TW200910257A - System and method for cutting point clouds - Google Patents

Abstract

A method for cutting point clouds is provided. The method includes the steps of: (a) receiving point clouds from a point clouds obtaining apparatus; (b) constructing a topological structure for the point clouds; (c) selecting a point from the point clouds; (d) searching plurality of points that are nearest to the selected point from the point clouds; (e) constructing a paraboloid according to the selected point and the points that are nearest to the selected point, calculating an equation of the paraboloid, and computing a curvature of the selected point according the equation; (f) repeating steps from (c) to (e), until all the points in the point clouds has been selected; and (g) cutting the point clouds according the curvatures of all points in the point clouds. A related system is also provided.

Description

200910257 IX. INSTRUCTIONS: TECHNICAL FIELD OF THE INVENTION The present invention relates to a simplification system and method, a simplified system and a method.疋一点云精 [Prior Art] Reverse engineering is a design drawing of θ existing products relative to forward engineering. Bran I is processed according to the Ming gong, τθ ^, ..., and then processed according to the drawings. . And the accurate and high-speed scanning of the "speed three-dimensional recording and scanning series" has been carried out to obtain the three-dimensional digital model of the point cloud data obtained by the sample or the model, and the point cloud data is based on the product. The use of CAM system to complete the eyes, the use of two-dimensional laser scanner point cloud data - the general density is large, usually there are dozens of objects after the 'obtained million. And currently in the reverse engineering million, even the upper Most of them are... Therefore, time consumption = the most complicated problem of the time of constructing the algorithm. 疋 耘 耘 耘 需要 需要 需要 需要 , , , , , , , , , , , , , 利用 利用 利用 利用 利用 利用 利用 利用 利用 利用 利用 利用 利用 利用 利用 利用 利用 利用 利用 利用 利用Due to various reasons, the ice is too late, and even the noise of the point cloud is misleading. The sample will cause the reconstructed surface to be extremely uneven. [Inventive content] Provide a method that can quickly send points to ', a variety of points to streamline the system and a small amount of data, no distortion: two? streamlined and transition' in order to obtain - a more uniform point cloud of cookware. 200910257 Cloud streamlined system package Applying the feeding device. The application is applied to the family; the topology building module, the flapping structure, is to establish a set of all points in the π Ρ Ρ ,, for the topology established according to the above Structure, the distance of the point is the closest (four) dry point, · curvature meter, modulo 35: the curvature of the point that the brother finds, that is, the distance of a certain point-dot, 曰 = the proximity of the personification of the local paraboloid in the cloud The points are based on the general equation and surface: the Syrian private, and the point cloud simplification module for = curvature; and the simplification parameters of the point cloud setting, the point cloud production 7 and the user pair = rate and The nearest to the point: a value in the range of the concise parameter = the difference between the mean thousand is not within the range of the confinement parameter, the guarantee (four) = the point, otherwise, if the point:: = method ' The method includes the following steps: 〇 接收 接收 接收 筏 筏 筏 筏 筏 筏 筏 筏 筏 筏 筏 筏 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收 接收^, (c) select the number of points closest to the point, the structure, in the point cloud Find a number of points to perform a local paraboloid quasi-two f. The point is the closest equation to the point and calculate the curvature of the point according to the two-part paraboloid of the paraboloid; repeat the above (4) and ft rate calculation formula f in the cloud The curvature of all the points is counted in step (4) until the calculated curvature, and the user pairs 2::, and (1) the point cloud is streamlined according to the simplification parameter set by the above-mentioned counting point cloud. In the conventional technique, the three-dimensional