interest area to the edge reference plane of the target material in the corresponding material edge thickness measurement interest area in the measured second material depth image, and taking the distance as the edge thickness value of the material to be measured. The method solves the problems that the current edge thickness detection method is to manually measure by a vernier caliper, the requirements of the modern industry on the efficiency, the precision and the like of the measurement process cannot be met, and the cost and the complexity of measurement equipment are increased by other measurement technologies, so that the measurement precision and the efficiency are improved, the measurement cost is saved, and the measurement means are simplified.
Drawings
FIG. 1 is a flow chart of a method for measuring edge thickness according to a first embodiment of the present invention;
FIG. 2 is a flow chart of a method for measuring edge thickness according to a second embodiment of the present invention;
fig. 3 is a schematic diagram of a construction structure of a first line camera, a second line camera and a scanning platform according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of an edge thickness measurement principle according to an embodiment of the present invention;
FIG. 5 is a block diagram of an edge thickness measuring device according to a third embodiment of the present invention;
fig. 6 is a schematic hardware structure of an edge thickness measuring device according to a fourth embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the following detailed description of specific embodiments of the present invention is given with reference to the accompanying drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof.
It should be further noted that, for convenience of description, only some, but not all of the matters related to the present invention are shown in the accompanying drawings. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart depicts operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently, or at the same time. Furthermore, the order of the operations may be rearranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figures. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Example 1
Fig. 1 is a flowchart of an edge thickness measurement method according to an embodiment of the present invention, where the embodiment is applicable to a case of accurately measuring an edge thickness of a copper sheet in an electronic device, the edge thickness measurement method may be performed by an edge thickness measurement device, and the edge thickness measurement device may be implemented in a software and/or hardware form. The edge thickness measuring method specifically comprises the following steps:
s110, acquiring a rigid transformation relation between a first linear array camera and a second linear array camera coordinate system which are arranged on two sides of a scanning platform, wherein the rigid transformation relation is represented by a rotation translation matrix between the first coordinate system where the first linear array camera is located and the second coordinate system where the second linear array camera is located.
The scanning platform is used for placing the material to be measured and the calibration plate and can drive the material to be measured or the calibration plate to move so as to enable the linear array camera to collect images of the material to be measured or the calibration plate, and the scanning platform adopts a conventional platform used by the conventional edge thickness measuring equipment.
The first linear array camera is a first linear scanning camera, the second linear array camera is a second linear scanning camera, and the sensors of the first linear array camera and the second linear array camera are only formed by one or more rows of photosensitive chips, so that the first linear array camera and the second linear array camera need to form relative motion through mechanical motion when photographing, and further corresponding images are obtained through photographing.
In this embodiment, the scanning platform is driven by the motor to move at a uniform speed in a transverse direction or a longitudinal direction, and the first line camera and the second line camera acquire a line of images at a fixed time interval, wherein the time interval is mainly dependent on light integration time, and the acquired multiple lines of images are combined into a complete image, so that image shooting of the material to be detected or the calibration plate is completed.
On the basis of the above, obtaining the rigid transformation relation between the first linear array camera and the second linear array camera installed on two sides of the scanning platform, comprising: after a calibration plate with a plurality of calibration balls is placed on the scanning platform, starting the scanning platform to move, and shooting the calibration plate through the first linear array camera and the second linear array camera respectively to correspondingly obtain a first calibration depth image and a second calibration depth image of the calibration plate; respectively determining the spherical center coordinates of each calibration sphere according to the first calibration depth image and the second calibration depth image, and correspondingly obtaining a first calibration point set and a second calibration point set; and determining a rigid body transformation relation between the first linear array camera and the second linear array camera coordinate system according to the first calibration point set and the second calibration point set.
Further, the number of elements in the first set of calibration points is the same as the number of elements in the second set of calibration points and corresponds to each other one by one; before determining the rigid body transformation relation between the first linear array camera and the second linear array camera coordinate system according to the first set of calibration points and the second set of calibration points, the method further comprises: calibrating elements in the first calibration point set and the second calibration point set, wherein the elements correspond to each other one by one; and screening the elements in the first calibration point set and the second calibration point set according to the point distances among the calibrated one-to-one corresponding elements.
S120, after the material to be detected is placed on the scanning platform, the scanning platform is started to move, the first linear array camera and the second linear array camera are used for respectively shooting the material to be detected, and a first material depth image and a second material depth image of the material to be detected are correspondingly obtained.
The material to be tested is a heat conducting copper sheet in the embodiment, and the long side of the heat conducting copper sheet is parallel to the moving direction of the scanning platform and the long side direction of the first linear array camera and the second linear array camera.
The scanning platform moves in a set stroke, the set stroke of the scanning platform is the effective physical movement stroke of the moving platform, and optionally, the set stroke of the scanning platform is about 50 mm.
Specifically, after the scanning platform starts to move, the encoder is used for triggering the first linear array camera and the second linear array camera to acquire depth images of the materials to be detected, and a first material depth image and a second material depth image of the materials to be detected are obtained.
