CN103279989B - A kind of three-dimensional laser imaging system plane cloud data trigonometric ratio processing method - Google Patents
A kind of three-dimensional laser imaging system plane cloud data trigonometric ratio processing method Download PDFInfo
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Abstract
The invention discloses a kind of three-dimensional laser imaging system plane cloud data trigonometric ratio processing method. the present invention obtains and belongs to conplane three-dimensional cloud data from 3 D stereo cloud data, conplane three-dimensional cloud data is projected to and on two dimensional surface, forms planar cloud data, the virtual center point of Calculation Plane two dimension cloud data, using the real center point as scattered data being apart from the nearest point of virtual center point, again by the distance of more each discrete point and real center point, two-dimentional cloud data presort is found to initial delta and initial boundary summit, sorted by counterclockwise in initial boundary summit again, insert successively each two dimensional surface cloud data according to the order having sequenced, go forward side by side row bound vertex update and triangle upgrades, the planar point cloud data-mapping of plane trigonometry net is returned to three-dimensional coordinate and generate scanned THREE DIMENSIONAL TRIANGULATION NET lattice model. thinking of the present invention is simple and clear, and programming easily realizes, and can process the planes such as hole or concave surface.
Description
Technical field
The present invention relates to a kind of three-dimensional laser imaging system plane cloud data trigonometric ratio processing method, especially relate toAnd a kind of method that adopts Incremental insertion and triangulation network growth plane cloud data trigonometric ratio, belong to free form surfaceConstructing technology field.
Background technology
Three-dimensional laser imaging system refers to collection such as laser scanner, global positioning system, inertial measurement systemsBecome a set of equipment, be contained on carrier and scan on a surface target, obtain the three-dimensional information of ground target,Obtain the three-dimension space image needing by processing. Because the laser spots data that reflect of obtaining are nebulaShape dense distribution, so be called visually laser point cloud (PointCloud), looks like for countless points is to surveyThe rule of amount presents the result of object in computer. Three-dimensional laser imaging system is by joining to digital spot cloud figureRGB, thus the true threedimensional model of colour of scanned object obtained. Obtain by three-dimensional laser imaging systemLaser spots cloud atlas can not present scanned three-dimensional shape features, and three-dimensional laser imaging system workWhile work, repeatedly scan scanned, the data point in the laser spots cloud atlas therefore forming is much for repeatingPoint, first needs to delete the number repeating in laser spots cloud atlas in order to construct scanned threedimensional modelStrong point, then carries out laser point cloud according to scanned shape facility (length, highly, width etc.)Segmentation, finally connects the cloud data point after segmentation for plane by certain rule, so just can be completeScanned three-dimensional imaging in pairs.
The laser point cloud that three-dimensional laser imaging system forms is three-dimensional laser point cloud, carries out for three-dimensional some cloudSurface modeling and very this technology of the Delaunay triangulation network of three-dimensional that builds there also are not maturation. Current unificationAlgorithm can solve this problem completely, and the model of structure in detail can't be satisfactory. Because three-dimensional is looseThe complexity of topological relation between random number strong point, theory and algorithm to its direct subdivision are not perfect. ThisThe bright a kind of method that discloses Incremental insertion and triangulation network growth plane cloud data trigonometric ratio, in this, method is notOnly can be used in the triangulation of plane scattered data points, also can be used in three-dimensional laser imaging system laserIn the triangulation of some cloud. It is simple that the present invention has thinking, and programming easily realizes and can process concave surface or holeDeng the advantage of the plane of complex surface situation.
Summary of the invention
The technical problem that the present invention solves is: overcome the deficiencies in the prior art, provide a kind of three-dimensional laser imaging to beSystem plane cloud data trigonometric ratio processing method, the method is tied three-dimensional laser point cloud data point, fromAnd generating scanned threedimensional model, the inventive method is simple, is easy to programming realize triangulation curved surfaceThe advantage smooth meticulous, generating three-dimensional models resolution ratio is high, can process the complexity table that has hole or concave surfaceThe curved surface of planar condition.
The technical scheme that the present invention solves is: a kind of three-dimensional laser imaging system plane cloud data trigonometric ratio placeReason method, step is as follows:
(1) scan the 3 D stereo cloud data obtaining and obtain and belong to same flat from three-dimensional laser imaging systemThe 3 D stereo cloud data of face, projects to shape on two dimensional surface by conplane 3 D stereo cloud dataBecome planar cloud data;
(2) virtual center point of calculation procedure (1) planar cloud data;
(3) ask for the distance between all planar cloud datas and its virtual center point, find out all flatIn face two dimension cloud data, distance virtual center point, apart from minimum planar cloud data, sets it as trueReal central point, and be designated as a little 1;
(4) ask between the real center point finding in all planar cloud datas and step (3)Distance, according to real center point distance order from small to large, planar cloud data being sorted,The result of sequence is designated as a little 1 successively, point 2, point 3, put 4 ... point N;
(5) utilize through sequence first three planar cloud data after treatment and surround at the beginning of one as summitBeginning triangle, three summits of initial delta are as initial boundary summit, and definite initial boundary summit sideTo for taking put 1 for border vertices rise press counter clockwise direction sort;
(6) insertion point 4 on the basis of step (5), calculation level 4, to the vector on initial boundary summit, is looked forTo the visible starting point on initial boundary summit and visible destination node, form new border vertices, then to initiallyTriangle upgrades;
(7) according to the method for step (6) successively insertion point 5, point 6 ... point N, calculates respectively insertion point and arrivesBefore form border vertices between vector, find before form border vertices visible starting point and canSee destination node, finally form a plane trigonometry net;
(8) plane trigonometry net is optimized to processing;
(9) will return three-dimensional from two-dimensional map through step (8) plane trigonometry net after treatment, finally obtainThe 3 D stereo triangulation network trrellis diagram of 3 D stereo cloud data, realizes three-dimensional laser imaging system planar point cloudThe trigonometric ratio processing of data.
