A laser measuring device for measuring human body shape

Abstract

The present invention relates to the technical field of medical devices, and in particular to a laser measuring device for measuring human body morphology, comprising a telescopic rod, an annular guide rail, a laser measuring assembly and a laser scanning device, wherein the telescopic rod can adjust its own height according to the height of a target to be measured, so as to satisfy the laser scanning device for scanning the target to be measured; a data analysis module obtains a two-dimensional image according to an initial morphological three-dimensional image, determines an actual two-dimensional image complexity value according to the area of ​​the two-dimensional image and the number of feature points, determines a secondary refinement scanning difficulty level according to the actual complexity value of the two-dimensional image, and determines an actual secondary refinement scanning speed according to the secondary refinement scanning difficulty level; and obtains a target secondary refinement scanning speed according to a comparison result of a coincidence value of the initial morphological three-dimensional image and a coincidence value of a standard morphological three-dimensional image. The present invention performs a refinement scanning on a target to be measured by adjusting the scanning speed of a scanning device, thereby improving scanning efficiency and increasing scanning clarity.

Description

Technical Field

[0001] The invention relates to the technical field of medical instruments, and in particular to a laser measuring device for measuring human body morphology. Background Art

[0002] Human morphology measurement is one of the contents of sports measurement, among which morphology assessment includes physique assessment, body shape assessment, body composition assessment and body posture assessment.

[0003] Chinese Patent Publication No.: CN109489522A discloses a fish morphology measuring device and a method of using the same. The device includes a measuring platform, a measuring cavity is formed in the measuring platform, a measuring ruler, a baffle and a fixed bracket are arranged on the measuring platform, an inner slot for installing the measuring ruler is arranged on the measuring platform, the baffle is fixedly connected to the scale starting end of the measuring ruler, the fixed bracket is perpendicular to the measuring platform and detachably slidably connected to the measuring platform, the sliding direction of the fixed bracket is consistent with the length direction of the measuring ruler, two fixed rods are arranged on the fixed bracket, the moving directions of the two fixed rods are perpendicular to the length direction of the measuring ruler, a distance measuring tool for measuring the distance between the two fixed rods is arranged on the fixed bracket, and at least one of the fixed rods is provided with a scale.

[0004] It can be seen that the prior art has the following problems: lack of the ability to fine-tune the scanning of the target to be measured by adjusting the scanning speed of the scanning device, thereby improving the scanning efficiency and increasing the scanning clarity. Summary of the invention

[0005] To this end, the present invention provides a laser measuring device for measuring human body morphology, so as to overcome the problem in the prior art that there is a lack of fine scanning of a target to be measured by adjusting the scanning speed of a scanning device, thereby improving scanning efficiency and increasing scanning clarity.

[0006] To achieve the above-mentioned object, the present invention provides a laser measuring device for measuring human body morphology, comprising: a base for carrying an object to be measured;

[0007] A telescopic rod, one end of which is connected to the base and the other end of which is connected to the connecting rod, for controlling the measuring height of the laser measuring assembly;

[0008] an annular guide rail connected to the connecting rod, used to enable the laser measurement assembly to slide around the human body for measurement;

[0009] A laser measurement assembly, which is composed of an annular guide rail and a searchlight, wherein the annular guide rail is used for the laser scanning device to perform laser scanning around the target to be measured;

[0010] A laser scanning device, which is slidably connected to the annular guide rail and is used to scan the shape of the target to be measured;

[0011] An image generation module, used for generating a three-dimensional image of the morphology of the target to be measured;

[0012] A control module, used to control the telescopic length of the telescopic rod; and control the scanning speed and scanning height of the laser scanning device;

[0013] A data analysis module, which is connected to the image generation module, the image conversion module and the control module, and is used to analyze the morphological three-dimensional image of the target to be detected collected by the image generation module to obtain an initial morphological three-dimensional image;

[0014] The image conversion module generates a two-dimensional image according to the initial three-dimensional image, wherein the two-dimensional image includes a front projection image, a side projection image, and a rear projection image;

