CN106447715A - Plane reflection target central point position extraction method for laser radar - Google Patents
Plane reflection target central point position extraction method for laser radar Download PDFInfo
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Abstract
The invention discloses a plane reflection target central point position extraction method for laser radar. The method comprises the following steps of: projecting three-dimensional point cloud data of a plane reflection target to a fitting plane and carrying out grid division on the fitting plane; combining the reflection strength of point cloud to generate a depth image of the target; establishing a corresponding relationship between a plane projection point and the point cloud data; determining a plane reflection target central point position by utilizing the twice modifications carried out on the gray values of the grids; and pre-processing the point cloud data of the target by adoption of a steady Z fractional method so as to decrease the influences of noise points close to the reflection target and improve the correctness of the fitting plane. The plane reflection target central point position extraction method for laser radar is reasonable, correct and high in analysis and calculation speed, and is capable of getting rid of the influences of accidental errors and effectively extracting the central point of the plane reflection target so as to improve the scanning precision.
Description
Technical field
The present invention relates to the field such as historical relic's protection, ground mapping, specifically, it is related to a kind of plane for laser radar anti-
Penetrate Target Center point position extracting method.
Background technology
Three-dimensional laser scanning technique is the new technique of the survey field rising in recent years it is achieved that laser scanner technique and survey
The fusion of amount technology.Three-dimensional laser scanning technique has the advantages that not contact, automatization, speed are fast, can rapidly and efficiently obtain
Take the high accuracy three-dimensional cloud data of destination object, be widely used in fields such as historical relic's protection, ground mappings.
Three-dimensional laser scanner can carry out the splicing between survey station and configuration using measurement target during using, directly
Connect the Coordinate Conversion for cloud data, thus realizing the integrity of the measurement data to big scale of construction target.Existing target
The extraction algorithm at center is that this premise of emissive porwer maximum point is carried out based on plane Target Center mostly, but in reality
In situation, the easy heart in the target of laser is formed about multiple reflection effect, and the data at reflex strength center is easily subject to noise number
According to interference.And in actual scanning is applied, it is multiple that the precision of scanning is highly susceptible to temperature, pressure, humidity, illumination etc.
The impact of factor.The laser beam of three-dimensional laser scanner transmitting is highly susceptible to microgranule in air, steam, the suction of carbon dioxide
Receive, the impact of refractive power and interference be so that should be that the point cloud of a plane forms irregular plane in the ideal situation.
Content of the invention
The purpose of the present invention is for technological deficiency present in prior art, provides a kind of plane for laser radar
Instrument reflection target center position extracting method, using supporting plane reflection target, rejects the impact of incidental error, can be effective
Extraction plane reflection target central point, thus improving the precision of scanning.
In order to realize object of the present invention and further advantage, provide a kind of plane reflection target for laser radar
Center position extracting method, comprises the following steps:
The circular plane reflection target of step one, use, and two kinds of reflex strength differences are coated on plane reflection target
Coating, and make this two kinds of coating formed at least on plane reflection target two cross the centers of circle demarcation line;
Step 2, using three-dimensional laser scanner plane reflection target surface is scanned measure, obtain comprise plane
The cloud data of the reflex strength of the three-dimensional coordinate of instrument reflection target surface each point and each point;
Step 3, the cloud data obtaining step 2 project to the projection plane parallel with plane reflection target, will be each
The corresponding reflex strength of subpoint is converted into the gray value of each point, then divides grid in this projection plane, by each grid
The corresponding gray value of point as the gray value of each grid, and set up the corresponding relation between subpoint and cloud data;
Step 4, the gray value of each grid obtaining step 3 are modified according to below equation:I=| I1-I8|+|
