Three-dimensional scanning distance and range determination method under given precision condition

Abstract

The invention relates to the technical field of three-dimensional scanning, in particular to a method for determining a three-dimensional scanning distance and range under a given precision condition, which determines the precision of a three-dimensional scanner within a specified range under different distances through a calibration test and detailed data analysis of a system, provides reliable scanning parameter selection, and improves the accuracy of the three-dimensional scanning distance and range. The method is widely applied to the fields of building measurement, industrial detection, cultural heritage protection and the like; according to the method, subjectivity and blindness of scanning parameter selection are avoided through a scientific parameter selection method, meanwhile, the working efficiency of scanning operation is improved, accidental errors are reduced through multiple tests and data averaging processing, comprehensive data are provided, influence factors and rules of scanning precision are clarified, the scanning process is optimized, and the scanning accuracy is improved. The efficiency and the result precision are improved, and the problem that the precision reliability of an existing three-dimensional scanning system in practical application is limited is solved.

Description

Technical Field

[0001] The present invention relates to the field of three-dimensional scanning technology, and in particular to a method for determining a three-dimensional scanning distance and range under given accuracy conditions. Background Art

[0002] In the field of 3D scanning technology, point cloud is the output result of 3D scanning technology, which consists of a large number of discrete points. Each point has a certain 3D coordinate (x, y, z). These points together describe the surface features of the object and represent the detailed 3D information of the scanned object. Point cloud data can be further used for modeling, analysis, measurement and visualization. The measurement accuracy of point cloud is an important indicator for judging the scanning accuracy of the scanner.

[0003] In terms of point cloud accuracy, the accuracy of the scanner is an important factor affecting the reliability of measurement. Existing 3D scanning systems usually rely on the specifications and test data provided by the manufacturer. These data may be biased in actual applications and cannot reflect the actual measurement accuracy of the scanner. The existing technology mainly has the following problems and shortcomings: Incomplete data: Most of the current accuracy verification is only carried out under limited test conditions, lacking comprehensive verification under different distances, ranges and complex environments; The selection of parameters is highly subjective: There is currently no specific reference for parameter selection. Users cannot choose the appropriate scanning distance and effective range according to specific accuracy requirements. They can only select subjectively based on experience and cannot judge whether the accuracy meets the requirements; The accuracy range provided by the manufacturer is vague: The manufacturer cannot provide a detailed accuracy gradient range, and can only provide accuracy data under a single condition, lacking the accuracy changes under multiple working conditions; Insufficient optimization: The existing technology fails to provide an effective method for optimizing scanning parameters, and it is difficult for users to adjust scanning parameters according to specific measurement requirements to achieve the required accuracy.

[0004] In summary, in existing three-dimensional scanning systems, the above-mentioned problems and shortcomings limit the accuracy and reliability of three-dimensional scanning technology in practical applications. Summary of the invention

[0005] The purpose of the present invention is to provide a method for determining a three-dimensional scanning distance and range under given accuracy conditions, aiming to solve the problem of limiting the accuracy reliability of existing three-dimensional scanning systems in practical applications.

[0006] To achieve the above-mentioned purpose, the present invention adopts a method for determining the distance and range of three-dimensional scanning under given accuracy conditions, comprising: performing an accuracy calibration test based on a three-dimensional scanner;

[0007] Identify the influence of scanning accuracy on scanning distance and range;

[0008] Scanning parameters are selected according to specific accuracy requirements.

[0009] Among them, the specific method of conducting accuracy calibration test based on 3D scanner is:

[0010] Based on the standard flat plate test, three-dimensional point cloud modeling of the standard flat plate was carried out using different scanning distances;

[0011] For each scanning distance, the distribution law of the standard flat plate size recognition accuracy at different positions is examined, and a distribution diagram of the recognition accuracy on the plane is drawn to complete the accuracy calibration test based on the 3D scanner.

[0012] Among them, the specific way to identify the influence of scanning accuracy on scanning distance and range is as follows:

[0013] After completing the accuracy calibration test based on the 3D scanner, the scanned data is registered into the computer in the form of a point cloud model and processed, and then the average point error is calculated;

[0014] The distribution law of recognition accuracy is drawn based on the calculation results of the average point error.

[0015] Among them, after completing the accuracy calibration test based on the 3D scanner, the scanned data is registered into the computer in the form of a point cloud model and data processing is performed, and then the specific method for calculating the average point error is as follows:

[0016] Taking the scanned data of a given site as an example, first find the center plate scanned at the site, and then find the The number of plates in each divergent direction is equal, and these plates are used as the selected calibration range;

[0017] Then, the four-side dimensions of all selected plates are measured in the point cloud model, and the difference between the dimensions and the actual measured dimensions is averaged to obtain the corresponding error of a point.