[0015] The data analysis module is further used to: determine the actual two-dimensional image complexity value according to the two-dimensional image area and the number of feature points, determine the secondary refinement scanning difficulty level according to the actual complexity value of the two-dimensional image, determine the actual secondary refinement scanning speed according to the secondary refinement scanning difficulty level to obtain a secondary refinement scanning result, and obtain a secondary refinement morphological three-dimensional image according to the secondary refinement scanning result;

[0016] Determine the scanning mode of the laser scanning device according to the difficulty level of the secondary refinement scanning; determine the complexity value of each segmented two-dimensional image according to the curvature of the edge line of each projection image and the number of segmented feature points;

[0017] According to the complexity value of the first segment segment two-dimensional image of the target to be measured scanned in the segmented scanning mode, the laser scanning overlap height of the lower segment segment is judged to determine the descending height of the telescopic rod, wherein the laser scanning overlap height of the lower segment segment is the overlap scanning height of the laser scanning height of the first segment segment and the laser scanning height of the lower segment segment;

[0018] Compare the segmented secondary refined morphological three-dimensional image of the first segment area and the segmented secondary refined morphological three-dimensional image of the lower segment area of ​​the target to be measured, and obtain the overlap value of the initial morphological three-dimensional image according to the comparison result;

[0019] The target secondary refinement scanning speed is obtained based on the comparison result of the initial morphology three-dimensional image coincidence value and the standard morphology three-dimensional image coincidence value.

[0020] Furthermore, the height of the telescopic rod can be adjusted according to the height of the target to be measured, and can be shortened from top to bottom to meet the measurement height of the target to be measured.

[0021] Furthermore, the data analysis module performs segmented scanning on the laser scanning area of ​​the three-dimensional image of the target morphology to be measured according to a first distinguishing method, wherein the first distinguishing method distinguishes the segments of the target to be measured according to anatomical partitions.

[0022] Furthermore, the data analysis module determines a scanning mode of the laser scanning device according to the secondary refinement scanning difficulty level, and the scanning mode is divided into an overall scanning mode and a segmented scanning mode. The overall scanning mode is a scanning mode in which the data analysis module determines an initial scanning speed of the laser scanning device according to the secondary refinement scanning difficulty level, and the segmented scanning mode is a scanning mode in which an initial scanning speed of the laser scanning device of each zone is adjusted according to the complexity value of the two-dimensional image of each zone of the target to be measured.

[0023] Furthermore, the data analysis module obtains the front projection image, the side projection image and the back projection image of each segment of the two-dimensional image of the target to be measured, and determines the complexity value of the segmented two-dimensional image of each area according to the curvature of the edge line of each projection image and the number of segment feature points.

[0024] Furthermore, the data analysis module determines whether to adjust the actual secondary refinement scanning speed to obtain the target secondary refinement scanning speed according to a comparison result between the initial form three-dimensional image coincidence value and the standard form three-dimensional image coincidence value.

[0025] Compared with the prior art, the beneficial effect of the present invention is that, through the real-time adjustment of the control module, the telescopic rod can accurately reach the height of the target to be measured, thereby ensuring the accuracy of the measurement data. The real-time adjustment function greatly reduces the preparation time before measurement and the adjustment time during measurement, thereby improving the overall work efficiency. The mutually nested tubular parts and locking devices ensure the stability of the telescopic rod during extension and contraction, thereby reducing the measurement error caused by shaking.

[0026] Furthermore, by fixing the target to be measured on the base and ensuring its stability, the movement and vibration during the scanning process can be reduced, thereby improving the accuracy of laser scanning. Dividing the target to be measured into several sections according to anatomical divisions can make the scan data more targeted and facilitate subsequent data processing and analysis. By scanning several sections in sequence, the scanning process can be effectively organized, repeated scanning and unnecessary scanning time can be reduced, and the overall scanning efficiency can be improved. Scanning the head, torso, and limbs of the target to be measured separately and recording the scan data can more accurately reflect the three-dimensional morphology of different parts and provide detailed information for subsequent data analysis.

