Three-dimensional imaging method and device based on calibration block, electronic equipment and medium

Abstract

The invention relates to the technical field of three-dimensional imaging, and provides a three-dimensional imaging method and device based on a calibration block, related equipment and a medium. The method comprises the following steps: scanning a calibration block at a set position under a target scanning attitude to obtain a calibration block laser point cloud distribution diagram set; in the target scanning attitude, scanning a target object at a set position to obtain a target object laser point cloud distribution map set; and generating a three-dimensional model of the target object according to the target scanning attitude and the target object laser point cloud distribution map set. The target scanning posture of the scanning device is determined through the calibration block, and it is guaranteed that the point cloud data of the target object can be completely and accurately obtained. And performing coordinate conversion on the laser point cloud distribution map set of the target object to the global coordinate system corresponding to the calibration block to obtain target object laser point cloud data of the target object, thereby generating a three-dimensional model. The problem that traditional three-dimensional imaging needs to depend on an external device to establish a coordinate system and cannot change the attitude is solved.

Description

Technical Field

[0001] The present application relates to the field of three-dimensional imaging technology, and in particular to a three-dimensional imaging method, device, electronic device and medium based on a calibration block. Background Art

[0002] Existing 3D line laser scanning equipment can quickly generate high-resolution data point clouds, which are then merged into a coherent 3D model through specific processing to provide real-time 3D imaging.

[0003] However, in the existing processing scheme, 3D line laser scanning equipment needs to rely on third-party devices to establish a three-dimensional coordinate system to process the data point cloud. The processing process requires very complex three-dimensional operations, and the data of multiple 3D sensors with different postures need to be spatially converted and placed in the same three-dimensional coordinate system. The establishment of this three-dimensional coordinate system cannot be realized if there is no device that can provide a precise spatial coordinate system in the application scenario. 3D line laser scanning equipment relies on external devices to provide a three-dimensional coordinate system, resulting in the 3D line laser scanning equipment Once the posture is determined, it cannot be changed. If it needs to be changed, cumbersome operations must be performed. Summary of the invention

[0004] In view of this, the embodiments of the present application provide a three-dimensional imaging method, system and storage medium based on a calibration block, which can solve the problem that the 3D line laser scanning device relies on external devices to provide a three-dimensional coordinate system and cannot change its posture.

[0005] In a first aspect, the present application provides a three-dimensional imaging method based on a calibration block, the method comprising: Under the target scanning posture, the calibration block at the set position is scanned to obtain a set of laser point cloud distribution maps of the calibration block; Under the target scanning posture, scanning the target object at the set position to obtain a set of laser point cloud distribution maps of the target object; A three-dimensional model of the target object is generated according to the target scanning posture and the target object laser point cloud distribution map set.

[0006] In an optional embodiment, the method further comprises: In a first scanning posture, scanning the calibration block at the set position to obtain a first laser point cloud distribution map set; Determining whether the first laser point cloud distribution map set matches a preset calibration block drawing; When the first laser point cloud distribution map set matches the preset calibration block drawing, the first scanning posture is determined as the target scanning posture.

[0007] In an optional implementation, the determining whether the first laser point cloud distribution map set matches a preset calibration block drawing includes: Determining a calibration area of ​​the calibration block according to the first laser point cloud distribution map set; Obtain a laser point cloud distribution map having the same calibration block area; Calculating the matching degree between the laser point cloud distribution map of the same calibration block area and the corresponding calibration block area in the preset calibration block drawing; Determining whether the matching degree is less than a preset matching degree threshold; When the matching degree is less than or equal to the preset matching degree threshold, it is determined that the laser point cloud distribution map of the same calibration block area is successfully matched with the corresponding calibration block area in the preset calibration block drawing; When the matching degree is greater than the preset matching degree threshold, it is determined that the laser point cloud distribution map of the same calibration block area fails to match the corresponding calibration block area in the preset calibration block drawing.

[0008] In an optional embodiment, the method further comprises: When the first laser point cloud distribution map set does not match the preset calibration block drawing, adjusting the first scanning posture to a second scanning posture; Controlling the scanning device to scan the calibration block at the set position in the second scanning posture to obtain a second laser point cloud distribution map set; Determining whether the second laser point cloud distribution map set matches the preset calibration block drawing; When the second laser point cloud distribution map set matches the preset calibration block drawing, the second scanning posture is determined as the target scanning posture.

[0009] In an optional embodiment, generating a three-dimensional model of the target object according to the target scanning posture and the target object laser point cloud distribution map set includes: Performing coordinate transformation on the target object laser point cloud distribution map set according to the target scanning posture to obtain the target object laser point cloud data; Point cloud fusion is performed according to the laser point cloud data of the target object to obtain a three-dimensional model of the target object.

[0010] In an optional embodiment, the step of performing coordinate transformation on the target object laser point cloud distribution map set according to the scanning posture to obtain the target object laser point cloud data includes: Acquire the local three-dimensional coordinate system of each laser point cloud distribution map in the laser point cloud distribution map set of the target object; Obtaining a global three-dimensional coordinate system corresponding to the calibration block; The coordinate points of each laser point cloud distribution map are converted to the global three-dimensional coordinate system according to the local three-dimensional coordinate system to obtain the laser point cloud data of the target object in the global three-dimensional coordinate system.

[0011] In an optional embodiment, the method further comprises: When the scanning posture of the scanning device is updated, the three-dimensional model of the target object is regenerated according to the updated scanning posture.

[0012] In a second aspect, the present application provides a three-dimensional imaging device based on a calibration block, the device comprising: The first control module is used to scan the calibration block at a set position under the target scanning posture to obtain a set of laser point cloud distribution maps of the calibration block.

[0013] The second control module is used to scan the target object at the set position under the target scanning posture to obtain a set of laser point cloud distribution maps of the target object.

[0014] The model generation module is used to generate a three-dimensional model of the target object according to the target scanning posture and the target object laser point cloud distribution map set.

[0015] In a third aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the calibration block-based three-dimensional imaging method when executing the computer program.

[0016] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the calibration block-based three-dimensional imaging method are implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flow chart of a three-dimensional imaging method based on a calibration block shown in an embodiment of the present application; Figure 2 It is a functional module diagram of a three-dimensional imaging device based on a calibration block shown in an embodiment of the present application; Figure 3 It is a structural diagram of an electronic device shown in an embodiment of the present application. DETAILED DESCRIPTION

[0018] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0019] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0020] In the existing related technical solutions, the 3D point cloud data splicing solution usually involves the following steps: First, data is collected through 3D line laser scanning equipment to collect point clouds of objects or environments from different positions and angles. The collected point cloud data is filtered, denoised and outliers are removed to improve the quality of the data. The point cloud data from different scanning angles are then registered, that is, a common reference frame is found between different data sets. The registration process requires manual selection of control points or relies on the iterative closest point (ICP) algorithm. After registration, the point cloud data sets are fused or spliced ​​together through point cloud fusion. The fused point cloud data is smoothed to remove artifacts or repeated information generated during the splicing process, optimize data representation and reduce data volume. Finally, the spliced ​​point cloud data can be used to generate a continuous three-dimensional surface model through polygonization or surface reconstruction algorithms.