S130, fitting an initial material edge reference plane where the material edge to be measured is located according to the first material depth image, and determining a material edge thickness measurement interest area according to the initial material edge reference plane, wherein a coordinate system of the initial material edge reference plane is the first coordinate system.
The material edge thickness measurement region of interest is a region of interest selected on an initial material edge reference plane, and a coordinate system of a plane in which the material edge thickness measurement region of interest is located is the first coordinate system.
It can be understood that in this embodiment, an initial material edge reference plane where the material to be measured is located may also be fitted according to the second material depth image, and the material edge thickness measurement interest area may be determined according to the initial material reference plane, where the coordinate system of the initial material edge reference plane is the second coordinate system. Further, according to the rotation translation matrix, the coordinate system of the initial material edge reference plane is switched from the second coordinate system to the first coordinate system, so that a target material edge reference plane is obtained, and the coordinate system of the target material edge reference plane is the first coordinate system; and under a first coordinate system, measuring the distance from a three-dimensional space point in a region of interest to the target material edge reference plane in the corresponding material edge thickness measurement interest in the first material depth image, and taking the distance as an edge thickness value of the material to be measured.
In this embodiment, the method for fitting the initial material edge reference plane where the material edge to be measured is located may be based on an improved RANSAC algorithm (random sampling consensus algorithm, RANdom SAmple Consensus), a suboptimal plane is obtained by setting a distance threshold, a confidence level or an outlier proportion, and then an optimal fitting plane is obtained by a method of iterative optimization of the suboptimal plane, so as to obtain the initial material edge reference plane in this embodiment.
The RANSAC algorithm is an iterative method for estimating parameters of a mathematical model from a set of observed data containing outliers. The RANSAC algorithm assumes that the data contains both correct data and anomalous data (otherwise known as noise). The correct data is denoted as interior points (inliers) and the outliers (outliers), while the RANSAC algorithm also assumes that given a set of correct data, there are methods by which model parameters that fit these data can be calculated. The core idea of the RANSAC algorithm is randomness and supposition, the randomness is to randomly select sampling data according to the probability of occurrence of correct data, and the randomness simulation can approximately obtain a correct result according to the law of large numbers. The assumption is that the sampled data selected are all correct data, then the correct data are used to calculate other points through the model of the problem satisfaction, and then the result is scored.
On the basis, according to the first material depth image, a plane fitting method with external points is carried out based on a RANSAC algorithm, and an initial material edge reference plane is obtained. The method comprises the following steps: extracting feature points of the first material depth image, and determining model parameter points according to the extracted feature points of the first material depth image through a minimum variance estimation algorithm; if the deviation between the characteristic points and the model parameter points is smaller than a deviation threshold value, the characteristic points are considered as sample points in the model; after traversing all the characteristic points in the first material depth image, recording sample points in the model, and fitting an initial material edge reference plane where the edges of the materials to be detected are located according to the sample points in the model.
Specifically, in this embodiment, feature point extraction is performed on the first material depth image, a feature point sample subset is randomly extracted from the extracted feature point samples, model parameter points are determined on the feature point sample subset through a minimum variance estimation algorithm, and then deviations between feature points and model parameter points in all the feature point samples are calculated, that is, deviation thresholds are set. If the deviation between the characteristic points and the model parameter points is smaller than a deviation threshold value, the characteristic points are identified as sample points (inliers) in the model, or called internal points, local internal points or internal points; and if the deviation between the characteristic points and the model parameter points is greater than a deviation threshold, identifying the characteristic points as model outlier sample points (outliers), or called outliers, outliers or outliers. After traversing all the characteristic points in the first material depth image, recording sample points in the model, and fitting an initial material edge reference plane where the edges of the materials to be detected are located according to the sample points in the model.
After each deviation judgment is performed on one feature point, the optimal model parameters corresponding to the RANSAC algorithm, namely the number of sample points in the model is the greatest, and the number of the corresponding sample points in the model is recorded as the number of the corresponding sample points in the model. And traversing all the characteristic points in the first material depth image, calculating an iteration ending judgment factor at the end of each iteration according to the expected error rate, the number of the total characteristic sample points and the current iteration times, and determining whether the iteration is ended or not based on the iteration ending judgment factor. After the iteration is finished, the optimal model parameter is the final model parameter estimated value, and then an initial material edge reference plane where the edge of the material to be measured is positioned is fitted according to the sample points in the model.
And S140, switching the coordinate system of the initial material edge reference plane from the first coordinate system to the second coordinate system according to the rotation translation matrix to obtain a target material edge reference plane, wherein the coordinate system of the target material edge reference plane is the second coordinate system.
Specifically, according to a rigid transformation relationship between the first linear array camera and the second linear array camera, namely a rotation translation matrix, the coordinate system of the initial material edge reference plane is switched from the first coordinate system to the second coordinate system, so as to obtain a target material edge reference plane, wherein the coordinate system of the target material edge reference plane is the second coordinate system.