laser scanning:: point cloud simplification system and square simplification, the curvature difference is used to express the accuracy of each point data, and the plane with smaller deformation is only =, . Jingdian's shape-variation redundant point, other points cloud with a greater degree of deformation, without distortion and more uniform [Embodiment] As shown in Fig. 1, it is a point structure diagram of the present invention. The system mainly includes a hard network 3 and a plurality of client computers 4 of the preferred embodiment. Should be, use the servo stolen 2, which is distributed among a number of extravagant application feeders 2, network & = computer 4 using network 3 and (5) coffee), or network (four) road ^ - corporate intranet Communication network. Eyes (a) or other types of point cloud acquisition devices! It is connected to the application feeder 2 for measuring the point cloud data obtained by the object. In the implementation method of 'Tianfu's Luo/Jia, the point cloud gets the point cloud data疋. A solid two-dimensional misdirected cropper, which scans the object to be tested = ΓΓ 32 for receiving point cloud information from the point cloud acquiring device 1, and streamlining the point cloud. The π 贝 user terminal computer 4 provides a graphic processing interface, which is capable of generating and displaying a graph of the point cloud data that is fed into the application server 2 200910257 -. and can display the result after the point cloud is reduced. . As shown in FIG. 2, it is a functional module diagram of the server 2 in the preferred embodiment of the point cloud reduction system of the present invention. The application server 2 mainly includes: a point cloud receiving module 20, a topology building module 21, a point selecting module 22, an adjacent point finding module 23, a curvature calculating module 24, a determining module 25, and a point. The cloud reduction module 26 and the point cloud output module 27. The module referred to in the present invention is a computer program segment for performing a specific function, and is more suitable for describing the execution process of the software in the computer than the program. Therefore, the following description of the software is described in the module. The point cloud receiving module 20 is configured to receive point cloud data from the point cloud acquiring device 1 and generate and display an image formed by the point cloud data in a graphic processing interface provided by the user terminal computer 4. The topology building module 21 is mainly used to establish a topology for the point cloud, that is, to associate all the points in the point cloud. The topology building module 21 meshes the cube area where the point cloud is located by a certain number of grids according to a set grid spacing Step to obtain a plurality of V. grids, and sets a sequence number for each grid. The serial number of each mesh is stored in a list with the serial numbers of the 26 meshes adjacent to the mesh in the cubic space, thereby associating all the meshes. The grid spacing Step can set different values according to actual conditions. For example, if the user wants more points in each grid, the grid spacing Step value can be set larger, if desired in each grid. If the number of points is small, the value of the grid spacing Step can be smaller. The point selection module 22 is configured to arbitrarily select one of the above-mentioned point clouds, 200910257*, a point (hereinafter referred to as: the point). The adjacent point finding module 23 is configured to find a number of points closest to the point according to the established _ knot. The contiguous point finding module 23 obtains the = ^ ^ ^ 1 βη , which includes a number of points in the grid in which all points in the grid are close to the point. The distance „海点取数=ΖΓ24 is mainly used to make the point closest to the point = 24 to 32 points in the preferred embodiment Γ f f 佳 进行 进行 进行 进行 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部 局部The Λ 计 计 出 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 。 This point (origin) is a parabolic seat under the original coordinate system: 'The general equation for the local transfer of the point to the local paraboloid from the 24 to 32 points: 2 Λ 3 Ν hu: a

