CN105825506A - Method for extracting contour line of water body via point cloud data of LiDAR - Google Patents
Method for extracting contour line of water body via point cloud data of LiDAR Download PDFInfo
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- 239000003653 coastal water Substances 0.000 claims description 65
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Abstract
The invention discloses a method for extracting a contour line of a water body via point cloud data of an LiDAR. Via the method, the contour line of the water body can be extracted only via scattered point cloud data of the airborne LiDAR, and the method can be applied to water body edge detection via point cloud data of the airborne LiDAR. The method is simple, easy to realize, and high in execution efficiency, the contour line of the water body can be directly obtained from the point cloud data of the airborne LiDAR needless of other auxiliary data, and the water body is extracted accurately and comprehensively.
Description
Technical field
The present invention relates to a kind of method extracting coastal waters line, particularly to a kind of method utilizing LiDAR point cloud data to extract coastal waters line.
Background technology
Water is the essential condition determining wetland living or death, utilizes remote sensing technology to obtain wetland water body area and has important indicative significance to wetland, and remote sensing technology, as a kind of novel earth observation from space technology, has been widely used for dynamic monitoring and the resource investigation of mud wetland.But traditional optical remote sensing technology exists in terms of beach water body investigation that the quality of data is affected seriously by weather conditions, night cannot work and vegetative coverage stronger area optical remote sensing can not penetrate vegetation etc. and affect, thus optical remote sensing technology in wetland is applied by a definite limitation.
Airborne lidar detection system is a kind of active earth observation systems, there is the features such as high reliability, high-resolution and high accuracy, it is used widely at numerous areas, Airborne LiDAR Technology being applied to wetland potential storage capacity detection aspect and has bigger prospect, water body contour line based on scattered point cloud data accurately extracts, and is the committed step obtaining storage capacity.At present, utilize scattered point cloud data extracting directly to go out one of Main Means that boundary point is Boundary extracting algorithm.
Summary of the invention
The technical problem to be solved is to provide a kind of method utilizing LiDAR point cloud data to extract coastal waters line, the method only utilizing airborne LiDAR scattered point cloud data can extract water body contour line, can apply to the detection of airborne LiADR cloud data coastal waters.
The present invention solves above-mentioned technical problem by the following technical solutions:
The present invention provides a kind of method utilizing LiDAR point cloud data to extract coastal waters line, including step in detail below:
Step 1, reads the original airborne LiDAR point cloud data of target area, obtains total number n of original LiDAR point cloud data;
Step 2, determines the step-length of grid partition and determines x direction and number n of y direction gridxAnd ny;
Step 3, the n obtained in traversal step 2x×nyAccording to the number putting cloud in grid, individual grid, judges that whether grid is grid in water body, and record the position of grid in each water body, thus grid and position thereof in obtaining all water bodys, specifically comprise the following steps that
301: make w=1, v=1;
302: be numbered four summits of w row v row grid, the wherein summit, the lower right corner numbered 1 of this grid, other summits number consecutively counterclockwise is 2,3 and 4, utilizes formula 4 to calculate the coordinate on this grid 1~4 summit
(xright,ydown)、(xright,yup)、(xleft,yup) and (xleft,ydown):
303: in calculating current mesh, put number z of cloud, if z >=5, then perform step 304;If z < 5, then current mesh is labeled as grid in water body, proceeds to step 305;
304: make w=w+1, if w≤nx, then v keeps constant, returns step 302;If w is > nx, then make w=1, v=v+1, return step 302;
305: record the position of grid in each water body, thus grid and position thereof in obtaining all water bodys;
Step 4, the eight connectivity grid of grid in l the water body that search step 3 obtains one by one, it is thus achieved that all land and water boundary grid in target area, and determine that all land and water boundary grid are positioned at the summit of water body, specifically comprise the following steps that
401: make I=1;
