CN107702663A - A kind of point cloud registration method based on the rotation platform with index point - Google Patents
A kind of point cloud registration method based on the rotation platform with index point Download PDFInfo
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- 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
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/25—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object
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Abstract
The invention discloses a kind of point cloud registration method based on the rotation platform with index point, using rotation platform as carrier, object is positioned on rotation platform, operating basis is used as using the index point on rotation platform, the anglec of rotation of rotation platform is accurately calculated by various algorithms, and repeat the above steps repeatedly, so as to obtain the data value of multiple anglecs of rotation, further using these angles by under the coordinate unification of each reconstruction point cloud to same coordinate system, so as to realize the registration of object under test point cloud.The present invention is used as operating basis using index point so that method practicality simple to operate, is easy to those skilled in the art to implement, operating range is more accurate simultaneously, the error brought by operating range is smaller, so as to improve registration accuracy, meets the measuring three-dimensional morphology demand of those skilled in the art.
Description
Technical field
The invention belongs to measuring three-dimensional morphology field, especially a kind of point cloud based on the rotation platform with index point is matched somebody with somebody
Quasi- method.
Background technology
In recent years, as deep and commercial production levels the continuous improvement of modern scientific research, measuring three-dimensional morphology are got over
To be more concerned by people.Wherein, based on digital stripe projection measuring three-dimensional morphology technology due to its have it is simple to operate,
The advantages that in real time and precision is high, it is widely used in the industries such as historical relic measurement, automobile making and mould.But due to light
Learn measurement to be limited by its own, to obtain a complete three-dimensional information of object can only be by multi-angle and comprehensive place
Reason, therefore the reconstruct three-dimensional to object dimensional can only be carried out step by step.When the three-dimensional point cloud number for obtaining same object different angle
According to rear, and the coordinate system where these different angles reconstruct data is all different, therefore to obtain three-dimensional complete of object dimensional
Integral point cloud, it is necessary to carry out registration to object point cloud, all unify under same coordinate system by the point cloud that will be reconstructed.
Therefore the rotation platform of an auxiliary can be used, object is positioned on the rotation platform, by accurately controlling
The angle of rotation platform, this angle is recycled all to unify the coordinate of each reconstruction point cloud under same coordinate system, so as to real
The registration of existing object point cloud, the conventional point cloud registering based on rotation platform are typically directly by rotation platform or object under test
View goes out to send a series of computing of progress from viewdata or view spread data, matched somebody with somebody with reaching a cloud as initiate point
Accurate purpose, this method have the drawback that the view of selection is complex, are not easy to those skilled in the art's implementation, and
And it is likely to occur that the range of views directly chosen is excessive, and point cloud registering has the problem of larger error.
The content of the invention
In order to solve the above problems, it is an object of the invention to provide a kind of point cloud based on the rotation platform with index point
Method for registering, the object based on index point, the object of selection is relatively simple, is easy to those skilled in the art to implement, choosing
Take the scope of object small, by a series of processing to index point, obtain the object under test overall picture point cloud after accuracy registration, obtain
Improve the effect of registration accuracy.
In order to obtain the effect above, the technical solution adopted by the present invention is：
A kind of point cloud registration method based on the rotation platform with index point, it is characterised in that comprise the following steps：
A, the labelling point on rotation platform, then object under test is positioned on rotation platform；
B, one angle of the rotation platform is rotated；
C, identify the index point position on rotation platform and calculate the central value coordinate of index point；
D, overlapping index point point cloud is calculated according to central value coordinate；
E, the rotation translation relation between overlapping index point is calculated, the overlapping mark of relation pair is translated according to the rotation
Will point point cloud makees coordinate transform；
F, registration is carried out to the overlapping index point point cloud after coordinate transform, you can obtain this anglec of rotation after registration
Under object under test point cloud；
G, repeat step B-F twice and more than, you can obtain the object under test overall picture point cloud after registration.
Further, the index point position on the identification rotation platform in step C and the central value coordinate of index point is calculated,
Specific steps include：
C1, utilize projecting apparatus and the original image of video camera acquisition object under test；
C2, the original image using edge detection algorithm processing object under test, the original image after processing are converted into line
Digitized first image of bar profile, the interior index point comprising hole and fracture of described first image, the outline
Interior formation connected domain；
C3, the hole in the first image of filling and completion fracture index point；
C4, the noise spot that threshold requirement is not met in the connected domain being made up of in the first image outline is filtered out, and
The region with index point that shared pixel ratio does not meet pixel ratio threshold requirement is filtered out, is obtained comprising index point region
Digitized second image；
C5, the picture element matrix of the first image is multiplied with the picture element matrix of the second image, obtains comprising only mark point edge
3rd image of information, that is, identify the index point position on rotation platform；
C6, using based on the ellipse fitting algorithm of least square method to the 3rd image carry out ellipse fitting, calculate mark
The central value coordinate of point.