[0027] Furthermore, by preprocessing the two-dimensional image, including denoising, graying and binarization, the interference in the subsequent processing process can be reduced and the accuracy of feature point extraction can be improved. Adjusting the scanning difficulty level and scanning speed according to the complexity value of the image helps to optimize the scanning process and improve the overall scanning efficiency. By evaluating the complexity of the image, the scanning mode can be reasonably allocated to ensure that more scanning resources are invested in areas with high complexity, while simple areas can be scanned quickly, thereby improving the scanning efficiency. Post-processing of the secondary refined morphological three-dimensional image, including smoothing and denoising, can significantly improve the quality of the secondary refined morphological three-dimensional image, making the image clearer and richer in details, which is conducive to subsequent analysis and application. Processing high-complexity images through segmented scanning mode can reduce scanning errors caused by overly complex images and improve the accuracy of scanning results.

[0028] Furthermore, when the actual image complexity is lower than the standard complexity, the scanning speed can be accelerated by adjusting the initial scanning speed, thereby improving the overall scanning efficiency and reducing the scanning time. The adjusted scanning speed ensures that the preset image quality requirements can be maintained even when the actual complexity is low, avoiding image distortion or loss of details caused by excessive scanning speed. Dynamically adjusting the scanning speed according to the actual image complexity helps to more reasonably utilize the resources of the scanning device and avoid unnecessary energy consumption and equipment wear. The scanning device can adapt to scanning targets of different complexities, enhancing the versatility and adaptability of the device. By adjusting the scanning speed of each segment, the scanning details of each area can be more accurately controlled to ensure that areas with higher complexity obtain sufficient scanning time to capture more details. For areas where the actual complexity value of the two-dimensional image is greater than the second standard complexity value of the two-dimensional image, reducing the scanning speed can ensure image quality. The segmented scanning mode uses segmented adjustment of the scanning speed to help improve the overall scanning effect, so that the image maintains a high quality standard in different areas.

[0029] Furthermore, by dividing the facial projection image into several regions and performing detailed feature extraction and complexity calculation on each region, the accuracy of facial feature recognition can be effectively improved, providing more reliable data support for applications such as facial recognition and face reconstruction. The adaptability of facial image processing is enhanced. It is applicable to facial projection images at different angles such as the front, side and back, and can comprehensively evaluate the complexity of facial features, thus improving the adaptability of facial image processing. By calculating the edge line curvature and the number of feature points, the complexity of each facial region can be analyzed quickly and efficiently, providing convenience for subsequent facial recognition and processing. The Canny algorithm is used for edge detection, which is conducive to reducing the complexity of the overall algorithm and improving computational efficiency. According to the complexity distribution of each facial region, targeted data support is provided for the fields of facial beauty, plastic surgery, animation production, etc., which has high practical value.

[0030] Furthermore, according to the comparison result between the complexity value of the first segment segmented two-dimensional image and the standard complexity value, the laser scanning overlap height is intelligently adjusted, which can appropriately reduce the scanning overlap area and improve the scanning efficiency while ensuring the scanning quality. By accurately controlling the laser scanning overlap height, the amount of data that needs to be spliced ​​and corrected in subsequent data processing is reduced, thereby shortening the data processing time. The scanning parameters can be automatically adjusted according to the actual complexity of the target to be measured, thereby enhancing the system's adaptability to targets of different types and complexities. By reducing unnecessary scanning overlap areas, the time and resource consumption in the scanning process is reduced, thereby reducing the scanning cost. The standardized scanning overlap height ensures a good connection between the data of different scanning segments and enhances the consistency of the entire measurement data set.