The implementation method of described step (1) is:
(1) select and belong to conplane 3 D stereo point cloud according to the three-dimensional coordinate of 3 D stereo cloud dataData are also preserved;
(2) by the 3 D stereo cloud data preserving or be rotated remove or directly remove the 3rdDimension cloud data obtains planar cloud data, and the third dimension cloud data after removing is preserved.
The implementation method of described step (2) is:
(1) find the minimum abscissa x of all planar cloud data point cloud datasmin, maximum abscissaxmax, minimum ordinate ymin, maximum ordinate ymax, according to minimum abscissa xmin, maximum abscissa xmax、Minimum ordinate ymin, maximum ordinate ymaxObtain the minimum rectangle that comprises all planar cloud datas,Four summits of rectangle are denoted as respectively: A(xmin，ymin）、B（xmax，ymin）、C（xmax，ymax）、D（xmin，ymax）；
(2) ask for the central point E of rectangle, the coordinate of some E isPoint E isThe virtual center point of planar cloud data.
In described step (5), initial boundary zenith directions is for pressing counterclockwise as border vertices rises to put 1The method sorting is:
(1) planar cloud data is increased to three-dimensional data, wherein the value of third dimension data is 0;
(2) try to achieve a little and 1 arrive the vector of putting 2With the vector of point 1 to point 3
(3) to vectorWithCarry out multiplication cross computing, judge that the third dimension value of the vector that multiplication cross computing obtains isNoly be greater than zero, if be greater than 0, initial boundary summit is point 1, point 2, point 3 by sequence counterclockwise, otherwise,Initial boundary summit is by sorting counterclockwise as point 1, point 3, point 2.
In described step (6), find the method for the visible starting point on initial boundary summit to be:
(1) planar cloud data is increased to three-dimensional data, wherein the value of third dimension data is 0, calculatesThe vector on 4 to three initial boundary summits of point, is designated as
(2) by vectorWithCarry out multiplication cross computing, judge that the third dimension value of the vector that multiplication cross computing obtains isNoly be more than or equal to zero, if be more than or equal to 0, by vectorWithCarry out multiplication cross computing, judge vectorWithWhether the third dimension value that multiplication cross computing obtains vector is more than or equal to zero, if be more than or equal to 0, by vectorWithCarry out multiplication cross computing, judge vectorWithWhether the third dimension value of the vector that multiplication cross computing obtains is more than or equal toZero, work as vectorWithThe third dimension value of the vector that multiplication cross computing obtains is less than zero, the 3rd initial boundarySummit is the visible starting point on initial boundary summit, works as vectorWithMultiplication cross computing obtains the third dimension of vectorValue is less than zero, second visible starting point that initial boundary summit is initial boundary summit; IfWithEnterThe vector obtaining after the computing of row multiplication cross is less than 0, by vectorWithCarry out multiplication cross computing, judge vectorWithWhether the third dimension value that multiplication cross computing obtains vector is more than or equal to zero, if be more than or equal to 0, by vectorWithCarry out multiplication cross computing, judge vectorWithWhether the third dimension value of the vector that multiplication cross computing obtains is greater than etc.In zero, work as vectorWithThe third dimension value of the vector that multiplication cross computing obtains is less than zero, initial line at the beginning of the 3rdSummit, boundary is the visible starting point on initial boundary summit, works as vectorWithOf the vector that multiplication cross computing obtainsThree-dimensional value is less than zero, and first initial boundary summit is the visible starting point on initial boundary summit.
In described step (6), find the method for the visible destination node on initial boundary summit to be:
(1) planar cloud data is increased to three-dimensional data, wherein the value of third dimension data is 0, calculatesThe vector on 4 to three initial boundary summits of point, is designated as
(2) by vectorWithCarry out multiplication cross computing, judge vectorWithThe vector that multiplication cross computing obtainsWhether third dimension value is less than or equal to zero, if be less than or equal to 0, by vectorWithCarry out multiplication cross computing, judgementVectorWithWhether the third dimension value that multiplication cross computing obtains vector is less than or equal to zero, if be less than or equal to 0, willVectorWithCarry out multiplication cross computing, judge vectorWithThe third dimension value of the vector that multiplication cross computing obtains isNoly be less than or equal to zero, if vectorWithThe third dimension value of the vector that multiplication cross computing obtains is greater than zero, and firstIndividual initial boundary summit is the visible destination node on initial boundary summit, if vectorWithMultiplication cross computing is vowedThe third dimension value of amount is greater than zero, second visible destination node that initial boundary summit is initial boundary summit;IfWithThe vector that carries out obtaining after multiplication cross computing is greater than 0, by vectorWithCarry out multiplication cross computing,Judge vectorWithWhether the third dimension value of the vector that multiplication cross computing obtains is less than or equal to zero, if be less than or equal to0, by vectorWithCarry out multiplication cross computing, if vectorWithMultiplication cross computing obtains the 3rd of vectorDimension value is greater than zero, and first initial boundary summit is the visible destination node on initial boundary summit, if vectorWithThe third dimension value of the vector that multiplication cross computing obtains is greater than zero, and the 3rd initial boundary summit is first initial lineThe visible destination node on summit, boundary.