Further, overlapping index point point cloud is calculated according to central value coordinate in step D, specific steps include：
D1, the anglec of rotation for calculating according to the central value coordinate of index point rotation platform；
D2, the angular range for calculating according to the anglec of rotation contiguous tokens point point cloud overlapping region, this angular range it
Interior index point is overlapping index point point cloud.
Further, the anglec of rotation of rotation platform is calculated in step D1 according to the central value coordinate of index point, specific step
Suddenly include：
D11, demarcated according to the central value coordinate pair projecting apparatus and video camera of index point, obtain projecting apparatus and video camera
Intrinsic Matrix and outer parameter matrix；
D12, obtain bar graph by projection of the projecting apparatus to the 3rd image, then by camera acquisition to translation-angle after
Bar graph, i.e. deforming stripe figure；
D13, handle deforming stripe figure using phase measuring profilometer and phase unwrapping is carried out to it and wiping out background is made an uproar
Sound, obtain the 4th image；
D14, go out the 3 D stereo point cloud comprising index point according to Intrinsic Matrix, outer parameter matrix and the 4th image structure；
D15, the index point in 3 D stereo point cloud is ranked up by order from left to right, then with through rotation platform
On the basis of the outside axis in center by the index point in 3 D stereo point cloud respectively minute in two parts region of left and right；
D16, calculate the index point in two parts region of left and right and the angle through the outside axis in rotation platform center
The anglec of rotation of angle value, as rotation platform.
Further, the rotation translation relation between overlapping index point is calculated in step E, is closed according to the rotation translation
System makees coordinate transform to overlapping index point point cloud, and specific steps include：E1, rejecting standoff distance error amount do not meet threshold value and wanted
The index point in contiguous tokens point point cloud overlapping region asked, obtains the first overlapping domains；
E2, using SVD decomposition methods the rotation translation relation in the first overlapping domains between index point is calculated, it is as overlapping
Rotation translation relation between index point；
E3, coordinate transform made according to the overlapping index point point cloud of rotation translation relation pair.
Further, in step F, registration is carried out to the overlapping index point point cloud after conversion using modified ICP algorithm.
The beneficial effects of the invention are as follows：A kind of point cloud registration method based on the rotation platform with index point, with rotation
Platform is carrier, and object is positioned on rotation platform, using the index point on rotation platform as operating basis, passes through various calculations
Method accurately calculates the anglec of rotation of rotation platform, and repeats the above steps repeatedly, so as to obtain the number of multiple anglecs of rotation
It is to be measured so as to realize further using these angles by under the coordinate unification of each reconstruction point cloud to same coordinate system according to value
The registration of object point cloud.Therefore, the present invention chooses index point and enables to point cloud registration method operation more as operating basis
It is simple and practical, implement beneficial to those skilled in the art, while operating range is more accurate, also can just reduce by operating range
The error brought, so as to improve registration accuracy, meet the measuring three-dimensional morphology demand of those skilled in the art.
Brief description of the drawings
Fig. 1 is the step flow chart of the point cloud registration method of the present invention；
Fig. 2 is the flow example figure that 3 D stereo point cloud is generated in the present invention；
Content is embodied
Present pre-ferred embodiments are provided below in conjunction with the accompanying drawings, to describe embodiment of the present invention in detail, reference picture 1,
A kind of point cloud registration method based on the rotation platform with index point, it is characterised in that comprise the following steps：
A, the labelling point on rotation platform, then object under test is positioned on rotation platform；
B, one angle of the rotation platform is rotated；
C, identify the index point position on rotation platform and calculate the central value coordinate of index point；
D, overlapping index point point cloud is calculated according to central value coordinate；
E, the rotation translation relation between overlapping index point is calculated, the overlapping mark of relation pair is translated according to the rotation
Will point point cloud makees coordinate transform；
F, registration is carried out to the overlapping index point point cloud after coordinate transform, you can obtain this anglec of rotation after registration
Under object under test point cloud；
G, repeat step B-F twice and more than, you can obtain the object under test overall picture point cloud after registration.
