CN109556540A - A kind of contactless object plane degree detection method based on 3D rendering, computer - Google Patents
A kind of contactless object plane degree detection method based on 3D rendering, computer Download PDFInfo
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- CN109556540A CN109556540A CN201811320337.5A CN201811320337A CN109556540A CN 109556540 A CN109556540 A CN 109556540A CN 201811320337 A CN201811320337 A CN 201811320337A CN 109556540 A CN109556540 A CN 109556540A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
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Abstract
The invention belongs to object plane degree detection technique fields, disclose the contactless object plane degree detection method based on 3D rendering of one kind, computer, are made of image capture module and image processing and analyzing module；Image capture module includes that the high-precision 3D scanner of platform one for scanning object under test obtains panel data to be measured, passes to next module；The effect of image processing and analyzing module is after getting shooting object 3D information, under vs (Microsoft Visual Studio)+pcl (Point Cloud Library) environment, it is compiled with c++, carry out plane to be measured goes noise, filtering, the processes such as fitting, finally obtain the flatness data of plane to be measured.Emphasis of the invention is handled using mean filter, is given full play to the more advantage of 3D point cloud points and is reduced the error that camera shooting generates noise；Be it is a kind of fast and automatically, non-contacting flatness detection scheme.
Description
Technical field
The invention belongs to object plane degree detection technique fields, more particularly to a kind of contactless object based on 3D rendering
Flatness detection method, computer.
Background technique
Currently, the prior art commonly used in the trade is such that domestic and international personnel early 20th century just carry out the measurement of planeness
Research, what is used in early days is all the traditional measurement method of comparison, such as gap method, indicator method, level meter method, workpiece is also mostly
The plate level of medium-sized or slightly larger type, the measurement method of flatness error is numerous, conventional measurement method measurement accuracy it is not high or
Person's complex steps.Domestic and international universal measuring instrument is not suitable for the measurement of micro parts, profile tolerance instrument, ultra precise measurement at present
Although the equipment such as instrument, step instrument are able to carry out small size part measurement, but its price is but very expensive.It adopts in the prior art
It is in terms of resting on two dimensional image mostly with the scheme that vision prescription carries out flatness detection.With the approximate scheme of this programme
Principle is the three-dimensionalreconstruction based on digital camera images, and main body includes high-resolution digital camera, directional reflective mark (target)
With 3 part of data processing software.The plane of tape label is mainly shot by high-resolution digital camera by the way of marking,
Mark point three-dimensional coordinate is obtained further according to the mapping relations in object dimensional space to digital camera two-dimensional CCD plane, is being intended
Occlusal reconstruction plane simultaneously carries out the measurement of planeness.In comparison, 2 d-to-3 d conversion just has certain error, this is just to two
There are also fixture systems when shooting high-precision requirement for dimension digital camera, and the measurement of each plane requires to be marked
Note, mark point, and obtained flatness information is more accurate, this keeps flatness detection process more cumbersome, time-consuming longer.
A kind of small size part flatness precision measurement apparatus is designed, realizes that high-precision is surveyed under the premise of meeting low cost
Amount, for the measurement of small size part flatness, to provide the convenient accurate measurement means of one kind necessary.
In conclusion problem of the existing technology is: domestic and international universal measuring instrument is not suitable for micro parts at present
The measurement of planeness, price is relatively high.
It solves the difficulty and meaning of above-mentioned technical problem: obtaining flatness information in high precision, the points of test point are very heavy
It wants, information that are more more more can more precisely describing plane to be measured of counting also can more find out the deviation of ideal plane and reality.To tradition
Square such as three-coordinate instrument hair surveys flatness and to obtain more count certainly will mean more to take operation a little, sample detecting point
Operation becomes complicated.The present invention quickly can carry out high-density sampling to plane, while can guarantee certain precision.
Summary of the invention
In view of the problems of the existing technology, the present invention provides a kind of contactless object plane degree based on 3D rendering
Detection method, computer.
The invention is realized in this way a kind of contactless object plane degree detection method based on 3D rendering, described non-
After contact gets shooting object 3D information based on the object plane degree detection method of 3D rendering, under vs+pcl environment, c is used
++ compiling carries out the noise of going of plane to be measured, filters, fit procedure；Obtain the flatness data of plane to be measured.