N U; 2^4 11 200910257

C

among them:

Where U' V' h of S6 N represents the point and the coordinates of the 24 to 32 ', y, z coordinates respectively; n represents the incorporation and private I ( 茗 the phase _ 寻卿 έ fit #帅录'For example' Heart 2: "Finding plate set 23 finds 3. The last closest to the point, the curvature calculation module 24 calculates Curvature = ( 4 * a * c _ b * b ) / 2 using the curvature calculation The curvature of the point is calculated. The same point is calculated. The other points of the point (4) rate and the above-mentioned 12 200910257 are used to determine whether the rate of the point cloud t has been calculated. If not, the point is Select module ^ to select another point in the point cloud. ”· The point cloud reduction module 26 is mainly used to calculate the curvature of all points according to the above, and the user needs to simplify the point cloud. The following is a detailed description of the functions of the process and the ten-point cloud streamlining module 26: First, the phase_axis amount 23 is based on the point cloud: finding the nearest distance from the point. a number of points, in the preferred embodiment, = dry points are 9 to 15 points; calculate the 9~(5) fixed point of the juice nose at the point (4) The above-mentioned difference between the average users ^ = ==, to determine whether the point should be reduced by two ===:==; if it is less, the point can be reduced; otherwise, the deformation of the face is smaller than the right Within the dry perimeter, %' alum: the deformation of the surface composed of 9~15 points is larger, and the point is not; the streamlining of other points in the point cloud is the same as the above process. = cloud f out module 27 For outputting the streamlined point cloud. The second flow chart of the preferred embodiment of the preferred embodiment. Cloud (four) _ 〇 'point cloud receiving module 2G from the point cloud to obtain the receiving point in the device 1 step S11, the ceremonial gentleman 槐The structure is about to be in the point cloud; the vertical module 21 establishes an association for all the points of the point cloud establishing topology. 200910257. In step S12, the point selection module 22 selects a point in the point cloud (hereinafter: the point) In step S13, the neighboring point finding module 23 searches for a plurality of points in the point cloud that are closest to the point according to the above-mentioned topological structure. In the embodiment, the points here are 24 to 32. Step S14, the curvature calculation module 24 compares the point with the obtained points closest to the point (24~32) perform local paraboloid fitting, and calculate the curvature of the point according to the general equation of the paraboloid and the calculation formula of the curvature. In step S15, the determining module 25 determines whether the curvature of all points in the point cloud has been The calculation is completed. If not, returning to step S12, the point selection module 22 selects another point in the point cloud. If the curvature of all the points in the point cloud has been calculated, then in step S16, the point cloud reduction module 26 is based on The point cloud is streamlined according to the calculated curvature and the user's simplification requirement. In step S17, the point cloud output module 27 outputs the streamlined point cloud. Referring to FIG. 4, it is a specific implementation flowchart of establishing a topology structure between point clouds in step S11 in FIG. In step S110, the topology building module 21 meshes the cube area where the point cloud is located by a certain number of grids according to a set grid spacing Step to obtain a plurality of grids. The grid spacing Step can set different values according to actual conditions. For example, if the user wants more points in each grid, the grid spacing Step value can be set larger, if desired in each grid. If the number of points is small, the value of the grid spacing Step can be smaller. 14 200910257 Step sill, the topology building module 21 is for each grid/sequence, the _junction domain group 21 has its towel-net sequence=preface and 26 adjacent to the grid in the cubic space. The order of the grids = in a list - thus establishing the grid with other grids - step S113, the judgment group 25 judges whether the adjacent grids have been established. If not, then: =; S112. Otherwise, the topology between the point clouds is established. Referring to FIG. 5, it is a specific implementation flowchart of searching for a number of points closest to the point in the point cloud in step S13 in FIG. Step S130, the neighboring point finding module 23 obtains the smuggling number of the selected point, and obtains 26 nets adjacent to the grid in the cubic space according to the grid number. grid. Step S131' determines whether the total number of points in the grid of 27 grids and the adjacent 26 grids of the point is not less than a set value. In the present embodiment, the set value is 24. If the total number of points in the 27 grids is less than the set value, that is, less than 24', then in step S132, the neighboring point finding module 23 can obtain the adjacent grid by using the above list. Other grids. Until the total number of points in the obtained grid is not less than 24, in step S133, the adjacent point finding module 23 calculates the distance of all points in all the obtained grids from the point 'to get the closest to the point 24 to 32 points. Referring to Fig. 6, there is shown a specific implementation flow chart for calculating the curvature of a point in step S14 of Fig. 3. 15 200910257 ^Step 5140 'The curvature calculation module 24 establishes a local coordinate system with the selected point as the origin, and the coordinate values of the 24 to 32 points under the local coordinate system are respectively % is the coordinate value under the standard coordinate system minus the coordinate value of the point (origin) under the original coordinate system. ▲Step S141' The curvature calculation module 24 performs local paraboloid fitting with the 24~32 points under the local coordinate system (4), the general equation of the paraboloid:

b = S1S5 - C =

SlS 5 - S 2S 4 where:

Ufv.