The method that forms new border vertices in described step (6) is:
(1) the visible starting point obtaining according to step (6) and visible destination node, connect insertion point with visibleStarting point is to each border vertices between visible destination node;
(2) if the sequence sequence number of visible starting point is greater than the sequence sequence number of visible destination node, by new limitSummit, boundary comprises from visible destination node to all border vertices visible starting point and new insertion point, borderThe order on summit is counterclockwise; If the sequence sequence number of visible starting point is less than the sequence sequence number of visible destination node,New border vertices comprises from visible destination node to the top, all borders former border vertices last pointPoint, first of former border vertices arrive all border vertices and the new insertion point between visible starting point, top, borderThe order of point is counterclockwise.
The method of in described step (6), initial delta being upgraded is: if the sequence of visible starting pointSequence number is greater than the sequence sequence number of visible destination node, newly-increased triangle be insertion point with from visible starting point toAll limits that former border vertices last point forms, from former border vertices last point to former border vertices firstThe triangle of the limit of point, all limits composition from first of former border vertices to visible destination node; If visibleThe sequence sequence number of starting point is less than the sequence sequence number of visible destination node, newly-increased triangle be insertion point with fromThe triangle of all limits composition that visible starting point forms to visible destination node.
The method that in described step (8), plane trigonometry net is optimized to processing is:
(1) all triangles in traversal plane trigonometry net, calculate leg-of-mutton three angle sizes, if itsIn the angular dimension at an angle be greater than 90 °, the opposite side of just finding out this angle from plane trigonometry net is as wherein oneThe triangle on limit, the angular dimension at leg-of-mutton this diagonal angle, limit that calculating is found out, is added upper two angle values,If be greater than 180 °, be optimized, the quadrangle of two original triangle compositions is cut from another diagonal angle,Become two new triangles, originally two triangles are replaced.
(2) all triangles in traversal plane trigonometry net, delete the length of side in plane trigonometry net and are greater than setting thresholdAll triangles of value are realized the optimization to plane trigonometry net.
In described step (8), plane trigonometry net being returned to three-dimensional method from two-dimensional map is: by step (1)The third dimension cloud data removed adds to and in the plane trigonometry net after optimization, obtains 3 D stereo cloud data3 D stereo triangulation network trrellis diagram.
The present invention's advantage is compared with prior art as follows: first the present invention scans from three-dimensional laser imaging systemIn the 3 D stereo cloud data obtaining, obtain and belong to conplane 3 D stereo cloud data, by same flatThe 3 D stereo cloud data of face projects to and on two dimensional surface, forms planar cloud data, Calculation Plane twoThe virtual center point of dimension cloud data, then by the distance of more each data point and virtual center point, by distanceReal center point from the nearest point of virtual center point as scattered data being, then by more each discrete point with trueThe distance of real central point, by two-dimentional cloud data presort, finds initial according to distance rule from small to largeTriangle and initial boundary summit, then sorted by counterclockwise in initial boundary summit, suitable according to what sequencedOrder is inserted each two dimensional surface cloud data successively, and go forward side by side row bound vertex update and triangle upgrade. To flatThe face triangulation network is optimized planar point cloud data-mapping after treatment and returns three-dimensional coordinate, so just can realize threeThe processing of dimension laser imaging system plane cloud data trigonometric ratio, thus scanned THREE DIMENSIONAL TRIANGULATION NET lattice generatedModel. The three-dimensional laser point cloud data point that the present invention can generate three-dimensional laser imaging system is by certainRule is tied, and the method is compared existing method, and to have thinking simple and clear, the advantage that programming easily realizes,Can process the plane that has the complex surface such as hole or concave surface situation.
Brief description of the drawings
Fig. 1 is realization flow figure of the present invention;
Fig. 2 is the schematic diagram that the present invention finds virtual center point;
Fig. 3 is the schematic diagram of determining initial delta and initial boundary summit;
Fig. 4 looks for visible starting point and visible destination node schematic diagram for inserting at the 4th;
Fig. 5 looks for visible starting point and visible destination node schematic diagram for inserting at the 5th;
Fig. 6 is the treatment effect figure after plane cloud data trigonometric ratio;
Fig. 7 is the treatment effect figure after plane trigonometry network optimization;
Fig. 8 is the final 3 D stereo triangulation network trrellis diagram obtaining.