Specifically, using rotation platform as carrier, object is positioned on rotation platform, made with the index point on rotation platform
For operating basis, the anglec of rotation of rotation platform is accurately calculated by various algorithms, and is repeated the above steps repeatedly, so as to
The data value of multiple anglecs of rotation is obtained, further using these angles by the coordinate unification of each reconstruction point cloud to same seat
Under mark system, so as to realize the registration of object under test point cloud.Therefore, the present invention chooses index point and enabled to a little as operating basis
Cloud method for registering operates simpler practicality, implements beneficial to those skilled in the art, while operating range is more accurate, also
The error brought by operating range can be reduced, so as to improve registration accuracy, meets that the three-dimensional appearance of those skilled in the art is surveyed
Amount demand.
Wherein, the index point position on the identification rotation platform in step C and the central value coordinate of index point is calculated, had
Body step includes：
C1, utilize projecting apparatus and the original image of video camera acquisition object under test；
C2, the original image using edge detection algorithm processing object under test, the original image after processing are converted into line
Digitized first image of bar profile, the interior index point comprising hole and fracture of described first image, the outline
Interior formation connected domain；
C3, the hole in the first image of filling and completion fracture index point；
C4, the noise spot that threshold requirement is not met in the connected domain being made up of in the first image outline is filtered out, and
The region with index point that shared pixel ratio does not meet pixel ratio threshold requirement is filtered out, is obtained comprising index point region
Digitized second image；
C5, the picture element matrix of the first image is multiplied with the picture element matrix of the second image, obtains comprising only mark point edge
3rd image of information, that is, identify the index point position on rotation platform；
C6, using based on the ellipse fitting algorithm of least square method to the 3rd image carry out ellipse fitting, calculate mark
The central value coordinate of point.
Specifically, the edge detection algorithm in step C2 is a kind of prior art, and in the present embodiment, it is mainly used in the greatest extent
The actual edge of the original image of object under test may be identified more, and then obtains the outline of original image, must due to existing
Right error, so obtained outline is not all the actual profile of object under test, some is untrue profile, wherein
There are many flaws in untrue profile, it is therefore desirable to index point and repairing hole in step C3 to its completion fracture；Step
Threshold value in rapid C4 refers to the minimum input value that can produce a corrective action in systems, for variable, less than most
The input of small input value can not all make system worked well, so needing to filter out noise point in step C4 or not meeting pixel
Than the region of threshold value, in order to more accurate, those skilled in the art can also filter out that pixel girth is long or standoff distance too far
Region, in addition, frequently with equal-sized white marker point in the present embodiment, be easy to control variable, those skilled in the art
Also can voluntarily selection marker point parameter, the first image after digitlization is respectively provided with specific picture with the second image after digitlization
Prime matrix, therefore the picture element matrix of both can be multiplied in step C5, so as to obtain the picture element matrix of another image, this is another
One image is the 3rd image, and the ellipse fitting algorithm based on least square method in step C6 is a kind of prior art, at this
In embodiment, its mainly for the treatment of the 3rd image to reach very high fitting precision, while also can be to the shape of the 3rd image
Enter row constraint with location parameter.
Wherein, overlapping index point point cloud is calculated according to central value coordinate in step D, specific steps include：
D1, the anglec of rotation for calculating according to the central value coordinate of index point rotation platform；
D2, the angular range for calculating according to the anglec of rotation contiguous tokens point point cloud overlapping region, this angular range it
Interior index point is overlapping index point point cloud.
Specifically, the index point distribution in contiguous tokens point point cloud overlapping region is relatively intensive, is suitable as research object,
And relative error is smaller, so selecting overlapping index point point cloud from adjacent index point point cloud overlapping region.
Wherein, reference picture 2, the anglec of rotation of rotation platform is calculated in step D1 according to the central value coordinate of index point,
Specific steps include：
D11, demarcated according to the central value coordinate pair projecting apparatus and video camera of index point, obtain projecting apparatus and video camera
Intrinsic Matrix and outer parameter matrix；
D12, obtain bar graph by projection of the projecting apparatus to the 3rd image, then by camera acquisition to translation-angle after
Bar graph, i.e. deforming stripe figure；
D13, handle deforming stripe figure using phase measuring profilometer and phase unwrapping is carried out to it and wiping out background is made an uproar
Sound, obtain the 4th image；
D14, go out the 3 D stereo point cloud comprising index point according to Intrinsic Matrix, outer parameter matrix and the 4th image structure；
D15, the index point in 3 D stereo point cloud is ranked up by order from left to right, then with through rotation platform
On the basis of the outside axis in center by the index point in 3 D stereo point cloud respectively minute in two parts region of left and right；
D16, calculate the index point in two parts region of left and right and the angle through the outside axis in rotation platform center
The anglec of rotation of angle value, as rotation platform.
