A method and device for calculating projection area based on point cloud image

Abstract

The present invention discloses a method and device for calculating the projection area based on a point cloud map, the method comprising: confirming multiple measurement points according to the object to be measured, moving the scanner to each measurement point in turn for scanning; taking the calibration zero point as the center, generating rough stitching data about the point position distribution of multiple measurement points; combining the rough stitching data with the scanning results of multiple measurement points for fine stitching to obtain a fine stitching point cloud map; according to the projection of the carrier platform, eliminating the carrier platform point cloud data in the fine stitching point cloud map; performing positive direction projection on the fine stitching point cloud map, obtaining the projection point cloud map of the object to be measured and calculating the projection area. The present invention only requires one scanner to scan the measurement points of the object to be measured, perform fine stitching on each measurement point, and then calculate the projection area, which greatly saves the detection cost while ensuring accuracy.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method and device for calculating a projection area based on a point cloud image. Background Art

[0002] Currently, the solution for measuring the orthographic projection area of ​​objects such as cars, furniture, airplanes, and ships is a fixed 3D scanning measurement method. However, the disadvantages of fixed 3D scanning measurement devices are that they are expensive to build and require multiple 3D scanners to complete the construction. The maintenance cost is high because multiple 3D scanners need to be maintained at the same time to ensure the normal scanning work. Summary of the invention

[0003] The embodiment of the present invention provides a method and device for calculating the projection area based on a point cloud map, which only uses one scanner to scan the measurement points of the object to be measured, and then calculates the projection area after precisely assembling each measurement point, thereby greatly saving the detection cost while ensuring accuracy.

[0004] To achieve the above-mentioned purpose, a first aspect of an embodiment of the present application provides a method for calculating a projection area based on a point cloud image, comprising:

[0005] Scan the carrier at the calibration zero point, and perform projection transformation on the calibration zero point scanning result to obtain the carrier projection;

[0006] According to the difference between the projection of the carrier platform and the calibration map, the relative position of the carrier platform is adjusted; the pixels of the projection of the carrier platform and the calibration map are the same;

[0007] Confirm multiple measuring points according to the object to be measured, and move the scanner to each measuring point for scanning in turn;

[0008] Taking the calibration zero point as the center, generating rough data on the point distribution of multiple measurement points;

[0009] Combining the rough stitching data with the scanning results of multiple measurement points to perform fine stitching to obtain a fine stitching point cloud map;

[0010] According to the projection of the carrier platform, the point cloud data of the carrier platform in the fine-grained point cloud image is eliminated;

[0011] The precise point cloud image is projected in the forward direction to obtain a projected point cloud image of the object to be measured and calculate the projection area.

[0012] In a possible implementation manner of the first aspect, the generating of rough data on the distribution of the plurality of measurement points with the calibration zero point as the center specifically includes:

[0013] The relative position information of each measuring point and the calibration zero point is written into the data matrix corresponding to the rough-spliced ​​data, thereby obtaining the rough-spliced ​​data containing the point distribution of multiple measuring points.

[0014] In a possible implementation of the first aspect, combining the rough stitching data with the scanning results of the plurality of measurement points to perform fine stitching to obtain a fine stitching point cloud map specifically includes:

[0015] Select characteristic regions that appear repeatedly in the scanning results of the multiple measuring points, combine the characteristic regions with the rough stitching data, and perform ICP fine stitching on the scanning results of the multiple measuring points.

[0016] In a possible implementation manner of the first aspect, removing the point cloud data of the carrier platform in the fine-grained point cloud image according to the projection of the carrier platform specifically includes:

[0017] The point cloud data of the carrier platform is extracted from the projection of the carrier platform, the point cloud data with the same structure as the point cloud data of the carrier platform in the fine-grained point cloud image is eliminated, and the point cloud data of the contour of the object to be measured is retained.

[0018] In a possible implementation manner of the first aspect, adjusting the relative position of the supporting platform according to the difference between the projection of the supporting platform and the calibration map is specifically:

[0019] Comparing the projection of the support platform with the calibration map pixel by pixel to obtain the proportion of different pixels;

[0020] The carrier platform is moved according to the proportions of the different pixels, and the moving distance is positively correlated with the proportions of the different pixels.