Detailed description of the invention
The principle that realizes of the present invention is: first scan from three-dimensional laser imaging system the 3 D stereo point cloud obtainingIn data, obtain and belong to conplane 3 D stereo cloud data, by conplane 3 D stereo point cloud numberOn two dimensional surface, form planar cloud data according to projecting to, in Calculation Plane two dimension cloud data virtualHeart point, then by the distance of more each data point and virtual center point, by nearest apart from virtual center pointPut the real center point as scattered data being, then by the distance of more each discrete point and real center point, rootBy two-dimentional cloud data presort, find initial delta and initial boundary top according to distance rule from small to largePoint, then sorted by counterclockwise in initial boundary summit. Insert successively each two dimension according to the order having sequencedPlane cloud data, go forward side by side row bound vertex update and triangle upgrade. Plane trigonometry net is optimized to placePlanar point cloud data-mapping after reason returns three-dimensional coordinate, so just can realize three-dimensional laser imaging system planeThe processing of cloud data trigonometric ratio, thus scanned THREE DIMENSIONAL TRIANGULATION NET lattice model generated.
Introduce this three-dimensional laser imaging system plane cloud data trigonometric ratio processing method below in conjunction with Fig. 1, stepRapid as follows:
A kind of three-dimensional laser imaging system plane cloud data trigonometric ratio processing method, step is as follows:
(1) scan the 3 D stereo cloud data obtaining and obtain and belong to same flat from three-dimensional laser imaging systemThe 3 D stereo cloud data of face, projects to shape on two dimensional surface by conplane 3 D stereo cloud dataBecome planar cloud data;
(2) virtual center point of calculation procedure (1) planar cloud data;
(3) ask for the distance between all planar cloud datas and its virtual center point, find out all flatIn face two dimension cloud data, distance virtual center point, apart from minimum planar cloud data, sets it as trueReal central point, and be designated as a little 1;
(4) ask between the real center point finding in all planar cloud datas and step (3)Distance, according to real center point distance order from small to large, planar cloud data being sorted,The result of sequence is designated as a little 1 successively, point 2, point 3, put 4 ... point N;
(5) utilize through sequence first three planar cloud data after treatment and surround at the beginning of one as summitBeginning triangle, three summits of initial delta are as initial boundary summit, and definite initial boundary summit sideTo for taking put 1 for border vertices rise press counter clockwise direction sort;
(6) insertion point 4 on the basis of step (5), calculation level 4, to the vector on initial boundary summit, is looked forTo the visible starting point on initial boundary summit and visible destination node, form new border vertices, then to initiallyTriangle upgrades;
(7) according to the method for step (6) successively insertion point 5, point 6 ... point N, calculates respectively insertion point and arrivesBefore form border vertices between vector, find before form border vertices visible starting point and canSee destination node, finally form a plane trigonometry net;
(8) plane trigonometry net is optimized to processing;
(9) will return three-dimensional from two-dimensional map through step (8) plane trigonometry net after treatment, finally obtainThe 3 D stereo triangulation network trrellis diagram of 3 D stereo cloud data, realizes three-dimensional laser imaging system planar point cloudThe trigonometric ratio processing of data.
The implementation method of step (1) is:
(1) select and belong to conplane 3 D stereo point cloud according to the three-dimensional coordinate of 3 D stereo cloud dataData are also preserved;
(2) by the 3 D stereo cloud data preserving or be rotated remove or directly remove the 3rdDimension cloud data obtains planar cloud data, and the third dimension cloud data after removing is preserved.
The implementation method of step (2) is:
(1) find the minimum abscissa x of all planar cloud data point cloud datasmin, maximum abscissaxmax, minimum ordinate ymin, maximum ordinate ymax, according to minimum abscissa xmin, maximum abscissa xmax、Minimum ordinate ymin, maximum ordinate ymaxObtain the minimum rectangle that comprises all planar cloud datas,Four summits of rectangle are denoted as respectively: A(xmin，ymin）、B（xmax，ymin）、C（xmax，ymax）、D（xmin，ymax）；
(2) ask for the central point E of rectangle, the coordinate of some E isPoint E isThe virtual center point of planar cloud data.
As shown in Figure 2, the stain in figure represents all planar cloud datas, and black quadrangle represents to compriseThe minimum rectangle of all planar cloud datas, E represents virtual center point. The order of planar cloud dataNumber point 1, point 2, point 3, point 4 ... it is the planar cloud data sequence order after sequence.
In step (5), initial boundary zenith directions is for counterclockwise carrying out as border vertices rises to press to put 1The method of sequence is:
(1) planar cloud data is increased to three-dimensional data, wherein the value of third dimension data is 0;
(2) try to achieve a little and 1 arrive the vector of putting 2With the vector of point 1 to point 3
(3) to vectorWithCarry out multiplication cross computing, judge that the third dimension value of the vector that multiplication cross computing obtains isNoly be greater than zero, if be greater than 0, initial boundary summit is point 1, point 2, point 3 by sequence counterclockwise, otherwise,Initial boundary summit is by sorting counterclockwise as point 1, point 3, point 2.