16 2 200910257

N N

Where u, v, h represent the point, and the X, y, z coordinate values of the nearest 24 to 32 points from the point; N represents the number of points at which the paraboloid fit is performed, for example, if the phase The neighbor finding module 23 finds 30 points closest to the point, then N=31. In step S142, the curvature calculation module 24 calculates the curvature of the point using the curvature calculation formula: Curvature = (4*a*c - b*b)/2. Referring to FIG. 7, it is a specific implementation flowchart of the process of streamlining the point cloud in step S16 in FIG. In step S160, the user sets a requirement for the simplicity of the point cloud, that is, inputs a simplification parameter. In step S161, the point selection module 22 selects a point in the point cloud. In step S162, the point cloud reduction module 26 searches for the closest 9 to 15 points from the point according to the topology between the point clouds (the method is similar to the step shown in Fig. 5 above). In step S163, the point cloud reduction module 26 calculates the average of the curvature values of the above 9 to 15 points. In step S164, the point cloud reduction module 26 calculates the difference between the curvature of the point and the average value of the curvature of the above 9 to 15 points. In step S165, the point cloud reduction module 26 compares the calculated difference with the simplification parameter set by 17 200910257, and sets different simplification flags for the point according to the comparison result. If the difference is within the set range of the simplification parameter, it means that the deformation of the surface formed by the point and the above 9~15 points is less, and the point can be simplified, and the point cloud simplification module 26 can At this point, the simplification flag is set to "1"; otherwise, if the difference is not within the range of the simplification parameter set by the user, it means that the deformation of the surface formed by the point and the above 9 to 15 points is large, and the point cannot be Being reduced, the point cloud reduction module 26 can set the point to a simplification standard of "0." In step S166, the judging module 25 judges whether all the points in the grid in which the point is located have been set with the compact flag. If the grid in which the point is located is not set to be reduced, then the point selection module 22 selects other points in the grid, and then returns to step S162. Otherwise, if all the points of the grid in which the point is located have been set with the streamlined flag, then in step S168, the determining module 25 determines whether all the points in the grid will be streamlined according to the set compact flag, that is, whether All points in the grid are set with the flag "1". If so, in step S169, the point cloud reduction module 26 retains a point in the grid that is closest to the center position, i.e., the reduced flag of a point closest to the center of the grid is modified to "0". Keeping at least one point in each grid makes the streamlined point cloud distribution more uniform. If at least one point in the grid can be reserved, then in step S170, the determining module 25 determines whether all the points in the point cloud have been set with the simplification standard 18 200910257. If there is still no point to set the condensed flag, then return to step S161. The point selection module 22 continues to select another point in the point cloud. ' If all the points in the point cloud have been set with the streamlined flag, then in step S171, the point cloud reduction module 26 condenses the points in the point cloud according to the reduced flag set above. The 24 to 32 points or 9 to 15 points of the present invention are only preferred ranges of values obtained after verification, and the other ranges of values should not be excluded from the scope of protection of the present invention. The point cloud simplification system and method provided by the invention can simplify the point cloud data scanned by the three-dimensional laser scanner, and use the curvature difference to express the degree of deformation of each point compared to its adjacent point, and the deformation is small. Plane, only retain the necessary points, and streamline other redundant points. For surfaces with a large degree of deformation, the number of points to be reserved is determined according to the requirements of the simplification, so that a point cloud with less data, no distortion and more uniformity can be obtained. . Further, the present invention establishes an association between point clouds, so when calculating a number of points closest to a certain point, it is not necessary to calculate the distance between the point and all points in the point cloud, and the association between the point clouds is Searching at a point closer to the point, thus greatly improving the speed of the operation. The above is only the preferred embodiment of the present invention, and has been used in a wide range of applications. Any other equivalent changes or modifications which are not departing from the spirit of the present invention should be included in the following claims. Inside. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 is a hardware architecture diagram of a preferred embodiment of the point cloud reduction system of the present invention. 19 200910257 Figure 2 is a functional block diagram of the application server of Figure 1. 3 is a main flow chart of a preferred embodiment of the point cloud reduction method of the present invention. Fig. 4 is a flow chart showing the step of establishing a point in step S11 of Fig. 3. The specific implementation flow chart of each of the topologies is shown in step S13 of Fig. 3 in the point cloud to find the closest point of the distance-point. The flow is a specific implementation of calculating the curvature of 1 point in step S14 in Fig. 3. Fig. 7 is a flowchart of the point cloud in step S16 in Fig. 3. π Inter-process processing [main component symbol description] Point cloud acquisition device application server 1 network 2 user terminal computer 3 point cloud receiving module 4 lifting structure establishment module 20 selection module 21 adjacent point finding module Group 22 curvature calculation module 23 judgment module 24 point cloud reduction module 25 point cloud output module 26 receiving point cloud data 27 S10 200910257 511 512 brother finds the point selection distance between the selected point point and the point cloud The point in the cloud is based on the above topology, and several points in the point cloud are the most recent points S13 = the selected Lai ship is converted to the parabolic ship for parabolic fitting, and all the points in the curvature point cloud of the point are calculated. The curvature has been = calculated according to the above #. Cloud to reduce the curvature and the degree of refinement of m U 'point to point 516 517 rounded down point cloud 21

Claims (1)