I2-I7|+|I3-I6|+|I4-I5|, and the grid being located on two kinds of coating demarcation line is determined according to amended gray value;Wherein,
I is the gray value of grid to be modified, I1It is the gray value with the grid of the upper left of grid to be modified next-door neighbour, I2Be with to be modified
The gray value of the grid of front-left of grid next-door neighbour, I3It is the gray value with the grid of the lower left of grid to be modified next-door neighbour, I4For
With the gray value of the grid of the surface of grid to be modified next-door neighbour, I5It is the ash with the grid of the underface of grid to be modified next-door neighbour
Angle value, I6It is the gray value with the grid of the upper right of grid to be modified next-door neighbour, I7It is the front-right with grid to be modified next-door neighbour
The gray value of grid, I8It is the gray value with the grid of the lower right of grid to be modified next-door neighbour;
Step 5, by the gray value of the grid determining through step 4 on two kinds of coating demarcation line more as follows
Modify:
I '=I1’+I2’+I3’+I4’+I5’+I6’+I7’+I8', and determine through this formula amended gray value maximum
Grid, the corresponding relation between the subpoint then set up according to step 3 and cloud data, determine maximum with by this gray value
Grid in point in cloud data corresponding point, the corresponding point in cloud data be plane reflection target center
Point;Wherein, I ' is the gray value of grid to be modified, I1' be with grid to be modified next-door neighbour upper left grid gray value, I2’
It is the gray value with the grid of the front-left of grid to be modified next-door neighbour, I3' be with grid to be modified next-door neighbour lower left grid
Gray value, I4' be with grid to be modified next-door neighbour surface grid gray value, I5' it is just to be close to grid to be modified
The gray value of the grid of lower section, I6' be with grid to be modified next-door neighbour upper right grid gray value, I7' be and lattice to be modified
The gray value of the grid of front-right of net next-door neighbour, I8' be with grid to be modified next-door neighbour lower right grid gray value.
Preferably, in the described plane reflection Target Center point position extracting method for laser radar, in step
In three, if having in grid at multiple, using the meansigma methodss of each point gray value in the range of grid as grid gray value.
Preferably, in the described plane reflection Target Center point position extracting method for laser radar, in step
In five, if the maximum grid quantity of gray value is more than one, between the subpoint set up according to step 3 and cloud data
Corresponding relation, determine point in the maximum each grid of gray value corresponding point in cloud data respectively, gray value is maximum
Point in each grid coordinate of the meansigma methodss composition in each number axis for the corresponding point in cloud data is in plane reflection target
Heart point coordinates.
Preferably, in the described plane reflection Target Center point position extracting method for laser radar, if gray scale
When having at multiple in the maximum grid of value, then corresponding relation between the subpoint set up according to step 3 and cloud data, point
Do not determine the plurality of point corresponding point in cloud data, the plurality of point corresponding point in cloud data is average in each number axis
The coordinate of value composition is plane reflection Target Center point coordinates.
Preferably, in the described plane reflection Target Center point position extracting method for laser radar, in step
Before step 3 after two, also include:
Cloud data is carried out with multiple sampling and obtains multiple cloud subsets, calculate institute's invocation point cloud subset using PCA algorithm
Eigenvalue, selects the minimum point cloud subset of eigenvalue, simulates initial plane using this cloud subset;
WhenThen think that this point is rough error point, rejected;
Wherein, d is the vertical dimension to initial plane for this point;d0.5For arrive a little in cloud data initial plane away from
From median, d '0.5=1.4826 | d-d0.5|0.5, | d-d0.5|0.5For | d-d0.5| median, 2.0≤k≤2.5.
Preferably, in the described plane reflection Target Center point position extracting method for laser radar, in projection
Arrange in plane that orthogonal grid lines marks off multiple grid in projection plane, and so that the subpoint in each grid is not surpassed
Cross 3.
Preferably, in the described plane reflection Target Center point position extracting method for laser radar, plane is anti-
Penetrate target surface to be coated using abasier and the white two kinds of colors of crystal coating.
Preferably, in the described plane reflection Target Center point position extracting method for laser radar, its feature
It is, the demarcation line of two kinds of coating is mutually perpendicular to, and the equal diameters all with plane reflection target for the length.
