CN111127312B - Method for extracting circles from point clouds of complex objects and scanning device - Google Patents
Method for extracting circles from point clouds of complex objects and scanning device Download PDFInfo
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Abstract
The invention discloses a method for extracting circles from point clouds of complex objects, which comprises the following steps: firstly, visualizing a complex object point cloud, manually selecting data points of a slice reference plane, and obtaining a feature vector of the reference slice plane by using a plane fitting method; slicing the complex object point cloud by using two slicing planes with the interval delta to obtain a three-dimensional tangential point cloud, wherein the two slicing planes are respectively parallel to a reference slicing plane; converting the three-dimensional tangential point cloud into a two-dimensional tangential point cloud by adopting a projection method; and finally, extracting a circle according to the two-dimensional tangential point cloud and calculating a circle parameter. The invention integrates the data in a certain range into a smaller range, thereby converting the problem of processing three-dimensional data into the problem of processing two-dimensional data, reducing the data searching range, simplifying the calculation and improving the efficiency.
Description
Technical Field
The invention relates to the technical field of three-dimensional scanning, in particular to a method for extracting circles by using point clouds of complex objects and a scanning device.
Background
The existing industrial size detection mode generally adopts a CCD/CMOS image sensor to collect images, and the mode needs to consider various factors such as light sources, lens selection, sensor selection, installation arrangement, automatic integration, environmental factor consideration, workpiece state change and the like. Deviations in either aspect can affect imaging quality and thus imaging outcome. The industrial part is a three-dimensional part, and aiming at the difficulty in parameter detection of deep hole parts, binocular camera three-dimensional imaging is utilized, binocular vision three-dimensional reconstruction is one of important research contents in the field of computer vision, and the three-dimensional reconstruction method has wide application in the aspects of precision measurement, robot navigation, virtual reality and the like, and has very important practical significance and theoretical research value for three-dimensional sense modeling.
The file obtained by three-dimensional scanning is called point cloud data. The point cloud file consists of a large number of coordinate points, and the points can be from hundreds to millions according to the nature of the scanner, the scanning parameters and the size of the scanned object. Currently, under the dual driving of sensor technology and industrial detection requirements, three-dimensional scanning equipment has made great progress in terms of hardware and point cloud data processing, but at the same time has also faced challenges.
In the process of scanning point cloud data, for a large object, the scanning equipment cannot scan the whole view of the object at one time, so that three-dimensional data are scattered. The point cloud slicing technology can convert space discrete points into point cloud slices, integrate data in a certain range into a smaller range, and thus convert the problem of processing three-dimensional data into the problem of processing two-dimensional data, namely, performing dimension reduction processing, reducing the data searching range and simplifying some problems which are difficult to process in a three-dimensional space.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a method for extracting circles from point clouds of complex objects, which converts three-dimensional data into two-dimensional data and simplifies data processing.
The technical scheme adopted for solving the technical problems is as follows:
the method for extracting the circle from the point cloud of the complex object comprises the following steps:
s1, visualizing a complex object point cloud, manually selecting data points of a slice reference plane, and obtaining a feature vector of the reference slice plane by using a plane fitting method;
s2, slicing the complex object point cloud by using two slicing planes with the distance delta to obtain a three-dimensional tangential point cloud, wherein the two slicing planes are respectively parallel to a reference slicing plane;
s3, converting the three-dimensional tangential point cloud into a two-dimensional tangential point cloud by adopting a projection method;
and S4, extracting a circle according to the two-dimensional tangential point cloud and calculating a circle parameter.
In the above technical solution, the plane fitting method in step S1 is a total least square method, and the feature vector A, B, C, D of the reference slice plane satisfies the following conditions:
where A, B, C is the plane equation coefficient and D is a constant term.
In the above technical solution, the distance δ between two slice planes in step S2 is a certain multiple of the point cloud density.
By adopting the technical scheme, the calculation process of the point cloud density is as follows:
s21, randomly selecting n points in the point cloud of the complex object, and marking the n points as points (P 0 ,…,P i ,…,P n )；
S22, for any selected point P i Searching and P in complex object point cloud i M points closest to the point and calculating m points to P respectively i Is a distance of (2);
s23, calculating the point cloud density, wherein the calculation formula is as follows:
wherein ρ is the density of the point cloud,is the distance between the i-th point selected randomly and the k-th point in m points nearest to the point.
In the above technical solution, the circle parameters in step S4 include a center and a radius.