Further, the contactless object plane degree detection method based on 3D rendering specifically includes:
(1) measured object is put into fixed position, the acquisition and preservation of 3D point cloud is completed by 3D scanner, 3D scanner is
Laser triangulation: distance is acquired using triangle geometry relationship；
(2) point cloud information that image capture module transmits is received, image preprocessing, filtering point-cloud fitting, number are carried out
Measurement result is obtained according to measurement；The 3D point cloud got is first pre-processed, laser scanner scans would generally generate density
Non-uniform point cloud data collection；Sparse outlier removing method is based on the range distribution in input data to point to point of proximity
It calculates；To each point, calculate it to it all point of proximity average distance；
(3) after removing noise, the point cloud data of plane to be measured is obtained by straight-through filtering；Plane to be measured is got to arrive
The distance of 3D scanner optical center is partitioned into the point cloud of plane to be measured by the distance range of limitation point cloud in this direction；
(4) mean filter is carried out to the point cloud split, is replaced with the average value of all pixels coordinate in local window
The coordinate of window center point, a single point cloud is replaced with multiple point datas, takes full advantage of the advantage more than a cloud point number；
(5) the point cloud after obtaining mean filter, the fitting for carrying out plane are rebuild；The point cloud information for indicating plane to be measured is used
Certain mode is organized into a plane information；Obtain exact plane equation ax+by+cz=d；
(6) after getting plane equation, calculate mean filter after planar point cloud each point to fit Plane=distance
D finds out the flatness of plane to be measured according to flatness calculation formula (flatness=dMax-dMin).
Further, described (1) using 3D scanner principle be laser triangulation: using triangle geometry relationship acquire away from
From, it is first that laser is emitted to body surface by scanner, it utilizes and receives object reflection signal, note in the CCD camera of the baseline other end
Record the angle of incident light and reflected light, it is known that baseline length b, image objects length x, ccd focal length between laser light source and CCD
F inquires into the distance between scanner and object z out by triangle similarity relation,
Further, described (2) are by the way that one distance d of each point setting, it is round for constructing one by radius of d then with point
The ball-type region of the heart, a then number threshold x is arranged, value are determined by judging in region whether point number is more than given threshold x
Whether point is outlier.
The contactless object plane degree inspection based on 3D rendering is realized another object of the present invention is to provide a kind of
The contactless object plane degree detection system based on 3D rendering of survey method, the contactless object based on 3D rendering are flat
Face degree detection system includes: image capture module, image processing and analyzing module；
Image capture module includes light source, 3D scanner.Light source is adjusted, after fixing determinand, 3D scanner is launched
Laser carries out determinand the three dimensional point cloud that line is swept and obtains determinand in real time, entirely after scanned title, obtain to
Survey the point cloud data of object；
Image processing and analyzing module: receiving the 3D point cloud data that scanner transmitted, first pre-processed, including removal
Outlier processing；Plane to be measured is partitioned into the mode of straight-through filtering according to the position of scanner and object under test, distance relation；
Ransac finally is carried out to plane to be measured to be fitted to obtain the plane of high quality, and flatness information is calculated.
Another object of the present invention is to provide a kind of using the contactless object plane degree inspection based on 3D rendering
The computer of survey method.
In conclusion advantages of the present invention and good effect are as follows: image capture module main hardware is 3D scanner.It is fixed
After determinand, 3D scanner launches laser and carries out the three dimensional point cloud that line is swept and obtains determinand in real time to determinand, whole
After a scanned title, the point cloud data of object under test is obtained.Image processing and analyzing receives the 3D that scanner passes over
Point cloud data is first pre-processed, including removal outlier processing；It is closed afterwards according to the position of scanner and object under test, distance
System's mode of straight-through filtering and mean filter is divided and optimization plane to be measured；Ransac fitting finally is carried out to plane to be measured
Obtain the plane of high quality, and Calculation Plane degree information.The present invention can be realized under noncontact condition and fast, accurately be automated
Flatness detection.
The present invention uses high-precision 3D scanner, can obtain testee in the case where not contacting testee
Point cloud information, so as to the subsequent segmentation to plane, measurement.The point cloud that 3D scanner is got using the point methods that go to peel off
Preliminary screening is carried out, the influence of the miscellaneous point-to-point cloud accuracy of the factors such as light source, external disturbance generation can be effectively removed.Using straight
Pass filter handles the point cloud after going outlier, according to the positional relationship for fixing object under test and camera before, can obtain
The three-dimensional coordinate range for taking plane to be measured can be split plane to be measured by straight-through filtering.