[0021] A second aspect of an embodiment of the present application provides a projection area calculation device based on a point cloud image, comprising:

[0022] A scanning module is used to scan the carrier at the calibration zero point and perform projection transformation on the calibration zero point scanning result to obtain the carrier projection;

[0023] A calibration module, used to adjust the relative position of the carrier platform according to the difference between the projection of the carrier platform and the calibration map; the projection of the carrier platform and the calibration map have the same pixels;

[0024] The moving and measuring module is used to confirm multiple measuring points according to the object to be measured, and move the scanner to each measuring point for scanning in turn;

[0025] A rough stitching module, used to generate rough stitching data on the point distribution of multiple measurement points with the calibration zero point as the center;

[0026] A fine stitching module, used for combining the rough stitching data with the scanning results of multiple measurement points to perform fine stitching to obtain a fine stitching point cloud map;

[0027] A removal module, used for removing the point cloud data of the carrier platform in the fine-grained point cloud image according to the projection of the carrier platform;

[0028] The calculation module is used to perform positive projection on the precise point cloud image, obtain the projected point cloud image of the object to be measured and calculate the projection area.

[0029] In a possible implementation manner of the second aspect, the rough stitching module is specifically used to:

[0030] The relative position information of each measuring point and the calibration zero point is written into the data matrix corresponding to the rough-spliced ​​data, thereby obtaining the rough-spliced ​​data containing the point distribution of multiple measuring points.

[0031] In a possible implementation manner of the second aspect, the precise spelling module is specifically configured to:

[0032] Select characteristic regions that appear repeatedly in the scanning results of the multiple measuring points, combine the characteristic regions with the rough stitching data, and perform ICP fine stitching on the scanning results of the multiple measuring points.

[0033] In a possible implementation manner of the second aspect, the rejection module is specifically configured to:

[0034] The point cloud data of the carrier platform is extracted from the projection of the carrier platform, the point cloud data with the same structure as the point cloud data of the carrier platform in the fine-grained point cloud image is eliminated, and the point cloud data of the contour of the object to be measured is retained.

[0035] In a possible implementation manner of the second aspect, the lowering the calibration module is specifically configured to:

[0036] Comparing the projection of the support platform with the calibration map pixel by pixel to obtain the proportion of different pixels;

[0037] The carrier platform is moved according to the proportions of the different pixels, and the moving distance is positively correlated with the proportions of the different pixels.

[0038] Compared with the prior art, the embodiment of the present invention provides a method and device for calculating the projection area based on a point cloud map, which moves the scanner to different measuring points to scan the object to be measured, obtains point cloud data of the object to be measured at different angles, and then adjusts the fine stitching method in combination with the measuring point position distribution information in the rough stitching data to fine stitch the scanning results of multiple measuring points, thereby obtaining a complete point cloud map of the object to be measured. The entire process can be completed with the help of only one scanner, saving the cost of the instrument; and the fine stitching ensures the integrity of the point cloud map of the object to be measured, thereby realizing the accurate measurement of the projection area of ​​the object to be measured. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1It is a schematic flow chart of a method for calculating a projection area based on a point cloud image provided by an embodiment of the present invention;

[0040] Figure 2 It is a structural diagram of a projection area calculation device based on a point cloud image in one embodiment of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] See also Figure 1 A first aspect of an embodiment of the present application provides a method for calculating a projection area based on a point cloud image, comprising:

[0043] S10, scanning the carrier platform at the calibration zero point, and performing projection transformation on the calibration zero point scanning result to obtain the carrier platform projection.

[0044] S11. Adjust the relative position of the supporting platform according to the difference between the projection of the supporting platform and the calibration map; the pixels of the projection of the supporting platform and the calibration map are the same.

[0045] S12, confirming a plurality of measuring points according to the object to be measured, and moving the scanner to each measuring point in turn for scanning.

[0046] S13, generating rough data on the distribution of multiple measuring points with the calibration zero point as the center.

[0047] S14, combining the rough stitching data with the scanning results of multiple measurement points to perform fine stitching to obtain a fine stitching point cloud map.