402;Using grid in i-th water body as seed grid, being numbered the eight connectivity grid of seed grid, wherein lower right corner grid numbered 1, other grid number consecutively counterclockwise is 2~8;
403: calculate some cloud number h in 1~No. 8 grid respectively, if h >=5, be land and water boundary grid by this grid ticks;
404: make I=I+1, if I≤l, return step 402, otherwise terminate iteration, thus all land and water boundary grid in obtaining target area, perform step 405;
405: determine that the land and water boundary grid of labelling in step 403 is positioned at the summit of water body;
Step 5, K the land and water boundary grid that search step 4 obtains one by one, obtain the coastal waters point of each land and water boundary grid, specifically comprise the following steps that
501: make t=1;
502, optional the t land and water boundary grid is positioned at the summit of water body as kind of a son vertex w1, use the some cloud in K-D tree seed tissue summit and this land and water boundary grid, utilize nearest neighbor algorithm to obtain the nearest neighbor point of kind son vertex, using nearest neighbor point as initial seed point o of water body limit marginal point1;
503: with initial seed point o1For starting point, determine initial seed point o1The coastal waters point of side, specifically comprises the following steps that counterclockwise
50301: use k nearest neighbor algorithm search initial seed point o1Nearest neighbor point cloud point p in this land and water boundary grid1,p2,...,pq, wherein q is the number of the nearest neighbor point cloud point searched;
50302: utilize formula 5 to calculate initial angle alpha0:
In formula, a is o1And w1Between distance, b is w1And w2Between distance, c is o1And w2Between distance, w2For w in this land and water boundary grid1Anticlockwise next summit;
50303: utilize formula 6 to calculate pi、w1And w2The ∠ p constitutediw1w2The number of degrees, and be designated as αi:
In formula, i=1,2 ..., q;aiFor piAnd w1Between distance, b is w1And w2Between distance, ciFor piAnd w2Between distance;
50304: from α1,α2,…,αqMiddle selection is more than initial angle alpha0Angle, and the nearest neighbor point cloud point of its correspondence is designated as N again1,…,Ns, wherein s is α1,α2,.….,αqIn more than initial angle alpha0The number at angle;
50305: utilize formula 7 to calculate ∠ Njo1w1The number of degrees, and be designated as βj:
In formula, j=1,2 ..., s;AjFor NjAnd o1Between distance, a is o1And w1Between distance, CjFor NjAnd w1Between distance;
50306: from β1,β2,…,βsThe angle that the middle selection number of degrees are minimum, nearest neighbor point cloud point corresponding to this angle is coastal waters point;
50307: coastal waters point step 50306 obtained, as new initial seed point, repeats step 50301~50306, continually look for next coastal waters point, until occurring without new coastal waters point;
504: with initial seed point o1For starting point, determine initial seed point o1The coastal waters point of side, specifically comprises the following steps that clockwise
50401: utilize formula 8 to calculate initial angle θ0:
In formula, a is o1And w1Between distance, e is w1And w3Between distance, f is o1And w3Between distance, w3For w in this land and water boundary grid1Clockwise next summit;
50402: utilize formula 9 to calculate pi、w1And w3The ∠ p constitutediw1w3The number of degrees, and be designated as θi:
In formula, aiFor piAnd w1Between distance, e is w1And w3Between distance, fiFor piAnd w3Between distance;
50403: from θ1,θ2,...,θqMiddle selection is more than initial angle θ0Angle, and the nearest neighbor point cloud point of its correspondence is designated as M again1,M2,...,Md, wherein d is θ1,θ2,...,θqMore than initial angle θ0The number at angle;
50404: utilize formula 10 to calculate ∠ Muo1w1The number of degrees, and be designated as ωu:
In formula, u=1,2 ..., d;DuFor MuAnd o1Between distance, a is o1And w1Between distance, FuFor MuAnd w1Between distance;
50405: from ω1,ω2,...,ωdThe angle that the middle selection number of degrees are minimum, nearest neighbor point cloud point corresponding to this angle is coastal waters point;
50406: coastal waters point step 50305 obtained, as new initial seed point, repeats step 50401~50405, continually look for next coastal waters point, until occurring without new coastal waters point;
505: the coastal waters point that integration step 503 and step 504 obtain, obtain all coastal waters points of current land and water boundary grid;
506, make t=t+1, if t≤K, then return step 502, the coastal waters point of the next land and water boundary grid of search;If t is > K, then terminate iteration, perform step 6;Thus obtain the coastal waters point of all land and water boundary grid;
Step 6, the coastal waters point of all land and water boundary grid obtained in integration step 5, thus obtain the edge image of target area water body.