As shown in Figure 3, try to achieve a little and 1 arrive the vector of putting 2With the vector of point 1 to point 3To vectorWithEnterThe computing of row multiplication cross, the third dimension value of the vector that multiplication cross computing obtains is greater than zero, so initial boundary summit is by the inverse timeNeedle sort is point 1, point 2, point 3.
In described step (6), find the method for the visible starting point on initial boundary summit to be:
(1) planar cloud data is increased to three-dimensional data, wherein the value of third dimension data is 0, calculatesThe vector on 4 to three initial boundary summits of point, is designated as
(2) by vectorWithCarry out multiplication cross computing, judge that the third dimension value of the vector that multiplication cross computing obtains isNoly be more than or equal to zero, if be more than or equal to 0, by vectorWithCarry out multiplication cross computing, judge vectorWithWhether the third dimension value that multiplication cross computing obtains vector is more than or equal to zero, if be more than or equal to 0, by vectorWithCarry out multiplication cross computing, judge vectorWithWhether the third dimension value of the vector that multiplication cross computing obtains is more than or equal toZero, work as vectorWithThe third dimension value of the vector that multiplication cross computing obtains is less than zero, the 3rd initial boundarySummit is the visible starting point on initial boundary summit, works as vectorWithMultiplication cross computing obtains the third dimension of vectorValue is less than zero, second visible starting point that initial boundary summit is initial boundary summit; IfWithEnterThe vector obtaining after the computing of row multiplication cross is less than 0, by vectorWithCarry out multiplication cross computing, judge vectorWithWhether the third dimension value that multiplication cross computing obtains vector is more than or equal to zero, if be more than or equal to 0, by vectorWithCarry out multiplication cross computing, judge vectorWithWhether the third dimension value of the vector that multiplication cross computing obtains is greater than etc.In zero, work as vectorWithThe third dimension value of the vector that multiplication cross computing obtains is less than zero, initial line at the beginning of the 3rdSummit, boundary is the visible starting point on initial boundary summit, works as vectorWithOf the vector that multiplication cross computing obtainsThree-dimensional value is less than zero, and first initial boundary summit is the visible starting point on initial boundary summit.
As shown in Figure 4,5, in Fig. 4, initial boundary summit is point 1, point 2, point 3, and new insertion point 4, by planeTwo dimension cloud data increases three-dimensional data, and wherein the value of third dimension data is 0, initial line at the beginning of 4 to three of calculation levelsThe vector on summit, boundary, is designated asBy vectorWithCarry out multiplication cross computing, multiplication cross computing obtainsThe third dimension value of vector be greater than zero, by vectorWithCarry out multiplication cross computing, the vector that multiplication cross computing obtainsThird dimension value be greater than zero, by vectorWithCarry out multiplication cross computing, the 3rd of the vector that multiplication cross computing obtainsDimension value is less than the visible starting point that zero, the three initial boundary summit is initial boundary summit; Top, border in Fig. 5Point is point 1, point 2, point 3, point 4, and new insertion point 5, increases three-dimensional data by planar cloud data, itsThe value of middle third dimension data is 0, and the vector on 5 to three initial boundary summits of calculation level, is designated as By vectorWithCarry out multiplication cross computing, the third dimension value of the vector that multiplication cross computing obtains is less than zero, willVectorWithCarry out multiplication cross computing, the third dimension value of the vector that multiplication cross computing obtains is more than or equal to zero, will vowAmountWithCarry out multiplication cross computing, the third dimension value of the vector that multiplication cross computing obtains is less than zero, at the beginning of the 4thBeginning border vertices is the visible starting point on initial boundary summit.
In described step (6), find the method for the visible destination node on initial boundary summit to be:
(1) planar cloud data is increased to three-dimensional data, wherein the value of third dimension data is 0, calculatesThe vector on 4 to three initial boundary summits of point, is designated as
(2) by vectorWithCarry out multiplication cross computing, judge vectorWithThe vector that multiplication cross computing obtainsWhether third dimension value is less than or equal to zero, if be less than or equal to 0, by vectorWithCarry out multiplication cross computing, judgementVectorWithWhether the third dimension value that multiplication cross computing obtains vector is less than or equal to zero, if be less than or equal to 0, willVectorWithCarry out multiplication cross computing, judge vectorWithThe third dimension value of the vector that multiplication cross computing obtains isNoly be less than or equal to zero, if vectorWithThe third dimension value of the vector that multiplication cross computing obtains is greater than zero, and firstIndividual initial boundary summit is the visible destination node on initial boundary summit, if vectorWithMultiplication cross computing is vowedThe third dimension value of amount is greater than zero, second visible destination node that initial boundary summit is initial boundary summit;IfWithThe vector that carries out obtaining after multiplication cross computing is greater than 0, by vectorWithCarry out multiplication cross computing,Judge vectorWithWhether the third dimension value of the vector that multiplication cross computing obtains is less than or equal to zero, if be less than or equal to0, by vectorWithCarry out multiplication cross computing, if vectorWithMultiplication cross computing obtains the 3rd of vectorDimension value is greater than zero, and first initial boundary summit is the visible destination node on initial boundary summit, if vectorWithThe third dimension value of the vector that multiplication cross computing obtains is greater than zero, and the 3rd initial boundary summit is first initial lineThe visible destination node on summit, boundary.