[0018] Repeat the above steps several times and average the errors obtained multiple times to get the average error of the points within a certain distance range to eliminate accidental errors.

[0019] Among them, by repeating the above steps for multiple times and averaging the errors obtained for multiple times, the average error of the points within a certain distance can be obtained to eliminate accidental errors. The steps are repeated for no less than 10 times.

[0020] Among them, according to the calculation results of the average point error, the recognition accuracy distribution shows the following law:

[0021] As the distance increases, the accuracy of all points within the range, the density of the point cloud and the overall accuracy will decrease overall; at a fixed distance, the accuracy of the points extending from the center to the outside will form a gradient, and the overall trend is that the accuracy is high in the middle and the accuracy is lower as it approaches the edge of the range.

[0022] Among them, the specific method of selecting scanning parameters according to specific accuracy requirements is:

[0023] After determining the accuracy gradient within the range, the user can select scanning parameters according to the specific accuracy requirements;

[0024] In the selected accuracy gradient range, the range that meets the accuracy requirements is defined as the effective range.

[0025] The present invention provides a method for determining the three-dimensional scanning distance and range under given accuracy conditions. Through systematic calibration tests and detailed data analysis, the accuracy of the three-dimensional scanner within a specified range at different distances is determined, and reliable scanning parameter selection is provided. It is applicable to three-dimensional scanners of various models and brands, and users can flexibly select scanning parameters according to accuracy requirements, and is widely used in fields such as building measurement, industrial inspection, and cultural heritage protection. The present invention avoids the subjectivity and blindness of scanning parameter selection through a scientific parameter selection method, while improving the work efficiency of the scanning operation. Multiple tests and data averaging processing reduce accidental errors, provide comprehensive data, enable users to intuitively understand the law of accuracy changes, accurately control the scanning range, and ensure the accuracy and reliability of the scanning results. The present invention clarifies the influencing factors and laws of scanning accuracy, optimizes the scanning process, further improves the accuracy of the results, and solves the problem of limiting the accuracy and reliability of the existing three-dimensional scanning system in practical applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 It is a design drawing of a test model of the present invention.

[0028] Figure 2 The present invention Schematic diagram of the selection and missing positions of the glyph measurement board.

[0029] Figure 3 This is a distribution diagram of average station accuracy at different distances of the present invention.

[0030] Figure 4It is a schematic diagram of selecting cases according to the accuracy range of the present invention. DETAILED DESCRIPTION

[0031] Embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, but should not be construed as limiting the present invention.

[0032] See also Figure 1 to Figure 4 ,in Figure 1 It is the design drawing of the test model of the present invention, Figure 2 The present invention Schematic diagram of the selection and missing of the font measurement board position. Figure 3 is the average station accuracy distribution diagram at different distances of the present invention, Figure 4 The present invention provides a method for determining a three-dimensional scanning distance and range under given accuracy conditions, comprising the following steps:

[0033] S101, precision calibration test based on 3D scanner;

[0034] For this specific implementation, based on the standard flat plate test, three-dimensional point cloud modeling is performed on the standard flat plate using different scanning distances;

[0035] For each scanning distance, the distribution law of standard plate size recognition accuracy at different positions is investigated, and the distribution diagram of recognition accuracy on the plane is drawn to complete the accuracy calibration test based on the 3D scanner; in order to reduce the interference of accidental errors, the recognition accuracy here is usually the average value of multiple tests, and the number of tests is recommended to be no less than 10;

[0036] See also Figure 1 , the center of each standard plate in the middle row will be used as the point of vertical incidence of the scanner, so that the obtained standard plate model data is evenly symmetrical from top to bottom; the user first determines the approximate scanning distance and distance segmentation according to his own needs, such as 1m, 2m, and 3m segments, to suit scanned objects of different sizes; secondly, at each segmented distance, the scanner is ordered to collect data in turn facing all the standard plates in the middle row; at this point, the data collection stage is completed.

[0037] S102, identifying the influence of scanning accuracy on scanning distance and range;

[0038] According to this specific implementation, after completing the accuracy calibration test based on the three-dimensional scanner, the scanned data is registered into the computer in the form of a point cloud model and data processing is performed, and then the average point position error is calculated;

[0039] The distribution law of recognition accuracy is drawn based on the calculation results of the average point error.