As the further prioritization scheme of the present invention, step 2 determine the step-length of grid partition and determines x direction and the number of y direction grid, specifically comprising the following steps that
201: preset some cloud number m that each grid is expected to comprise;
202: calculate some coordinate minima minx in cloud x direction and maximum maxx, and coordinate minima miny in y direction and maximum maxy;
203: calculate the average density of target area point cloud;
204: calculate the step-length of grid partition;
205: calculate x direction and the number of y direction grid, thus obtain nyRow nxThe grid of row.
As the further prioritization scheme of the present invention, utilize the average density of target area point cloud in formula 1 calculation procedure 203, particularly as follows:
In formula, σ is the average density of target area point cloud.
As the further prioritization scheme of the present invention, utilize the step-length of grid partition in formula 2 calculation procedure 204, particularly as follows:
In formula, step is the step-length of grid partition.
As the further prioritization scheme of the present invention, utilize x direction and the number of y direction grid in formula 3 calculation procedure 205, particularly as follows:
In formula, nxAnd nyBeing respectively x direction and the number of y direction grid, fix represents intercepting mantissa function.
As the further prioritization scheme of the present invention, in step 405, land and water boundary grid is positioned at the summit of water body and is: the common vertex of land and water boundary grid and seed grid.
The present invention uses above technical scheme compared with prior art, have following technical effect that the inventive method is simple, execution efficiency is high, does not utilize other assistance datas just directly can obtain water body contour line from airborne LiDAB point cloud, it is possible to the most accurately and comprehensively to extract water body.
Accompanying drawing explanation
Fig. 1 is the method flow diagram of the present invention.
Fig. 2 is grid summit method for numbering serial.
Fig. 3 is the eight connectivity grid method for numbering serial of seed grid.
Fig. 4 is the schematic diagram of search coastal waters point.
Fig. 5 is original airborne LiDAR point cloud image.
Fig. 6 is the coastal waters image extracted.
Detailed description of the invention
Below in conjunction with the accompanying drawings and technical scheme is described in further detail by specific embodiment:
As it is shown in figure 1, a kind of method utilizing LiDAR point cloud data to extract coastal waters line, comprise the following steps:
1, the original airborne LiDAR point cloud image of certain lake region is as it is shown in figure 5, read original airborne LiDAR point cloud data, total number n=1244620 of cloud data.
2, determine the step-length of grid partition and determine x direction and the number of y direction grid, specifically comprising the following steps that
201: preset some cloud number k=100 that each grid is expected to comprise;
202: calculate X-direction minima minx and maximum maxx, and Y-direction minima miny and maximum maxy;
204: utilize formula 1 calculate target area some cloud average density σ:
205: utilize formula 2 to calculate step-length step of grid partition:
206: utilize formula 3 to calculate x direction and the number of y direction grid, there are nyRow nxRow grid.
Step 3, travels through 109 × 113 grid, judges that whether grid is grid in water body according to the number putting cloud in grid, and records the position of grid in each water body, thus grid and position thereof in obtaining all water bodys, specifically comprise the following steps that
301: make w=1, v=1;
302: be numbered four summits of w row v row grid, as in figure 2 it is shown, the summit, the lower right corner numbered 1 of wherein this grid, other summits number consecutively counterclockwise is 2,3 and 4, utilizes formula 4 to calculate the coordinate (x on this grid 1~4 summitright,ydown)、(xright,yup)、(xleft,yup) and (xleft,ydown):
303: in calculating current mesh, put number z of cloud, if z >=5, then perform step 304;If z < 5, then current mesh is labeled as grid in water body, proceeds to step 305;
304: make w=w+1, if w≤109, then v keeps constant, returns step 302;If w > 109, then make w=1, v=v+1, return step 302;
305: record the position of grid in each water body, thus grid and position thereof in obtaining all water bodys.