As shown in Figure 4,5, in Fig. 4, planar cloud data is increased to three-dimensional data, wherein third dimension dataValue be 0, the vector on 4 to three initial boundary summits of calculation level, is designated asVectorWithCarry out multiplication cross computing, the third dimension value of the vector that multiplication cross computing obtains is less than zero, by vectorWithPitchMultiplication, the third dimension value of the vector that multiplication cross computing obtains is less than zero, by vectorWithCarry out multiplication cross computing,The third dimension value of the vector that multiplication cross computing obtains is greater than zero, and first initial boundary summit is initial boundary topThe visible destination node of point. Fig. 5 midplane two dimension cloud data increases three-dimensional data, the wherein value of third dimension dataBe 0, the vector on 5 to three initial boundary summits of calculation level, is designated asVectorWithCarry out multiplication cross computing, the third dimension value of the vector that multiplication cross computing obtains is less than zero, by vectorWithPitchMultiplication, the third dimension value of the vector that multiplication cross computing obtains is less than zero, by vectorWithCarry out multiplication cross computing,The third dimension value of the vector that multiplication cross computing obtains is greater than zero, and second initial boundary summit is initial boundary topThe visible destination node of point.
The method that forms new border vertices in described step (6) is:
(1) the visible starting point obtaining according to step (6) and visible destination node, connect insertion point with visibleStarting point is to each border vertices between visible destination node;
(2) if the sequence sequence number of visible starting point is greater than the sequence sequence number of visible destination node, by new limitSummit, boundary comprises from visible destination node to all former border vertices visible starting point and new insertion point, limitThe order on summit, boundary is counterclockwise; If the sequence sequence number of visible starting point is less than the sequence order of visible destination nodeNumber, new border vertices comprises from visible destination node to all borders former border vertices last pointSummit, first of former border vertices arrive all border vertices and the new insertion point between visible starting point, borderThe order on summit is counterclockwise.
As shown in Figure 4,5, Fig. 4 Central Plains border vertices is point 1, point 2, point 3, the sequence order of visible starting pointNumber be three, the sequence sequence number of visible destination node is one, so the sequence sequence number of visible starting point is greater than visibleThe sequence sequence number of destination node, new border vertices is point 1, point 2, point 3, new insertion point 4. Limit, Fig. 5 Central PlainsSummit, boundary is the border vertices behind insertion point 4, and the sequence sequence number of visible starting point is four, visible destination nodeSequence sequence number is two, so the sequence sequence number of visible starting point is greater than the sequence sequence number of visible destination node,New border vertices is point 2, point 3, point 4, new insertion point 5.
The method of in step (6), initial delta being upgraded is: if the sequence sequence number of visible starting pointBe greater than the sequence sequence number of visible destination node, newly-increased triangle be insertion point with from visible starting point to former limitAll limits that summit, boundary last point forms, from former border vertices last point to first of former border verticesThe triangle of limit, all limits composition from first of former border vertices to visible destination node; If initial as seenThe sequence sequence number of point is less than the sequence sequence number of visible destination node, newly-increased triangle be insertion point with fromThe triangle of all limits composition that starting point forms to visible destination node.
Describe in conjunction with Fig. 4, Fig. 5, because the sequence sequence number of visible starting point is greater than visible destination node in Fig. 4Sequence sequence number, newly-increased vertex of a triangle be (point 3, point 1, point 4); Because rise as seen in Fig. 5The sequence sequence number of initial point is greater than the sequence sequence number of visible destination node, newly-increased vertex of a triangle be (point 4,Point 1, point 5), (point 1, point 2, point 5).
As shown in Figure 6,7, the method that in step (8), plane trigonometry net is optimized to processing is:
(1) all triangles in traversal plane trigonometry net, calculate leg-of-mutton three angle sizes, if itsIn the angular dimension at an angle be greater than 90 °, the opposite side of just finding out this angle from plane trigonometry net is as wherein oneThe triangle on limit, the angular dimension at leg-of-mutton this diagonal angle, limit that calculating is found out, is added upper two angle values,If be greater than 180 °, be optimized, the quadrangle of two original triangle compositions is cut from another diagonal angle,Become two new triangles, originally two triangles are replaced.
(2) all triangles in traversal plane trigonometry net, delete the length of side in plane trigonometry net and are greater than setting thresholdAll triangles of value are realized the optimization to plane trigonometry net.
In conjunction with Fig. 6,7 known, the threshold values size of setting can be spacing distance between planar cloud dataThe three-to-four-fold of size, is optimized plane triangle, removes triangle in concave surface. Fig. 6 does not also haveDesign sketch before optimization process, Fig. 7 is the design sketch after optimization process.
In step (8), plane trigonometry net being returned to three-dimensional method from two-dimensional map is: step (1) is removedThird dimension cloud data add the three-dimensional that obtains 3 D stereo cloud data in the plane trigonometry net after optimization toThree-dimensional triangle grid chart, as shown in Figure 8.
The unspecified content of the present invention is known to the skilled person technology.