Specifically, Fig. 2 flow example figure should from left to right, viewed from above, last step connection on the right of top
Lower section first left step, it should be noted that the following identifier such as " (D12) " and " (D13) " only shows the figure and phase
The corresponding relation of step is answered, should not be construed as the reference in Fig. 2, in actual figure 2 above and does not have a reference.Fig. 2's
Step is respectively that projection obtains bar graph (D12), the 3rd image (D12) of selection object under test and rotation platform, collection deformation
Bar graph (D12), deforming stripe figure (D13), expansion phase (D13), wiping out background noise are handled using phase measuring profilometer
(D13), structure goes out 3 D stereo point cloud (D14) and filters out noise spot cloud；Intrinsic Matrix and outer parameter matrix in step D11 are
Known technology in the art, Intrinsic Matrix be generally used to describe specific object point by video camera or the camera lens of projector,
Pin-hole imaging and electronics are transformed as the transformation relation of pixel, and outer parameter matrix be generally used to describe real world point or
The transformation relation that world coordinates is fallen in another real world point or camera coordinates by rotation and translation, step D13
In phase measuring profilometer be a kind of optical projection D profile detection, it is relatively conventional in this area, can also use More take turns
The common methods such as wide art, time domain phase measuring profilometer and Fourier transform profilometry, surveyed using phase in the present embodiment
Measure a kind of parcel algorithm of technology of profiling, it is had easy and effective based on one-dimensional Fourier transformation (FFT), it is easy to accomplish spy
Point, the purpose for deploying phase and wiping out background noise are to try to remove the impurity part in deforming stripe figure, in practice, step
Noise spot cloud is filtered out again in generation 3 D stereo point Yun Houke in D14, and also can is further removed in 3 D stereo point cloud
Miscellaneous point and noise spot, the anglec of rotation computational methods in step D15 and D16 are summarized as follows：An index point out of left region
Draw vertical line to through the outside axis in rotation platform center, two lines are intersecting must an intersection point, then by this intersection point and right region
The connection of another index point produce straight line, the angle of this straight line and vertical line is the anglec of rotation.
Wherein, the rotation translation relation between overlapping index point is calculated in step E, according to the rotation translation relation
Coordinate transform is made to overlapping index point point cloud, specific steps include：E1, rejecting standoff distance error amount do not meet threshold requirement
Contiguous tokens point point cloud overlapping region in index point, obtain the first overlapping domains；
E2, using SVD decomposition methods the rotation translation relation in the first overlapping domains between index point is calculated, it is as overlapping
Rotation translation relation between index point；
E3, coordinate transform made according to the overlapping index point point cloud of rotation translation relation pair.
Specifically, the threshold value in step E1 is mainly judged according to the index point standoff distance in overlapping region, also may be used
Whether the factors such as marginal position are in be judged according to index point；The object under test being placed on rotation platform and rotation
Index point on platform, it is constant in the relative position after rotation.As long as therefore calculate the rotation between index point
Translation relation, then the rotation translation relation between object under test point cloud also determines that, in the present embodiment, obtains the first weight
Behind folded domain, the rotation translation relation between index point is calculated using SVD decomposition methods, this rotation translation relation is equally applicable to
First overlapping domains, then the first overlapping domains are converted on an equal basis, obtain the object under test point cloud of rough registration, in wherein step E2
SVD decomposition methods are also decomposition of singular matrix method, and decomposition of singular matrix is popularization of the spectrum analysis theory on Arbitrary Matrix, using compared with
To be extensive, be mainly used to analyze principal component in statistics, identify specific pattern or carry out data compression etc., in the present embodiment its
It is mainly used in distinguishing mark point and carries out corresponding matrix operation, obtains the rotation translation matrix between index point.
Wherein, in step F, registration, tool are carried out to the overlapping index point point cloud after conversion using modified I CP algorithms
Body, overlapping index point point cloud is converted in step E, that is, has carried out rough registration, in the present embodiment, has accurately matched somebody with somebody
Standard realizes that modified I CP algorithms are a kind of prior arts, and in practice, I CP algorithms are mainly by modified I CP algorithms
It is a kind of approach iterative algorithm, it is necessary to point converge and should have larger overlapping range, to meet that the convergence precision of accuracy registration will
Ask, traditional I CP algorithms have the shortcomings such as initial point cloud position is high, efficiency of algorithm is low, and conventional modified I CP algorithms are general
With reference to K- neighbor search and normal estimation, and the structure algorithm based on Octree is used, a cloud accuracy registration can be carried out, entered
One step reduces the registering time, in the present embodiment, has mainly used the accurate of modified I CP algorithm combination K- neighbor search
Method for registering.
