CN102012964B - Method and device for processing sampling data of laser scanning - Google Patents

Abstract

The embodiment of the invention provides a method and a device for processing sampling data of laser scanning. The method mainly comprises the following steps: and obtaining the average value of the Range values corresponding to the set number of sampling nodes on the same layer as the sampling nodes, wherein the sampling nodes with the same longitudinal scanning angle theta are the sampling nodes on the same layer. When the difference value between the Range value corresponding to the sampling node and the average value is larger than a set threshold value, determining the sampling node as a noise node and marking the noise node as a missing node; otherwise, determining the sampling node as a normal node. By utilizing the embodiment of the invention, the noise, hole repairing and sparse data supplementing processing can be carried out on the sampling data of the laser scanning based on the working parameters of the sampling data of the laser scanning. The embodiment of the invention can accurately and quickly determine the missing node and the sparse area and effectively supplement the missing node and the sparse area.

Description

The disposal route of the sampled data of laser scanning and device

Technical field

The invention belongs to the laser measurement field, be specifically related to a kind of disposal route and device of laser scanning sampled data.

Background technology

A kind of new technology that laser scanning is got up as development in recent years has detection accuracy height, imaging advantage such as directly perceived, in the accurate detection of each spacelike region, demonstrates original advantage.Three-dimensional laser scanner is the distance between a kind of each measurement point that obtains three-dimensional laser scanner and measured target surface through laser range sensor, and then obtains the equipment of the three-dimensional space shape of measured target.Three-dimensional laser scanner can be realized the high precision nondestructive measurement, all has significant application value at numerous areas such as 3 d modeling of building, the structures digitizing of down-hole, mine, historical relic's protections.

The synoptic diagram of a kind of 3 D laser scanning process of the prior art is as shown in Figure 1, and the core component of scanner head can be done 360 ° of laterally rotations, and collects distance value and scanning angle data.After 360 ° of transversal scanning of the every completion of scanner head, vertically turn over the scanning of carrying out a new round behind the certain angle according to the elevation angle of prior setting.Simultaneously, scanner head integral body can move up and down, and scans the positional information of whole dead zone scope.

Because receive dead zone dust pollution, steam in the actual scanning process, by the influence of factors such as sweep volume rough surface, measuring system error; Be mixed with the noise of 0.1%-5% in the laser scanning data that three-dimensional laser scanner measurement obtains (being cloud data); For subsequent treatment such as the reconstruct of dead zone form and surface fitting are brought difficulty; Therefore, need eliminate noise processed to the sampled data of laser scanning.

Because the reflectivity on surface, dead zone; The dead zone exist laser scanning less than the influence of factors such as restriction of dead angle (such as blocking), laser measurement angle; Three-dimensional laser scanner can't measure some local cloud data of dead zone, and the laser scanning data that collects often contains hole.Therefore, need carry out hole repair to the sampled data of laser scanning handles.

The density of laser scanning data depends on laser scanning interval and scanning distance.For long and narrow dead zone, because the longitudinal scanning angle is big, scanning distance is far away, and there is tangible sparse zone in the laser scanning data that collects.The distance value of image data is big more, and the dot density of scanning is low more, and then laser scanning data is sparse more.Therefore, need carry out sparse data to the sampled data of laser scanning and augment processing.

Of the prior artly a kind ofly laser scanning data eliminated the method that noise, hole repair handle be: adopt median filter method or image processing method to eliminate the noise of laser scanning data, adopt curve reestablishing before, in the curve reestablishing and the patch algorithm behind the curve reestablishing carry out hole repair and handle.Hole repair before the curve reestablishing mainly is the defect area that extracts hole, and constructing curve carries out the data benefit survey in hole zone then, carries out the grid model that curve reestablishing obtains data at last.

In realizing process of the present invention; The inventor finds above-mentionedly of the prior artly laser scanning data is eliminated the method that noise, hole repair handle to have following problem at least: adopting median filter method to eliminate noise need be based on the scanning relation of data; Be difficult to handle continuous noise data, and calculated amount is very big.Adopt image processing method to eliminate noise and need find suitable projecting plane, carry out projection at two dimensional surface, the complexity of realization is bigger.

Based on curve reestablishing laser scanning data is carried out hole repair, calculated amount is bigger, and does not describe the Processing Algorithm of hole edge.

Summary of the invention

Embodiments of the invention provide a kind of three-dimensional laser scanning measurement method and device, to realize that the sampled data of laser scanning is eliminated noise, hole repair and sparse data effectively augments processing.

A kind of disposal route of sampled data of laser scanning comprises:

Obtain and the mean value of sampling node with the corresponding distance R ange value of the sampling node of the setting quantity of layer, the sampling node with identical longitudinal scanning angle θ is the sampling node with layer;

When the corresponding distance R ange value of said sampling node and the difference between the said mean value during greater than preset threshold, then definite said sampling node is the noise node, and is labeled as the disappearance node; Otherwise, confirm that said sampling node is a normal node.