The present invention at least includes following beneficial effect:
The plane reflection Target Center point position extracting method for laser radar of the present invention rationally, accurately, is analyzed, is counted
Calculate quick, the impact of incidental error being rejected, can effectively extracting the central point of plane reflection target, thus improving scanning
Precision.
Part is embodied by the further advantage of the present invention, target and feature by description below, and part also will be by this
Invention research and practice and be understood by the person skilled in the art.
Brief description
Fig. 1 is the flow process of the plane reflection Target Center point position extracting method for laser radar of the present invention
Figure;
Fig. 2 is the step 3 of the plane reflection Target Center point position extracting method for laser radar of the present invention
In the depth image of plane target that obtains;
Fig. 3 is the step 4 of the plane reflection Target Center point position extracting method for laser radar of the present invention
The label of middle grid periphery grid;
Fig. 4 is the step 4 of the plane reflection Target Center point position extracting method for laser radar of the present invention
In refetch gray value after the depth image of plane target that obtains;
Fig. 5 is the step 5 of the plane reflection Target Center point position extracting method for laser radar of the present invention
The label of middle grid periphery grid;
Fig. 6 is the step 5 of the plane reflection Target Center point position extracting method for laser radar of the present invention
In refetch gray value after the depth image of plane target that obtains.
Specific embodiment
The present invention is described in further detail below in conjunction with the accompanying drawings, to make those skilled in the art with reference to description literary composition
Word can be implemented according to this.
As shown in figs 1 to 6, the present invention provides a kind of plane reflection Target Center point position for laser radar to extract
Method:
The circular plane reflection target of step one, use, and two kinds of reflex strength differences are coated on plane reflection target
Coating, and make this two kinds of coating formed at least on plane reflection target two cross the centers of circle demarcation line;
Step 2, using three-dimensional laser scanner plane reflection target surface is scanned measure, obtain comprise plane
The cloud data of the reflex strength of the three-dimensional coordinate of instrument reflection target surface each point and each point;
Step 3, the cloud data obtaining step 2 project to the projection plane parallel with plane reflection target, will be each
The corresponding reflex strength of subpoint is converted into the gray value of each point, then divides grid in this projection plane, by each grid
The corresponding gray value of point as the gray value of each grid, and set up the corresponding relation between subpoint and cloud data;
Step 4, the gray value of each grid obtaining step 3 are modified according to below equation:I=| I1-I8|+|
I2-I7|+|I3-I6|+|I4-I5|, and the grid being located on two kinds of coating demarcation line is determined according to amended gray value;Wherein,
I is the gray value of grid to be modified, I1It is the gray value with the grid of the upper left of grid to be modified next-door neighbour, I2Be with to be modified
The gray value of the grid of front-left of grid next-door neighbour, I3It is the gray value with the grid of the lower left of grid to be modified next-door neighbour, I4For
With the gray value of the grid of the surface of grid to be modified next-door neighbour, I5It is the ash with the grid of the underface of grid to be modified next-door neighbour
Angle value, I6It is the gray value with the grid of the upper right of grid to be modified next-door neighbour, I7It is the front-right with grid to be modified next-door neighbour
The gray value of grid, I8It is the gray value with the grid of the lower right of grid to be modified next-door neighbour;
Step 5, by the gray value of the grid determining through step 4 on two kinds of coating demarcation line more as follows
Modify:
I '=I1’+I2’+I3’+I4’+I5’+I6’+I7’+I8', and determine through this formula amended gray value maximum
Grid, the corresponding relation between the subpoint then set up according to step 3 and cloud data, determine maximum with by this gray value
Grid in point in cloud data corresponding point, the corresponding point in cloud data be plane reflection target center
Point;Wherein, I ' is the gray value of grid to be modified, I1' be with grid to be modified next-door neighbour upper left grid gray value, I2’
It is the gray value with the grid of the front-left of grid to be modified next-door neighbour, I3' be with grid to be modified next-door neighbour lower left grid
Gray value, I4' be with grid to be modified next-door neighbour surface grid gray value, I5' it is just to be close to grid to be modified
The gray value of the grid of lower section, I6' be with grid to be modified next-door neighbour upper right grid gray value, I7' be and lattice to be modified
The gray value of the grid of front-right of net next-door neighbour, I8' be with grid to be modified next-door neighbour lower right grid gray value.