The present invention uses mean filter process points cloud, carries out flatness calculating, this side using cloud mode fit Plane
Formula advantage is that a cloud point number multipotency does not omit the feature of plane, and disadvantage is that the precision of a single point is not achieved as three-coordinate instrument is surveyed
Measure precision when flatness.Multiple points in one point neighbour domain can be indicated using mean filter, reduce a single point
Error, while also the high frequency detail of cloud can be damaged and be lost.But the present invention using before mean filter
Through being removed by going outlier and leading directly to filtering to high-frequency noise, so the effect of mean filter is to remaining part
Points cloud processing promotes precision.Using ransac approximating method to the plane fitting to be measured obtained after straight-through filtering, ransac fitting
In can be that areal model automatically removes noise spot by setting model of fit, this be also under the known models type cases,
Ransac fitting is better than the place of least square fitting.
Following table is the comparison of the present invention and existing similar techniques.
It can be seen that the invention has the advantages that not having to prior marking to reduce detection time, and high quantity sampled point
Number can guarantee measurement accuracy.
Detailed description of the invention
Fig. 1 is the contactless object plane degree detection method flow chart based on 3D rendering provided in an embodiment of the present invention.
Fig. 2 is the contactless object plane degree detection method implementation process based on 3D rendering provided in an embodiment of the present invention
Figure.
Fig. 3 is laser triangulation range measurement principle schematic diagram provided in an embodiment of the present invention.
Fig. 4 is removal outlier algorithm flow chart provided in an embodiment of the present invention.
Fig. 5 is the simplification version algorithm flow chart of RANSAC provided in an embodiment of the present invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.
Be not suitable for the measurement of micro parts, the relatively high problem of price for domestic and international universal measuring instrument at present.This
Invention can realize fast, accurately automation flatness detection under noncontact condition.
Application principle of the invention is explained in detail with reference to the accompanying drawing.
As shown in Figure 1, the contactless object plane degree detection method packet based on 3D rendering provided in an embodiment of the present invention
Include following steps:
S101: after getting shooting object 3D information, in vs (Microsoft Visual Studio)+pcl (Point
Cloud Library) under environment, is compiled with c++, carry out the noise of going of plane to be measured, it filters, the processes such as fitting；
S102: the flatness data of plane to be measured are obtained.
Application principle of the invention is explained in detail with reference to the accompanying drawing.
The contactless object plane degree detection system based on 3D rendering provided in an embodiment of the present invention is by Image Acquisition mould
Block and image processing and analyzing module composition, as shown in Figure 2.
(1) image capture module hardware is 3D scanner.Measured object is put into fixed position, 3D is completed by 3D scanner
The acquisition and preservation of point cloud.3D point cloud is exactly 3D scanner scanning to the set of the point of body surface, and each point has its three
Tie up coordinate.3D scanner obtain 3D point cloud mode there are many as former base in pulse away from method, phase ranging method, laser triangulation,
One phase type of pulse etc..The 3D scanner principle that the present invention uses is laser triangulation: using triangle geometry relationship acquire away from
From.Laser is first emitted to body surface by scanner, object is received using the CCD camera in the baseline other end and reflects signal, note
Record the angle of incident light and reflected light, it is known that baseline length b, image objects length x, ccd focal length between laser light source and CCD
F inquires into the distance between scanner and object z out by triangle similarity relation,Fig. 3 is that laser triangulation ranging is former
Reason.In order to guarantee the integrality of scanning information, scanner maximum measurement range is 240mm*160mm2, and precision can reach
0.02mm, the scanner detail parameters thus of table 1.High-precision cloud provides guarantee for the accuracy of later rebuilding plane.
1 3D scanner detail parameters of table
| Product type | Raygo240 |
| Measurement accuracy | ≥0.02mm |
| Maximum measurement range | 240*160mm2 |
| Measure distance | 400±60mm |
| Sweep time | ≤6min |
| Point away from | 0.05-0.1mm |
| Scan pattern | Blue laser |
(2) it is pre- to carry out image for the point cloud information that image processing and analyzing module is transmitted by receiving image capture module
Processing, filtering point-cloud fitting, DATA REASONING and etc. obtain measurement result.The 3D point cloud got is first pre-processed,
Laser scanner scans would generally generate the point cloud data collection of Density inhomogeneity.In addition, measurement in error can generate it is sparse
Outlier keeps 3D point cloud effect even worse.Sparse outlier removing method is based on the distance for arriving point of proximity to point in input data
The calculating of distribution.To each point, calculate it to it all point of proximity average distance.Assuming that obtain the result is that a Gauss
Distribution, shape are determined that average distance (is defined) in critical field by global distance average and variance by mean value and standard deviation
Except point, outlier can be defined as and can be got rid of from data set.By setting a distance d to each point, then
One is constructed by radius of d to put the ball-type region for the center of circle, then a number threshold x is set, value is by judging point in region
Whether it is a little outlier that whether number is more than given threshold x to determine, Fig. 4 algorithm flow chart thus.