[0031] Furthermore, by performing a secondary refinement scan on the first segment segment and the lower segment segment, high-resolution morphological three-dimensional image data can be obtained, thereby improving the overall accuracy of the scan. By comparing the overlapping areas of the two morphological three-dimensional images and calculating the overlap, the scanning speed can be intelligently adjusted, the scanning process can be optimized, and unnecessary scanning time can be reduced. The use of the image registration algorithm ensures that the morphological three-dimensional images of the first segment segment and the lower segment segment are aligned in space, thereby ensuring the consistency of the scan data. By automatically adjusting the scanning speed, the manual intervention required in subsequent data processing is reduced, and the data processing efficiency and automation level are improved. By reducing the overlapping scanning area and improving the scanning efficiency, the resource consumption in the scanning process is reduced, thereby reducing the scanning cost. By accurately controlling the scanning speed, the scanning error is reduced and the reliability and repeatability of the scanning results are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 Schematic diagram of the structure of the laser measuring device for measuring human body shape in this embodiment;

[0033] Figure 2 Schematic diagram of the locking device structure of the laser measuring device for measuring human body shape in this embodiment;

[0034] Figure 3 is a flow chart of the operation process of the laser measuring device for measuring human body shape in this embodiment;

[0035] Figure 4 4 is a flow chart of scanning mode determination of the laser measuring device for measuring human body shape in this embodiment.

[0036] Figure 1Middle: 1-base; 2-telescopic rod; 3-locking device; 301-locking buckle; 302-first locking claw; 303-second locking claw; 4-annular guide rail; 5-searchlight; 6-laser scanning device; 7-connecting rod. DETAILED DESCRIPTION

[0037] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0038] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0039] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0040] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0041] See also Figure 1-Figure 4 As shown, Figure 1 Schematic diagram of the structure of the laser measuring device for measuring human body shape in this embodiment; Figure 2 Schematic diagram of the locking device structure of the laser measuring device for measuring human body shape in this embodiment; Figure 3 is a flow chart of the operation process of the laser measuring device for measuring human body shape in this embodiment; Figure 4 4 is a flow chart of scanning mode determination of the laser measuring device for measuring human body shape in this embodiment.

[0042] This embodiment provides a laser measuring device for measuring human body shape, comprising:

[0043] Base 1, used for carrying the object to be measured;

[0044] A telescopic rod 2, one end of which is connected to the base and the other end is connected to the connecting rod 7, and is used to control the measuring height of the laser measuring assembly. The telescopic rod is composed of a plurality of mutually nested tubular parts, and each part can be telescoped relative to the adjacent part;

[0045] The locking device 3 is composed of a locking buckle 301, a first locking claw 302 and a second locking claw 303, and is used to fix the height of the telescopic rod;

[0046] an annular guide rail 4, which is connected to the connecting rod and is used to enable the laser measurement assembly to slide around the human body for measurement;

[0047] The laser measurement assembly is composed of the annular guide rail 4 and a searchlight 5. The annular guide rail is used for the laser scanning device to perform laser scanning around the target to be measured; the searchlight is slidably mounted on the annular guide rail to illuminate the measurement area of ​​the target to be measured, and the brightness of the searchlight can be adjusted according to the measurement requirements;

[0048] A laser scanning device 6, which is slidably connected to the annular guide rail and is used to scan the shape of the target to be measured;

[0049] An image generation module, used for generating an initial morphological three-dimensional image of the target to be measured;

[0050] An image conversion module, used for converting the morphological three-dimensional image into a two-dimensional image of the object to be measured;

[0051] A control module, used to control the telescopic length of the telescopic rod; and control the scanning speed and scanning height of the laser scanning device;

[0052] A data analysis module, which is connected to the image generation module, the image conversion module and the control module, is used to analyze the image data of the target to be detected collected by the image generation module to obtain an initial morphological three-dimensional image, and generate a two-dimensional image according to the initial morphological three-dimensional image; determine the actual two-dimensional image complexity value according to the two-dimensional image area and the number of feature points, determine the secondary refinement scanning difficulty level according to the actual complexity value of the two-dimensional image, and determine the actual secondary refinement scanning speed according to the secondary refinement scanning difficulty level; determine the scanning mode of the laser scanning device according to the secondary refinement scanning difficulty level; determine the complexity value of each segmented two-dimensional image according to the curvature of the edge line of each projection image and the number of segmented feature points; judge the overlap height of the segmented laser scanning of the next segment according to the complexity value of the segmented two-dimensional image of the first segment area of ​​the target to be measured scanned by the segmented scanning mode; and obtain the target secondary refinement scanning speed according to the comparison result of the overlap value of the initial morphological three-dimensional image and the overlap value of the standard morphological three-dimensional image.