Step 4, the eight connectivity grid of grid in l the water body that search step 3 obtains one by one, it is thus achieved that all land and water boundary grid in target area, and determine that all land and water boundary grid are positioned at the summit of water body, specifically comprise the following steps that
401: make I=1;
402;Using grid in i-th water body as seed grid, being numbered the eight connectivity grid of seed grid, as it is shown on figure 3, wherein lower right corner grid numbered 1, other grid number consecutively counterclockwise is 2~8;
403: calculate some cloud number h in 1~No. 8 grid respectively, if h >=5, be land and water boundary grid by this grid ticks;
404: make I=I+1, if I≤l, return step 402, otherwise iteration terminates, thus all land and water boundary grid in obtaining target area, perform step 405;
405: determine that the land and water boundary grid of labelling in step 403 is positioned at the summit of water body, be the common vertex of land and water boundary grid and seed grid.
Step 5, search step 4 obtains K land and water boundary grid one by one, obtains the coastal waters point of each land and water boundary grid, as shown in Figure 4, specifically comprises the following steps that
501: make t=1;
502, optional the t land and water boundary grid is positioned at the summit of water body as kind of a son vertex w1, use the some cloud in K-D tree seed tissue summit and this land and water boundary grid, utilize nearest neighbor algorithm to obtain the nearest neighbor point of kind son vertex, using nearest neighbor point as initial seed point o of coastal waters point1;
503: with initial seed point o1For starting point, determine initial seed point o1The coastal waters point of side, specifically comprises the following steps that counterclockwise
50301: use k nearest neighbor algorithm search initial seed point o1Nearest neighbor point cloud point p in this land and water boundary grid1,p2,...,pq, wherein q is the number of the nearest neighbor point cloud point searched;
50302: utilize formula 5 to calculate initial angle alpha0:
In formula, a is o1And w1Between distance, b is w1And w2Between distance, c is o1And w2Between distance, w2For w in this land and water boundary grid1Anticlockwise next summit;
50303: utilize formula 6 to calculate pi、w1And w2The ∠ p constitutediw1w2The number of degrees, and be designated as αi:
In formula, i=1,2 ..., q;aiFor piAnd w1Between distance, b is w1And w2Between distance, ciFor piAnd w2Between distance;
50304: from α1,α2,...,αqMiddle selection is more than initial angle alpha0Angle, and the nearest neighbor point cloud point of its correspondence is designated as N again1,...,Ns, wherein s is α1,α2,…,αqMore than initial angle alpha0The number at angle;
50305: utilize formula 7 to calculate ∠ Njo1w1The number of degrees, and be designated as βj:
In formula, j=1,2 ..., s;AjFor NjAnd o1Between distance, a is o1And w1Between distance, CjFor NjAnd w1Between distance;
50306: from β1,β2,...,βsThe angle that the middle selection number of degrees are minimum, nearest neighbor point cloud point corresponding to this angle is coastal waters point;
50307: coastal waters point step 50306 obtained, as new initial seed point, repeats step 50301~50306, continually look for next coastal waters point, until occurring without new coastal waters point;
504: with initial seed point o1For starting point, determine initial seed point o1The coastal waters point of side, specifically comprises the following steps that clockwise
50401: utilize formula 5 to calculate initial angle θ0:
In formula, a is o1And w1Between distance, e is w1And w3Between distance, f is o1And w3Between distance, w3For w in this land and water boundary grid1Clockwise next summit;
50402: utilize formula 6 to calculate pi、w1And w3The ∠ p constitutediw1w3The number of degrees, and be designated as θi:
In formula, aiFor piAnd w1Between distance, e is w1And w3Between distance, fiFor piAnd w3Between distance;
50403: from θ1,θ2,…,θqMiddle selection is more than initial angle θ0Angle, and the nearest neighbor point cloud point of its correspondence is designated as M again1,M2,…,Md, wherein d is θ1,θ2,…,θqMore than initial angle θ0The number at angle;
50404: utilize formula 7 to calculate ∠ Muo1w1The number of degrees, and be designated as ωu:
In formula, u=1,2 ..., d;DuFor MuAnd o1Between distance, a is o1And w1Between distance, FuFor MuAnd w1Between distance;
50405: from ω1,ω2,...,ωdThe angle that the middle selection number of degrees are minimum, nearest neighbor point cloud point corresponding to this angle is coastal waters point;
50406: coastal waters point step 50305 obtained, as new initial seed point, repeats step 50401~50405, continually look for next coastal waters point, until occurring without new coastal waters point;
505: the coastal waters point that integration step 503 and step 504 obtain, obtain all coastal waters points of current land and water boundary grid;
506, make t=t+1, if t≤K, then return step 502, the coastal waters point of the next land and water boundary grid of search;If t is > K, then terminates performing, perform step 6;Thus obtain the coastal waters point of all land and water boundary grid.