Exemplary, specific coordinate system switching processes are as follows:
1) Writing an initial material edge reference plane equation into a matrix form as follows:
2) The points in the initial material edge reference plane are transformed by a rotation translation matrix T:
3) After carrying out inverse transformation on points in an initial material edge reference plane, substituting the points into an initial material edge reference plane equation, and then carrying out rotation translation transformation on a rotation translation matrix T to obtain a target material edge reference plane matrix equation, wherein the target material edge reference plane equation is as follows:
further, the material edge thickness measurement interest area is an interest area selected on the initial material edge reference plane, and then the coordinate system of the plane of the material edge thickness measurement interest area is switched from the first coordinate system to the second coordinate system, that is, the plane of the current material edge thickness measurement interest area is the target material edge reference plane.
And S150, measuring the distance from the three-dimensional space point in the interest area to the target material edge reference plane in the corresponding material edge thickness measurement interest area in the second material depth image under the second coordinate system, and taking the distance as the edge thickness value of the material to be measured.
The distance measurement from the three-dimensional space point in the region of interest of measuring the thickness of the edge of the material corresponding to the second material depth image to the target material edge reference plane can be obtained by measuring through an existing thickness measuring module or a software tool in the existing edge thickness measuring equipment, and the embodiment is not limited in any way.
Specifically, an existing thickness measurement module or software tool in the existing edge thickness measurement equipment measures the thickness distance from a three-dimensional space point in a region of interest to the edge reference plane of the target material by acquiring the corresponding material edge thickness in the second material depth image, and completes statistics of thickness information such as a thickness distance histogram, a minimum value, a maximum value, a mean value, a median value, a standard deviation, a low tail or a high tail, so as to realize more accurate acquisition of thickness distance distribution, thereby determining the edge thickness value of the material to be measured.
In an embodiment, in the second coordinate system, measuring distances from three-dimensional space points in the region of interest to the target material edge reference plane in the corresponding material edge thicknesses in the plurality of measured second material depth images; dividing the distances from the three-dimensional space points in the material edge thickness measurement interested areas corresponding to the plurality of second material depth images to the target material edge reference plane into at least one data screening interested area, and selecting the distance with the largest value in each data screening interested area as the edge thickness value of the material to be measured. Further, after dividing the plurality of distances into at least one data filtering region of interest, further comprising: and selecting the distance of the data screening interested region, wherein the value of the distance is larger than the lower thickness threshold and smaller than the upper thickness threshold, and determining the target distance in the data screening interested region according to the high tail value.
In another embodiment, in the second coordinate system, a thickness distance histogram is generated based on the measured distances from the three-dimensional space points in the region of interest to the target material edge reference plane measured on the basis of the measured corresponding material edge thicknesses in the second material depth image; and selecting the distance meeting the preset thickness range as a target distance according to the thickness distance histogram, and determining the edge thickness value of the material to be detected according to the target distance.
According to the technical scheme, the problem that the existing edge thickness detection method is manually used for measuring through a vernier caliper, the requirements of the modern industry on the efficiency, the precision and the like of a measuring process cannot be met, and meanwhile, other measuring technologies increase the cost and the complexity of measuring equipment is solved, so that the measuring precision and the efficiency are improved, the measuring cost is saved, and meanwhile, the measuring means are simplified.
Example two
Fig. 2 is a flowchart of a method for measuring edge thickness according to a second embodiment of the present invention, which is optimized based on the above embodiment.
Correspondingly, the edge thickness measuring method of the embodiment specifically includes:
s210, after a calibration plate with a plurality of calibration balls is placed on the scanning platform, the scanning platform is started to move, the first linear array camera and the second linear array camera are used for shooting the calibration plate respectively, and a first calibration depth image and a second calibration depth image of the calibration plate are correspondingly obtained.
Fig. 3 is a schematic diagram of a construction structure of a first line camera, a second line camera and a scanning platform provided in an embodiment of the present invention, referring to fig. 3, in the drawing, the first line camera 310, the second line camera 320 and the scanning platform 330 are placed according to the drawing, where the calibration plate 340 is a metal calibration plate with high-precision calibration balls, optionally, the calibration plate 340 is a metal calibration plate with 10 x 10 calibration balls, each calibration ball has a radius of 5mm, and the calibration plate 340 is used for calibrating rigid transformation relations between the first line camera 310 and the second line camera 320. It will be appreciated that the calibration plate 340 is mounted on the fixture of the scanning platform 330 before the edge thickness measurement is started and removed after calibration.
It should be noted that, in order to ensure the accuracy of the images shot by the first line-up camera and the second line-up camera, avoid the imaging interference of the first line-up camera and the second line-up camera, the light outlets of the first line-up camera and the second line-up camera need to be ensured to be incompletely aligned, and optionally, the first line-up camera and the second line-up camera are staggered by about 8mm in the short side direction. The light outlets of the first linear array camera and the second linear array camera are not completely aligned, and a Micro ToF technical scheme can be adopted, namely, the influence of indirect light is reduced or eliminated by observing the changes of the phase and amplitude of the direct light and the indirect light, so that a certain distance is staggered.
S220, respectively determining the spherical center coordinates of each calibration sphere according to the first calibration depth image and the second calibration depth image, and correspondingly obtaining a first calibration point set and a second calibration point set.