[0021] In the existing technical solutions, if you want to achieve a good stitching effect, you need to perform very complex three-dimensional operations. Among them, it is easy to cause the loss of real image data in the process of removing noise and smoothing, and it may affect the stitching accuracy. In addition, a common spatial coordinate system is required to spatially transform the data of multiple 3D sensors in different postures and place them in the same coordinate system. The selection of this common coordinate system will bring many uncertainties to practical applications and increase the difficulty of implementation. First of all, the establishment of a common coordinate system requires the assistance of other physical positioning to ensure the position accuracy of the coordinate system and confirm the coordinate origin. If there is no device that can provide an accurate spatial coordinate system in the application scenario, it cannot be achieved, and it is necessary to know the exact position relationship between the coordinate system of each sensor and the common coordinate system. Secondly, the accuracy of the coordinate system depends on the accuracy of the device that provides the coordinate system, so the final stitching accuracy will be subject to the accuracy of the device that provides the coordinate system. And because the coordinate system depends on the provision of external devices, it cannot be changed once it is determined. If it needs to be changed, cumbersome operations must be performed.

[0022] In order to solve the above-mentioned technical problems, an embodiment of the present application provides a three-dimensional imaging method based on a calibration block, which solves the problem that the 3D line laser scanning device relies on an external device to provide a three-dimensional coordinate system and cannot change its posture.

[0023] See also Figure 1 As shown, it is a flow chart of a three-dimensional imaging method based on a calibration block shown in an embodiment of the present application. The three-dimensional imaging method based on a calibration block specifically includes the following steps.

[0024] In the three-dimensional imaging method based on the calibration block, it is first necessary to determine the set position scanned by the laser scanning network and the target scanning posture of the laser scanning network, and the method includes: In a first scanning posture, scanning the calibration block at the set position to obtain a first laser point cloud distribution map set; Determining whether the first laser point cloud distribution map set matches a preset calibration block drawing; When the first laser point cloud distribution map set matches the preset calibration block drawing, the first scanning posture is determined as the target scanning posture.

[0025] The first scanning posture refers to the specific position and scanning direction of each scanning device when the laser scanning network performs the first scan. The scanning device may include laser scanning instruments such as laser scanners and three-dimensional scanning devices. The laser scanning network is a scanning network composed of multiple scanning instruments according to the scanning requirements. The higher the scanning requirements, the more scanning devices the laser scanning network consists of. In this application, the laser scanning network refers to a scanning network composed of at least two or more scanning devices.

[0026] The calibration block drawing is a 3D model drawing of the calibration block designed based on the specific position and scanning direction of each scanning device. The calibration block drawing may include geometric information and feature information of the calibration block. For example, in a calibration block drawing, the geometric information included is a block, and the feature information included may be the size of the block.

[0027] The calibration block is a physical entity made of stainless steel based on the calibration block drawing, which can be used as a calibration tool for laser scanning measurement. The calibration block has precise geometric shape and specific size, and can be used as a precise reference point in scanning to generate a global coordinate system. At the same time, the calibration block is made of stainless steel, so that the surface of the calibration block has a good reflective effect, which can ensure that in the specific implementation of the calibration block, more accurate calibration block point cloud data can be obtained through laser scanning. The set position refers to the position area used to obtain the object or calibration block when scanning. During the first scan, the set position in the laser scanning network will be determined to ensure that the subsequent scanning process can accurately obtain the point cloud data of the calibration block.

[0028] The first laser point cloud distribution map set refers to a set of laser point cloud distribution maps obtained by each scanning device scanning the calibration block in the first scanning posture. The laser point cloud refers to a set of three-dimensional coordinate points obtained by scanning an object with a laser scanning device. The surface shape and structure of the scanning area can be accurately described in space through the set of three-dimensional coordinate points. For example, (1, 0, 0), (1, 1, 0), (1, 1, 1), (1, 0, 1) can represent a square plane in a three-dimensional space coordinate system. The laser point cloud distribution map is a visualization of the point cloud data obtained in the three-dimensional space coordinate system in the local coordinate system of each scanning device.

[0029] After setting the first scanning posture of the laser scanning network, scan the calibration block at the set position. Each scanning device obtains the laser point cloud distribution map of the corresponding angle through the corresponding scanning direction at the corresponding special position, and all the obtained laser point cloud distribution maps constitute a set of laser point cloud distribution maps. Pattern matching is performed on each laser point cloud distribution map in the laser point cloud distribution map set and the calibration block drawing. The degree of matching between each laser point cloud distribution map and the calibration block drawing in the same area is used to determine whether the matching between the laser point cloud distribution map set and the calibration block drawing is successful. If each laser point cloud distribution map successfully matches the calibration block drawing in the same area, then under the first scanning posture, through the special position and scanning direction of each scanning device, the complete calibration block laser point cloud distribution map set at the set position can be accurately obtained. Then the first scanning posture is the target scanning posture.

[0030] In an optional implementation, the determining whether the first laser point cloud distribution map set matches a preset calibration block drawing includes: Determining a calibration area of ​​the calibration block according to the first laser point cloud distribution map set; Obtain a laser point cloud distribution map having the same calibration block area; Calculating the matching degree between the laser point cloud distribution map of the same calibration block area and the corresponding calibration block area in the preset calibration block drawing; Determining whether the matching degree is less than a preset matching degree threshold; When the matching degree is greater than or equal to the preset matching degree threshold, it is determined that the laser point cloud distribution map of the same calibration block area is successfully matched with the corresponding calibration block area in the preset calibration block drawing; When the matching degree is less than the preset matching degree threshold, it is determined that the laser point cloud distribution map of the same calibration block area fails to match the corresponding calibration block area in the preset calibration block drawing.

[0031] The calibration area of ​​the calibration block refers to the specific area divided on the surface of the calibration block. The surface of the entire calibration block is composed of specific areas. Each laser point cloud distribution map that can be obtained through the laser scanning network can contain one or more calibration areas, and the positional relationship between different laser point cloud distribution maps can be determined by different laser point cloud distribution maps with the same calibration area. The matching degree is used to measure the similarity between the laser point cloud distribution map and the calibration area in the calibration block drawing. The higher the matching degree, the higher the similarity between the laser point cloud distribution map and the calibration block drawing, and the more accurate the laser point cloud data obtained.

[0032] In this application, the matching degree between the laser point cloud distribution map and the calibration block drawing is mainly calculated by the template matching algorithm, wherein the template matching algorithm is a method for finding and locating specific patterns or objects in image or point cloud data. In the scenario where the laser point cloud distribution map is matched with the calibration block drawing, the feature information of the feature points of the calibration block drawing and the laser point cloud distribution map is extracted by the template matching algorithm, wherein the feature point refers to the laser point of the calibration area of ​​the calibration block, and the feature information is the number and distribution of the laser points in the calibration area. The feature information of the two is generated into a feature descriptor by the template matching algorithm, wherein the feature descriptor can be represented by a number or a vector, and the feature descriptors of the two are calculated by the similarity measurement method to obtain the same feature points of the feature information, and the matching degree of the laser point cloud distribution map and the calibration block drawing is determined according to the ratio of the number of the same feature points to the total number of feature points. For example, suppose that the template matching algorithm is used to extract feature points and feature information from the laser point cloud distribution map and the calibration block drawing, and the feature points in the laser map are matched with the feature points in the calibration block drawing. The number of successfully matched feature points is 100, and the total number of feature points is 120. The matching degree is the ratio of successfully matched feature points to the total number of feature points, that is, 100 / 120 = 83.33%.