200910257 X. Patent application scope: 1.:: Point cloud streamlining system, including application servo server includes: 〃r The application material ^ receiving pull group is used to acquire the device from a point cloud to make the receiving point cloud topology a module for establishing a topology in all points in the point cloud, that is, an adjacent point finding module, for finding a point closest to the point in the cloud according to the above-mentioned established cloud The calculation module is used to calculate the point =... the point closest to the point, the '', the rate, that is, the local quadratic parabola 及^ and the curvature calculation for the local scalar point (4) = The general equation point cloud simplification module is configured to calculate a simplification parameter of the point cloud according to the above calculation= and a curvature average value of a plurality of points of the user value closest to the point in the simplification parameter Scope - Otherwise 1 is not within the range of the simplification parameter, the mate = the point, the point cloud simplification system described in the first item of the patent scope, in which the second hop structure is established by the module to establish the topology is based on the following step : 2:=The distance between the grids and the cubes where the point cloud is located is meshed by the number of the number of stagnations to obtain the number of multiple tiling numbers; the serial number of each grid is adjacent to the erect; The order of the six grids is stored in a list with the order of the network, thus establishing a correlation between the grids of the 22200910257. 3. If the application scope is 2 jg μ, +, • -y ^ edge cloud reduction system, where the 'points in the point cloud look for the nearest $L .... select a point in point ^; get the grid In the vertical 3 = according to the list to find the distance from all the points in the grid where the point is located, and obtain a number of points close to the point. 4. If the patent application rate is the first rate The point cloud reduction system, wherein a plurality of points in the description are 24 to 32 points, and a plurality of points in the point cloud group are 9 to 15 points. 5. ^ Seed cloud reduction Branch, the financial method includes the following (4): a Receive point cloud data from a point cloud acquisition device "The above point cloud establishes a topology structure, It is about to point all the points in the cloud; (c) select a point in the point cloud; the butterfly structure, in the (four) towel axis and the point distance (four) the nearest point of the point to the local difficult face -== face general Equation, and calculate the curvature of the point according to the repeated calculation formula of the point (C) to step (e) until the point rate is calculated; and the curvature of all points of r (1) "The above calculated curvature 'And the user's streamlined parameter of the point cloud setting 23 200910257, the point cloud is streamlined. 6. The point cloud step (b) of applying the special 5th rhyme includes: method, wherein Bl) according to a setting _ 妒卩 妒卩 LV LV ΑΛ λ α ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ Grid; (b3) store the serial number of one of the grids and the 26 grids adjacent to the grid in the ";s" and establish an association between the grid and other grids, fly, medium 'There will be the repetition of the above (4) (five)), and the drums will establish an association between the financial networks. ...Photographing grid=Applying the sacred sixth rhyme point cloud reduction step (d) includes: /, T, and according to the grid number, the selected points are obtained in 26 adjacent networks in the body space. The grid number in the above list is obtained in the cube with the grid; and the distance including the grid where the point is located, the distance of all the points in the 27 grids is the closest to the point. a point. 8. The point cloud reduction method described in item 7 of the patent application scope has a number of points of 24 to 32 points. 9. The point cloud reduction method described in claim 6 of the patent scope, the steps (f) includes: inputting a streamlined (fi) user setting for the point cloud's simplification requirement, degree parameter; 24 200910257 (f 2 ) selecting a point in the point cloud; (f3) according to the point cloud's knowledge* Topology, ,, °, find the closest point to the point; J stone =) · Calculate the curvature of the point and the average of the curvature of the above points (8) to reduce the above calculated difference with the above settings According to the result of the comparison, select (f3) to step (f5) in the grid where the point is located, until the point j, '稷' η All the points in the grid are smashed and set the fine mark; (9) according to the set of the simplified standard (four) break whether the net will be streamlined; 丨 another magic point (8) if it is, then retain the axis grid closest to the center position Duplicate (9) of the point closest to the center of the grid Steps (9) to (9) until the simplification flag is set; and the other phantom points (_ simplifies the point cloud according to the condensed flag set above. 10. The point cloud simplification method as described in claim 9 of the patent scope, The several points mentioned therein are 9 to 15 points. 11. The point cloud reduction method described in claim 5, wherein the general equation of the paraboloid is: Ν hu/ NNN 25 % 200910257 where: b = c =: ^2S 6 -S Is 5 ~ 5254 1 5 4 N hivfy.uf ^ N «S6 = W,2..2 where x is the number of points in the formula, yU :, the width represents the point and the nearest number to the point. Y'z coordinate value, N represents the point at which the paraboloid fit is performed. 12. The curvature calculation formula of the point cloud described in the application of the item 11 is: 1 method, where Curvature = (4*a* c — b*K \ 0 ) / 2. 26