A kind of treating apparatus of sampled data of laser scanning comprises:

The mean value calculation module is used to obtain and the mean value of sampling node with the corresponding distance R ange value of the sampling node of the setting quantity of layer, and the sampling node with identical longitudinal scanning angle θ is the sampling node with layer;

Disappearance node judge module; Be used for when the difference between the mean value that the corresponding distance R ange value of said sampling node and said mean value calculation module are calculated during greater than preset threshold; Confirm that then said sampling node is the noise node, and mark disappearance node; Otherwise, confirm that said sampling node is a normal node.

Technical scheme by the embodiment of the invention described above provides can find out that the embodiment of the invention is carried out noise, hole repair and sparse data to the sampled data of laser scanning and augmented processing based on the running parameter of the sampled data of laser scanning.The embodiment of the invention can be confirmed disappearance node and sparse zone accurately and rapidly, and disappearance node and sparse zone are augmented effectively.

Description of drawings

In order to be illustrated more clearly in the technical scheme of the embodiment of the invention; The accompanying drawing of required use is done to introduce simply in will describing embodiment below; Obviously, the accompanying drawing in describing below only is some embodiments of the present invention, for those of ordinary skills; Under the prerequisite of not paying creative work property, can also obtain other accompanying drawing according to these accompanying drawings.

Fig. 1 is the synoptic diagram of a kind of 3 D laser scanning process of the prior art;

A kind of sampled data to laser scanning that Fig. 2 provides for the embodiment of the invention one is carried out the processing flow chart that noise, hole repair and sparse data are augmented the method for processing;

It is a kind of when 90 °＜β≤135 ° that Fig. 3 provides for the embodiment of the invention one, makees the synoptic diagram of the angular bisector of angle β;

It is a kind of when 135 °＜β≤180 °, to the synoptic diagram of angle β trisection that Fig. 4 provides for the embodiment of the invention one;

It is a kind of when β＞200 ° that Fig. 5 provides for the embodiment of the invention one, makees the synoptic diagram of the angular bisector of angle β;

The concrete structure figure of a kind of 3 D laser scanning measurement mechanism that Fig. 6 provides for the embodiment of the invention.

Embodiment

For ease of the understanding to the embodiment of the invention, will combine accompanying drawing below is that example is done further and explained with several specific embodiments, and each embodiment does not constitute the qualification to the embodiment of the invention.

Embodiment one

A kind of sampled data to laser scanning that this embodiment provides is carried out noise, hole repair and sparse data, and to augment the treatment scheme of method of processing as shown in Figure 2, comprises following treatment step:

Step 21, transversal scanning angle [alpha], longitudinal scanning angle θ, distance R ange value and the three dimensional space coordinate that each sampling node is corresponding are stored.

Near the centre laser scanner is installed in the dead zone; According to dead zone form and size; The transversal scanning angle intervals and the longitudinal scanning angle intervals of adjustment laser scanner; Whole dead zone scanned obtain laser scanning data, comprise a plurality of corresponding sampled datas of sampling node in this laser scanning data with different sequence numbers.

Sampling pattern to the sampled data of above-mentioned laser scanning is analyzed; The three dimensional space coordinate of confirming each sampling node according to the corresponding transversal scanning angle [alpha] of each sampling node and longitudinal scanning angle θ; And each sampled data carried out position mark, the sampled data with identical longitudinal scanning angle θ is labeled as one deck of circumferential.

The variation range of above-mentioned transversal scanning angle [alpha] is between [0 °, 360 °], and the SI of above-mentioned transversal scanning angle [alpha] is 0.1 °; The angle variation range of above-mentioned longitudinal scanning angle θ is between [90 °, 90 °], and the SI of above-mentioned longitudinal scanning angle θ is 4 °.In practical application, can be according to variation range and the SI of the size adjustment α and the θ of dead zone.

Transversal scanning angle [alpha], longitudinal scanning angle θ, distance R ange value and three dimensional space coordinate that each sampling node is corresponding are kept in the sampled data information table shown in the below table 1.

Table 1:

The sampled point sequence number

The θ angle

The α angle

?Range

x

?y

z

Flag

Next sampled point pointer

The scanner head of the Range value representation laser scanner in the above-mentioned table 1 and the distance between the sampling node, whether FLAG is used to identify sampling node is the noise node, when FLAG=0 is expressed as noise, FLAG=1 representes not to be noise.

Step 22, according to the Range value of sampling node and with the gap of sampling node with the corresponding average Range value of the sampling node in the setting range of layer, judge whether sampling node is the noise node.

Above-mentioned sampled data information table is read in internal memory; Handle the Range value of each sampling node successively; Compare with the Range average Aver_Range of 300 sampled datas of neighborhood inside in the front and back of same one deck (being same longitudinal scanning angle θ); The sampling node that error is greater than or less than preset threshold is labeled as the noise node, and the three-dimensional sampled data that this node is corresponding is removed, and is labeled as the disappearance node.Above-mentioned preset threshold can be 10%.