[0033] The preset matching degree threshold is used to determine whether the matching degree between the laser point cloud distribution map and the calibration block drawing in the calibration area meets the required matching standard. The preset matching degree threshold can be expressed as a percentage. When the matching degree between the laser point cloud distribution map and the calibration block drawing in a certain calibration area is greater than the preset matching degree threshold, the laser point cloud distribution map and the calibration block drawing are successfully matched in the calibration area. For example, when the laser scanning network obtains each laser point cloud distribution map and the calibration block drawing for matching, assuming that the preset matching degree threshold is set to 95%, assuming that a certain calibration area contains a set of corner points and edges of a specific shape in the calibration block drawing, and the laser point cloud distribution map also contains similar corner points and edges. The matching degree calculated by the pattern matching algorithm is 98%, which is greater than the preset matching degree threshold of 95%. It can be considered that the laser point cloud distribution map and the calibration block drawing are successfully matched in the calibration area.

[0034] After the laser scanning network obtains the first laser point cloud distribution map, the calibration block is divided into calibration areas according to different feature information of the calibration block obtained by the first laser point cloud distribution map. The laser point cloud distribution maps with the same calibration area are obtained, and these laser point cloud distribution maps are matched in the same calibration area through the template matching algorithm, and the matching degree between different laser point cloud distribution maps in the same calibration area and the calibration block drawings is obtained, and the matching degree is compared with the preset matching degree threshold. When the matching degree is greater than or equal to the preset matching degree threshold, the first laser point cloud distribution map and the calibration block drawings in the calibration area are successfully matched. When the matching degree is less than the preset matching degree threshold, the first laser point cloud distribution map and the calibration block drawings in the calibration area fail to match. The matching degree of each laser point cloud distribution map in the first laser point cloud distribution map set and the calibration block drawings in the corresponding calibration area is obtained, and each matching degree obtained is compared with the preset matching degree threshold. When all matching degrees are greater than the preset matching degree threshold, the first laser point cloud distribution map set is successfully matched with the calibration block drawings. That is, the laser point cloud distribution map acquired by each scanning device in the laser scanning network accurately corresponds to the calibration block drawing, and the first laser point cloud distribution map set accurately contains all point cloud data of the calibration block, then the three-dimensional image of the calibration block can be completely acquired according to the first laser point cloud distribution map set; when there is at least one matching degree less than a preset matching degree threshold, the first laser cloud point distribution map and the calibration block drawing fail to match in the corresponding calibration area, then there is an error between the first laser point cloud distribution map and the calibration block drawing, and the three-dimensional image of the calibration block cannot be accurately acquired through the first laser point cloud distribution map set.

[0035] In this embodiment, by determining the calibration area of ​​the calibration block, and matching the laser point cloud distribution map with the calibration block drawing according to the calibration area, the matching area can be positioned more accurately and conveniently. The matching degree between the laser point cloud distribution map and the calibration block drawing of each calibration block area can be obtained through the template matching algorithm. If the matching degree is lower than the preset matching degree threshold, the calibration area where the matching fails can be quickly obtained to perform the corresponding first posture adjustment, thereby improving the efficiency of accurately obtaining the accurate three-dimensional image of the calibration block. At the same time, through the automatic matching of the calibration area, the matching accuracy and matching efficiency of the laser point cloud distribution map set and the calibration block drawing are improved, and the accuracy of the laser scanning network in obtaining the three-dimensional image of the calibration block can be improved.

[0036] In an optional embodiment, the method further comprises: When the first laser point cloud distribution map set does not match the preset calibration block drawing, adjusting the first scanning posture to a second scanning posture; Controlling the scanning device to scan the calibration block at the set position in the second scanning posture to obtain a second laser point cloud distribution map set; Determining whether the second laser point cloud distribution map set matches the preset calibration block drawing; When the second laser point cloud distribution map set matches the preset calibration block drawing, the second scanning posture is determined as the target scanning posture.

[0037] When matching the first laser point cloud distribution map set with the calibration block drawing, if the first laser point cloud distribution map set does not match the calibration block drawing, that is, there is at least one laser point cloud distribution map in the first laser point cloud distribution map set that does not match the calibration block drawing, and among the unmatched laser point cloud distribution maps, there is at least one laser point cloud distribution map corresponding to the calibration area whose matching degree with the calibration block drawing is less than a preset matching degree threshold. The corresponding laser point cloud distribution map and scanning device can be obtained according to the calibration area, and the specific position or scanning angle of the corresponding scanning device can be adjusted according to the reason for the mismatch. If there are multiple laser point cloud distribution maps that do not match the calibration block drawing, the specific positions or scanning angles of the multiple scanning devices are adjusted. That is, the first scanning posture of the laser scanning network is adjusted to the second scanning posture.

[0038] The calibration block is scanned again with a second scanning posture through the laser scanning network, and a second laser point cloud distribution map of the calibration block under the second scanning posture is obtained. The second laser point cloud distribution map set is matched with the calibration block drawing again. When the second laser point cloud distribution map set matches the calibration block drawing, the second scanning posture is the target scanning posture. If the second laser point cloud distribution map set still does not match the calibration block drawing, the scanning device is adjusted again according to the unmatched calibration area until the obtained laser point cloud distribution map set matches the calibration block drawing.

[0039] In the present application, when the first laser point cloud distribution map set does not match the calibration block drawing, a calibration area with insufficient matching degree can be obtained, and the corresponding scanning device can be obtained through the calibration area, and the scanning device posture information can be quickly obtained and changed. According to the actual situation of the first laser point cloud distribution map and the calibration block drawing matching in the calibration area, precise adjustment is performed to optimize the calibration effect and speed up the adjustment efficiency. The calibration area where the matching degree of the first laser point cloud distribution map set and the calibration block drawing is less than the preset matching degree threshold is obtained, and the second scanning posture matching the first laser point cloud distribution map set and the calibration block drawing is obtained by adjusting the posture information of the scanning device corresponding to each calibration area. By adjusting the scanning device corresponding to the calibration area, the adjustability of the overall laser scanning network is enhanced, and it can adapt to a variety of different working environments. By adjusting the scanning posture corresponding to the scanning device and performing multiple scans, the matching degree of the laser point cloud distribution map set obtained by the scanning device and the calibration block drawing is improved, and a more accurate laser point cloud distribution map set can be obtained. At the same time, the posture information of the laser scanning network is continuously optimized to obtain the target scanning posture.

[0040] S11, scanning the calibration block at the set position under the target scanning posture to obtain a set of laser point cloud distribution maps of the calibration block.

[0041] After determining the target scanning posture of the laser scanning network, the laser scanning network scans the calibration block at the set position in the target scanning posture, and obtains a complete set of calibration block laser point cloud distribution maps through the specific position angle and scanning direction of each scanning device under the target scanning posture.

[0042] The calibration block laser point cloud distribution map set contains the feature information of all angles of the calibration block. Through the calibration block laser point cloud distribution map set, the calibration block can be used to establish a three-dimensional coordinate system with the calibration block as the origin, and each calibration block laser point cloud distribution map is represented in the three-dimensional coordinate system. It can be used to mark a three-dimensional coordinate system. Compared with the existing technical solutions, there is no need to establish a three-dimensional coordinate system according to the equipment in the application scenario. The three-dimensional coordinate system is established by acquiring the calibration block laser point cloud distribution map set through the target scanning posture, which improves the applicability of the laser scanning network and can achieve the acquisition of the calibration block laser point cloud distribution map set in a variety of different scenarios to generate a three-dimensional coordinate system.

[0043] S12, scanning the target object at the set position under the target scanning posture to obtain a set of laser point cloud distribution maps of the target object.

[0044] After determining the target scanning posture of the laser scanning network, the laser scanning network scans the target object at the set position in the target scanning posture, and obtains a complete set of target object laser point cloud distribution maps through the specific position angle and scanning direction of each scanning device under the target scanning posture.