[0048] S15. According to the projection of the carrier platform, the point cloud data of the carrier platform in the fine-grained point cloud image is eliminated.

[0049] S16, performing forward projection on the precise point cloud image, obtaining a projected point cloud image of the object to be measured and calculating the projection area.

[0050] The entire projection area calculation process can be divided into instrument calibration (corresponding to S10-S11), operation scanning (corresponding to S12), data stitching (corresponding to S13-S14) and projection calculation (corresponding to S15-S16). The purpose is achieved through a scanning instrument and a mobile measuring device, and it can be expanded to the three-dimensional scanning field of various equipment (such as automobiles, furniture, airplanes, ships, etc.). Moreover, the larger the object to be measured, the greater the cost savings of this solution, and the more obvious the benefits.

[0051] Compared with the prior art, the embodiment of the present invention provides a projection area calculation method based on a point cloud map, which moves the scanner to different measuring points to scan the object to be measured, obtains point cloud data of the object to be measured at different angles, and then adjusts the fine stitching method in combination with the measuring point position distribution information in the rough stitching data to perform fine stitching on the scanning results of multiple measuring points, thereby obtaining a complete point cloud map of the object to be measured. The entire process can be completed with the help of only one scanner, saving the cost of the instrument; and the fine stitching ensures the integrity of the point cloud map of the object to be measured, thereby realizing the accurate measurement of the projection area of ​​the object to be measured.

[0052] Exemplarily, the adjusting the relative position of the carrier platform according to the difference between the carrier platform projection and the calibration map is specifically as follows:

[0053] Comparing the projection of the support platform with the calibration map pixel by pixel to obtain the proportion of different pixels;

[0054] The carrier platform is moved according to the proportions of the different pixels, and the moving distance is positively correlated with the proportions of the different pixels.

[0055] S10-S11 is to calibrate the relative positions of the instruments (scanner, transfer frame, and carrier) needed in the scanning calculation process. The calibration process is as follows:

[0056] 1. Run the scanner to the calibration zero point.

[0057] 2. Run the scan, perform projection transformation on the scan result according to the calibration matrix, and save the transformation result as the platform projection.

[0058] 3. Compare the difference between the projection of the carrier and the calibration map. For two projections with the same pixels, compare them pixel by pixel, and obtain the difference ratio based on the different pixel ratios / total pixel ratios. Then adjust the position of the carrier relative to the scanner and the measuring frame according to the difference ratio.

[0059] Exemplarily, the generating of rough data on the distribution of the plurality of measuring points with the calibration zero point as the center specifically includes:

[0060] The relative position information of each measuring point and the calibration zero point is written into the data matrix corresponding to the rough-spliced ​​data, thereby obtaining the rough-spliced ​​data containing the point distribution of multiple measuring points.

[0061] S12 is the scanning process. When the instrument calibration test is normal, the scanning calculation can be started:

[0062] According to the different types of objects to be measured, select the corresponding measurement point plan and scan after selection:

[0063] 1. Move to the first point and run the scan;

[0064] 2. Move to the next point and run the scan until all scans are completed.

[0065] Exemplarily, the combining the rough stitching data and the scanning results of the plurality of measurement points to perform fine stitching to obtain a fine stitching point cloud map specifically includes:

[0066] Select characteristic regions that appear repeatedly in the scanning results of the multiple measuring points, combine the characteristic regions with the rough stitching data, and perform ICP fine stitching on the scanning results of the multiple measuring points.

[0067] S13-S14 is the process of data stitching. After the data scanning is completed in S12, the scanning results of multiple measurement points will be sent to the local computing server. When stitching, it is necessary to download the scanning results of multiple measurement points from the local computing server, first generate the rough stitching data of the point distribution with the calibration point as the center; then convert the multi-point scanning results and the rough stitching data to obtain the fine stitching data.

[0068] Exemplarily, the removing the point cloud data of the carrier platform in the fine-grained point cloud image according to the projection of the carrier platform specifically includes:

[0069] The point cloud data of the carrier platform is extracted from the projection of the carrier platform, the point cloud data with the same structure as the point cloud data of the carrier platform in the fine-grained point cloud image is eliminated, and the point cloud data of the contour of the object to be measured is retained.