Specifically, corresponding calibration balls are selected from the first calibration depth image and the second calibration depth image respectively, one or more calibration balls can be selected, and spherical center coordinates of each calibration ball are sequentially extracted by a sphere fitting method, so that a first calibration point set corresponding to the first calibration depth image is obtained, and a second calibration point set corresponding to the second calibration depth image is obtained.
It can be understood that the number of elements in the first calibration point set is the same as the number of elements in the second calibration point set, and the elements are in one-to-one correspondence, that is, the order of the calibration balls extracted from the first calibration depth image and the second calibration depth image is to one-to-one correspondence, and the positions of the calibration balls are selected to be distributed as diffusely as possible, and the calibration balls cannot be collinear.
For example, in order to obtain the spherical center coordinates of the same calibration sphere in the coordinate system of the first linear array camera and the second linear array camera, the radius and the position of the spherical center are obtained by fitting the point cloud data of the same calibration sphere to the first calibration depth image and the second calibration depth image. Specifically, in this embodiment, a gauss newton method is adopted, an initial calibration sphere center circle center c and a radius r are given first, the initial calibration sphere center circle center c and the radius r are given randomly, then iteration solution is performed to update the circle center c and the radius r, and the circle center c and the radius r are solved through a jacobian matrix, and a specific iteration process is as follows:
Setting p i For a point on a sphere, the sphere equation is derived: f (f) i (c,r)＝||c-p i || 2 -r 2 ；
Error equation:
namely: e= ||F (c, r) || 2
Wherein: f (c, r) = [ F 1 (c,r),...,f 2 (c,r)]
In order to obtain the center c and the radius r, the function error is minimized: (c, r) * ＝argmin||F(c,r)|| 2
Wherein: f (c) k+1 ,r k+1 )≈F(c k ,r k )+δJ k (c,r)
δ＝(c k+1 ,r k+1 )-(c k ,r k )
Further, the following steps are obtained: delta * ＝argmin||F(c k ,r k )+δJ k (c,r)|| 2
Wherein: j (J) k (c k ,r k ) T J k (c k ,r K )δ＝-J k (c k ,r k ) T F(c k ,r k )
The jacobian matrix is:
deriving to obtain a circle center c and a radius r:
s230, determining a rigid transformation relation between the first linear array camera and the second linear array camera coordinate system according to the first calibration point set and the second calibration point set, wherein the rigid transformation relation is represented by a rotation translation matrix between the first coordinate system where the first linear array camera is located and the second coordinate system where the second linear array camera is located.
The rotation translation matrix comprises a rotation matrix and a translation matrix, and the rigid body transformation relation between the first coordinate system and the second coordinate system is represented through the rotation matrix and the translation matrix.
On the basis of the above embodiment, before determining the rigid body transformation relationship between the first line-camera and the second line-camera coordinate system according to the first set of calibration points and the second set of calibration points, the method further includes: calibrating elements in the first calibration point set and the second calibration point set, wherein the elements correspond to each other one by one; and screening the elements in the first calibration point set and the second calibration point set according to the point distances among the calibrated one-to-one corresponding elements.
Specifically, the rigid body change relation between the first linear array camera and the second linear array camera coordinate system can be obtained through a global calibration tool carried by the first linear array camera and the second linear array camera. The specific calibration process is as follows: and calibrating the global calibration tool by the extracted first calibration point set and second calibration point set, namely, just starting to select as many calibration point pairs as possible for calibration, then screening elements in the first calibration point set and the second calibration point set according to the point distances among calibrated one-to-one corresponding elements, and eliminating point pairs with large errors.
Illustratively, assume that the first set of calibration points p=p 1 ,p 2 ,...,p n And a second set of calibration points q=q 1 ,q 2 ,...,q n Wherein p and q are coordinates of elements in the first set of calibration points and the second set of calibration points, i.e. the center c. To find the rigid transformation relationship between the first set of calibration points and the second set of calibration points, i.eThe rotation matrix R and translation matrix t can be modeled as follows:
the first set of calibration points and the second set of calibration points are de-centered, and the new point sets x and y are expressed as:
x i :＝p i -p
y i :＝q i -q
at this time, the matrix is shifted: t=q-Rp
Rotating the matrix:
in order to make tr (sigma V) t RU) reaches a maximum value, i=v T RU
Gradually simplifying to obtain a rotation matrix: v=ru, r=vu T 。
S240, after the material to be detected is placed on the scanning platform, the scanning platform is started to move, the first linear array camera and the second linear array camera are used for respectively shooting the material to be detected, and a first material depth image and a second material depth image of the material to be detected are correspondingly obtained.
S250, fitting an initial material edge reference plane where the material edge to be measured is located according to the first material depth image, and determining a material edge thickness measurement interest area according to the initial material edge reference plane, wherein a coordinate system of the initial material edge reference plane is the first coordinate system.