Claims (9)
1. a three-dimensional laser imaging system plane cloud data trigonometric ratio processing method, is characterized in that stepRapid as follows:
(1) scan the 3 D stereo cloud data obtaining and obtain and belong to same from three-dimensional laser imaging systemThe 3 D stereo cloud data of plane, projects to conplane 3 D stereo cloud data on two dimensional surfaceForm planar cloud data;
(2) virtual center point of calculation procedure (1) planar cloud data;
(3) ask for the distance between all planar cloud datas and its virtual center point, find out allIn planar cloud data, distance virtual center point, apart from minimum planar cloud data, sets it asReal center point, and be designated as a little 1;
(4) ask between the real center point finding in all planar cloud datas and step (3)Distance, according to real center point distance order from small to large, planar cloud data being sorted,The result of sequence is designated as a little 1 successively, point 2, point 3, put 4 ... point N;
(5) utilize through sequence first three planar cloud data after treatment and surround one as summitInitial delta, three summits of initial delta are as initial boundary summit, and definite initial boundary topPoint direction is for counterclockwise sorting as border vertices rises to press to put 1;
(6) insertion point 4 on the basis of step (5), calculation level 4 arrives the vector on initial boundary summit,The visible starting point and the visible destination node that find initial boundary summit, form new border vertices, then rightInitial delta upgrades;
(7) according to the method for step (6) successively insertion point 5, point 6 ... point N, calculates respectively insertion pointTo the vector between the border vertices forming before, the visible starting point of the border vertices forming before findingWith visible destination node, finally form a plane trigonometry net;
(8) plane trigonometry net is optimized to processing;
(9) will return three-dimensional from two-dimensional map through step (8) plane trigonometry net after treatment, finally obtainObtain the 3 D stereo triangulation network trrellis diagram of 3 D stereo cloud data, realize three-dimensional laser imaging system planeThe trigonometric ratio processing of cloud data;
The implementation method of described step (2) is:
(1) find the minimum abscissa x of all planar cloud data point cloud datasmin, maximum horizontal seatMark xmax, minimum ordinate ymin, maximum ordinate ymax, according to minimum abscissa xmin, maximum abscissa xmax、Minimum ordinate ymin, maximum ordinate ymaxObtain the minimum rectangle that comprises all planar cloud datas,Four summits of rectangle are denoted as respectively: A (xmin，ymin)、B(xmax，ymin)、C(xmax，ymax)、D(xmin，ymax)；
(2) ask for the central point E of rectangle, the coordinate of some E isPoint EBe the virtual center point of planar cloud data.
2. a kind of three-dimensional laser imaging system plane cloud data trigonometric ratio according to claim 1 placeReason method, is characterized in that: the implementation method of described step (1) is:
(1) select and belong to conplane 3 D stereo point according to the three-dimensional coordinate of 3 D stereo cloud dataCloud data are also preserved;
(2) by the 3 D stereo cloud data preserving or be rotated and remove or directly remove theThree dimensional point cloud obtains planar cloud data, and the third dimension cloud data after removing is protectedDeposit.
3. a kind of three-dimensional laser imaging system plane cloud data trigonometric ratio according to claim 1 processingMethod, is characterized in that: initial boundary zenith directions is for rising as border vertices to put 1 in described step (5)Pressing the method counterclockwise sorting is:
(1) planar cloud data is increased to three-dimensional data, wherein the value of third dimension data is 0;
(2) try to achieve a little and 1 arrive the vector of putting 2With the vector of point 1 to point 3
(3) to vectorWithCarry out multiplication cross computing, judge the third dimension value of the vector that multiplication cross computing obtainsWhether be greater than zero, if be greater than 0, initial boundary summit is point 1, point 2, point 3 by sorting counterclockwise, otherwise,Initial boundary summit is by sorting counterclockwise as point 1, point 3, point 2.
4. a kind of three-dimensional laser imaging system plane cloud data trigonometric ratio according to claim 1 processingMethod, is characterized in that: the method that finds the visible starting point on initial boundary summit in described step (6)For:
(1) planar cloud data is increased to three-dimensional data, wherein the value of third dimension data is 0, calculatesThe vector on 4 to three initial boundary summits of point, is designated as
(2) by vectorWithCarry out multiplication cross computing, judge the third dimension value of the vector that multiplication cross computing obtainsWhether be more than or equal to zero, if be more than or equal to 0, by vectorWithCarry out multiplication cross computing, judge vectorWithWhether the third dimension value that multiplication cross computing obtains vector is more than or equal to zero, if be more than or equal to 0, by vectorWithCarry out multiplication cross computing, judge vectorWithWhether the third dimension value of the vector that multiplication cross computing obtainsBe more than or equal to zero, work as vectorWithThe third dimension value of the vector that multiplication cross computing obtains is less than zero, and the 3rdIndividual initial boundary summit is the visible starting point on initial boundary summit, works as vectorWithMultiplication cross computing obtainsThe third dimension value of vector is less than zero, and second initial boundary summit is the initial as seen of initial boundary summitPoint;
IfWithThe vector that carries out obtaining after multiplication cross computing is less than 0, by vectorWithCarry out multiplication cross fortuneCalculate, judge vectorWithWhether the third dimension value that multiplication cross computing obtains vector is more than or equal to zero, if be greater thanEqual 0, by vectorWithCarry out multiplication cross computing, judge vectorWithThe arrow that multiplication cross computing obtainsWhether the third dimension value of amount is more than or equal to zero, works as vectorWithThe third dimension of the vector that multiplication cross computing obtainsValue is less than zero, and the 3rd the visible starting point that initial boundary summit is initial boundary summit, works as vectorWithThe third dimension value of the vector that multiplication cross computing obtains is less than zero, and first initial boundary summit is first initial lineThe visible starting point on summit, boundary.