In the above technical solution, the step of extracting the circle according to the two-dimensional tangential point cloud in the step S5 is as follows:
s41, translating the two-dimensional tangential point cloud into a first quadrant;
s42, rounding the two-dimensional tangential point cloud data;
s43, carrying out Hough transformation on the two-dimensional tangential point cloud data subjected to rounding processing, and primarily calculating circle parameters;
s44, acquiring an original two-dimensional tangential point cloud of a circle according to the preliminarily calculated circle parameters;
s45, performing circle fitting by using a least square method according to the obtained two-dimensional tangent point cloud of the circle, and calculating a circle parameter.
By adopting the technical scheme, the complex object point cloud is obtained by scanning the complex object point cloud scanning device, the complex object point cloud scanning device comprises a base, a rotating mechanism, a control mechanism and a supporting rod are arranged on the base, a binocular camera mechanism is arranged on the supporting rod, and the rotating mechanism and the binocular camera mechanism are both connected with the control mechanism.
Connect above-mentioned technical scheme, binocular camera mechanism includes mounting bracket and binocular camera, connects through the steering wheel between the two, the mounting bracket is fixed in on the bracing piece, the installation height can be adjusted, the steering wheel with control mechanism connects.
Connect above-mentioned technical scheme, rotary mechanism includes rotary module and drive module, rotary module includes rotary platform, rotary platform below center is provided with the axis of rotation, be provided with from the driving wheel in the axis of rotation, the axis of rotation pass through the bearing to be fixed with on the base, drive module includes the motor, the motor is fixed with on the base, be provided with the action wheel on its output shaft, the action wheel pass through the belt with from the wheel connection.
The invention also provides a computer storage medium, in which a computer program executable by a computer processor is stored, and the computer program executes the method for extracting the circle from the complex object point cloud in the technical scheme.
The invention has the beneficial effects that: according to the method for extracting the circles from the point clouds of the complex object, the point clouds of the complex object are sliced by manually selecting a reference slice plane, the three-dimensional point clouds of the characteristic contours are converted into two-dimensional point clouds through a projection method, and then the circles are extracted. The invention integrates the data in a certain range into a smaller range, thereby converting the problem of processing three-dimensional data into the problem of processing two-dimensional data, reducing the data searching range, simplifying the calculation and improving the efficiency.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a flow chart of a complex object point cloud circle extraction method of the present invention;
FIG. 2 is a flow chart of a two-dimensional point cloud circle extraction method of the present invention;
fig. 3 is a schematic diagram of a complex object point cloud scanning apparatus of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1, the invention provides a method for extracting circles from a point cloud of a complex object, which comprises the following steps:
s1, visualizing a complex object point cloud, manually selecting data points of a slice reference plane, and obtaining a feature vector of the reference slice plane by using a plane fitting method;
s2, slicing the complex object point cloud by using two slicing planes with the distance delta to obtain a three-dimensional tangential point cloud, wherein the two slicing planes are respectively parallel to a reference slicing plane;
s3, converting the three-dimensional tangential point cloud into a two-dimensional tangential point cloud by adopting a projection method;
and S4, extracting a circle according to the two-dimensional tangential point cloud and calculating a circle parameter.
According to the method, the data in a certain range are integrated into a smaller range, so that the problem of processing three-dimensional data is converted into the problem of processing two-dimensional data, the data searching range is reduced, the calculation is simplified, and the efficiency is improved.
Further, the plane fitting method in step S1 is an overall least square method, and the matrix eigenvectors A, B, C, D of the reference slice plane satisfy:
where A, B, C is the plane equation coefficient and D is a constant term. When outliers are added to the plane, a more accurate value can be obtained using the plane fitting method of the global least squares method.
Further, in step S2, the distance δ between two slice planes is a certain multiple of the point cloud density. Typically 4-8 times.
Further, the calculation process of the point cloud density is as follows:
s21, randomly selecting n points in the point cloud of the complex object, and marking the n points as points (P 0 ,…,P i ,…,P n )；
S22, for any selected point P i Searching and P in complex object point cloud i M points closest to the point and calculating m points to P respectively i Is a distance of (2);
s23, calculating the point cloud density, wherein the calculation formula is as follows:
wherein ρ is the density of the point cloud,is the distance between the i-th point selected randomly and the k-th point in m points nearest to the point.
Further, the circle parameters in step S4 include a center and a radius.
Further, as shown in fig. 2, the step of extracting a circle from the two-dimensional tangential point cloud in step S5 is as follows:
s41, translating the two-dimensional tangential point cloud into a first quadrant;
s42, rounding the two-dimensional tangential point cloud data, namely reserving an integer part of the data, so that the data processing can be simplified;
s43, carrying out Hough transformation on the two-dimensional tangential point cloud data subjected to rounding processing, and primarily calculating circle parameters;
s44, acquiring an original two-dimensional tangential point cloud of a circle according to the preliminarily calculated circle parameters;
s45, performing circle fitting by using a least square method according to the obtained two-dimensional tangent point cloud of the circle, and calculating a circle parameter.