On the basis of the above embodiment, fitting an initial material edge reference plane where the edge of the material to be measured is located according to the first material depth image includes: extracting feature points of the first material depth image, and determining model parameter points according to the extracted feature points of the first material depth image through a minimum variance estimation algorithm; if the deviation between the characteristic points and the model parameter points is smaller than a deviation threshold value, the characteristic points are considered as sample points in the model; after traversing all the characteristic points in the first material depth image, recording sample points in the model, and fitting an initial material edge reference plane where the edges of the materials to be detected are located according to the sample points in the model.
S260, switching the coordinate system of the initial material edge reference plane from the first coordinate system to the second coordinate system according to the rotation translation matrix to obtain a target material edge reference plane, wherein the coordinate system of the target material edge reference plane is the second coordinate system.
And S270, measuring the distance from the three-dimensional space point in the interest area to the target material edge reference plane in the corresponding material edge thickness measurement interest area in the second material depth image under the second coordinate system, and taking the distance as the edge thickness value of the material to be measured.
Specifically, the material edge thickness measurement interested area is used as a measurement area, the distance measurement from the three-dimensional space point in the corresponding material edge thickness measurement interested area in the second material depth image to the target material edge reference plane is performed under the second coordinate system by using the existing thickness measurement module or software tool in the existing edge thickness measurement equipment, namely, the thickness measurement is performed on the measured material edge, fig. 4 is a schematic diagram of the edge thickness measurement principle provided by the embodiment of the invention, and referring to fig. 4, the upper and lower limits of the edge thickness range can be floated up and down by 0.15mm according to the true value of the measured material, the high tail fraction is set to be 0.05, and the noise point is removed in cooperation with the upper and lower limits.
In an embodiment, in the second coordinate system, measuring distances from three-dimensional space points in the region of interest to the target material edge reference plane in the corresponding material edge thicknesses in the plurality of measured second material depth images; dividing the distances into at least one data screening interested region, and selecting the distance with the largest value in each data screening interested region as the edge thickness value of the material to be tested. Further, after dividing the plurality of distances into at least one data filtering region of interest, further comprising: and selecting the distance of the data screening interested region, wherein the value of the distance is larger than the lower thickness threshold and smaller than the upper thickness threshold, and determining the target distance in the data screening interested region according to the high tail value.
Exemplary, thickness data h=h from a three-dimensional space point in a region of interest of the corresponding material edge thickness measurement in the plurality of the second material depth images to the target material edge reference plane is obtained through thickness measurement 1 ,h 2 ,...,h n The total number of thickness data is Num, the distances are divided into at least one data screening interested region, and the segmentation limit of the statistical interval is x i I=0, 1,2. Further, an upper limit thickness threshold value and a lower limit thickness threshold value, namely a minimum thickness value and a maximum thickness value in the thickness data, are used, so that extraction noise points are eliminated.
Then, selecting 0.05 high tail value in each data screening interested region as output thickness, and determining target distance in the data screening interested region, wherein the high tail value refers to a thickness value of which the data quantity is larger than a certain value and reaches a specified proportion;
wherein, highFrac is the proportion parameter of high tail value, and the value range is [0,1].
And finally, selecting the maximum value of thickness data in the region of interest of measuring the edge thickness of all the materials as the edge thickness value of the material to be measured.
In another embodiment, in the second coordinate system, a thickness distance histogram is generated based on the measured distances from the three-dimensional space points in the region of interest to the target material edge reference plane measured on the basis of the measured corresponding material edge thicknesses in the second material depth image; and selecting the distance meeting the preset thickness range as a target distance according to the thickness distance histogram, and determining the edge thickness value of the material to be detected according to the target distance.
In the edge thickness measurement process, a thickness distance histogram is generated, histogram statistics is observed, calculated thickness data are filtered, and the distance meeting the preset thickness range is selected as a target distance, so that the edge thickness measurement process is assisted to be analyzed in cooperation with a visualization tool, and the accuracy of the edge thickness measurement is ensured.
According to the technical scheme, based on the depth image thickness measurement method, only the scanning platform is carried on the realization, so that the increase of equipment cost and system complexity is avoided; the relative thickness at the same position is measured, so that the edge thickness measurement precision is higher, and the measurement method can meet the detection precision and the speed requirement during workpiece measurement through practical detection; on the other hand, when the edge thickness is measured, only data in the depth direction of the material is selected for processing, so that the method has higher robustness to environmental change, and the influence of noise on the thickness measurement accuracy of the copper sheet material can be effectively reduced.
Example III
Fig. 5 is a block diagram of an edge thickness measuring device according to a third embodiment of the present invention, where the embodiment is applicable to a case of accurately measuring an edge thickness of a copper sheet in an electronic device.