[0045] There may be some feature information gaps between the target object and the calibration block, such as some corners of specific shapes, different edge lengths, and some grooves on the surface. By placing the target object at a set position, it is possible to obtain a complete target object laser point cloud distribution map set of the target object under the target scanning posture. And because the target object and the calibration block are both at the set position, and the laser scanning network is scanned with the same target posture, that is, the target object laser point cloud distribution map set of the target object and the calibration block laser point cloud distribution map set of the calibration block have a spatial set correspondence relationship.

[0046] S13, generating a three-dimensional model of the target object according to the target scanning posture and the target object laser point cloud distribution map set.

[0047] A three-dimensional coordinate system can be established through the set of laser point cloud distribution maps of the calibration block obtained under the target scanning posture, and a model of the calibration block can be established in the three-dimensional coordinate system using the laser point cloud distribution map of each calibration block. Through the set of laser point cloud distribution maps of the target object obtained under the target scanning posture, the position relationship between the target object and the calibration block can be used to represent the set of laser point cloud distribution maps of the target object in the three-dimensional coordinate system of the calibration block. According to the matching relationship of the calibration area in the calibration block, the coordinate transformation of the laser point cloud distribution of the target object is performed, and the converted data point cloud distribution is used to build a three-dimensional model of the target object according to the model of the calibration block to generate a three-dimensional model of the target object.

[0048] In an optional embodiment, generating a three-dimensional model of the target object according to the target scanning posture and the target object laser point cloud distribution map set includes: Performing coordinate transformation on the target object laser point cloud distribution map set according to the scanning posture to obtain target object laser point cloud data; Point cloud fusion is performed according to the laser point cloud data of the target object to obtain a three-dimensional model of the target object.

[0049] Coordinate transformation refers to the process of converting the corresponding three-dimensional coordinates of the laser point cloud distribution map of the target object obtained in the scanning device to the three-dimensional coordinate system corresponding to the calibration block. Point cloud fusion is a technology that integrates data from multiple laser point clouds into a single complete three-dimensional model, including point cloud registration, fusion and surface reconstruction. Registration is to register the laser point cloud data of the target object and align them in the global coordinate system through feature matching. Fusion refers to merging the registered point cloud data and integrating them into a complete point cloud model. Reconstruction refers to surface reconstruction of the fused point cloud data to obtain the surface model of the target object, convert the point cloud data into a surface mesh, and finally optimize the surface mesh, such as removing noise points, filling surface holes, etc., and finally obtain the three-dimensional model of the target object through smoothing.

[0050] After obtaining the set of laser point cloud distribution maps of the target object, obtain the point cloud distribution data of each laser point cloud distribution map, convert the point cloud distribution data of each scanning device to the three-dimensional coordinate system of the calibration block through coordinate conversion, and represent each laser point cloud distribution data through the three-dimensional coordinate system of the calibration block to obtain the laser point cloud data of the target object in the three-dimensional coordinate system of the calibration block. Then perform point cloud fusion on the laser point cloud data of the target object. First, align the laser point cloud data of the target object so that they are aligned in the three-dimensional coordinate system of the calibration block. Then, fuse and merge the registered laser point cloud data of the target object to obtain a complete point cloud model. Perform surface reconstruction on the complete point cloud model to obtain the surface model of the target object. Finally, optimize the surface model of the target object to obtain the three-dimensional model of the target object.

[0051] Through the matching relationship between the target laser distribution map set and the calibration block drawing in the calibration area, the laser point cloud data obtained by the laser scanning network is accurately converted to the calibration block three-dimensional coordinate system, which solves the limitation that the traditional three-dimensional imaging method needs to rely on the device of the application scenario to provide an accurate spatial coordinate system. Point cloud fusion through the target object laser point cloud data can ensure that the generated three-dimensional model is more complete and will not be affected by the limited field of view of a single scanning device. It can obtain more comprehensive and accurate surface features of the target object and generate a more accurate three-dimensional model of the target object.

[0052] In an optional embodiment, the step of performing coordinate transformation on the target object laser point cloud distribution map set according to the scanning posture to obtain the target object laser point cloud data includes: Acquire the local three-dimensional coordinate system of each laser point cloud distribution map in the laser point cloud distribution map set of the target object; Obtaining a global three-dimensional coordinate system corresponding to the calibration block; The coordinate points of each laser point cloud distribution map are converted to the global three-dimensional coordinate system according to the local three-dimensional coordinate system to obtain the laser point cloud data of the target object in the global three-dimensional coordinate system.

[0053] The local coordinate system refers to the three-dimensional coordinate system of each scanning device itself, whose origin and coordinate axis direction are related to the specific position and scanning direction of the scanning device. The laser point cloud distribution map of each target object can be represented by the local coordinate system, and each laser point in the laser point cloud distribution map of the target object corresponds to different data on the local coordinate system. The global coordinate system refers to a three-dimensional coordinate system established based on the calibration block, whose origin is the set position center of the calibration block, and the coordinate axis direction is related to the target scanning posture. Coordinate point conversion refers to the process of converting the coordinate points of the local coordinate system to the global coordinate system through the translation and rotation transformation of the coordinates according to the position information and direction information of each local coordinate system. Among them, the position information refers to the physical position distance information of each scanning device and the calibration block, and the direction information refers to the scanning angle direction of each scanning device to the calibration block.

[0054] After obtaining the local 3D coordinate system of each scanning device and the global 3D coordinate system of the calibration block, the laser point data on each 3D coordinate system is displaced to the global 3D coordinate system through the position information. After the physical position distance is displaced, the reverse rotation is performed according to the direction information of each scanning device to obtain the accurate coordinates of each laser point in the global 3D coordinate system. Each laser point in the target object laser point cloud distribution map set is converted to the global 3D coordinate system to obtain the target object laser point cloud data.

[0055] In an optional real-time mode, the method further comprises: When the scanning posture of the scanning device is updated, the three-dimensional model of the target object is regenerated according to the updated scanning posture.

[0056] When the scanning posture of the laser scanning network is updated, the updated laser point cloud distribution map set of the calibration block at the set position is obtained, and the obtained updated laser point cloud distribution map set is re-matched with the calibration block drawing, and the updated target scanning posture is adjusted according to the matching result. The calibration block is re-scanned with the updated target scanning posture to obtain the updated calibration block laser point cloud distribution map set, and the updated global coordinate system is obtained. The target object is re-scanned with the updated target scanning posture to obtain the updated target object laser point cloud distribution map set, and the updated local coordinate system is obtained. The updated target object laser point cloud data is obtained by converting the target object laser point cloud data on the updated local coordinate system to the updated global coordinate system, and the shape and position of the calibration block are re-modeled for the updated target object laser point cloud data, and the new three-dimensional model of the target object under the updated posture is obtained through point cloud fusion.

[0057] In the present application, the scanning posture of the laser scanning network can be adjusted to update the acquired laser point cloud data, which enhances the adjustability of the laser scanning network and enables the laser scanning network to obtain three-dimensional images of the target object in more application scenarios. For example, if the target object moves in space, the traditional three-dimensional imaging method needs to re-design the three-dimensional coordinate system according to the position of the object movement and select the device in the application scenario. In the present application, the scanning posture of the laser scanning network is determined by moving the corresponding calibration block position, and the three-dimensional model of the target object is obtained through the determined scanning posture. Especially in some application scenarios that require real-time or dynamic updates, the three-dimensional imaging method based on the calibration block can better meet the use requirements.