[0070] After the precise assembly is completed, the precise assembly point cloud map is compared with the projection of the carrier platform, the point cloud data of the carrier platform is eliminated, and the forward projection area is calculated. The specific calculation process is as follows:

[0071] 1. According to the calibration results, the point cloud data of the carrier platform is compared and eliminated, and only the point cloud data of the outline of the object to be measured is retained;

[0072] 2. Calculate and count the area from the positive direction to obtain the projection point cloud map of the object to be measured.

[0073] See also Figure 2 The second aspect of the embodiment of the present application provides a projection area calculation device based on a point cloud map, including: a scanning module, a calibration module, a movement measurement module, a rough stitching module, a fine stitching module, a rejection module and a calculation module.

[0074] The scanning module is used to scan the carrier platform at the calibration zero point and perform projection transformation on the calibration zero point scanning result to obtain the carrier platform projection.

[0075] The calibration module is used to adjust the relative position of the carrier platform according to the difference between the projection of the carrier platform and the calibration map; the pixels of the projection of the carrier platform and the calibration map are the same.

[0076] The moving and measuring module is used to confirm multiple measuring points according to the object to be measured, and move the scanner to each measuring point in turn for scanning.

[0077] The rough stitching module is used to generate rough stitching data about the point distribution of multiple measurement points with the calibration zero point as the center.

[0078] The fine stitching module is used to combine the rough stitching data with the scanning results of multiple measurement points to perform fine stitching to obtain a fine stitching point cloud map.

[0079] The elimination module is used to eliminate the point cloud data of the carrier platform in the fine-grained point cloud image according to the projection of the carrier platform.

[0080] The calculation module is used to perform positive projection on the precise point cloud image, obtain the projected point cloud image of the object to be measured and calculate the projection area.

[0081] Generally speaking, the scanning module will be installed in the scanner; the transfer and measurement module will be installed in the transfer and measurement frame; the rough assembly module, fine assembly module, rejection module, and calculation module will be installed in the local computer; and the calibration module will be installed on the carrier.

[0082] Exemplarily, the rough stitching module is specifically used for:

[0083] The relative position information of each measuring point and the calibration zero point is written into the data matrix corresponding to the rough-spliced ​​data, thereby obtaining the rough-spliced ​​data containing the point distribution of multiple measuring points.

[0084] Exemplarily, the precise spelling module is specifically used for:

[0085] Select characteristic regions that appear repeatedly in the scanning results of the multiple measuring points, combine the characteristic regions with the rough stitching data, and perform ICP fine stitching on the scanning results of the multiple measuring points.

[0086] Exemplarily, the rejection module is specifically used for:

[0087] The point cloud data of the carrier platform is extracted from the projection of the carrier platform, the point cloud data with the same structure as the point cloud data of the carrier platform in the fine-grained point cloud image is eliminated, and the point cloud data of the contour of the object to be measured is retained.

[0088] Exemplarily, the lowering of the calibration module is specifically used for:

[0089] Comparing the projection of the support platform with the calibration map pixel by pixel to obtain the proportion of different pixels;

[0090] The carrier platform is moved according to the proportions of the different pixels, and the moving distance is positively correlated with the proportions of the different pixels.

[0091] Compared with the prior art, the projection area calculation device based on the point cloud provided by the embodiment of the present invention moves the scanner to different measuring points to scan the object to be measured, obtains the point cloud data of the object to be measured at different angles, and then adjusts the fine stitching method in combination with the measuring point position distribution information in the rough stitching data to perform fine stitching on the scanning results of multiple measuring points, thereby obtaining a complete point cloud map of the object to be measured. The entire process can be completed with the help of only one scanner, saving the instrument cost; and the fine stitching ensures the integrity of the point cloud map of the object to be measured, thereby realizing the accurate measurement of the projection area of ​​the object to be measured.

[0092] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be described again here.