Presently preferred embodiments of the present invention and general principle are discussed in detail above content, but the invention is not limited in
Above-mentioned embodiment, those skilled in the art should be recognized that also had on the premise of without prejudice to spirit of the invention it is various
Equivalent variations and replacement, these equivalent variations and replacement all fall within the protetion scope of the claimed invention.
Claims (6)
1. a kind of point cloud registration method based on the rotation platform with index point, it is characterised in that comprise the following steps：
A, the labelling point on rotation platform, then object under test is positioned on rotation platform；
B, one angle of the rotation platform is rotated；
C, identify the index point position on rotation platform and calculate the central value coordinate of index point；
D, overlapping index point point cloud is calculated according to central value coordinate；
E, the rotation translation relation between overlapping index point is calculated, the overlapping index point of relation pair is translated according to the rotation
Point cloud makees coordinate transform；
F, registration is carried out to the overlapping index point point cloud after coordinate transform, you can obtain under this anglec of rotation after registration
Object under test point cloud；
G, repeat step B-F twice and more than, you can obtain the object under test overall picture point cloud after registration.
2. a kind of point cloud registration method based on the rotation platform with index point according to claim 1, its feature exist
In the index point position on identification rotation platform in the step C simultaneously calculates the central value coordinate of index point, specific steps
Including：
C1, utilize projecting apparatus and the original image of video camera acquisition object under test；
C2, the original image using edge detection algorithm processing object under test, the original image after processing are converted into lines wheel
Wide digitized first image, the index point comprising hole and fracture in described first image, shape in the outline
Into connected domain；
C3, the hole in the first image of filling and completion fracture index point；
C4, the noise spot that threshold requirement is not met in the connected domain being made up of in the first image outline is filtered out, and filtered out
Shared pixel ratio does not meet the region with index point of pixel ratio threshold requirement, obtains including the numeral in index point region
The second image changed；
C5, the picture element matrix of the first image is multiplied with the picture element matrix of the second image, obtains comprising only index point marginal information
The 3rd image, that is, identify the index point position on rotation platform；
C6, using based on the ellipse fitting algorithm of least square method to the 3rd image carry out ellipse fitting, calculate index point
Central value coordinate.
3. a kind of point cloud registration method based on the rotation platform with index point according to claim 2, its feature exist
In calculating overlapping index point point cloud according to central value coordinate in the step D, specific steps include：
D1, the anglec of rotation for calculating according to the central value coordinate of index point rotation platform；
D2, the angular range for calculating according to the anglec of rotation contiguous tokens point point cloud overlapping region, within this angular range
Index point is overlapping index point point cloud.
4. a kind of point cloud registration method based on the rotation platform with index point according to claim 3, its feature exist
In the anglec of rotation of rotation platform being calculated in the step D1 according to the central value coordinate of index point, specific steps include：
D11, demarcated according to the central value coordinate pair projecting apparatus and video camera of index point, obtain the interior of projecting apparatus and video camera
Parameter matrix and outer parameter matrix；
D12, bar graph obtained by projection of the projecting apparatus to the 3rd image, then pass through the bar after camera acquisition to translation-angle
Line figure, i.e. deforming stripe figure；
D13, handle deforming stripe figure using phase measuring profilometer and phase unwrapping and wiping out background noise are carried out to it, obtain
To the 4th image；
D14, go out the 3 D stereo point cloud comprising index point according to Intrinsic Matrix, outer parameter matrix and the 4th image structure；
D15, the index point in 3 D stereo point cloud is ranked up by order from left to right, then with through rotation platform center
On the basis of outside axis by the index point in 3 D stereo point cloud respectively minute in two parts region of left and right；
D16, the index point in two parts region of left and right and the angle value through the outside axis in rotation platform center are calculated,
The as anglec of rotation of rotation platform.
5. a kind of point cloud registration method based on the rotation platform with index point according to claim 3 or 4, its feature
It is, the rotation translation relation between overlapping index point is calculated in the step E, relation pair weight is translated according to the rotation
Folded index point point cloud makees coordinate transform, and specific steps include：
E1, rejecting standoff distance error amount do not meet the index point in the contiguous tokens point point cloud overlapping region of threshold requirement, obtain
To the first overlapping domains；
E2, using SVD decomposition methods calculate the rotation translation relation in the first overlapping domains between index point, as overlapping mark
Rotation translation relation between point；
E3, coordinate transform made according to the overlapping index point point cloud of rotation translation relation pair.
6. a kind of point cloud registration method based on the rotation platform with index point according to claim 1, its feature exist
In in the step F, using modified I CP algorithms to the overlapping index point point cloud progress registration after conversion.
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