[0058] The present application obtains a set of laser point cloud distribution maps of the calibration block by scanning a calibration block at a set position under a target scanning posture; obtains a set of laser point cloud distribution maps of the target object by scanning a target object at the set position under the target scanning posture; and generates a three-dimensional model of the target object according to the target scanning posture and the set of laser point cloud distribution maps of the target object. The present application determines the target scanning posture of the scanning device through a calibration block to ensure that the point cloud data of the target object can be completely and accurately acquired. The target object laser point cloud data of the target object is acquired by performing coordinate conversion of the laser point cloud distribution map set of the target object to the global coordinate system corresponding to the calibration block, thereby generating a three-dimensional model. This solves the problem that traditional three-dimensional imaging needs to rely on external devices to establish a coordinate system and cannot change the posture.

[0059] Figure 2 It is a functional module diagram of a three-dimensional imaging device based on a calibration block provided in an embodiment of the present application.

[0060] In some embodiments, the calibration block-based 3D imaging device 20 may include a plurality of functional modules composed of computer program segments. The computer programs of the various program segments in the calibration block-based 3D imaging device 20 may be stored in a memory of the calibration block-based 3D imaging device and executed by at least one processor to perform (see Figure 1 Description) Functionality of the calibration block-based 3D imaging method.

[0061] In this embodiment, the calibration block-based three-dimensional imaging device 20 can be divided into multiple functional modules according to the functions it performs. The functional modules can include: a first determination module 201, a second determination module 202, a first control module 203, a second control module 204, a model generation module 205 and a posture update module 206.

[0062] The module referred to in the present invention refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, and is stored in a memory.

[0063] The first determination module 201 is used to scan the calibration block at the set position in a first scanning posture to obtain a first laser point cloud distribution map set; determine whether the first laser point cloud distribution map set matches a preset calibration block drawing; when the first laser point cloud distribution map set matches the preset calibration block drawing, determine the first scanning posture as the target scanning posture.

[0064] The first scanning posture refers to the specific position and scanning direction of each scanning device when the laser scanning network performs the first scan. The scanning device may include laser scanning instruments such as laser scanners and three-dimensional scanning devices. The laser scanning network is a scanning network composed of multiple scanning instruments according to the scanning requirements. The higher the scanning requirements, the more scanning devices the laser scanning network consists of. In this application, the laser scanning network refers to a scanning network composed of at least two or more scanning devices.

[0065] The calibration block drawing is a 3D model drawing of the calibration block designed based on the specific position and scanning direction of each scanning device. The calibration block drawing may include geometric information and feature information of the calibration block. For example, in a calibration block drawing, the geometric information included is a block, and the feature information included may be the size of the block.

[0066] The calibration block is a physical entity made of stainless steel based on the calibration block drawing, which can be used as a calibration tool for laser scanning measurement. The calibration block has precise geometric shape and specific size, and can be used as a precise reference point in scanning to generate a global coordinate system. At the same time, the calibration block is made of stainless steel, so that the surface of the calibration block has a good reflective effect, which can ensure that in the specific implementation of the calibration block, more accurate calibration block point cloud data can be obtained through laser scanning. The set position refers to the position area used to obtain the object or calibration block when scanning. During the first scan, the set position in the laser scanning network will be determined to ensure that the subsequent scanning process can accurately obtain the point cloud data of the calibration block.

[0067] The first laser point cloud distribution map set refers to a set of laser point cloud distribution maps obtained by each scanning device scanning the calibration block in the first scanning posture. The laser point cloud refers to a set of three-dimensional coordinate points obtained by scanning an object with a laser scanning device. The surface shape and structure of the scanning area can be accurately described in space through the set of three-dimensional coordinate points. For example, (1, 0, 0), (1, 1, 0), (1, 1, 1), (1, 0, 1) can represent a square plane in a three-dimensional space coordinate system. The laser point cloud distribution map is a visualization of the point cloud data obtained in the three-dimensional space coordinate system in the local coordinate system of each scanning device.

[0068] After setting the first scanning posture of the laser scanning network, scan the calibration block at the set position. Each scanning device obtains the laser point cloud distribution map of the corresponding angle through the corresponding scanning direction at the corresponding special position, and all the obtained laser point cloud distribution maps constitute a set of laser point cloud distribution maps. Pattern matching is performed on each laser point cloud distribution map in the laser point cloud distribution map set and the calibration block drawing. The degree of matching between each laser point cloud distribution map and the calibration block drawing in the same area is used to determine whether the matching between the laser point cloud distribution map set and the calibration block drawing is successful. If each laser point cloud distribution map successfully matches the calibration block drawing in the same area, then under the first scanning posture, through the special position and scanning direction of each scanning device, the complete calibration block laser point cloud distribution map set at the set position can be accurately obtained. Then the first scanning posture is the target scanning posture.

[0069] In an optional implementation, the determining whether the first laser point cloud distribution map set matches a preset calibration block drawing includes: Determining a calibration area of ​​the calibration block according to the first laser point cloud distribution map set; Obtain a laser point cloud distribution map having the same calibration block area; Calculating the matching degree between the laser point cloud distribution map of the same calibration block area and the corresponding calibration block area in the preset calibration block drawing; Determining whether the matching degree is less than a preset matching degree threshold; When the matching degree is greater than or equal to the preset matching degree threshold, it is determined that the laser point cloud distribution map of the same calibration block area is successfully matched with the corresponding calibration block area in the preset calibration block drawing; When the matching degree is less than the preset matching degree threshold, it is determined that the laser point cloud distribution map of the same calibration block area fails to match the corresponding calibration block area in the preset calibration block drawing.

[0070] The calibration area of ​​the calibration block refers to the specific area divided on the surface of the calibration block. The surface of the entire calibration block is composed of specific areas. Each laser point cloud distribution map that can be obtained through the laser scanning network can contain one or more calibration areas, and the positional relationship between different laser point cloud distribution maps can be determined by different laser point cloud distribution maps with the same calibration area. The matching degree is used to measure the similarity between the laser point cloud distribution map and the calibration area in the calibration block drawing. The higher the matching degree, the higher the similarity between the laser point cloud distribution map and the calibration block drawing, and the more accurate the laser point cloud data obtained.

[0071] In this application, the matching degree between the laser point cloud distribution map and the calibration block drawing is mainly calculated by the template matching algorithm, wherein the template matching algorithm is a method for finding and locating specific patterns or objects in image or point cloud data. In the scenario where the laser point cloud distribution map is matched with the calibration block drawing, the feature information of the feature points of the calibration block drawing and the laser point cloud distribution map is extracted by the template matching algorithm, wherein the feature point refers to the laser point of the calibration area of ​​the calibration block, and the feature information is the number and distribution of the laser points in the calibration area. The feature information of the two is generated into a feature descriptor by the template matching algorithm, wherein the feature descriptor can be represented by a number or a vector, and the feature descriptors of the two are calculated by the similarity measurement method to obtain the same feature points of the feature information, and the matching degree of the laser point cloud distribution map and the calibration block drawing is determined according to the ratio of the number of the same feature points to the total number of feature points. For example, suppose that the template matching algorithm is used to extract feature points and feature information from the laser point cloud distribution map and the calibration block drawing, and the feature points in the laser map are matched with the feature points in the calibration block drawing. The number of successfully matched feature points is 100, and the total number of feature points is 120. The matching degree is the ratio of successfully matched feature points to the total number of feature points, that is, 100 / 120 = 83.33%.