5. a kind of three-dimensional laser imaging system plane cloud data trigonometric ratio according to claim 1 processingMethod, is characterized in that: the method that finds the visible destination node on initial boundary summit in described step (6)For:
(1) planar cloud data is increased to three-dimensional data, wherein the value of third dimension data is 0, calculatesThe vector on 4 to three initial boundary summits of point, is designated as
(2) by vectorWithCarry out multiplication cross computing, judge vectorWithThe arrow that multiplication cross computing obtainsWhether flow control three-dimensional value is less than or equal to zero, if be less than or equal to 0, by vectorWithCarry out multiplication cross computing,Judge vectorWithWhether the third dimension value that multiplication cross computing obtains vector is less than or equal to zero, if be less than or equal to0, by vectorWithCarry out multiplication cross computing, judge vectorWithOf the vector that multiplication cross computing obtainsWhether three-dimensional value is less than or equal to zero, if vectorWithThe third dimension value of the vector that multiplication cross computing obtains is greater thanZero, first initial boundary summit is the visible destination node on initial boundary summit, if vectorWithForkThe third dimension value that multiplication obtains vector is greater than zero, and second initial boundary summit is initial boundary summitVisible destination node;
IfWithThe vector that carries out obtaining after multiplication cross computing is greater than 0, by vectorWithCarry out multiplication cross fortuneCalculate, judge vectorWithWhether the third dimension value of the vector that multiplication cross computing obtains is less than or equal to zero, if littleIn equaling 0, by vectorWithCarry out multiplication cross computing, if vectorWithMultiplication cross computing obtains vectorThird dimension value be greater than zero, first initial boundary summit is the visible destination node on initial boundary summit, asFruit vectorWithThe third dimension value of the vector that multiplication cross computing obtains is greater than zero, the 3rd initial boundary topPoint is the visible destination node on initial boundary summit.
6. according to a kind of three-dimensional laser imaging system plane cloud data triangle described in claim 1,4 or 5Change processing method, it is characterized in that: the method that forms new border vertices in described step (6) is:
(1) the visible starting point obtaining according to step (6) and visible destination node, connect insertion point with visibleStarting point is to each border vertices between visible destination node;
(2) if the sequence sequence number of visible starting point is greater than the sequence sequence number of visible destination node, by newBorder vertices comprises from visible destination node to all border vertices visible starting point and new insertion point, limitThe order on summit, boundary is counterclockwise; If the sequence sequence number of visible starting point is less than the sequence order of visible destination nodeNumber, new border vertices comprises from visible destination node to all borders former border vertices last pointSummit, first of former border vertices arrive all border vertices and the new insertion point between visible starting point, borderThe order on summit is counterclockwise.
7. a kind of three-dimensional laser imaging system plane cloud data trigonometric ratio according to claim 6 processingMethod, is characterized in that: the method for in described step (6), initial delta being upgraded is: ifThe sequence sequence number of visible starting point is greater than the sequence sequence number of visible destination node, and newly-increased triangle is insertion pointWith all limits that form to former border vertices last point from visible starting point, from former border vertices last pointForm to all limits of visible destination node to the limit of first of former border vertices, from first of former border verticesTriangle; If the sequence sequence number of visible starting point is less than the sequence sequence number of visible destination node, newly-increased threeDihedral is insertion point and the triangle forming to all limits of visible destination node formation from visible starting point.
8. a kind of three-dimensional laser imaging system plane cloud data trigonometric ratio according to claim 1 placeReason method, is characterized in that: the method that in described step (8), plane trigonometry net is optimized to processing is:
(1) all triangles in traversal plane trigonometry net, calculate leg-of-mutton three angle sizes, ifThe angular dimension at one of them angle is greater than 90 °, just from plane trigonometry net, finds out the opposite side at this angle as itThe triangle on middle one side, the angular dimension at leg-of-mutton this diagonal angle, limit that calculating is found out, by upper two angle valuesBe added, if be greater than 180 °, be optimized, the quadrangle that two original triangles are formed is from anotherDiagonal angle cuts, and becomes two new triangles, and originally two triangles are replaced;
(2) all triangles in traversal plane trigonometry net, delete the length of side in plane trigonometry net and are greater than settingAll triangles of threshold value are realized the optimization to plane trigonometry net.
9. a kind of three-dimensional laser imaging system plane cloud data trigonometric ratio according to claim 2 processingMethod, returns plane trigonometry net to three-dimensional method from two-dimensional map in described step (8) and is: by step (1)The third dimension cloud data of removing adds in the plane trigonometry net after optimization and obtains 3 D stereo cloud data3 D stereo triangulation network trrellis diagram.
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