Such as, establish the corresponding distance R ange value of i sampling node and be Rangei, then

$\mathrm{Aver}\_{\mathrm{Range}}_i=\frac{\underset{i=-150,i\≠0}{\overset{150}{\mathrm{\Σ}}}{\mathrm{Range}}_i}{300}$

if

then judge that above-mentioned i sampling node is the noise node; The three-dimensional sampled data deletion that above-mentioned i sampling node is corresponding, the corresponding Flag of above-mentioned i sampling node is set to 0.

Step 23, continue to search the disappearance node, and constitute a blind bore hole,, take the corresponding perforations method for repairing and mending respectively according to the size of the internal angle beta in the hole through certain α angular range in the adjacent layer of disappearance node.

For each disappearance node,, check the interior necessarily deficient phenomena of the sampling node of α angular range of adjacent layer (adjacent θ angle) of this disappearance node according to the transversal scanning angle [alpha] of this disappearance node:

If there are a plurality of disappearance nodes in the certain α angular range in the adjacent layer of 1 above-mentioned disappearance node (adjacent θ angle), then write down all normal node and disappearance node, the normal node that will be positioned at a plurality of disappearance nodes two ends is labeled as the summit.Then, the deficient phenomena of the sampling node of the certain α angular range in the adjacent layer (adjacent θ angle) on the above-mentioned summit of continuation inspection.If there are a plurality of disappearance nodes, then write down all normal node and disappearance node, the normal node that will be positioned at a plurality of disappearance nodes two ends is labeled as the summit.Repeat above-mentioned processing procedure, until there is not the deficient phenomena of sampling node in the certain α angular range in the adjacent layer (adjacent θ angle) on above-mentioned summit.The summit of above-mentioned mark is coupled together with line segment between any two, and all summits constitute a blind bore hole.

Above-mentioned hole is a not polygon of coplane, and this polygon comprises a plurality of internal angle beta, and each internal angle beta is the angle between two line segments that connect 3 adjacent summits.

According to the size of each above-mentioned internal angle beta, be divided into following four kinds of situation and handle respectively:

(a) when β≤90 °, do not handle, promptly do not augment the disappearance node between 3 corresponding summits of this internal angle beta;

(b) when 90 °＜β≤135 °, be the angular bisector P of angle β _iV _i, see Fig. 3, line segment P _iV _iLength be:

$P_i{V}_i=\frac{P_i{P}_{i+1}+P_i{P}_{i-1}}{2}$

Said P _i, P _I-1, P _I+1For 3 corresponding summits of said β, at line segment P _iV _iThe newly-increased interpolation knot V of endpoint location _i, this interpolation knot V _iThe sampling node of augmenting for hole inside.

(c) when 135 °＜β≤180 °, to angle β trisection, see Fig. 4, line segment P _iV ₁And P _iV ₂Length be respectively:

$P_i{V}_1=\frac{P_i{P}_{i+1}+P_i{P}_{i-1}+P_{i+2}{P}_{i+1}}{3}$

$P_i{\mathrm{<figure-callout\; id="2"\; label="V"\; filenames="HSA00000281257000023.png"\; state="\{\{state\}\}">V</figure-callout>}}_2=\frac{P_i{P}_{i+1}+P_i{P}_{i-1}+P_{i-2}{P}_{i-1}}{3}$

Said P _i, P _I-1, P _I+1, P _I+2, P _I-2For corresponding 5 the adjacent summits of said β, at line segment P _iV ₁And P _iV ₂Newly-increased interpolation knot V1 of endpoint location and V2, this interpolation knot V1 and V2 are the sampling node of augmenting of hole inside.

(d) when β＞200 °, do angle β bisector, see Fig. 5, line segment P _I+1V ₁And P _I-1V ₂All be parallel to angular bisector, V ₁Be P _I+1V ₁And P _I-1P _iExtending line intersection point, V ₂Be P _I-1V ₂And P _I+1P _iExtending line intersection point, said P _i, P _I-1, P _I+1, P _I+2, P _I-2Be corresponding 5 the adjacent summits of said β.

Above-mentioned interpolation knot V ₁And V ₂The sampling node of augmenting for hole inside.