[0072] The preset matching degree threshold is used to determine whether the matching degree between the laser point cloud distribution map and the calibration block drawing in the calibration area meets the required matching standard. The preset matching degree threshold can be expressed as a percentage. When the matching degree between the laser point cloud distribution map and the calibration block drawing in a certain calibration area is greater than the preset matching degree threshold, the laser point cloud distribution map and the calibration block drawing are successfully matched in the calibration area. For example, when the laser scanning network obtains each laser point cloud distribution map and the calibration block drawing for matching, assuming that the preset matching degree threshold is set to 95%, assuming that a certain calibration area contains a set of corner points and edges of a specific shape in the calibration block drawing, and the laser point cloud distribution map also contains similar corner points and edges. The matching degree calculated by the pattern matching algorithm is 98%, which is greater than the preset matching degree threshold of 95%. It can be considered that the laser point cloud distribution map and the calibration block drawing are successfully matched in the calibration area.

[0073] After the laser scanning network obtains the first laser point cloud distribution map, the calibration block is divided into calibration areas according to different feature information of the calibration block obtained by the first laser point cloud distribution map. The laser point cloud distribution maps with the same calibration area are obtained, and these laser point cloud distribution maps are matched in the same calibration area through the template matching algorithm, and the matching degree between different laser point cloud distribution maps in the same calibration area and the calibration block drawings is obtained, and the matching degree is compared with the preset matching degree threshold. When the matching degree is greater than or equal to the preset matching degree threshold, the first laser point cloud distribution map and the calibration block drawings in the calibration area are successfully matched. When the matching degree is less than the preset matching degree threshold, the first laser point cloud distribution map and the calibration block drawings in the calibration area fail to match. The matching degree of each laser point cloud distribution map in the first laser point cloud distribution map set and the calibration block drawings in the corresponding calibration area is obtained, and each matching degree obtained is compared with the preset matching degree threshold. When all matching degrees are greater than the preset matching degree threshold, the first laser point cloud distribution map set is successfully matched with the calibration block drawings. That is, the laser point cloud distribution map acquired by each scanning device in the laser scanning network accurately corresponds to the calibration block drawing, and the first laser point cloud distribution map set accurately contains all point cloud data of the calibration block, then the three-dimensional image of the calibration block can be completely acquired according to the first laser point cloud distribution map set; when there is at least one matching degree less than a preset matching degree threshold, the first laser cloud point distribution map and the calibration block drawing fail to match in the corresponding calibration area, then there is an error between the first laser point cloud distribution map and the calibration block drawing, and the three-dimensional image of the calibration block cannot be accurately acquired through the first laser point cloud distribution map set.

[0074] In this embodiment, by determining the calibration area of ​​the calibration block, and matching the laser point cloud distribution map with the calibration block drawing according to the calibration area, the matching area can be positioned more accurately and conveniently. The matching degree between the laser point cloud distribution map and the calibration block drawing of each calibration block area can be obtained through the template matching algorithm. If the matching degree is lower than the preset matching degree threshold, the calibration area where the matching fails can be quickly obtained to perform the corresponding first posture adjustment, thereby improving the efficiency of accurately obtaining the accurate three-dimensional image of the calibration block. At the same time, through the automatic matching of the calibration area, the matching accuracy and matching efficiency of the laser point cloud distribution map set and the calibration block drawing are improved, and the accuracy of the laser scanning network in obtaining the three-dimensional image of the calibration block can be improved.

[0075] The second determination module 202 is configured to adjust the first scanning posture to a second scanning posture when the first laser point cloud distribution map set does not match the preset calibration block drawing; Control the scanning device to scan the calibration block at the set position under the second scanning posture to obtain a second laser point cloud distribution map set; determine whether the second laser point cloud distribution map set matches the preset calibration block drawing; when the second laser point cloud distribution map set matches the preset calibration block drawing, determine the second scanning posture as the target scanning posture.

[0076] When matching the first laser point cloud distribution map set with the calibration block drawing, if the first laser point cloud distribution map set does not match the calibration block drawing, that is, there is at least one laser point cloud distribution map in the first laser point cloud distribution map set that does not match the calibration block drawing, and among the unmatched laser point cloud distribution maps, there is at least one laser point cloud distribution map corresponding to the calibration area whose matching degree with the calibration block drawing is less than a preset matching degree threshold. The corresponding laser point cloud distribution map and scanning device can be obtained according to the calibration area, and the specific position or scanning angle of the corresponding scanning device can be adjusted according to the reason for the mismatch. If there are multiple laser point cloud distribution maps that do not match the calibration block drawing, the specific positions or scanning angles of the multiple scanning devices are adjusted. That is, the first scanning posture of the laser scanning network is adjusted to the second scanning posture.

[0077] The calibration block is scanned again with a second scanning posture through the laser scanning network, and a second laser point cloud distribution map of the calibration block under the second scanning posture is obtained. The second laser point cloud distribution map set is matched with the calibration block drawing again. When the second laser point cloud distribution map set matches the calibration block drawing, the second scanning posture is the target scanning posture. If the second laser point cloud distribution map set still does not match the calibration block drawing, the scanning device is adjusted again according to the unmatched calibration area until the obtained laser point cloud distribution map set matches the calibration block drawing.

[0078] In the present application, when the first laser point cloud distribution map set does not match the calibration block drawing, a calibration area with insufficient matching degree can be obtained, and the corresponding scanning device can be obtained through the calibration area, and the scanning device posture information can be quickly obtained and changed. According to the actual situation of the first laser point cloud distribution map and the calibration block drawing matching in the calibration area, precise adjustment is performed to optimize the calibration effect and speed up the adjustment efficiency. The calibration area where the matching degree of the first laser point cloud distribution map set and the calibration block drawing is less than the preset matching degree threshold is obtained, and the second scanning posture matching the first laser point cloud distribution map set and the calibration block drawing is obtained by adjusting the posture information of the scanning device corresponding to each calibration area. By adjusting the scanning device corresponding to the calibration area, the adjustability of the overall laser scanning network is enhanced, and it can adapt to a variety of different working environments. By adjusting the scanning posture corresponding to the scanning device and performing multiple scans, the matching degree of the laser point cloud distribution map set obtained by the scanning device and the calibration block drawing is improved, and a more accurate laser point cloud distribution map set can be obtained. At the same time, the posture information of the laser scanning network is continuously optimized to obtain the target scanning posture.

[0079] The first control module 203 is used to scan the calibration block at a set position under the target scanning posture to obtain a set of laser point cloud distribution maps of the calibration block.

[0080] After determining the target scanning posture of the laser scanning network, the laser scanning network scans the calibration block at the set position in the target scanning posture, and obtains a complete set of calibration block laser point cloud distribution maps through the specific position angle and scanning direction of each scanning device under the target scanning posture.

[0081] The calibration block laser point cloud distribution map set contains the feature information of all angles of the calibration block. Through the calibration block laser point cloud distribution map set, the calibration block can be used to establish a three-dimensional coordinate system with the calibration block as the origin, and each calibration block laser point cloud distribution map is represented in the three-dimensional coordinate system. It can be used to mark a three-dimensional coordinate system. Compared with the existing technical solutions, there is no need to establish a three-dimensional coordinate system according to the equipment in the application scenario. The three-dimensional coordinate system is established by acquiring the calibration block laser point cloud distribution map set through the target scanning posture, which improves the applicability of the laser scanning network and can achieve the acquisition of the calibration block laser point cloud distribution map set in a variety of different scenarios to generate a three-dimensional coordinate system.

[0082] The second control module 204 is used to scan the target object at the set position in the target scanning posture to obtain a set of laser point cloud distribution maps of the target object.