Step 6, the coastal waters point of all land and water boundary grid obtained in integration step 5, thus obtain the edge image of target area water body, as shown in Figure 6.
Can be seen that from Fig. 5 and Fig. 6, in the case of not utilizing other assistance datas, the present invention just directly can get the profile cloud data of water body from original airborne LiDAR point cloud image, and the point cloud chart picture extracted can the profile of the most accurately and comprehensively body display water body.
The above; it is only the detailed description of the invention in the present invention; but protection scope of the present invention is not limited thereto; any it is familiar with the people of this technology in the technical scope that disclosed herein; it is appreciated that the conversion or replacement expected; all should contain within the scope of the comprising of the present invention, therefore, protection scope of the present invention should be as the criterion with the protection domain of claims.
Claims (6)
1. one kind utilizes the method that LiDAR point cloud data extract coastal waters line, it is characterised in that include step in detail below:
Step 1, reads the original airborne LiDAR point cloud data of target area, obtains total number n of original LiDAR point cloud data;
Step 2, determines the step-length of grid partition and determines x direction and number n of y direction gridxAnd ny;
Step 3, the n obtained in traversal step 2x×nyAccording to the number putting cloud in grid, individual grid, judges that whether grid is grid in water body, and record the position of grid in each water body, thus grid and position thereof in obtaining all water bodys, specifically comprise the following steps that
301: make w=1, v=1;
302: be numbered four summits of w row v row grid, the wherein summit, the lower right corner numbered 1 of this grid, other summits number consecutively counterclockwise is 2,3 and 4, utilizes formula 4 to calculate the coordinate (x on this grid 1~4 summitright,ydown)、(xright,yup)、(xleft,yup) and (xleft,ydown):
303: in calculating current mesh, put number z of cloud, if z >=5, then perform step 304;If z < 5, then current mesh is labeled as grid in water body, proceeds to step 305;
304: make w=w+1, if w≤nx, then v keeps constant, returns step 302;If w is > nx, then make w=1, v=v+1, return step 302;
305: record the position of grid in each water body, thus grid and position thereof in obtaining all water bodys;
Step 4, the eight connectivity grid of grid in l the water body that search step 3 obtains one by one, it is thus achieved that all land and water boundary grid in target area, and determine that all land and water boundary grid are positioned at the summit of water body, specifically comprise the following steps that
401: make I=1;
402;Using grid in i-th water body as seed grid, being numbered the eight connectivity grid of seed grid, wherein lower right corner grid numbered 1, other grid number consecutively counterclockwise is 2~8;
403: calculate some cloud number h in 1~No. 8 grid respectively, if h >=5, be land and water boundary grid by this grid ticks;
404: make I=I+1, if I≤l, return step 402, otherwise terminate iteration, thus all land and water boundary grid in obtaining target area, perform step 405;
405: determine that the land and water boundary grid of labelling in step 403 is positioned at the summit of water body;
Step 5, K the land and water boundary grid that search step 4 obtains one by one, obtain the coastal waters point of each land and water boundary grid, specifically comprise the following steps that
501: make t=1;
502, optional the t land and water boundary grid is positioned at the summit of water body as kind of a son vertex w1, use the some cloud in K-D tree seed tissue summit and this land and water boundary grid, utilize nearest neighbor algorithm to obtain the nearest neighbor point of kind son vertex, using nearest neighbor point as initial seed point o of coastal waters point1;