Provided by the present invention in the plane reflection Target Center point position extracting method of laser radar, in step one
The two kinds of different coating using, its reflex strength change in different optical maser wavelength is little, and reflex strength therebetween is deposited
Reflex strength difference between larger gap, the different coating of use is bigger, and the effect of use is better, thus ensureing to scan
Result has higher accuracy, and two kinds of coating intersections have larger discrimination, for example can be using abasier and crystal white two
The coating planting color is coated to plane reflection target surface, the reflex strength change in different optical maser wavelength of both coating
Less, and there is stable strength difference between the two, abasier substantially remain in numerical value 2 about, crystal end is basic to keep
In numerical value 48 about, suitable laser scanner identification;The coating smearing use is mainly pigment, and pigment is ancient Chinese drawing work
The key component of skill, is widely used in the allotment of the color of building and other implements, briefly pigment is exactly can
To be suspended in stain or the coloring agent of the drying in substrate, will adsorb after the substrate of liquid air-dries in building or
The surface of person's implements, wherein coloring earth have lasting color and the raw material sources compared with horn of plenty, and always colored drawing is main
Color is originated, so coating used in the present invention is mainly coloring earth;Can be using two diameters by described plane reflection mark
Target surface is divided into 4 90 ° of sectors, using two different colors of coating, sector is intersected and smears, now in step 3
The demarcation line of the depth image of plane reflection target obtaining is two orthogonal diameters, or using three diameters by institute
State the covering of the fan face that plane reflection target surface is divided into 6 60 °, using two different colors of coating, sector intersected and smear,
The demarcation line of the depth image of plane reflection target now obtaining in step 3 is three intersecting diameters, except rule applies
Smear outer, with the radius of more than two, plane reflection target surface can also be divided into multiple irregular sectors, such as with two
Plane reflection target surface is divided into a little sector fan-shaped greatly with one by radius, smears different paintings on two sectors
Material, the demarcation line of the depth image of plane reflection target now obtaining in step 3 is half that two angles are less than 180 °
Footpath, it is possible to use plane reflection target surface is divided into all different sector of four number of degrees etc. by four radiuses, to adjacent
Sector smears different coating, and the demarcation line of the depth image of plane reflection target now obtaining in step 3 is four
Radius;
Provided by the present invention in the plane reflection Target Center point position extracting method of laser radar, in step 3
Corresponding for each subpoint reflex strength is converted into the gray value of each point, is that this point ash is represented with the value of the reflex strength of each point
Angle value, cloud data is projected to the projection plane parallel with plane reflection target, and it is right between subpoint and cloud data to set up
The method that should be related to can be adopted with the following method:
The plane equation of projection plane is:
P (x, y, z)=ax+by+cz+d=0
Divide out d simultaneously on above equation both sides, obtains the plane form being indicated using the amount of being sent to:
nxx+nyy+nzZ+1=0
The unit vector of the normal vector of plane is:
nu=[d nxd·nyd·nz]T
According to method of least square principle it is desirable to:
Wherein m is observation number, can obtain n=N-1T, that is,:
N can be tried to achieve by above formulax、ny、nzValue, obtain the plane equation of fit Plane;
After fit Plane, set up the index relative of subpoint and three-dimensional point cloud:
Any point (x in cloud data0,y0,z0) plane vertical line equation be:
Simultaneous plane equation:
X=x0+aT
Y=y0+bT
Z=z0+cT
The coordinate (x, y, z) that subpoint projects in plane can be tried to achieve, by fit Plane through translation rotation transformation (conversion square
Battle array) after be transformed into XOY plane, the subpoint drop point in same fit Plane has also been transformed into XOY plane after this matrixing
On, transformation matrix method is as follows:
Fit Plane normal vector:Vector n=(a, b, c), Z-direction vector (0,0,1)