As shown in fig. 3, a complex object point cloud scanning device is provided, which is used for obtaining a complex object point cloud, and comprises a base 1, wherein a rotating mechanism 2, a control mechanism 3 and a supporting rod 4 are arranged on the base 1, a binocular camera mechanism 5 is arranged on the supporting rod 4, and the rotating mechanism 2 and the binocular camera mechanism 5 are both connected with the control mechanism 3.
Further, the binocular camera mechanism 5 comprises a mounting frame 52 and a binocular camera 51, the mounting frame 52 is fixed on the support rod 4, the mounting height is adjustable, and the steering engine 53 is connected with the control mechanism 3.
Further, the rotating mechanism 2 comprises a rotating module and a driving module, the rotating module comprises a rotating platform 21, a rotating shaft is arranged at the center below the rotating platform, a driven wheel 22 is arranged on the rotating shaft, the rotating shaft is fixed on the base 1 through a bearing 23, the driving module comprises a motor 24, the motor 24 is fixed on the base 1, a driving wheel 25 is arranged on an output shaft of the motor, and the driving wheel 25 is connected with the driven wheel 22 through a belt 26.
The invention also provides a computer storage medium, in which a computer program executable by a computer processor is stored, and the computer program executes the method for extracting the circle from the complex object point cloud in the technical scheme.
It will be understood that modifications and variations will be apparent to those skilled in the art from the foregoing description, and it is intended that all such modifications and variations be included within the scope of the following claims.
Claims (7)
1. The method for extracting the circle from the point cloud of the complex object is characterized by comprising the following steps of:
s1, visualizing a complex object point cloud, manually selecting data points of a slice reference plane, and obtaining a feature vector of the reference slice plane by using a plane fitting method;
s2, using two intervals asSlicing the complex object point cloud to obtain a three-dimensional tangential point cloud, wherein two slice planes are respectively parallel to a reference slice plane; and the distance between the two slice planes +.>Is a multiple of the density of the point cloud;
s3, converting the three-dimensional tangential point cloud into a two-dimensional tangential point cloud by adopting a projection method;
s4, extracting a circle according to the two-dimensional tangential point cloud and calculating a circle parameter;
the plane fitting method in the step S1 is a total least square method, and refers to the feature vector of the slice planeThe method meets the following conditions:
（1）
wherein ,for plane equation coefficients +.>Is a constant term;
the step of extracting the circle according to the two-dimensional tangential point cloud in the step S4 is as follows:
s41, translating the two-dimensional tangential point cloud into a first quadrant;
s42, rounding the two-dimensional tangential point cloud data;
s43, carrying out Hough transformation on the two-dimensional tangential point cloud data subjected to rounding processing, and primarily calculating circle parameters;
s44, acquiring an original two-dimensional tangential point cloud of a circle according to the preliminarily calculated circle parameters;
s45, performing circle fitting by using a least square method according to the obtained two-dimensional tangent point cloud of the circle, and calculating a circle parameter.
2. The method for extracting circles from point clouds of complex objects according to claim 1, wherein the calculation process of the point cloud density is as follows:
s21, randomly selecting n points in the point cloud of the complex object, and marking the n points as points；
S22, for any selected pointSearching and +.>M points nearest to the point and calculating m points to +.>Is a distance of (2);
s23, calculating the point cloud density, wherein the calculation formula is as follows:
（2）
wherein ,for the density of point cloud->Is the distance between the i-th point selected randomly and the k-th point in m points nearest to the i-th point.
3. The method of claim 1, wherein the circle parameters in step S4 include a center and a radius.
4. A method of extracting circles from a point cloud of a complex object according to any one of claims 1-3, wherein the point cloud of the complex object is obtained by scanning a point cloud scanning device of the complex object, the point cloud scanning device of the complex object comprises a base, a rotating mechanism, a control mechanism and a supporting rod are arranged on the base, a binocular camera mechanism is arranged on the supporting rod, and the rotating mechanism and the binocular camera mechanism are both connected with the control mechanism.
5. The method for extracting circles from the point cloud of the complex object according to claim 4, wherein the binocular camera mechanism comprises a mounting frame and a binocular camera, the mounting frame is fixed on the supporting rod, the mounting height is adjustable, and the mounting frame is connected with the control mechanism through a steering engine.
6. The method for extracting circles from the point cloud of the complex object according to claim 4, wherein the rotating mechanism comprises a rotating module and a driving module, the rotating module comprises a rotating platform, a rotating shaft is arranged at the center below the rotating platform, a driven wheel is arranged on the rotating shaft, the rotating shaft is fixed on the base through a bearing, the driving module comprises a motor, the motor is fixed on the base, a driving wheel is arranged on an output shaft of the motor, and the driving wheel is connected with the driven wheel through a belt.