If there is not the disappearance node in the certain α angular range in the adjacent layer of 2 above-mentioned disappearance nodes (adjacent θ angle); Layer at disappearance node place obtains four adjacent α of the transversal scanning angle [alpha] of disappearance node; Three-dimensional coordinate according to four corresponding sampling node of said four adjacent α carries out three-dimensional weighted sum calculating; Obtain the three-dimensional coordinate of the sampling node of augmenting, the computing method that said three-dimensional weighted sum is calculated are following:

$x(\mathrm{\&alpha;},\mathrm{\&theta;})=\underset{i=-2,i\&NotEqual;0}{\overset{2}{\mathrm{\&Sigma;}}}{\mathrm{\&omega;}}_{i}x({\mathrm{\&alpha;}}_i,\mathrm{\&theta;}),$

$y(\mathrm{\&alpha;},\mathrm{\&theta;})=\underset{i=-2,i\&NotEqual;0}{\overset{2}{\mathrm{\&Sigma;}}}{\mathrm{\&omega;}}_{i}y({\mathrm{\&alpha;}}_i,\mathrm{\&theta;}),$

$z(\mathrm{\&alpha;},\mathrm{\&theta;})=\underset{i=-2,i\&NotEqual;0}{\overset{2}{\mathrm{\&Sigma;}}}{\mathrm{\&omega;}}_{i}z({\mathrm{\&alpha;}}_i,\mathrm{\&theta;})$

X (the α that aforementioned calculation goes out _i, θ), y (α _i, θ) and z (α _i, θ) for augmenting the three-dimensional coordinate of node, the x (α on right side _i, θ), y (α _i, θ) and z (α _i, θ) be the three-dimensional coordinate of above-mentioned adjacent four sampling node, wherein, ω _iBe the weight of four sampled points, ω ₁=ω _-1=1/3, ω ₂=ω _-2=1/6.

If there is not the disappearance node in the certain α angular range in the adjacent layer of the sampling node of 3 above-mentioned disappearances (adjacent θ angle); Only in the layer of the sampling node place of disappearance, there are a plurality of disappearance nodes; Then at first confirm the α angle value of the intermediate supports position of a plurality of disappearance nodes, α _MaxAnd α _MinThe transversal scanning angle of expression missing data section two ends sampling node:

α＝α _min+(α _max-α _min)/2

Carry out above-mentioned three-dimensional weighted sum according to the three-dimensional coordinate of four corresponding sampling node of four of the transversal scanning angle [alpha] of said intermediate supports position adjacent α and calculate, obtain the three-dimensional coordinate of the sampling node of augmenting.The position of the iterative computation left and right sides strong point is augmented until all disappearance points.

Step 24, confirm sparse zone, sparse data is carried out in above-mentioned sparse zone augment processing according to the difference between the Range average of the sampled data after the segmentation of the relevant position of the Range average of the sampled data of the same one deck after the segmentation and adjacent layer.

The sampling node of every layer disappearance is all augmented finish after, will carry out segmentation with the sampled data of one deck, calculate the Range average of the sampled data after the segmentation.When the difference between the Range average of the sampled data after the segmentation of the relevant position of the Range of the sampled data after above-mentioned segmentation average and adjacent layer during, confirm that then between above-mentioned sampled data place layer and the adjacent layer be sparse zone greater than preset threshold.

Such as, for the image data of every layer of θ j, according to the transversal scanning angle [alpha], per 30 ° are divided into an independently data segment, calculate the average Range value of all data segments:

$\mathrm{AverRange}({\mathrm{\&alpha;}}_{i,i+29},\mathrm{\&theta;})=\underset{i=1}{\overset{30}{\mathrm{\&Sigma;}}}\mathrm{Range}({\mathrm{\&alpha;}}_i,\mathrm{\&theta;})/30$

With above-mentioned AverRange (α _{I, i+29}, θ) with adjacent layer (θ _J+1Layer or θ _J-1The average Range value of the sampled data after the segmentation of same lateral scanning angle α i layer) compares, when the error between the two-layer average Range value during greater than pre-set threshold T, promptly ought:

| AverRange (α _{I, i+29}, θ _j)-AverRange (α _{I, i+29}, θ _J-1)＞T| perhaps, | AverRange (α _{I, i+29}, θ _j)-AverRange (α _{I, i+29}, θ _J+1)＞T|

Confirm that then between above-mentioned sampled data place layer and the adjacent layer be sparse zone, need be based on the image data of adjacent layer relevant position between two-layer, employing weighted sum method is carried out the interlayer interpolation.

The several absolute errors according to adjacent layer Range value of interpolated layer confirm that the coordinate of each interpolation knot is calculated by the collection point of the same horizontal acquisition angles α of adjacent layer.

Embodiment two

This embodiment provides a kind of treating apparatus of sampled data of laser scanning, and its concrete structure is as shown in Figure 6, specifically can comprise:

Mean value calculation module 61 is used to obtain and the mean value of sampling node with the corresponding distance R ange value of the sampling node of the setting quantity of layer, and the sampling node with identical longitudinal scanning angle θ is the sampling node with layer;

Disappearance node judge module 62; Be used for when the difference between the mean value that the corresponding distance R ange value of said sampling node and said mean value calculation module are calculated during greater than preset threshold; Confirm that then said sampling node is the noise node, and mark disappearance node; Otherwise, confirm that said sampling node is a normal node.