[0053] Specifically, the height of the telescopic rod can be adjusted according to the height of the target to be measured, and can be shortened from top to bottom to meet the measurement height of the target to be measured.

[0054] The telescopic rod is composed of a plurality of mutually nested tubular parts, each part can be telescoped relative to the adjacent part, and the control module adjusts the height of the telescopic rod in real time according to the target height to be measured. Each connecting part of the telescopic rod is equipped with a locking device for fixing the height of the telescopic rod.

[0055] Through real-time adjustment of the control module, the telescopic rod can accurately reach the height of the target to be measured, thus ensuring the accuracy of the measurement data. The real-time adjustment function greatly reduces the preparation time before measurement and the adjustment time during measurement, improving the overall work efficiency. The nested tubular parts and locking devices ensure the stability of the telescopic rod during extension and contraction, reducing the measurement errors caused by shaking.

[0056] Specifically, the data analysis module performs segmentation scanning on the laser scanning area of ​​the three-dimensional image of the target morphology to be measured according to a first differentiation method, wherein the first differentiation method is to differentiate the segments of the target to be measured according to anatomical partitions.

[0057] Fix the target to be measured on the base to ensure stability, then start the laser measurement device, divide the target to be measured into several sections according to the anatomical divisions, and scan the several sections in turn with the laser scanning device.

[0058] According to the first distinguishing method, the laser scanning area of ​​the three-dimensional image of the target morphology to be measured is scanned in sections.

[0059] The head, torso and limbs of the target to be measured are scanned respectively, and the scan data are recorded and input into the data processing module.

[0060] By fixing the target to be measured on the base and ensuring its stability, the movement and vibration during the scanning process can be reduced, thereby improving the accuracy of laser scanning. Dividing the target to be measured into several sections according to anatomical divisions can make the scan data more targeted and facilitate subsequent data processing and analysis. By scanning several sections in sequence, the scanning process can be effectively organized, repeated scanning and unnecessary scanning time can be reduced, and the overall scanning efficiency can be improved. Scanning the head, torso, and limbs of the target to be measured separately and recording the scan data can more accurately reflect the three-dimensional morphology of different parts and provide detailed information for subsequent data analysis.

[0061] The data analysis module generates an initial morphological three-dimensional image based on the initial morphological three-dimensional image data of the target to be measured collected by the image generation module, and the image conversion module generates a two-dimensional image based on the initial morphological three-dimensional image, and the two-dimensional image includes a front projection image, a side projection image and a rear projection image.

[0062] Fix the target to be measured on a dedicated scanning device to ensure that the target remains still during the scanning process. Start the image generation module and use the laser scanning device to perform an all-round scan of the target to be measured to collect its three-dimensional data. The image generation module integrates the collected three-dimensional data to generate an initial three-dimensional image of the target to be measured.

[0063] The image conversion module starts to convert the two-dimensional image according to the generated initial three-dimensional image. First, the connection point between the telescopic rod and the base is used as the origin of the three-dimensional coordinate system, the straight line where the connecting rod is located is the X-axis of the three-dimensional coordinate system, the positive direction is to the right, the straight line where the telescopic rod is located is the Z-axis of the three-dimensional coordinate system, the positive direction is upward, and the straight line perpendicular to the surface formed by the connecting rod and the telescopic rod is the Y-axis of the three-dimensional coordinate system, and the straight line passes through the origin, and the positive direction is forward.