As shown in fig. 5, the edge thickness measuring device includes: a rigid body transformation relationship determination module 510, a depth image acquisition module 520, a plane fitting module 530, a coordinate system conversion module 540, and an edge thickness value determination module 550, wherein:
the rigid transformation relation determining module 510 is configured to obtain a rigid transformation relation between a first linear array camera and a second linear array camera coordinate system installed on two sides of the scanning platform, where the rigid transformation relation is represented by a rotational translation matrix between the first coordinate system where the first linear array camera is located and the second coordinate system where the second linear array camera is located;
the depth image obtaining module 520 is configured to place a material to be tested on the scanning platform, then start the scanning platform to move, and respectively shoot the material to be tested through the first line-scan camera and the second line-scan camera to correspondingly obtain a first material depth image and a second material depth image of the material to be tested;
the plane fitting module 530 is configured to fit an initial material edge reference plane where the material edge to be measured is located according to the first material depth image, and determine a material edge thickness measurement interest area according to the initial material edge reference plane, where a coordinate system of the initial material edge reference plane is the first coordinate system;
The coordinate system conversion module 540 is configured to switch the coordinate system of the initial material edge reference plane from the first coordinate system to the second coordinate system according to the rotation translation matrix, so as to obtain a target material edge reference plane, where the coordinate system of the target material edge reference plane is the second coordinate system;
and an edge thickness value determining module 550, configured to use, in the second coordinate system, the measured distance from the three-dimensional space point in the region of interest to the target material edge reference plane in the corresponding material edge thickness measurement interest in the second material depth image as the edge thickness value of the material to be measured.
According to the edge thickness measuring device, a rigid transformation relation between a first linear array camera and a second linear array camera arranged on two sides of a scanning platform is obtained, and the rigid transformation relation is represented by a rotation translation matrix between a first coordinate system where the first linear array camera is located and a second coordinate system where the second linear array camera is located; after placing a material to be tested on the scanning platform, starting the scanning platform to move, and respectively shooting the material to be tested through the first linear array camera and the second linear array camera to correspondingly obtain a first material depth image and a second material depth image of the material to be tested; fitting an initial material edge reference plane where the material edge to be measured is located according to the first material depth image, and determining a material edge thickness measurement interest area according to the initial material edge reference plane, wherein a coordinate system of the initial material edge reference plane is the first coordinate system; switching the coordinate system of the initial material edge reference plane from the first coordinate system to the second coordinate system according to the rotation translation matrix to obtain a target material edge reference plane, wherein the coordinate system of the target material edge reference plane is the second coordinate system; and under the second coordinate system, measuring the distance from the three-dimensional space point in the interest area to the target material edge reference plane in the corresponding material edge thickness measurement interest area in the second material depth image, and taking the distance as the edge thickness value of the material to be measured. The method solves the problems that the current edge thickness detection method is to manually measure by a vernier caliper, the requirements of the modern industry on the efficiency, the precision and the like of the measurement process cannot be met, and the cost and the complexity of measurement equipment are increased by other measurement technologies, so that the measurement precision and the efficiency are improved, the measurement cost is saved, and the measurement means are simplified.
On the basis of the above embodiments, fitting an initial material edge reference plane where the edge of the material to be measured is located according to the first material depth image includes:
extracting feature points of the first material depth image, and determining model parameter points according to the extracted feature points of the first material depth image through a minimum variance estimation algorithm;
if the deviation between the characteristic points and the model parameter points is smaller than a deviation threshold value, the characteristic points are considered as sample points in the model;
after traversing all the characteristic points in the first material depth image, recording sample points in the model, and fitting an initial material edge reference plane where the edges of the materials to be detected are located according to the sample points in the model.
Based on the above embodiments, the rigid body transformation relation determining module 510 includes:
after a calibration plate with a plurality of calibration balls is placed on the scanning platform, starting the scanning platform to move, and shooting the calibration plate through the first linear array camera and the second linear array camera respectively to correspondingly obtain a first calibration depth image and a second calibration depth image of the calibration plate;
respectively determining the spherical center coordinates of each calibration sphere according to the first calibration depth image and the second calibration depth image, and correspondingly obtaining a first calibration point set and a second calibration point set;
And determining a rigid body transformation relation between the first linear array camera and the second linear array camera coordinate system according to the first calibration point set and the second calibration point set.
On the basis of the above embodiments, the number of elements in the first set of calibration points is the same as the number of elements in the second set of calibration points, and corresponds to one another;
before determining the rigid body transformation relation between the first linear array camera and the second linear array camera coordinate system according to the first set of calibration points and the second set of calibration points, the method further comprises:
calibrating elements in the first calibration point set and the second calibration point set, wherein the elements correspond to each other one by one;
and screening the elements in the first calibration point set and the second calibration point set according to the point distances among the calibrated one-to-one corresponding elements.
Based on the above embodiments, the edge thickness value determining module 550 includes:
measuring the distances from the three-dimensional space points in the interested region to the target material edge reference plane by the corresponding material edge thicknesses in the plurality of the second material depth images under the second coordinate system;
dividing the distances into at least one data screening interested region, and selecting the distance with the largest value in each data screening interested region as the edge thickness value of the material to be tested.
On the basis of the above embodiments, after dividing the plurality of distances into at least one data filtering region of interest, the method further includes:
and selecting the distance of the data screening interested region, wherein the value of the distance is larger than the lower thickness threshold and smaller than the upper thickness threshold, and determining the target distance in the data screening interested region according to the high tail value.