[0040] In this process, after completing the accuracy calibration test based on the 3D scanner, the scanned data is registered into the computer in the form of a point cloud model and processed. The specific method for calculating the average point error is as follows:

[0041] Taking the scanned data of a given site as an example, first find the center plate scanned at the site, and then find the The number of plates in each divergent direction is equal, and these plates are used as the selected calibration range;

[0042] Then, the four-side dimensions of all selected plates are measured in the point cloud model, and the difference between the dimensions and the actual measured dimensions is averaged to obtain the corresponding error of a point.

[0043] Repeat the above steps for no less than 10 times, and average the errors obtained multiple times to get the average error of the points within a certain distance to eliminate accidental errors. If the scanning center is close to the edge of the standard plate matrix, there will be In the case of missing shape, such as Figure 2 As shown, in this case The plates that are not missing in the shape can also be used as objects of average error;

[0044] According to the calculation results of the average point error, the recognition accuracy distribution shows the following law:

[0045] As the distance increases, the accuracy of all points within the range, the density of the point cloud and the overall accuracy will decrease overall; at a fixed distance, the accuracy of the points extending from the center to the outside will form a gradient, and the overall trend is that the accuracy is high in the middle and the accuracy is lower as it approaches the edge of the range.

[0046] S103, selecting scanning parameters according to specific accuracy requirements;

[0047] For this specific implementation, after determining the accuracy gradient within the range, the user can select scanning parameters according to the specific accuracy requirements;

[0048] In the selected accuracy gradient range, the range that meets the accuracy requirements is defined as the effective range;

[0049] If the user has high accuracy requirements, it is recommended to select a site with a smaller distance. The reason is that the smaller the distance, the larger the accuracy gradient range that can meet the accuracy requirements. A position close to the scanning center can also be selected one level farther away, so that the scanning range is wider, but the effective range will decrease accordingly, so more sites are needed; if the selected accuracy requirements are lower, it is recommended to select a site with a larger distance. The reason is that the larger the distance, the more stable the accuracy error within the effective range and the wider range can be scanned, improving the overall scanning efficiency.

[0050] For example:

[0051] In this case, the Leica RTC360 3D scanner is used for precision calibration and parameter selection. The test materials are composed of a standard flat plate, a background white plate, and a 3D scanner to be calibrated. The test design uses standard plates with a size of 300mm×300mm and a thickness of 20mm. The plates are arranged in a 15×7 matrix. The vertical and horizontal spacing between each plate is 150mm to ensure that the plates are evenly distributed in the test range. The centroid of the standard plate in the middle row is used as the scanning center. By selecting the center position, it can be ensured that the scanning covers the entire test area and the symmetry and comprehensiveness of the data are guaranteed. In the test, four different scanning distances (1m, 2m, 3m, 4m) are set. At each distance, each standard plate in the middle row is scanned, so that data of 15 standard plates will be obtained at each meter, and finally 4×15=60 sets of data will be obtained.

[0052] These data record the scanner parameter settings and the point cloud data obtained by scanning for subsequent data processing and error analysis. Figure 1 The black plate in the figure is the standard plate that needs to be scanned at each meter. After scanning, the point cloud data of the standard plate will be obtained.

[0053] According to the above method, the standard plate error analysis is carried out to obtain the error of each meter. The average accuracy distribution diagram of the shape is as follows: Figure 3 As shown; overall, the average error increases with the increase of distance, and the accuracy decreases accordingly; the range error near the center varies greatly, and the error decreases by about 1 to 1.5 mm for every increase of 1 m in distance; while the regional error near the edge varies less; from a single distance, when the distance is 1 m, the accuracy fluctuation from the center board to the edge in the range is large, from the minimum error of 1.41 mm to the maximum error of 4.94 mm; when the distance is 4 m, the error of all boards in the range is maintained at about 5 mm, and it can be seen that the accuracy fluctuation is small.

[0054] Select cases based on range of precision:

[0055] ①If the user requires an accuracy of about 2mm:

[0056] You can choose the second accuracy gradient at a distance of 1m, such as Figure 4 (a) The area within the white frame is a square with a side length of 1.20 m.

[0057] ②If the user requires an accuracy of about 3mm:

[0058] The third accuracy gradient at a distance of 1m can be selected, such as Figure 4 (a) The area within the black frame is a square with a side length of 1.95 m.

[0059] You can also choose a second accuracy gradient at a distance of 2m, such as Figure 4 (b) The range within the white frame is a square with a side length of 1.20 m.

[0060] ③If the user's accuracy requirement is around 4mm:

[0061] The fourth accuracy gradient at a distance of 2m can be selected, such as Figure 4 (b) The range within the black frame is a square with a side length of 2.85m.