[0064] The image conversion module extracts the data of the front image from the morphological three-dimensional image and generates a front projection image, wherein the front projection image is a projection of the target to be measured in the positive direction of the Y axis on the XZ two-dimensional plane;

[0065] The image conversion module extracts the data of the side image from the morphological three-dimensional image and generates a side projection image, wherein the side projection image is a projection of the target to be measured on the YZ two-dimensional plane;

[0066] The image conversion module extracts the data of the back image from the morphological three-dimensional image and generates a back projection image, which is a projection of the target to be measured on the XZ two-dimensional plane in the opposite direction of the Y axis.

[0067] The data analysis module determines an actual two-dimensional image complexity value according to the two-dimensional image area and the number of feature points, determines a secondary refinement scanning difficulty level according to the actual two-dimensional image complexity value, determines an actual secondary refinement scanning speed according to the secondary refinement scanning difficulty level to obtain a secondary refinement scanning result, and obtains a secondary refinement morphological three-dimensional image according to the secondary refinement scanning result.

[0068] Obtain the two-dimensional image of the target to be measured and preprocess it, including denoising, grayscale, binarization and other operations, for subsequent analysis.

[0069] Feature points are extracted from the preprocessed two-dimensional image, and the number of feature points is calculated. Feature points can be corner points, edge points and other points with obvious features in the image. The area of ​​the two-dimensional image is obtained by counting the number of non-zero pixels in the image.

[0070] According to each projection Figure 2 Dimensional image area and number of feature points, calculate each projection Figure 2 The actual complexity value of the dimensional image is calculated based on the projection Figure 2 The actual complexity value of the two-dimensional image is determined by the sum of the actual complexity values ​​of the two-dimensional image;

[0071] Front projection Figure 2 The image complexity value is obtained based on the front projection area and the number of feature points of the front projection.

[0072] Side projection Figure 2 The dimensional image complexity value is obtained based on the area of ​​the side projection image and the number of feature points of the side projection image;

[0073] Rear projection Figure 2 The dimensional image complexity value is obtained based on the area of ​​the back projection image and the number of feature points of the back projection image;

[0074] The complexity value of a two-dimensional image is H=S×q1+D×q2, where S is the projection Figure 2 dimensional image area; q1 projection Figure 2 dimensional image area projection Figure 2 The compensation parameter for the influence of the complexity value of the dimensional image; D is the number of feature points in the projection image; q2 is the influence of the number of feature points in the projection image on the projection Figure 2 The compensation parameters for the influence of the complexity value of the dimensional image;

[0075] The actual complexity value of the two-dimensional image is the front projection Figure 2 Dimensional image complexity value, side projection Figure 2 dimensional image complexity values ​​and back projection Figure 2 The sum of the complexity values ​​of the dimensional image;

[0076] By statistically analyzing the complexity values ​​of two-dimensional images in historical data, the first standard complexity value of two-dimensional images and the second standard complexity value of two-dimensional images are set.

[0077] If the actual complexity value of the two-dimensional image is less than the first standard complexity value of the two-dimensional image, the secondary refinement scanning difficulty level is the primary scanning difficulty level, and the control module controls the scanning mode of the laser scanning device to be the overall scanning mode, and speeds up the initial scanning speed of the scanning device;

[0078] If the first standard complexity value of the two-dimensional image is ≤ the actual complexity value of the two-dimensional image ≤ the second standard complexity value of the two-dimensional image, the secondary refinement scanning difficulty level is the intermediate scanning difficulty level, and the control module controls the scanning mode of the laser scanning device to the overall scanning mode, and does not adjust the initial scanning speed of the scanning device;

[0079] If the actual complexity value of the two-dimensional image is greater than the second standard complexity value of the two-dimensional image, the secondary refinement scanning difficulty level is the advanced scanning difficulty level, and the control module controls the laser scanning device to adopt the segmented scanning mode;

[0080] The laser scanning device scans the two-dimensional image to be processed according to the actual secondary refinement scanning speed to obtain the secondary refinement scanning result. The image generation module performs three-dimensional reconstruction on the secondary refinement scanning result to obtain a secondary refinement morphological three-dimensional image. The secondary refinement morphological three-dimensional image is post-processed, such as smoothing and denoising operations, to obtain the final secondary refinement morphological three-dimensional image.