503: with initial seed point o1For starting point, determine initial seed point o1The coastal waters point of side, specifically comprises the following steps that counterclockwise
50301: use k nearest neighbor algorithm search initial seed point o1Nearest neighbor point cloud point p in this land and water boundary grid1,p2,...,pq, wherein q is the number of the nearest neighbor point cloud point searched;
50302: utilize formula 5 to calculate initial angle alpha0:
In formula, a is o1And w1Between distance, b is w1And w2Between distance, c is o1And w2Between distance, w2For w in this land and water boundary grid1Anticlockwise next summit;
50303: utilize formula 6 to calculate pi、w1And w2The ∠ p constitutediw1w2The number of degrees, and be designated as αi:
In formula, i=1,2 ..., q;aiFor piAnd w1Between distance, b is w1And w2Between distance, ciFor piAnd w2Between distance;
50304: from α1,α2,...,αqMiddle selection is more than initial angle alpha0Angle, and the nearest neighbor point cloud point of its correspondence is designated as N again1,...,Ns, wherein s is α1,α2,...,αqIn more than initial angle alpha0The number at angle;
50305: utilize formula 7 to calculate ∠ Njo1w1The number of degrees, and be designated as βj:
In formula, j=1,2 ..., s;AjFor NjAnd o1Between distance, a is o1And w1Between distance, CjFor NjAnd w1Between distance;
50306: from β1,β2,…,βsThe angle that the middle selection number of degrees are minimum, nearest neighbor point cloud point corresponding to this angle is coastal waters point;
50307: coastal waters point step 50306 obtained, as new initial seed point, repeats step 50301~50306, continually look for next coastal waters point, until occurring without new coastal waters point;
504: with initial seed point o1For starting point, determine initial seed point o1The coastal waters point of side, specifically comprises the following steps that clockwise
50401: utilize formula 8 to calculate initial angle θ0:
In formula, a is o1And w1Between distance, e is w1And w3Between distance, f is o1And w3Between distance, w3For w in this land and water boundary grid1Clockwise next summit;
50402: utilize formula 9 to calculate pi、w1And w3The ∠ p constitutediw1w3The number of degrees, and be designated as θi:
In formula, aiFor piAnd w1Between distance, e is w1And w3Between distance, fiFor piAnd w3Between distance;
50403: from θ1,θ2,...,θqMiddle selection is more than initial angle θ0Angle, and the nearest neighbor point cloud point of its correspondence is designated as M again1,M2,...,Md, wherein d is θ1,θ2,...,θqMore than initial angle θ0The number at angle;
50404: utilize formula 10 to calculate ∠ Muo1w1The number of degrees, and be designated as ωu:
In formula, u=1,2 ..., d;DuFor MuAnd o1Between distance, a is o1And w1Between distance, FuFor MuAnd w1Between distance;
50405: from ω1,ω2,...,ωdThe angle that the middle selection number of degrees are minimum, nearest neighbor point cloud point corresponding to this angle is coastal waters point;
50406: coastal waters point step 50305 obtained, as new initial seed point, repeats step 50401~50405, continually look for next coastal waters point, until occurring without new coastal waters point;
505: the coastal waters point that integration step 503 and step 504 obtain, obtain all coastal waters points of current land and water boundary grid;
506, make t=t+1, if t≤K, then return step 502, the coastal waters point of the next land and water boundary grid of search;If t is > K, then terminate iteration, perform step 6;Thus obtain the coastal waters point of all land and water boundary grid;
Step 6, the coastal waters point of all land and water boundary grid obtained in integration step 5, thus obtain the edge image of target area water body.