WxAngle for plane normal vector and XOZ plane;
WyAngle for plane normal vector and YOZ plane;
First certain point in plane is moved to initial point;Plane first rotate Wx around X-axis, further around Y-axis rotation Wy it is possible to
Z axis overlap;
Plane around X-axis rotate when:
X '=x,
Y '=ycosWx+zsinWx
Z '=ysinWx+zcosWx
Plane rotates around Y-axis
X '=zsinWy+x cosWy,
Y '=y
Z '=z cosWy-x sinWy
All planar points all on XOY plane, obtain the corresponding relation between subpoint and cloud data after matrixing;
After having divided grid, set up in cloud data any point in the ranks number of gray level image:
False coordinate initial point is O, and any point P (x, y, z) represents the three-dimensional coordinate of one of arbitrary scanning element, OP with
The angle of XOY plane is β (pi/2 >=β >=-pi/2), and projection line on XOY plane for the OP is α (2 π >=α >=0) with the angle of X-axis,
The so corresponding α of each scanning element cloud and β value, solve the head office of depth image according to α and β value according to following two formulas
Number M and total columns N, wherein a are angular sampling interval:
M=rounds ((maximum β-minimum β)/a)+1
N=rounds ((maximum α-minimum of alpha)/a)+1
Solve each scanning element according to following two formula respectively in the corresponding ranks number of depth image:
Total line number M- of row=rounds ((β-minimum β)/a)
Column=total columns N- rounds ((α-minimum of alpha)/a)
So in cloud data, any point all has corresponding ranks number (M, N) in depth image, if in a grid
Include multiple scanning elements, grid gray scale then takes scanning element reflex strength meansigma methodss;
Provided by the present invention in the plane reflection Target Center point position extracting method of laser radar, in step 3
The depth image of the plane target obtaining is as shown in Fig. 2 the coating of Fig. 2 midplane instrument reflection target surface smear is abasier and water
Brilliant white, the two reflex strength difference is larger, and the region that in the depth image of formation, the two is smeared is distinguished substantially;Fig. 3 is step 4
The label of middle grid periphery grid, after the gray value of each grid that step 3 is obtained is modified according to below equation, obtains
To new depth image, the gray value maximum of the grid of line position of demarcating after changing gray value, the plane mark that Fig. 4 as newly obtains
The depth image of target, the white line position in Fig. 4 is the demarcation line of two kinds of coating, and Fig. 5 is grid periphery grid in step 4
Label, after modifying through the gray value positioned at the grid on two kinds of coating demarcation line that step 4 determines in step 5, Fig. 6
As obtain the depth image of new plane target, the maximum lattice of gray value after the white grid in Fig. 6, as modification gray value
Net.
In another kind of technical scheme, the described plane reflection Target Center point position extracting method for laser radar
In, in step 3, if having in grid at multiple, using the meansigma methodss of each point gray value in the range of grid as grid gray scale
Value, due to dividing during grid it is impossible to ensure only one of which subpoint in each grid, so when the multiple points of appearance in grid
When, need the gray value of the meansigma methodss of each point gray value using in the range of grid as grid.
In another kind of technical scheme, the described plane reflection Target Center point position extracting method for laser radar
In, in step 5, if the maximum grid quantity of gray value is more than one, the subpoint set up according to step 3 and point
Corresponding relation between cloud data, corresponding point, the gray scale in cloud data of the point in the maximum each grid of determination gray value respectively
It is anti-that point in the maximum each grid of value coordinate of the meansigma methodss composition in each number axis for the corresponding point in cloud data is plane
Penetrate Target Center point coordinates.
In another kind of technical scheme, the described plane reflection Target Center point position extracting method for laser radar
In, if having at multiple in the maximum grid of gray value, right between the subpoint set up according to step 3 and cloud data
Should be related to, determine the plurality of point corresponding point in cloud data respectively, the plurality of point in cloud data corresponding point each
The coordinate of the meansigma methodss composition of number axis is plane reflection Target Center point coordinates.