7. A computer storage medium, in which a computer program executable by a computer processor is stored, the computer program performing the method of extracting circles from a point cloud of a complex object according to any one of claims 1-3.
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| CN114485438A (en) * | 2022-01-06 | 2022-05-13 | 博迈科海洋工程股份有限公司 | Method for measuring distance between round stand columns of large module steel structure |
| CN115375718A (en) * | 2022-10-08 | 2022-11-22 | 南京航空航天大学 | Point cloud round hole extraction method based on projection graph and image segmentation |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101533529A (en) * | 2009-01-23 | 2009-09-16 | 北京建筑工程学院 | Range image-based 3D spatial data processing method and device |
| CN102920459A (en) * | 2012-09-26 | 2013-02-13 | 杭州电子科技大学 | Human body circumference parameter measuring method based on three-dimensional point cloud |
| CN103175484A (en) * | 2012-12-17 | 2013-06-26 | 谢鸿宇 | Crown measuring method based on three-dimensional laser scanning system |
| CN103886593A (en) * | 2014-03-07 | 2014-06-25 | 华侨大学 | Method for detecting hook face circular hole based on three-dimensional point cloud |
| CN104792274A (en) * | 2015-04-02 | 2015-07-22 | 同济大学 | Method for measuring circular tunnel convergence deformation |
| CN105091748A (en) * | 2015-05-29 | 2015-11-25 | 南京南车浦镇城轨车辆有限责任公司 | Measuring system for tolerance dimensions of railway vehicle |
| CN106548484A (en) * | 2016-10-27 | 2017-03-29 | 济宁学院 | Product model dispersion point cloud Boundary characteristic extraction method based on two-dimentional convex closure |
| CN106872476A (en) * | 2017-03-31 | 2017-06-20 | 武汉理工大学 | A kind of casting class workpiece surface quality detection method and system based on line-structured light |
| CN107507207A (en) * | 2017-07-07 | 2017-12-22 | 中国农业大学 | A kind of trimming evaluation method calculated based on fruit tree canopy illumination patterns |
| CN109493380A (en) * | 2017-09-11 | 2019-03-19 | 重庆大学 | The calculation method of irregular shear surface area in a kind of Rock Joint Plane shear test |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011070927A1 (en) * | 2009-12-11 | 2011-06-16 | 株式会社トプコン | Point group data processing device, point group data processing method, and point group data processing program |
| JP5462093B2 (en) * | 2010-07-05 | 2014-04-02 | 株式会社トプコン | Point cloud data processing device, point cloud data processing system, point cloud data processing method, and point cloud data processing program |
-
2019
- 2019-12-25 CN CN201911355611.7A patent/CN111127312B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101533529A (en) * | 2009-01-23 | 2009-09-16 | 北京建筑工程学院 | Range image-based 3D spatial data processing method and device |
| CN102920459A (en) * | 2012-09-26 | 2013-02-13 | 杭州电子科技大学 | Human body circumference parameter measuring method based on three-dimensional point cloud |
| CN103175484A (en) * | 2012-12-17 | 2013-06-26 | 谢鸿宇 | Crown measuring method based on three-dimensional laser scanning system |
| CN103886593A (en) * | 2014-03-07 | 2014-06-25 | 华侨大学 | Method for detecting hook face circular hole based on three-dimensional point cloud |
| CN104792274A (en) * | 2015-04-02 | 2015-07-22 | 同济大学 | Method for measuring circular tunnel convergence deformation |
| CN105091748A (en) * | 2015-05-29 | 2015-11-25 | 南京南车浦镇城轨车辆有限责任公司 | Measuring system for tolerance dimensions of railway vehicle |
| CN106548484A (en) * | 2016-10-27 | 2017-03-29 | 济宁学院 | Product model dispersion point cloud Boundary characteristic extraction method based on two-dimentional convex closure |
| CN106872476A (en) * | 2017-03-31 | 2017-06-20 | 武汉理工大学 | A kind of casting class workpiece surface quality detection method and system based on line-structured light |
| CN107507207A (en) * | 2017-07-07 | 2017-12-22 | 中国农业大学 | A kind of trimming evaluation method calculated based on fruit tree canopy illumination patterns |
| CN109493380A (en) * | 2017-09-11 | 2019-03-19 | 重庆大学 | The calculation method of irregular shear surface area in a kind of Rock Joint Plane shear test |
Non-Patent Citations (1)
| Title |
|---|
| Scan Matching of Laser Point Clouds Based on the 3D Angle Features within Indoor Environments;Yansong Gong, Yutong Zhang, Fengchi Sun, and JingYuan;《IEEE》;第1-6页 * |
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