Described treating apparatus specifically can also comprise:

First sampling node is augmented module 63; Be used to obtain the transversal scanning angle [alpha] of disappearance node; In the said α angular range in the adjacent layer of said disappearance node place layer, there are a plurality of disappearance nodes; Then write down all disappearance nodes, the normal node that will be positioned at disappearance node two ends is labeled as the summit;

The situation of the disappearance node of the said α angular range in the adjacent layer of place, the said summit of continuation inspection layer; If there is the sampling node of a plurality of disappearances; Then write down all disappearance nodes, the normal node that will be positioned at the sampling node two ends of a plurality of disappearances is labeled as the summit;

Repeat above-mentioned processing procedure, until the said α angular range in the adjacent layer of place, said summit layer do not have a disappearance node, said summit is coupled together with line segment successively, all summits constitute blind bore holes;

Obtain each internal angle beta of described hole, each internal angle beta is the angle between two line segments that connect 3 adjacent summits;

When said β≤90 °, do not augment the disappearance node between 3 corresponding summits of said β;

When 90 °＜said angle β≤135 °, be the angular bisector P of said angle β _iV _i, line segment P _iV _iLength be:

$P_i{V}_i=\frac{P_i{P}_{i+1}+P_i{P}_{i-1}}{2}$

Said P _i, P _I-1, P _I+1For corresponding 3 the adjacent summits of said β, at line segment P _iV _iEndpoint location augment sampling node V _i

When 135 °＜said β≤180 °, be the line segment P of said angle β trisection _iV ₁And P _iV ₂, line segment P _iV ₁And P _iV ₂Length be respectively:

$P_i{V}_i=\frac{P_i{P}_{i+1}+P_i{P}_{i-1}+P_{i+2}{P}_{i+1}}{3}$

$P_i{V}_2=\frac{P_i{P}_{i+1}+P_i{P}_{i-1}+P_{i-2}{P}_{i-1}}{3}$

Said P _i, P _I-1, P _I+1, P _I+2, P _I-2For corresponding 5 the adjacent summits of said β, at line segment P _iV ₁And P _iV ₂Endpoint location augment sampling node V ₁And V ₂

When said β＞200 °, be the angular bisector P of said angle β _iV _i, line segment P _I+1V ₁And P _I-1V ₂All be parallel to said angular bisector P _iV _i, V ₁Be P _I+1V ₁And P _I-1P _iExtending line intersection point, V ₂Be P _I-1V ₂And P _I+1P _iExtending line intersection point, said V ₁And V ₂Be the sampling node of augmenting.

Second sampling node is augmented module 64; Be used in the said α angular range in the adjacent layer of said disappearance node place layer, not having the disappearance node; Layer at disappearance node place obtains four adjacent α of the transversal scanning angle [alpha] of disappearance node; Carry out three-dimensional weighted sum according to the sampled data of four corresponding sampling node of said four adjacent α and calculate, obtain the three-dimensional coordinate of the sampling node of augmenting, the computing method that said three-dimensional weighted sum is calculated are following:

$x(\mathrm{\&alpha;},\mathrm{\&theta;})=\underset{i=-2,i\&NotEqual;0}{\overset{2}{\mathrm{\&Sigma;}}}{\mathrm{\&omega;}}_{i}x({\mathrm{\&alpha;}}_i,\mathrm{\&theta;}),$

$y(\mathrm{\&alpha;},\mathrm{\&theta;})=\underset{i=-2,i\&NotEqual;0}{\overset{2}{\mathrm{\&Sigma;}}}{\mathrm{\&omega;}}_{i}y({\mathrm{\&alpha;}}_i,\mathrm{\&theta;}),$

$z(\mathrm{\&alpha;},\mathrm{\&theta;})=\underset{i=-2,i\&NotEqual;0}{\overset{2}{\mathrm{\&Sigma;}}}{\mathrm{\&omega;}}_{i}z({\mathrm{\&alpha;}}_i,\mathrm{\&theta;})$

Said x (α _i, θ), y (α _i, θ) and z (α _i, θ) be the three-dimensional coordinate of the sampling node of augmenting that calculates, said x (α _i, θ), y (α _i, θ) and z (α _i, θ) be the three-dimensional coordinate of said adjacent four sampling node, said ω _iWeight for said adjacent four sampling node;

The 3rd sampling node is augmented module 65; Be used in the said α angular range in the adjacent layer of said disappearance node place layer, not having the disappearance node; Only in the layer of said disappearance node place, there are a plurality of disappearance nodes, then calculate the transversal scanning angle [alpha] of the intermediate supports position of said a plurality of disappearance nodes:

α＝α _min+(α _max-α _min)/2

Said α _MaxAnd α _MinThe transversal scanning angle of representing the two ends sampling node of said a plurality of disappearance nodes;

Carry out three-dimensional weighted sum according to the sampled data of four corresponding sampling node of four of the transversal scanning angle [alpha] of said intermediate supports position adjacent α and calculate, obtain the three-dimensional coordinate of the sampling node of augmenting.