[0062] ④If the user's accuracy requirement is around 5mm:

[0063] The fourth accuracy gradient at a distance of 3m can be selected, such as Figure 4 (c) The range within the black frame is a square with a side length of 2.85m.

[0064] A method for determining the three-dimensional scanning distance and range under given accuracy conditions is used in this embodiment. Through systematic calibration tests and detailed data analysis, the accuracy of the three-dimensional scanner within a specified range at different distances is determined, providing reliable scanning parameter selection; it is applicable to three-dimensional scanners of various models and brands, and users can flexibly select scanning parameters according to accuracy requirements, and is widely used in fields such as building measurement, industrial inspection, and cultural heritage protection; the present invention avoids the subjectivity and blindness of scanning parameter selection through a scientific parameter selection method, while improving the work efficiency of the scanning operation, and multiple tests and data averaging processing reduce accidental errors, provide comprehensive data, enable users to intuitively understand the law of accuracy changes, accurately control the scanning range, and ensure the accuracy and reliability of the scanning results. The present invention clarifies the influencing factors and laws of scanning accuracy, optimizes the scanning process, further improves the accuracy of the results, and solves the problem of limiting the accuracy and reliability of the existing three-dimensional scanning system in practical applications.

[0065] What is disclosed above is only a preferred embodiment of the present invention, and it certainly cannot be used to limit the scope of rights of the present invention. Ordinary technicians in this field can understand that all or part of the processes of the above embodiment and equivalent changes made according to the claims of the present invention still fall within the scope of the invention.

Claims

1. A method for determining the distance and range of three-dimensional scanning under given accuracy conditions, characterized in that: include: Conduct precision calibration tests based on 3D scanners; Identify the influence of scanning accuracy on scanning distance and range; Scanning parameters are selected according to specific accuracy requirements.

2. The method for determining the distance and range of three-dimensional scanning under given accuracy conditions as claimed in claim 1, characterized in that: The specific method of conducting precision calibration test based on 3D scanner is as follows: Based on the standard flat plate test, three-dimensional point cloud modeling of the standard flat plate was carried out using different scanning distances; For each scanning distance, the distribution law of the standard flat plate size recognition accuracy at different positions is examined, and a distribution diagram of the recognition accuracy on the plane is drawn to complete the accuracy calibration test based on the 3D scanner.

3. The method for determining the distance and range of three-dimensional scanning under given accuracy conditions as claimed in claim 2, characterized in that: The specific way to identify the influence of scanning accuracy on scanning distance and range is as follows: After completing the accuracy calibration test based on the 3D scanner, the scanned data is registered into the computer in the form of a point cloud model and processed, and then the average point error is calculated; The distribution law of recognition accuracy is drawn based on the calculation results of the average point error.

4. The method for determining the distance and range of three-dimensional scanning under given accuracy conditions as claimed in claim 3, characterized in that: After completing the accuracy calibration test based on the 3D scanner, the scanned data is registered into the computer in the form of a point cloud model and processed. The specific method for calculating the average point error is as follows: Taking the scanned data of a given site as an example, first find the center plate scanned at the site, and then find the The number of plates in each divergent direction is equal, and these plates are used as the selected calibration range; Then, the four-side dimensions of all selected plates are measured in the point cloud model, and the difference between the dimensions and the actual measured dimensions is averaged to obtain the corresponding error of a point. Repeat the above steps several times and average the errors obtained multiple times to get the average error of the points within a certain distance range to eliminate accidental errors.

5. The method for determining the distance and range of three-dimensional scanning under given accuracy conditions as claimed in claim 4, characterized in that: After repeating the above steps for multiple times, the errors obtained multiple times are averaged to obtain the average error of the points within a certain distance range to eliminate accidental errors. The steps are repeated for no less than 10 times.

6. The method for determining the distance and range of three-dimensional scanning under given accuracy conditions as claimed in claim 5, characterized in that: According to the calculation results of the average point error, the recognition accuracy distribution shows the following law: As the distance increases, the accuracy of all points within the range, the density of the point cloud and the overall accuracy will decrease overall; at a fixed distance, the accuracy of the points extending from the center to the outside will form a gradient, and the overall trend is that the accuracy is high in the middle and the accuracy is lower as it approaches the edge of the range.

7. The method for determining the distance and range of three-dimensional scanning under given accuracy conditions as claimed in claim 6, characterized in that: The specific method for selecting scanning parameters according to specific accuracy requirements is: After determining the accuracy gradient within the range, the user can select scanning parameters according to the specific accuracy requirements; In the selected accuracy gradient range, the range that meets the accuracy requirements is defined as the effective range.

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