[0083] After determining the target scanning posture of the laser scanning network, the laser scanning network scans the target object at the set position in the target scanning posture, and obtains a complete set of target object laser point cloud distribution maps through the specific position angle and scanning direction of each scanning device under the target scanning posture.

[0084] There may be some feature information gaps between the target object and the calibration block, such as some corners of specific shapes, different edge lengths, and some grooves on the surface. By placing the target object at a set position, it is possible to obtain a complete target object laser point cloud distribution map set of the target object under the target scanning posture. And because the target object and the calibration block are both at the set position, and the laser scanning network is scanned with the same target posture, that is, the target object laser point cloud distribution map set of the target object and the calibration block laser point cloud distribution map set of the calibration block have a spatial set correspondence relationship.

[0085] The model generation module 205 is used to generate a three-dimensional model of the target object according to the target scanning posture and the target object laser point cloud distribution map set.

[0086] A three-dimensional coordinate system can be established through the set of laser point cloud distribution maps of the calibration block obtained under the target scanning posture, and a model of the calibration block can be established in the three-dimensional coordinate system using the laser point cloud distribution map of each calibration block. Through the set of laser point cloud distribution maps of the target object obtained under the target scanning posture, the position relationship between the target object and the calibration block can be used to represent the set of laser point cloud distribution maps of the target object in the three-dimensional coordinate system of the calibration block. According to the matching relationship of the calibration area in the calibration block, the coordinate transformation of the laser point cloud distribution of the target object is performed, and the converted data point cloud distribution is used to build a three-dimensional model of the target object according to the model of the calibration block to generate a three-dimensional model of the target object.

[0087] In an optional embodiment, generating a three-dimensional model of the target object according to the target scanning posture and the target object laser point cloud distribution map set includes: Performing coordinate transformation on the target object laser point cloud distribution map set according to the scanning posture to obtain target object laser point cloud data; Point cloud fusion is performed according to the laser point cloud data of the target object to obtain a three-dimensional model of the target object.

[0088] Coordinate transformation refers to the process of converting the corresponding three-dimensional coordinates of the laser point cloud distribution map of the target object obtained in the scanning device to the three-dimensional coordinate system corresponding to the calibration block. Point cloud fusion is a technology that integrates data from multiple laser point clouds into a single complete three-dimensional model, including point cloud registration, fusion and surface reconstruction. Registration is to register the laser point cloud data of the target object and align them in the global coordinate system through feature matching. Fusion refers to merging the registered point cloud data and integrating them into a complete point cloud model. Reconstruction refers to surface reconstruction of the fused point cloud data to obtain the surface model of the target object, convert the point cloud data into a surface mesh, and finally optimize the surface mesh, such as removing noise points, filling surface holes, etc., and finally obtain the three-dimensional model of the target object through smoothing.

[0089] After obtaining the set of laser point cloud distribution maps of the target object, obtain the point cloud distribution data of each laser point cloud distribution map, convert the point cloud distribution data of each scanning device to the three-dimensional coordinate system of the calibration block through coordinate conversion, and represent each laser point cloud distribution data through the three-dimensional coordinate system of the calibration block to obtain the laser point cloud data of the target object in the three-dimensional coordinate system of the calibration block. Then perform point cloud fusion on the laser point cloud data of the target object. First, align the laser point cloud data of the target object so that they are aligned in the three-dimensional coordinate system of the calibration block. Then, fuse and merge the registered laser point cloud data of the target object to obtain a complete point cloud model. Perform surface reconstruction on the complete point cloud model to obtain the surface model of the target object. Finally, optimize the surface model of the target object to obtain the three-dimensional model of the target object.

[0090] Through the matching relationship between the target laser distribution map set and the calibration block drawing in the calibration area, the laser point cloud data obtained by the laser scanning network is accurately converted to the calibration block three-dimensional coordinate system, which solves the limitation that the traditional three-dimensional imaging method needs to rely on the device of the application scenario to provide an accurate spatial coordinate system. Point cloud fusion through the target object laser point cloud data can ensure that the generated three-dimensional model is more complete and will not be affected by the limited field of view of a single scanning device. It can obtain more comprehensive and accurate surface features of the target object and generate a more accurate three-dimensional model of the target object.

[0091] In an optional embodiment, the step of performing coordinate transformation on the target object laser point cloud distribution map set according to the scanning posture to obtain the target object laser point cloud data includes: Acquire the local three-dimensional coordinate system of each laser point cloud distribution map in the laser point cloud distribution map set of the target object; Obtaining a global three-dimensional coordinate system corresponding to the calibration block; The coordinate points of each laser point cloud distribution map are converted to the global three-dimensional coordinate system according to the local three-dimensional coordinate system to obtain the laser point cloud data of the target object in the global three-dimensional coordinate system.

[0092] The local coordinate system refers to the three-dimensional coordinate system of each scanning device itself, whose origin and coordinate axis direction are related to the specific position and scanning direction of the scanning device. The laser point cloud distribution map of each target object can be represented by the local coordinate system, and each laser point in the laser point cloud distribution map of the target object corresponds to different data on the local coordinate system. The global coordinate system refers to a three-dimensional coordinate system established based on the calibration block, whose origin is the set position center of the calibration block, and the coordinate axis direction is related to the target scanning posture. Coordinate point conversion refers to the process of converting the coordinate points of the local coordinate system to the global coordinate system through the translation and rotation transformation of the coordinates according to the position information and direction information of each local coordinate system. Among them, the position information refers to the physical position distance information of each scanning device and the calibration block, and the direction information refers to the scanning angle direction of each scanning device to the calibration block.

[0093] After obtaining the local 3D coordinate system of each scanning device and the global 3D coordinate system of the calibration block, the laser point data on each 3D coordinate system is displaced to the global 3D coordinate system through the position information. After the physical position distance is displaced, the reverse rotation is performed according to the direction information of each scanning device to obtain the accurate coordinates of each laser point in the global 3D coordinate system. Each laser point in the target object laser point cloud distribution map set is converted to the global 3D coordinate system to obtain the target object laser point cloud data.

[0094] The posture updating module 206 is used to regenerate the three-dimensional model of the target object according to the updated scanning posture after the scanning posture of the scanning device is updated.

[0095] When the scanning posture of the laser scanning network is updated, the updated laser point cloud distribution map set of the calibration block at the set position is obtained, and the obtained updated laser point cloud distribution map set is re-matched with the calibration block drawing, and the updated target scanning posture is adjusted according to the matching result. The calibration block is re-scanned with the updated target scanning posture to obtain the updated calibration block laser point cloud distribution map set, and the updated global coordinate system is obtained. The target object is re-scanned with the updated target scanning posture to obtain the updated target object laser point cloud distribution map set, and the updated local coordinate system is obtained. The updated target object laser point cloud data is obtained by converting the target object laser point cloud data on the updated local coordinate system to the updated global coordinate system, and the shape and position of the calibration block are remodeled for the updated target object laser point cloud data.

[0096] A new 3D model of the target object in an updated posture is obtained through point cloud fusion.

[0097] In the present application, the scanning posture of the laser scanning network can be adjusted to update the acquired laser point cloud data, which enhances the adjustability of the laser scanning network and enables the laser scanning network to obtain three-dimensional images of the target object in more application scenarios. For example, if the target object moves in space, the traditional three-dimensional imaging method needs to re-design the three-dimensional coordinate system according to the position of the object movement and select the device in the application scenario. In the present application, the scanning posture of the laser scanning network is determined by moving the corresponding calibration block position, and the three-dimensional model of the target object is obtained through the determined scanning posture. Especially in some application scenarios that require real-time or dynamic updates, the three-dimensional imaging method based on the calibration block can better meet the use requirements.