Sparse data is augmented module 66, is used for the transversal scanning angle [alpha] according to the disappearance node, and the sampled data of said disappearance node place layer is carried out segmentation, the Range average of the sampled data after the calculating segmentation;

When the difference between the Range average of the sampled data after the segmentation of the relevant position of the Range of the sampled data after said segmentation average and adjacent layer during, confirm that then between said disappearance node place layer and the adjacent layer be sparse zone greater than preset threshold;

Between said disappearance node place layer and adjacent layer,, adopt the weighted sum method to carry out the interlayer interpolation based on the image data of adjacent layer relevant position.

One of ordinary skill in the art will appreciate that and realize all or part of flow process in the foregoing description method; Be meant and accomplish through the relevant hardware of computer program control; Described program can be stored in the computer read/write memory medium; This program can comprise the flow process like the embodiment of above-mentioned each side method when carrying out.Wherein, described storage medium can be magnetic disc, CD, read-only storage memory body (Read-Only Memory, ROM) or at random store memory body (Random AccessMemory, RAM) etc.

In sum; The embodiment of the invention provides running parameters such as a kind of transversal scanning angle [alpha], longitudinal scanning angle θ, distance R ange value of the sampled data based on laser scanning, and the sampled data of laser scanning is carried out the method that noise, hole repair and sparse data are augmented processing.This method can be confirmed disappearance node and sparse zone accurately and rapidly, and disappearance node and sparse zone are augmented effectively.

The method calculated amount that the sampled data to laser scanning that the embodiment of the invention provides is handled is little; Simple and easy to do; Realize easily; Can be adapted to exist block, the modeling and the visualization display of complicated irregular scene of cavity, reverberation, expanded the usable range of three-dimensional laser scanner, strengthened the function of scanner.

The above; Be merely the preferable embodiment of the present invention, but protection scope of the present invention is not limited thereto, any technician who is familiar with the present technique field is in the technical scope that the present invention discloses; The variation that can expect easily or replacement all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection domain of claim.

Claims (7)

1. the disposal route of the sampled data of a laser scanning is characterized in that, comprising:

Obtain and the mean value of sampling node with the corresponding distance value of the sampling node of the setting quantity of layer, the sampling node with identical longitudinal scanning angle θ is the sampling node with layer;

When the corresponding distance value of said sampling node and the difference between the said mean value during, confirm that then said sampling node is the noise node, and be labeled as the disappearance node greater than preset threshold; Otherwise, confirm that said sampling node is a normal node;

Obtain the transversal scanning angle [alpha] of disappearance node, in the said α angular range in the adjacent layer of said disappearance node place layer, have a plurality of disappearance nodes, then write down all disappearance nodes, the normal node that will be positioned at disappearance node two ends is labeled as the summit;

The situation of the disappearance node of the said α angular range in the adjacent layer of place, the said summit of continuation inspection layer; If there is the sampling node of a plurality of disappearances; Then write down all disappearance nodes, the normal node that will be positioned at the sampling node two ends of a plurality of disappearances is labeled as the summit;

Repeat above-mentioned processing procedure, until the said α angular range in the adjacent layer of place, said summit layer do not have a disappearance node, all said summits are coupled together with line segment successively, all summits constitute blind bore holes;

Obtain each angle β of described hole, each angle β is the angle between two line segments that connect 3 adjacent vertexs;

When said β≤90 °, do not augment the disappearance node between 3 corresponding summits of said β;

When 90 °＜said angle β≤135 °, be the angular bisector P of said angle β _iV _i, line segment P _iV _iLength be:

$P_i{V}_i=\frac{P_i{P}_{i+1}+P_i{P}_{i-1}}{2}$

Said P _i, P _I-1, P _I+1For corresponding 3 the adjacent summits of said β, at line segment P _iV _iEndpoint location augment sampling node V _i

When 135 °＜said β≤180 °, be the line segment P of said angle β trisection _iV ₁And P _iV ₂, line segment P _iV ₁And P _iV ₂Length be respectively:

$P_i{V}_1=\frac{P_i{P}_{i+1}+P_i{P}_{i-1}+P_{i+2}{P}_{i+1}}{3}$

$P_i{V}_2=\frac{P_i{P}_{i+1}+P_i{P}_{i-1}+P_{i-2}{P}_{i-1}}{3}$

Said P _i, P _I-1, P _I+1, P _I+2, P _I-2For corresponding 5 the adjacent summits of said β, at line segment P _iV ₁And P _iV ₂Endpoint location augment sampling node V ₁And V ₂

When said β＞200 °, be the angular bisector P of said angle β _iV _i, line segment P _I+1V ₁And P _I-1V ₂All be parallel to said angular bisector P _iV _i, V ₁Be P _I+1V ₁And P _I-1P _iExtending line intersection point, V ₂Be P _I-1V ₂And P _I+1P _iExtending line intersection point, said V ₁And V ₂Be the sampling node of augmenting.