(3) after removing noise, the point cloud data of plane to be measured is obtained by straight-through filtering.Specific practice is to get
Plane to be measured puts the distance range of cloud in this direction by limitation to the distance of 3D scanner optical center, to be measured to be partitioned into
The point cloud of plane.
(4) mean filter is carried out to the point cloud split, mean filter is usually used in the filtering and noise reduction of image, the algorithm pair
Gaussian noise has good noise removal capability.Window is replaced with the average value of all the points coordinate in local window in Mean Filtering Algorithm
The coordinate of mouth central point, also can damage and lose to the high frequency detail of cloud while removing noise.Due to before
Through having carried out reason of going to peel off, lead directly to filtering etc. to cloud, and the present invention focuses on the flatness that point is measurement plane, to a cloud
Marginal information it is of less demanding, so using mean filter can be effectively treated camera shooting generate miscellaneous point without influence flatness
Calculating.
(5) the point cloud after obtaining mean filter, the fitting followed by plane are rebuild.Fitting, which is rebuild, just to be referred to expression
The point cloud information of plane to be measured is organized into a plane information with certain mode, exactly obtains exact plane equation.Using
RANSAC sampling algorithm can effectively play the advantage more than a cloud point, while can be reduced point Yun Zhongyou again and not can remove miscellaneous point and making
The disadvantage of error is generated at cloud plane fitting.
The input of RANSAC algorithm is one group of observation data, and one can explain or be adapted to the parametrization of observation data
Model, some believable parameters.RANSAC reaches target by one group of random subset being chosen in data.It is selected
Subset is assumed to be intra-office point, and is verified with following methods:
1. there is a model to be adapted to the intra-office point assumed, i.e., all unknown parameters can be calculated from the intra-office point of hypothesis
It obtains.
2. the model obtained in 1 goes to test all other data, if some point is suitable for the model of estimation, it is believed that
It is also intra-office point.
3. if there is enough points are classified as the intra-office point assumed, then the model estimated is just reasonable enough.
4. then, going to reevaluate model with the intra-office of all hypothesis point, because it is only by initial hypothesis intra-office point
Estimated.
5. finally, by the error rate of estimation intra-office point and model come assessment models.
Due to knowing that the model of tested point cloud is plane, plane can preferably be fitted using RANSAC sampling algorithm,
And it voluntarily removes those and filters the miscellaneous point not removed before.Fig. 5 is the simplification version algorithm flow chart of RANSAC
(6) after getting plane equation, distance of each point of planar point cloud to fit Plane, root after calculating mean filter
The flatness of plane to be measured can be found out according to flatness calculation formula.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (6)
1. a kind of contactless object plane degree detection method based on 3D rendering, which is characterized in that described contactless to be based on
After the object plane degree detection method of 3D rendering gets shooting object 3D information, under vs+pcl environment, compiled with c++, into
Row plane to be measured goes noise, filtering, fit procedure；Obtain the flatness data of plane to be measured.
2. the contactless object plane degree detection method based on 3D rendering as described in claim 1, which is characterized in that described
The contactless object plane degree detection method based on 3D rendering specifically includes:
(1) measured object is put into fixed position, the acquisition and preservation of 3D point cloud is completed by 3D scanner, 3D scanner is laser
Trigonometry: distance is acquired using triangle geometry relationship；
(2) receive the 3D point cloud information that image capture module transmits, carry out image preprocessing, filtering point-cloud fitting, data
Measurement obtains measurement result；The 3D point cloud got is pre-processed, laser scanner scans would generally generate density unevenness
Even point cloud data collection；Sparse outlier removing method is based on the range distribution in input data to point to point of proximity
It calculates；To each point, calculate it to it all point of proximity average distance；
(3) after removing noise, the point cloud data of plane to be measured is obtained by straight-through filtering；Plane to be measured is got to sweep to 3D
The distance for retouching instrument optical center is partitioned into the point cloud of plane to be measured by the distance range of limitation point cloud in this direction；
(4) mean filter is carried out to the point cloud split, replaces window with the average value of all pixels coordinate in local window
The coordinate of central point replaces a single point cloud with multiple point datas, takes full advantage of the advantage more than a cloud point number；
(5) the point cloud after obtaining mean filter, the fitting for carrying out plane are rebuild；The point cloud information for indicating plane to be measured is used certain
Mode be organized into a plane information；Obtain exact plane equation；
(6) after getting plane equation, calculate mean filter after planar point cloud each point arrive fit Plane distance, according to put down
Face degree calculation formula finds out the flatness of plane to be measured.