[0098] The present application obtains a set of laser point cloud distribution maps of the calibration block by scanning a calibration block at a set position under a target scanning posture; obtains a set of laser point cloud distribution maps of the target object by scanning a target object at the set position under the target scanning posture; and generates a three-dimensional model of the target object according to the target scanning posture and the set of laser point cloud distribution maps of the target object. The present application determines the target scanning posture of the scanning device through a calibration block to ensure that the point cloud data of the target object can be completely and accurately acquired. The target object laser point cloud data of the target object is acquired by performing coordinate conversion of the laser point cloud distribution map set of the target object to the global coordinate system corresponding to the calibration block, thereby generating a three-dimensional model. This solves the problem that traditional three-dimensional imaging needs to rely on external devices to establish a coordinate system and cannot change the posture.

[0099] An embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements all or part of the steps of a three-dimensional imaging method based on a calibration block when executing the computer program.

[0100] See also Figure 3 FIG. 2 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. In a preferred embodiment of the present application, the electronic device 3 includes a memory 31 , at least one processor 32 , and at least one communication bus 33 .

[0101] Those skilled in the art should understand that Figure 3 The structure of the electronic device shown does not constitute a limitation of the embodiments of the present application, and may be either a bus structure or a star structure. The electronic device may also include more or less other hardware or a different component arrangement than shown in the figure.

[0102] In some embodiments, the electronic device 3 is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application-specific integrated circuits, programmable gate arrays, digital processors, and embedded devices. The electronic device 3 may also include client devices, which include but are not limited to any electronic product that can interact with a client through a keyboard, mouse, remote control, touchpad, or voice-controlled device, such as a personal computer, tablet computer, smart phone, digital scanning device, etc.

[0103] In some embodiments, the memory 31 stores a computer program, and when the computer program is executed by the at least one processor 32, all or part of the steps in the three-dimensional imaging method based on the calibration block are implemented. The memory 31 includes a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data. Further, the computer-readable storage medium mainly includes a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function, etc.

[0104] In some embodiments, the at least one processor 32 is the control core (ControlUnit) of the electronic device 3, and uses various interfaces and lines to connect various components of the entire electronic device 3, and executes various functions and processes data of the electronic device 3 by running or executing programs or modules stored in the memory 31, and calling data stored in the memory 31. For example, when the at least one processor 32 executes the computer program stored in the memory, it implements all or part of the steps of the three-dimensional imaging method based on the calibration block described in the embodiment of the present application; or implements all or part of the functions of the three-dimensional imaging method based on the calibration block. The at least one processor 32 can be composed of an integrated circuit, for example, it can be composed of a single packaged integrated circuit, or it can be composed of multiple integrated circuits with the same function or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips.

[0105] In some embodiments, the at least one communication bus 33 is configured to realize the connection and communication between the memory 31 and the at least one processor 32. Although not shown, the electronic device 3 may also include a power supply (such as a battery) for powering each component. Preferably, the power supply may be logically connected to the at least one processor 32 through a power management device, so as to realize the functions of managing charging, discharging, and power consumption management through the power management device. The power supply may also include any components such as one or more DC or AC power supplies, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. The electronic device 3 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0106] The above integrated unit implemented in the form of software function modules can be stored in a computer-readable storage medium. The above software function modules are stored in a storage medium and include several instructions for a processor to execute parts of the methods described in various embodiments of the present application.

[0107] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0108] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0109] The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.

Claims

1. A three-dimensional imaging method based on a calibration block, characterized in that: The method comprises: Under the target scanning posture, the calibration block at the set position is scanned to obtain a set of laser point cloud distribution maps of the calibration block; Under the target scanning posture, scanning the target object at the set position to obtain a set of laser point cloud distribution maps of the target object; A three-dimensional model of the target object is generated according to the target scanning posture and the target object laser point cloud distribution map set.

2. The three-dimensional imaging method based on the calibration block according to claim 1, characterized in that: The method further comprises: In a first scanning posture, scanning the calibration block at the set position to obtain a first laser point cloud distribution map set; Determining whether the first laser point cloud distribution map set matches a preset calibration block drawing; When the first laser point cloud distribution map set matches the preset calibration block drawing, the first scanning posture is determined as the target scanning posture.

3. The three-dimensional imaging method based on the calibration block according to claim 2, characterized in that: The determining whether the first laser point cloud distribution map set matches a preset calibration block drawing includes: Determining a calibration area of ​​the calibration block according to the first laser point cloud distribution map set; Obtain a laser point cloud distribution map having the same calibration block area; Calculating the matching degree between the laser point cloud distribution map of the same calibration block area and the corresponding calibration block area in the preset calibration block drawing; Determining whether the matching degree is less than a preset matching degree threshold; When the matching degree is less than or equal to the preset matching degree threshold, it is determined that the laser point cloud distribution map of the same calibration block area is successfully matched with the corresponding calibration block area in the preset calibration block drawing; When the matching degree is greater than the preset matching degree threshold, it is determined that the laser point cloud distribution map of the same calibration block area fails to match the corresponding calibration block area in the preset calibration block drawing.

4. The three-dimensional imaging method based on the calibration block according to claim 2, characterized in that: The method further comprises: When the first laser point cloud distribution map set does not match the preset calibration block drawing, adjusting the first scanning posture to a second scanning posture; Controlling the scanning device to scan the calibration block at the set position in the second scanning posture to obtain a second laser point cloud distribution map set; Determining whether the second laser point cloud distribution map set matches the preset calibration block drawing; When the second laser point cloud distribution map set matches the preset calibration block drawing, the second scanning posture is determined as the target scanning posture.

5. The three-dimensional imaging method based on the calibration block according to any one of claims 1 to 4, characterized in that: Generating a three-dimensional model of the target object according to the target scanning posture and the target object laser point cloud distribution map set includes: Performing coordinate transformation on the target object laser point cloud distribution map set according to the target scanning posture to obtain the target object laser point cloud data; Point cloud fusion is performed according to the laser point cloud data of the target object to obtain a three-dimensional model of the target object.

6. The three-dimensional imaging method based on the calibration block according to any one of claim 5, characterized in that: The performing coordinate transformation on the target object laser point cloud distribution map set according to the scanning posture to obtain the target object laser point cloud data comprises: Acquire the local three-dimensional coordinate system of each laser point cloud distribution map in the laser point cloud distribution map set of the target object; Obtaining a global three-dimensional coordinate system corresponding to the calibration block; The coordinate points of each laser point cloud distribution map are converted to the global three-dimensional coordinate system according to the local three-dimensional coordinate system to obtain the laser point cloud data of the target object in the global three-dimensional coordinate system.

7. The three-dimensional imaging method based on the calibration block according to claim 6, characterized in that: The method further comprises: When the scanning posture of the scanning device is updated, the three-dimensional model of the target object is regenerated according to the updated scanning posture.

8. A three-dimensional imaging device based on a calibration block, characterized in that: The device comprises: A first control module is used to scan the calibration block at a set position under a target scanning posture to obtain a set of laser point cloud distribution maps of the calibration block; A second control module is used to scan the target object at the set position in the target scanning posture to obtain a set of laser point cloud distribution maps of the target object; The model generation module is used to generate a three-dimensional model of the target object according to the target scanning posture and the target object laser point cloud distribution map set.

9. An electronic device, characterized in that: It comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the calibration block-based three-dimensional imaging method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the calibration block-based three-dimensional imaging method as described in any one of claims 1 to 7 are implemented.

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