Based on the above embodiments, the edge thickness value determining module 550 includes:
under the second coordinate system, measuring the distance from a three-dimensional space point in the region of interest to the target material edge reference plane based on the measured material edge thickness in the second material depth image, and generating a thickness distance histogram;
and selecting the distance meeting the preset thickness range as a target distance according to the thickness distance histogram, and determining the edge thickness value of the material to be detected according to the target distance.
The edge thickness measuring device provided by the embodiments can execute the edge thickness measuring method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the edge thickness measuring method.
Example IV
Fig. 6 is a schematic structural diagram of an edge thickness measurement device according to a fourth embodiment of the present invention, and as shown in fig. 6, the edge thickness measurement device includes a first line camera, a second line camera, a scanning platform, a processor 610, a memory 620, an input device 630 and an output device 640; the number of processors 610 in the edge thickness measuring device may be one or more, one processor 610 being illustrated in fig. 6; the processor 610, memory 620, input 630 and output 640 devices in the edge thickness measuring device may be connected by a bus or other means, for example by a bus connection in fig. 6.
The memory 620 is used as a computer readable storage medium for storing software programs, computer executable programs, and modules, such as program instructions/modules corresponding to the edge thickness measurement method in the embodiment of the present invention (e.g., the rigid body transformation relation determining module 510, the depth image acquiring module 520, the plane fitting module 530, the coordinate system converting module 540, and the edge thickness value determining module 550 in the edge thickness measuring device). The processor 610 performs various functional applications of the edge thickness measuring device and data processing, i.e., implements the edge thickness measuring method described above, by running software programs, instructions, and modules stored in the memory 620.
Memory 620 may include primarily a program storage area and a data storage area, wherein the program storage area may store an operating system, at least one application program required for functionality; the storage data area may store data created according to the use of the terminal, etc. In addition, memory 620 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some examples, memory 620 may further include memory remotely located with respect to processor 610, which may be connected to the edge thickness measurement device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 630 may be used to receive input numeric or character information and to generate key signal inputs related to user settings and function control of the edge thickness measuring device. The output device 640 may include a display device such as a display screen.
Example five
A fifth embodiment of the present invention also provides a storage medium containing computer-executable instructions, which when executed by a computer processor, are for performing an edge thickness measurement method comprising:
acquiring a rigid transformation relation between a first linear array camera and a second linear array camera coordinate system which are arranged on two sides of a scanning platform, wherein the rigid transformation relation is represented by a rotation translation matrix between the first coordinate system where the first linear array camera is positioned and the second coordinate system where the second linear array camera is positioned;
after placing a material to be tested on the scanning platform, starting the scanning platform to move, and respectively shooting the material to be tested through the first linear array camera and the second linear array camera to correspondingly obtain a first material depth image and a second material depth image of the material to be tested;
fitting an initial material edge reference plane where the material edge to be measured is located according to the first material depth image, and determining a material edge thickness measurement interest area according to the initial material edge reference plane, wherein a coordinate system of the initial material edge reference plane is the first coordinate system;
Switching the coordinate system of the initial material edge reference plane from the first coordinate system to the second coordinate system according to the rotation translation matrix to obtain a target material edge reference plane, wherein the coordinate system of the target material edge reference plane is the second coordinate system;
and under the second coordinate system, measuring the distance from the three-dimensional space point in the interest area to the target material edge reference plane in the corresponding material edge thickness measurement interest area in the second material depth image, and taking the distance as the edge thickness value of the material to be measured.
Of course, the storage medium containing the computer executable instructions provided in the embodiments of the present invention is not limited to the method operations described above, and may also perform the related operations in the edge thickness measurement method provided in any embodiment of the present invention.
From the above description of embodiments, it will be clear to a person skilled in the art that the present invention may be implemented by means of software and necessary general purpose hardware, but of course also by means of hardware, although in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, etc., and include several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments of the present invention.
It should be noted that, in the above embodiment of the edge thickness measuring device, each unit and module included are only divided according to the functional logic, but not limited to the above division, so long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (10)
1. An edge thickness measurement method, comprising:
acquiring a rigid transformation relation between a first linear array camera and a second linear array camera coordinate system which are arranged on two sides of a scanning platform, wherein the rigid transformation relation is represented by a rotation translation matrix between the first coordinate system where the first linear array camera is positioned and the second coordinate system where the second linear array camera is positioned;
After placing a material to be tested on the scanning platform, starting the scanning platform to move, and respectively shooting the material to be tested through the first linear array camera and the second linear array camera to correspondingly obtain a first material depth image and a second material depth image of the material to be tested;
fitting an initial material edge reference plane where the material edge to be measured is located according to the first material depth image, and determining a material edge thickness measurement interest area according to the initial material edge reference plane, wherein a coordinate system of the initial material edge reference plane is the first coordinate system;
switching the coordinate system of the initial material edge reference plane from the first coordinate system to the second coordinate system according to the rotation translation matrix to obtain a target material edge reference plane, wherein the coordinate system of the target material edge reference plane is the second coordinate system;
and under the second coordinate system, measuring the distance from the three-dimensional space point in the interest area to the target material edge reference plane in the corresponding material edge thickness measurement interest area in the second material depth image, and taking the distance as the edge thickness value of the material to be measured.