A kind of method utilizing LiDAR point cloud data to extract coastal waters line the most according to claim 1, it is characterised in that determine the step-length of grid partition in step 2 and determine x direction and the number of y direction grid, specifically comprising the following steps that
201: preset some cloud number m that each grid is expected to comprise;
202: calculate some coordinate minima minx in cloud x direction and maximum maxx, and coordinate minima miny in y direction and maximum maxy;
203: calculate the average density of target area point cloud;
204: calculate the step-length of grid partition;
205: calculate x direction and the number of y direction grid, thus obtain nyRow nxThe grid of row.
A kind of method utilizing LiDAR point cloud data to extract coastal waters line the most according to claim 2, it is characterised in that utilize the average density of target area point cloud in formula 1 calculation procedure 203, particularly as follows:
In formula, σ is the average density of target area point cloud.
A kind of method utilizing LiDAR point cloud data to extract coastal waters line the most according to claim 3, it is characterised in that utilize the step-length of grid partition in formula 2 calculation procedure 204, particularly as follows:
In formula, step is the step-length of grid partition.
A kind of method utilizing LiDAR point cloud data to extract coastal waters line the most according to claim 4, it is characterised in that utilize x direction and the number of y direction grid in formula 3 calculation procedure 205, particularly as follows:
In formula, nxAnd nyBeing respectively x direction and the number of y direction grid, fix represents intercepting mantissa function.
A kind of method utilizing LiDAR point cloud data to extract coastal waters line the most according to claim 1, it is characterised in that in step 405, land and water boundary grid is positioned at the summit of water body and is: the common vertex of land and water boundary grid and seed grid.
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CN107993242A (en) * | 2017-12-14 | 2018-05-04 | 天津大学 | Based on airborne LiDAR point cloud shortage of data zone boundary extracting method |
CN108876785A (en) * | 2018-06-29 | 2018-11-23 | 山东鲁能智能技术有限公司 | Enclosure space water regime monitoring method and system |
CN109272458A (en) * | 2018-08-10 | 2019-01-25 | 河海大学 | A kind of point cloud filtering method based on prior information |
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CN113409347A (en) * | 2021-08-19 | 2021-09-17 | 深圳市信润富联数字科技有限公司 | Method and device for extracting point cloud boundary, storage medium and electronic equipment |
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Cited By (9)
Publication number | Priority date | Publication date | Assignee | Title |
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CN107993242A (en) * | 2017-12-14 | 2018-05-04 | 天津大学 | Based on airborne LiDAR point cloud shortage of data zone boundary extracting method |
CN107993242B (en) * | 2017-12-14 | 2022-06-03 | 天津大学 | Method for extracting boundary of missing area based on airborne LiDAR point cloud data |
CN108876785A (en) * | 2018-06-29 | 2018-11-23 | 山东鲁能智能技术有限公司 | Enclosure space water regime monitoring method and system |
CN108876785B (en) * | 2018-06-29 | 2020-08-18 | 国网智能科技股份有限公司 | Closed space water regime monitoring method and system |
CN109272458A (en) * | 2018-08-10 | 2019-01-25 | 河海大学 | A kind of point cloud filtering method based on prior information |
CN109272458B (en) * | 2018-08-10 | 2021-05-11 | 河海大学 | Point cloud filtering method based on prior information |
CN111912346A (en) * | 2020-06-30 | 2020-11-10 | 成都飞机工业(集团)有限责任公司 | Nest hole online detection method suitable for robot drilling and riveting system on surface of airplane |
CN111912346B (en) * | 2020-06-30 | 2021-12-10 | 成都飞机工业(集团)有限责任公司 | Nest hole online detection method suitable for robot drilling and riveting system on surface of airplane |
CN113409347A (en) * | 2021-08-19 | 2021-09-17 | 深圳市信润富联数字科技有限公司 | Method and device for extracting point cloud boundary, storage medium and electronic equipment |
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