3. the contactless object plane degree detection method based on 3D rendering as claimed in claim 2, which is characterized in that described
(1) it is laser triangulation using 3D scanner principle: acquires distance using triangle geometry relationship, laser is first emitted by scanner
To body surface, object is received using the CCD camera in the baseline other end and reflects signal, records the folder of incident light and reflected light
Angle, it is known that baseline length b, image objects length x, ccd focal length f between laser light source and CCD are pushed away by triangle similarity relation
The distance between scanner and object z are found out,
4. the contactless object plane degree detection method based on 3D rendering as claimed in claim 2, which is characterized in that described
(2) by setting a distance d to each point, one is constructed by radius of d then to put the ball-type region for the center of circle, then be arranged
Whether whether a number threshold x, value be more than given threshold x to determine are a little outlier by judging to put number in region.
5. a kind of contactless base for realizing the contactless object plane degree detection method based on 3D rendering described in claim 1
In the object plane degree detection system of 3D rendering, which is characterized in that the contactless object plane degree inspection based on 3D rendering
Examining system includes: image capture module, image processing and analyzing module；
Image capture module includes light source, 3D scanner；Light source is adjusted, after fixing determinand, 3D scanner launches laser
The three dimensional point cloud that line is swept and obtains determinand in real time is carried out to determinand, entirely after scanned title, obtains determinand
The point cloud data of body；
Image processing and analyzing module: receiving the 3D point cloud data that scanner transmitted, first pre-processed, including removal peels off
Point processing；Plane to be measured is partitioned into the mode of straight-through filtering according to the position of scanner and object under test, distance relation；Finally
Ransac is carried out to plane to be measured to be fitted to obtain the plane of high quality, and flatness information is calculated.
6. a kind of using the contactless object plane degree detection method based on 3D rendering described in Claims 1 to 4 any one
Computer.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102944174A (en) * | 2012-11-28 | 2013-02-27 | 北京矿冶研究总院 | Point cloud data processing method and system |
| US20130251195A1 (en) * | 2012-03-23 | 2013-09-26 | Chih-Kuang Chang | Electronic device and method for measuring point cloud of object |
| CN104422406A (en) * | 2013-08-30 | 2015-03-18 | 鸿富锦精密工业（深圳）有限公司 | Planeness measurement system and method |
| CN106705892A (en) * | 2016-11-30 | 2017-05-24 | 同济大学 | Method for detecting parallelism and flatness of truss track based on three-dimensional laser scanner |
| CN106846272A (en) * | 2017-01-18 | 2017-06-13 | 西安工程大学 | A kind of denoising compressing method of point cloud model |
| 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 |
| US20170337705A1 (en) * | 2011-03-04 | 2017-11-23 | General Electric Company | Graphic overlay for measuring dimensions of features using a video inspection device |
| CN107578464A (en) * | 2017-06-30 | 2018-01-12 | 长沙湘计海盾科技有限公司 | A kind of conveyor belt workpieces measuring three-dimensional profile method based on line laser structured light |
-
2018
- 2018-11-07 CN CN201811320337.5A patent/CN109556540A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170337705A1 (en) * | 2011-03-04 | 2017-11-23 | General Electric Company | Graphic overlay for measuring dimensions of features using a video inspection device |
| US20130251195A1 (en) * | 2012-03-23 | 2013-09-26 | Chih-Kuang Chang | Electronic device and method for measuring point cloud of object |
| CN102944174A (en) * | 2012-11-28 | 2013-02-27 | 北京矿冶研究总院 | Point cloud data processing method and system |
| CN104422406A (en) * | 2013-08-30 | 2015-03-18 | 鸿富锦精密工业（深圳）有限公司 | Planeness measurement system and method |
| CN106705892A (en) * | 2016-11-30 | 2017-05-24 | 同济大学 | Method for detecting parallelism and flatness of truss track based on three-dimensional laser scanner |
| CN106846272A (en) * | 2017-01-18 | 2017-06-13 | 西安工程大学 | A kind of denoising compressing method of point cloud model |
| 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 |
| CN107578464A (en) * | 2017-06-30 | 2018-01-12 | 长沙湘计海盾科技有限公司 | A kind of conveyor belt workpieces measuring three-dimensional profile method based on line laser structured light |
Non-Patent Citations (2)
| Title |
|---|
| XIAN-FENG HAN ET AL.: "A review of algorithms for filtering the 3D point cloud", 《SIGNAL PROCESSING: IMAGE COMMUNICATION》 * |
| 周炳南 等: "PCL环境下的3D点云分割算法研究", 《微电子学与计算机》 * |
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