2. the disposal route of the sampled data of laser scanning according to claim 1 is characterized in that, described method also comprises:

In the said α angular range in the adjacent layer of said disappearance node place layer, there is not the disappearance node; Layer at disappearance node place obtains four adjacent transversal scanning angles of the transversal scanning angle [alpha] of disappearance node; Three-dimensional coordinate according to four corresponding sampling node of said four adjacent transversal scanning angles carries out three-dimensional weighted sum calculating; Obtain the three-dimensional coordinate of the sampling node of augmenting, the computing method that said three-dimensional weighted sum is calculated are following:

$x(\mathrm{\&alpha;},\mathrm{\&theta;})=\underset{i=-2,i\&NotEqual;0}{\overset{2}{\mathrm{\&Sigma;}}}{\mathrm{\&omega;}}_{i}x({\mathrm{\&alpha;}}_i,\mathrm{\&theta;}),$

$y(\mathrm{\&alpha;},\mathrm{\&theta;})=\underset{i=-2,i\&NotEqual;0}{\overset{2}{\mathrm{\&Sigma;}}}{\mathrm{\&omega;}}_{i}y({\mathrm{\&alpha;}}_i,\mathrm{\&theta;}),$

$z(\mathrm{\&alpha;},\mathrm{\&theta;})=\underset{i=-2,i\&NotEqual;0}{\overset{2}{\mathrm{\&Sigma;}}}{\mathrm{\&omega;}}_{i}z({\mathrm{\&alpha;}}_i,\mathrm{\&theta;})$

Said x (α _i, θ), y (α _i, θ) and z (α _i, θ) be the three-dimensional coordinate of the sampling node of augmenting that calculates, said x (α _i, θ), y (α _i, θ) and z (α _i, θ) be the three-dimensional coordinate of said adjacent four sampling node, said ω _iWeight for said adjacent four sampling node.

3. the disposal route of the sampled data of laser scanning according to claim 1 is characterized in that, described method also comprises:

In the said α angular range in the adjacent layer of said disappearance node place layer, there is not the disappearance node, when in the layer of disappearance node place, having a plurality of disappearance node, then calculates the transversal scanning angle [alpha] of the intermediate supports position of said a plurality of disappearance nodes:

α＝α _min+(α _max-α _min)/2

Said α _MaxAnd α _MinThe transversal scanning angle of representing the two ends sampling node of said a plurality of disappearance nodes;

According to four adjacent transversal scanning angles of the transversal scanning angle [alpha] of said intermediate supports position respectively the three-dimensional coordinate of four corresponding sampling node carry out three-dimensional weighted sum and calculate, obtain the three-dimensional coordinate of the sampling node of augmenting.

4. according to the disposal route of the sampled data of claim 1 or 2 or 3 described laser scannings, it is characterized in that described method also comprises:

According to the transversal scanning angle [alpha] of disappearance node, the sampled data of said disappearance node place layer is carried out segmentation, the Range average of the sampled data after the calculating segmentation;

When the difference between the Range average of the sampled data after the segmentation of the relevant position of the Range of the sampled data after said segmentation average and adjacent layer during, confirm that then between said disappearance node place layer and the adjacent layer be sparse zone greater than preset threshold;

Between said disappearance node place layer and adjacent layer, the image data based on the relevant position of said adjacent layer adopts the weighted sum method to carry out the interlayer interpolation.

5. the treating apparatus of the sampled data of a laser scanning is characterized in that, comprising:

The mean value calculation module is used to obtain and the mean value of sampling node with the corresponding distance value of the sampling node of the setting quantity of layer, and the sampling node with identical longitudinal scanning angle θ is the sampling node with layer;

Disappearance node judge module is used for confirm that then said sampling node is the noise node, and mark lacking node when the difference between the mean value that the corresponding distance value of said sampling node and said mean value calculation module are calculated during greater than preset threshold; Otherwise, confirm that said sampling node is a normal node;

First sampling node is augmented module; Be used to obtain the transversal scanning angle [alpha] of disappearance node; In the said α angular range in the adjacent layer of said disappearance node place layer, there are a plurality of disappearance nodes; Then write down all disappearance nodes, the normal node that will be positioned at disappearance node two ends is labeled as the summit;

The situation of the disappearance node of the said α angular range in the adjacent layer of place, the said summit of continuation inspection layer; If there is the sampling node of a plurality of disappearances; Then write down all disappearance nodes, the normal node that will be positioned at the sampling node two ends of a plurality of disappearances is labeled as the summit;

Repeat above-mentioned processing procedure, until the said α angular range in the adjacent layer of place, said summit layer do not have a disappearance node, said summit is coupled together with line segment successively, all summits constitute blind bore holes;

Obtain each angle β of described hole, each angle β is the angle between two line segments that connect 3 adjacent summits;

When said β≤90 °, do not augment the disappearance node between 3 corresponding summits of said β;