2. The method for measuring the edge thickness according to claim 1, wherein fitting an initial material edge reference plane where the edge of the material to be measured is located according to the first material depth image comprises:
extracting feature points of the first material depth image, and determining model parameter points according to the extracted feature points of the first material depth image through a minimum variance estimation algorithm;
if the deviation between the characteristic points and the model parameter points is smaller than a deviation threshold value, the characteristic points are considered as sample points in the model;
after traversing all the characteristic points in the first material depth image, recording sample points in the model, and fitting an initial material edge reference plane where the edges of the materials to be detected are located according to the sample points in the model.
3. The edge thickness measurement method according to claim 1, wherein acquiring a rigid body transformation relationship between a first line camera and a second line camera coordinate system mounted on both sides of the scanning platform, comprises:
after a calibration plate with a plurality of calibration balls is placed on the scanning platform, starting the scanning platform to move, and shooting the calibration plate through the first linear array camera and the second linear array camera respectively to correspondingly obtain a first calibration depth image and a second calibration depth image of the calibration plate;
Respectively determining the spherical center coordinates of each calibration sphere according to the first calibration depth image and the second calibration depth image, and correspondingly obtaining a first calibration point set and a second calibration point set;
and determining a rigid body transformation relation between the first linear array camera and the second linear array camera coordinate system according to the first calibration point set and the second calibration point set.
4. The edge thickness measurement method according to claim 3, wherein the number of elements in the first set of calibration points and the number of elements in the second set of calibration points are the same and correspond one-to-one;
before determining the rigid body transformation relation between the first linear array camera and the second linear array camera coordinate system according to the first set of calibration points and the second set of calibration points, the method further comprises:
calibrating elements in the first calibration point set and the second calibration point set, wherein the elements correspond to each other one by one;
and screening the elements in the first calibration point set and the second calibration point set according to the point distances among the calibrated one-to-one corresponding elements.
5. The edge thickness measurement method according to claim 1, wherein measuring, in the second coordinate system, a distance from a three-dimensional spatial point in the region of interest to the target material edge reference plane in the corresponding material edge thickness measurement interest in the second material depth image as the edge thickness value of the material to be measured includes:
Measuring the distances from the three-dimensional space points in the interested region to the target material edge reference plane by the corresponding material edge thicknesses in the plurality of the second material depth images under the second coordinate system;
dividing the distances into at least one data screening interested region, and selecting the distance with the largest value in each data screening interested region as the edge thickness value of the material to be detected.
6. The edge thickness measurement method according to claim 5, further comprising, after dividing the plurality of distances into at least one data screening region of interest:
and selecting the distance of the data screening interested region, wherein the value of the distance is larger than the lower thickness threshold and smaller than the upper thickness threshold, and determining the target distance in the data screening interested region according to the high tail value.
7. The method according to claim 5, wherein measuring, in the second coordinate system, a distance from a three-dimensional space point in the region of interest to the target material edge reference plane in the corresponding material edge thickness measurement interest in the second material depth image as the edge thickness value of the material to be measured includes:
Under the second coordinate system, measuring the distance from a three-dimensional space point in the region of interest to the target material edge reference plane based on the measured material edge thickness in the second material depth image, and generating a thickness distance histogram;
and selecting the distance meeting the preset thickness range as a target distance according to the thickness distance histogram, and determining the edge thickness value of the material to be detected according to the target distance.
8. An edge thickness measuring device, comprising:
the rigid transformation relation determining module is used for obtaining rigid transformation relation between the first linear array camera and the second linear array camera coordinate systems arranged on two sides of the scanning platform, and the rigid transformation relation is represented by a rotation translation matrix between the first coordinate system where the first linear array camera is located and the second coordinate system where the second linear array camera is located;
the depth image acquisition module is used for starting the scanning platform to move after the material to be detected is placed on the scanning platform, and shooting the material to be detected through the first linear array camera and the second linear array camera respectively to correspondingly obtain a first material depth image and a second material depth image of the material to be detected;
The plane fitting module is used for fitting an initial material edge reference plane where the material edge to be measured is located according to the first material depth image, determining a material edge thickness measurement interest area according to the initial material edge reference plane, and the coordinate system of the initial material edge reference plane is the first coordinate system;
the coordinate system conversion module is used for switching the coordinate system of the initial material edge reference plane from the first coordinate system to the second coordinate system according to the rotation translation matrix to obtain a target material edge reference plane, wherein the coordinate system of the target material edge reference plane is the second coordinate system;
and the edge thickness value determining module is used for measuring the distance from the three-dimensional space point in the interest area to the edge reference plane of the target material, which is measured by the corresponding material edge thickness in the second material depth image, in the second coordinate system, and taking the distance as the edge thickness value of the material to be measured.
9. An edge thickness measurement device, characterized in that the edge thickness measurement device comprises:
a first line camera and a second line camera;
a scanning platform;
one or more processors;
A storage means for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the edge thickness measurement method of any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the edge thickness measurement method according to any one of claims 1-7.
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