[0093] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for calculating projection area based on point cloud image, characterized in that: include: Scan the carrier at the calibration zero point, and perform projection transformation on the calibration zero point scanning result to obtain the carrier projection; According to the difference between the projection of the carrier platform and the calibration map, the relative position of the carrier platform is adjusted; the projection of the carrier platform and the calibration map have the same pixels; Confirm multiple measuring points according to the object to be measured, and move the scanner to each measuring point for scanning in turn; Taking the calibration zero point as the center, generating rough patchwork data about the position distribution of multiple measuring points, specifically including: writing the relative position information of each measuring point and the calibration zero point into the data matrix corresponding to the rough patchwork data, thereby obtaining the rough patchwork data containing the position distribution of multiple measuring points; Combining the rough stitching data with the scanning results of the multiple measuring points to perform fine stitching to obtain a fine stitching point cloud map, specifically comprising: selecting feature areas that appear repeatedly in the scanning results of the multiple measuring points, combining the feature areas with the rough stitching data, and performing ICP fine stitching on the scanning results of the multiple measuring points; According to the projection of the carrier platform, the point cloud data of the carrier platform in the fine-grained point cloud image is eliminated; The precise point cloud image is projected in the forward direction to obtain a projected point cloud image of the object to be measured and calculate the projection area.

2. The method for calculating the projection area based on the point cloud image according to claim 1, characterized in that: The step of removing the point cloud data of the carrier platform in the fine-grained point cloud image according to the projection of the carrier platform specifically includes: The point cloud data of the carrier platform is extracted from the projection of the carrier platform, the point cloud data with the same structure as the point cloud data of the carrier platform in the fine-grained point cloud image is eliminated, and the point cloud data of the contour of the object to be measured is retained.

3. The method for calculating the projection area based on the point cloud image according to claim 1, characterized in that: The step of adjusting the relative position of the carrier platform according to the difference between the carrier platform projection and the calibration map is specifically as follows: Comparing the projection of the support platform with the calibration map pixel by pixel to obtain the proportion of different pixels; The carrier platform is moved according to the proportions of the different pixels, and the moving distance is positively correlated with the proportions of the different pixels.

4. A projection area calculation device based on a point cloud image, characterized in that: include: A scanning module is used to scan the carrier at the calibration zero point and perform projection transformation on the calibration zero point scanning result to obtain the carrier projection; A calibration module, used to adjust the relative position of the carrier platform according to the difference between the projection of the carrier platform and the calibration map; the projection of the carrier platform and the calibration map have the same pixels; The moving and measuring module is used to confirm multiple measuring points according to the object to be measured, and move the scanner to each measuring point for scanning in turn; A rough stitching module is used to generate rough stitching data about the position distribution of multiple measuring points with the calibration zero point as the center, specifically including: writing the relative position information of each measuring point and the calibration zero point into the data matrix corresponding to the rough stitching data, thereby obtaining the rough stitching data containing the position distribution of multiple measuring points; A fine stitching module is used to combine the rough stitching data and the scanning results of multiple measurement points to perform fine stitching to obtain a fine stitching point cloud map, specifically comprising: selecting feature areas that appear repeatedly in the scanning results of multiple measurement points, combining the feature areas with the rough stitching data, and performing ICP fine stitching on the scanning results of the multiple measurement points; A removal module, used for removing the point cloud data of the carrier platform in the fine-grained point cloud image according to the projection of the carrier platform; The calculation module is used to perform positive projection on the precise point cloud image, obtain the projected point cloud image of the object to be measured and calculate the projection area.

5. The projection area calculation device based on point cloud image according to claim 4, characterized in that: The rejection module is specifically used for: The point cloud data of the carrier platform is extracted from the projection of the carrier platform, the point cloud data with the same structure as the point cloud data of the carrier platform in the fine-grained point cloud image is eliminated, and the point cloud data of the contour of the object to be measured is retained.

6. The projection area calculation device based on point cloud image according to claim 4, characterized in that: The calibration module is specifically used for: Comparing the projection of the support platform with the calibration map pixel by pixel to obtain the proportion of different pixels; The carrier platform is moved according to the proportions of the different pixels, and the moving distance is positively correlated with the proportions of the different pixels.

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