When 90 °＜said angle β≤135 °, be the angular bisector P of said angle β _iV _i, line segment P _iV _iLength be:

$P_i{V}_i=\frac{P_i{P}_{i+1}+P_i{P}_{i-1}}{2}$

Said P _i, P _I-1, P _I+1For corresponding 3 the adjacent summits of said β, at line segment P _iV _iEndpoint location augment sampling node V _i

When 135 °＜said β≤180 °, be the line segment P of said angle β trisection _iV ₁And P _iV ₂, line segment P _iV ₁And P _iV ₂Length be respectively:

$P_i{V}_1=\frac{P_i{P}_{i+1}+P_i{P}_{i-1}+P_{i+2}{P}_{i+1}}{3}$

$P_i{V}_2=\frac{P_i{P}_{i+1}+P_i{P}_{i-1}+P_{i-2}{P}_{i-1}}{3}$

Said P _i, P _I-1, P _I+1, P _I+2, P _I-2For corresponding 5 the adjacent summits of said β, at line segment P _iV ₁And P _iV ₂Endpoint location augment sampling node V ₁And V ₂

When said β＞200 °, be the angular bisector P of said angle β _iV _i, line segment P _I+1V ₁And P _I-1V ₂All be parallel to said angular bisector P _iV _i, V ₁Be P _I+1V ₁And P _I-1P _iExtending line intersection point, V ₂Be P _I-1V ₂And P _I+1P _iExtending line intersection point, said V ₁And V ₂Be the sampling node of augmenting.

6. the treating apparatus of the sampled data of laser scanning according to claim 5 is characterized in that, described treating apparatus also comprises:

Second sampling node is augmented module; Be used in the said α angular range in the adjacent layer of said disappearance node place layer, not having the disappearance node; Layer at disappearance node place obtains four adjacent transversal scanning angles of the transversal scanning angle [alpha] of said disappearance node; Three-dimensional coordinate according to four corresponding sampling node of said four adjacent transversal scanning angles carries out three-dimensional weighted sum calculating; Obtain the three-dimensional coordinate of the sampling node of augmenting, the computing method that said three-dimensional weighted sum is calculated are following:

$x(\mathrm{\&alpha;},\mathrm{\&theta;})=\underset{i=-2,i\&NotEqual;0}{\overset{2}{\mathrm{\&Sigma;}}}{\mathrm{\&omega;}}_{i}x({\mathrm{\&alpha;}}_i,\mathrm{\&theta;}),$

$y(\mathrm{\&alpha;},\mathrm{\&theta;})=\underset{i=-2,i\&NotEqual;0}{\overset{2}{\mathrm{\&Sigma;}}}{\mathrm{\&omega;}}_{i}y({\mathrm{\&alpha;}}_i,\mathrm{\&theta;}),$

$z(\mathrm{\&alpha;},\mathrm{\&theta;})=\underset{i=-2,i\&NotEqual;0}{\overset{2}{\mathrm{\&Sigma;}}}{\mathrm{\&omega;}}_{i}z({\mathrm{\&alpha;}}_i,\mathrm{\&theta;})$

Said x (α _i, θ), y (α _i, θ) and z (α _i, θ) be the three-dimensional coordinate of the sampling node of augmenting that calculates, said x (α _i, θ), y (α _i, θ) and z (α _i, θ) be the three-dimensional coordinate of said adjacent four sampling node, said ω _iWeight for said adjacent four sampling node;

The 3rd sampling node is augmented module; Be used in the said α angular range in the adjacent layer of said disappearance node place layer, not having the disappearance node; When in disappearance node place layer, having a plurality of disappearance node, then calculate the transversal scanning angle [alpha] of the intermediate supports position of said a plurality of disappearance nodes:

α＝α _min+(α _max-α _min)/2

Said α _MaxAnd α _MinThe transversal scanning angle of representing the two ends sampling node of said a plurality of disappearance nodes;

According to four adjacent transversal scanning angles of the transversal scanning angle [alpha] of said intermediate supports position respectively the three-dimensional coordinate of four corresponding sampling node carry out three-dimensional weighted sum and calculate, obtain the three-dimensional coordinate of the sampling node of augmenting.

7. according to the treating apparatus of the sampled data of claim 5 or 6 described laser scannings, it is characterized in that described treating apparatus also comprises:

Sparse data is augmented module, is used for the transversal scanning angle [alpha] according to the disappearance node, and the sampled data of said disappearance node place layer is carried out segmentation, the Range average of the sampled data after the calculating segmentation;

When the difference between the Range average of the sampled data after the segmentation of the relevant position of the Range of the sampled data after said segmentation average and adjacent layer during, confirm that then between said disappearance node place layer and the adjacent layer be sparse zone greater than preset threshold;

Between said disappearance node place layer and adjacent layer, the image data based on the relevant position of said adjacent layer adopts the weighted sum method to carry out the interlayer interpolation.

Images