In another kind of technical scheme, the described plane reflection Target Center point position extracting method for laser radar
In, before step 3 after step 2, also include carrying out excluding gross error using sane Z score method;
In actual scanning is applied, the precision of scanning is highly susceptible to the many factors such as temperature, pressure, humidity, illumination
Impact, so pretreatment is carried out to the center cloud data of target using sane Z score method, picking out rough error, can reject
The impact of incidental error, the method for sane Z score method excluding gross error is as follows:
The random point cloud subset preferably going out multiple point compositions from cloud data, carries out multiple sampling and obtains multiple clouds
Collection, and 3 eigenvalues of institute's invocation point cloud subset are calculated using PCA algorithm:γ0<γ1<γ2, γ0More point cloud point collection is flat altogether
Face degree is higher, therefore wherein minimum eigenvalue γ0As the distinguishing rule of the copline degree of a cloud point collection, select feature
The minimum point cloud subset of value is optimum cloud subset, using a cloud subset matching reliability areal model initial value, obtains initial plane
Plane equation;
Because rough error point Statistical Distribution is unknown, it is difficult to disposably reject rough error, is entered than fractal methods using Z
Row circulation excluding gross error, that is, circulation obtains reliable initial model according to distance and minimum criteria every time, recalculates vertical dimension
Error in median and median, and calculate value Z of the sane Z score of each point of a cloud subset, by the point of >=k from a cloud subset
Middle rejecting, as a Z for all points of concentration<Stop circulation during k;
Excluding gross error is come using sane Z score method, the distance taking any point to initial plane in a cloud subset is d, then
The sane Z score of this point is defined as:
Wherein:D is the vertical dimension to fit Plane for this point;d0.5For arrive a little in cloud data initial plane away from
From median, d '0.5=1.4826 | d-d0.5|0.5, | d-d0.5|0.5For | d-d0.5| median, 2.0≤k≤2.5.
In another kind of technical scheme, the described plane reflection Target Center point position extracting method for laser radar
In, arrange that orthogonal grid lines marks off multiple grid in projection plane on a projection plane, and make in each grid
Subpoint is less than 3, and the grid area of division is less, and the result of calculating is more accurate, and described grid is square, its length of side
Computational methods are as follows:
Wherein:XmaxRepresent the maximum projecting to coordinate in X-axis in all subpoints after XOY plane;XminRepresent and throw
In shadow all subpoints to after XOY plane in X-axis coordinate minima;N represents a number at cloud midpoint.
In another kind of technical scheme, the described plane reflection Target Center point position extracting method for laser radar
In, plane reflection target surface is coated using abasier and the white two kinds of colors of crystal coating, and both coating is in difference
During optical maser wavelength less, and there is stable strength difference in reflex strength change between the two, abasier substantially remains in number
Value 2 about, crystal end substantially remains in numerical value 48 about, suitable laser scanner identification;In addition can also be applied using other
Material is smeared, and need to ensure that the coating using its reflex strength under conditions of the laser of different wave length is stable, the difference of use
Reflex strength difference between coating is bigger, and the effect of use is better.
In another kind of technical scheme, the described plane reflection Target Center point position extracting method for laser radar
In it is characterised in that the demarcation line of two kinds of coating is mutually perpendicular to, and equal diameters all with plane reflection target for the length;Can make
With two diameters, described plane reflection target surface is divided into 4 90 ° of sectors, using abasier and the two kinds of colors in crystal end
Coating intersection is filled with, and in addition to rule is smeared, can also be divided into plane reflection target surface with the radius of more than two
Plane reflection target surface is such as divided into a little sector fan-shaped greatly with one with two radiuses by multiple irregular sectors,
Smear different coating on two sectors, the boundary of the depth image of plane reflection target now obtaining in step 3
Line is the radius that two angles are less than 180 °, it is possible to use plane reflection target surface is divided into four number of degrees equal by four radiuses
Different sector etc., smears different coating to adjacent sector, the plane reflection target now obtaining in step 3
Depth image demarcation line be four radiuses;Smear target method have pure color target, varnish manual brushing, NIUJIAO brush and
Paint machine spraying etc..
Although embodiment of the present invention is disclosed as above, it is not restricted to listed in description and embodiment
With, it can be applied to various suitable the field of the invention completely, for those skilled in the art, can be easily
Realize other modification, therefore under the general concept being limited without departing substantially from claim and equivalency range, the present invention does not limit
In specific details with shown here as the legend with description.
Claims (8)
1. a kind of plane reflection Target Center point position extracting method for laser radar is it is characterised in that include:
The circular plane reflection target of step one, use, and the different painting of two kinds of reflex strengths is coated on plane reflection target
Material, and make this two kinds of coating form two demarcation line crossing the center of circle at least on plane reflection target;
Step 2, using three-dimensional laser scanner plane reflection target surface is scanned measure, obtain comprise plane reflection
The cloud data of the reflex strength of the three-dimensional coordinate of target surface each point and each point;
Step 3, the cloud data obtaining step 2 project to the projection plane parallel with plane reflection target, by each projection
The corresponding reflex strength of point is converted into the gray value of each point, then divides grid in this projection plane, by the point in each grid
Corresponding gray value is as the gray value of each grid, and sets up the corresponding relation between subpoint and cloud data;
Step 4, the gray value of each grid obtaining step 3 are modified according to below equation:I=| I1-I8|+|I2-I7
|+|I3-I6|+|I4-I5|, and the grid being located on two kinds of coating demarcation line is determined according to amended gray value;Wherein, I is
The gray value of grid to be modified, I1It is the gray value with the grid of the upper left of grid to be modified next-door neighbour, I2It is and grid to be modified
The gray value of the grid of front-left of next-door neighbour, I3It is the gray value with the grid of the lower left of grid to be modified next-door neighbour, I4It is and treat
The gray value of the grid of surface of modification grid next-door neighbour, I5It is the gray scale with the grid of the underface of grid to be modified next-door neighbour
Value, I6It is the gray value with the grid of the upper right of grid to be modified next-door neighbour, I7It is the lattice with the front-right of grid to be modified next-door neighbour
The gray value of net, I8It is the gray value with the grid of the lower right of grid to be modified next-door neighbour;
Step 5, the gray value of the grid determining through step 4 on two kinds of coating demarcation line is carried out as follows again
Modification:
I '=I1’+I2’+I3’+I4’+I5’+I6’+I7’+I8', and determine through the maximum lattice of the amended gray value of this formula
Net, the corresponding relation between the subpoint then set up according to step 3 and cloud data, determine maximum with by this gray value
Point in grid corresponding point in cloud data, the corresponding point in cloud data is the central point of plane reflection target;
Wherein, I ' is the gray value of grid to be modified, I1' be with grid to be modified next-door neighbour upper left grid gray value, I2' be
With the gray value of the grid of the front-left of grid to be modified next-door neighbour, I3' be with grid to be modified next-door neighbour lower left grid
Gray value, I4' be with grid to be modified next-door neighbour surface grid gray value, I5' be with grid to be modified next-door neighbour just under
The gray value of the grid of side, I6' be with grid to be modified next-door neighbour upper right grid gray value, I7' be and grid to be modified
The gray value of the grid of front-right of next-door neighbour, I8' be with grid to be modified next-door neighbour lower right grid gray value.
2. the plane reflection Target Center point position extracting method for laser radar according to claim 1, its feature
Be, in step 3, if having in grid at multiple, using the meansigma methodss of each point gray value in the range of grid as grid ash
Angle value.
3. the plane reflection Target Center point position extracting method for laser radar according to claim 1, its feature
Be, in step 5, if the maximum grid quantity of gray value is more than one, the subpoint set up according to step 3 with
Corresponding relation between cloud data, corresponding point, the ash in cloud data of the point in the maximum each grid of determination gray value respectively
Point in the maximum each grid of angle value coordinate of the meansigma methodss composition in each number axis for the corresponding point in cloud data is plane
Instrument reflection target center point coordinate.
4. the plane reflection Target Center point position extracting method for laser radar according to claim 1 and 2, it is special
Levy and be, if having at multiple in the maximum grid of gray value, between the subpoint set up according to step 3 and cloud data
Corresponding relation, determine the plurality of point corresponding point in cloud data, the plurality of point corresponding point in cloud data respectively
It is plane reflection Target Center point coordinates in the coordinate of the meansigma methodss composition of each number axis.
5. the plane reflection Target Center point position extracting method for laser radar according to claim 1, its feature
It is, before step 3 after step 2, also include:
Cloud data is carried out with multiple sampling and obtains multiple cloud subsets, calculate the feature of institute's invocation point cloud subset using PCA algorithm
Value, selects the minimum point cloud subset of eigenvalue, simulates initial plane using this cloud subset;
WhenThen think that this point is rough error point, rejected;
Wherein, d is the vertical dimension to initial plane for this point;d0.5For arriving a little the distance of initial plane in cloud data
Median, d '0.5=1.4826 | d-d0.5|0.5, | d-d0.5|0.5For | d-d0.5| median, 2.0≤k≤2.5.
6. the plane reflection Target Center point position extracting method for laser radar according to claim 1, its feature
It is, arrange that orthogonal grid lines marks off multiple grid in projection plane on a projection plane, and make in each grid
Subpoint be less than 3.
7. the plane reflection Target Center point position extracting method for laser radar according to claim 1, its feature
It is, plane reflection target surface is coated using abasier and the white two kinds of colors of crystal coating.
8. the plane reflection Target Center point position extracting method for laser radar according to claim 1 or 7, it is special
Levy and be, the demarcation line of two kinds of coating is mutually perpendicular to, and the equal diameters all with plane reflection target for the length.
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---|---|---|---|---|
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE19525561A1 (en) * | 1994-07-13 | 1996-01-25 | Murata Machinery Ltd | Three=dimensional measuring device using twin CCD cameras and sample beam projector |
KR100684630B1 (en) * | 2006-01-03 | 2007-02-22 | 삼성중공업 주식회사 | Image processing method for tracking welding line |
CN103606147A (en) * | 2013-11-06 | 2014-02-26 | 同济大学 | Coordinate system transformation and calibration method of multiple measurement cameras with different fields of view |
CN104007444A (en) * | 2014-06-09 | 2014-08-27 | 北京建筑大学 | Ground laser radar reflection intensity image generation method based on central projection |
CN104063860A (en) * | 2014-06-12 | 2014-09-24 | 北京建筑大学 | Method for refining edge of laser-point cloud |
CN104237868A (en) * | 2014-08-25 | 2014-12-24 | 北京建筑大学 | Multifunctional practical laser radar scanning target |
-
2016
- 2016-06-14 CN CN201610424032.3A patent/CN106447715B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE19525561A1 (en) * | 1994-07-13 | 1996-01-25 | Murata Machinery Ltd | Three=dimensional measuring device using twin CCD cameras and sample beam projector |
KR100684630B1 (en) * | 2006-01-03 | 2007-02-22 | 삼성중공업 주식회사 | Image processing method for tracking welding line |
CN103606147A (en) * | 2013-11-06 | 2014-02-26 | 同济大学 | Coordinate system transformation and calibration method of multiple measurement cameras with different fields of view |
CN104007444A (en) * | 2014-06-09 | 2014-08-27 | 北京建筑大学 | Ground laser radar reflection intensity image generation method based on central projection |
CN104063860A (en) * | 2014-06-12 | 2014-09-24 | 北京建筑大学 | Method for refining edge of laser-point cloud |
CN104237868A (en) * | 2014-08-25 | 2014-12-24 | 北京建筑大学 | Multifunctional practical laser radar scanning target |
Non-Patent Citations (1)
Title |
---|
陈俊杰,闫伟涛: "基于激光点云的平面标靶中心坐标提取方法研究", 《工程勘察》 * |
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