[0081] By preprocessing the two-dimensional image, including denoising, grayscale and binarization, the interference in the subsequent processing process can be reduced and the accuracy of feature point extraction can be improved. Adjusting the scanning difficulty level and scanning speed according to the complexity value of the image can help optimize the scanning process and improve the overall scanning efficiency. By evaluating the complexity of the image, the scanning mode can be reasonably allocated to ensure that more scanning resources are invested in areas with high complexity, while simple areas can be scanned quickly, thereby improving scanning efficiency. Post-processing of the secondary refined morphological three-dimensional image, including smoothing and denoising, can significantly improve the quality of the secondary refined morphological three-dimensional image, making the image clearer and more detailed, which is conducive to subsequent analysis and application. Processing high-complexity images through segmented scanning mode can reduce scanning errors caused by overly complex images and improve the accuracy of scanning results.

[0082] Specifically, the data analysis module determines a scanning mode of the laser scanning device according to the difficulty level of the secondary refinement scanning. The scanning mode is divided into an overall scanning mode and a segmented scanning mode. The overall scanning mode is a scanning mode in which the data analysis module determines an initial scanning speed of the laser scanning device according to the difficulty level of the secondary refinement scanning. The segmented scanning mode is a scanning mode in which the initial scanning speed of the laser scanning device in each zone is adjusted according to the complexity value of the two-dimensional image of each zone of the target to be measured.

[0083] When the scanning mode of the laser scanning device is the overall scanning mode and the actual complexity value of the two-dimensional image is less than the first standard complexity value of the two-dimensional image, the initial scanning speed of the scanning device is adjusted to obtain the adjusted initial scanning speed V0`, V0`=[1+(H1-H) / H]×V0, wherein H1 is the first standard complexity value of the two-dimensional image; V0 is the initial scanning speed of the scanning device, which is the initial scanning speed preset by the laser scanning device according to the characteristics of the target to be measured, the performance specifications of the scanning device, and the image quality requirements;

[0084] When the scanning mode of the laser scanning device is the segmented scanning mode, the initial scanning speed V1 of the segmented laser scanning device in each zone is adjusted, where V1=[1-(H-H2) / H2]×V0.

[0085] When the actual image complexity is lower than the standard complexity, the scanning speed can be increased by adjusting the initial scanning speed, thereby improving the overall scanning efficiency and reducing the scanning time. The adjusted scanning speed ensures that the preset image quality requirements can be maintained even when the actual complexity is low, avoiding image distortion or loss of details caused by excessive scanning speed. Dynamically adjusting the scanning speed according to the actual image complexity helps to more reasonably utilize the resources of the scanning device and avoid unnecessary energy consumption and equipment wear. The scanning device can adapt to scanning targets of different complexities, enhancing the versatility and adaptability of the device. By adjusting the scanning speed of each segment, the scanning details of each area can be more accurately controlled to ensure that the areas with higher complexity get enough scanning time to capture more details. For areas where the actual complexity value of the two-dimensional image is greater than the second standard complexity value of the two-dimensional image, reducing the scanning speed can ensure image quality. The segmented scanning mode uses segmented adjustment of the scanning speed to help improve the overall scanning effect, so that the image maintains a high quality standard in different areas.

[0086] Specifically, the data analysis module obtains the front projection image, side projection image and back projection image of each segment of the two-dimensional image of the target to be measured, and determines the complexity value of each segmented two-dimensional image according to the curvature of the edge line of each projection image and the number of segmented feature points.

[0087] Each 2D projection image is segmented into several regions, such as forehead, eyes, nose, mouth, chin, etc.

[0088] Extract the edge line curvature of each region, use edge detection algorithm such as Canny algorithm to detect the edge of the region, and calculate the curvature of the edge point, which is the protruding point of the edge line curve of each region.

[0089] Identify the feature points of each area, such as the corners of the eyes, the tip of the nose, the corners of the mouth, etc., and calculate the number of feature points in each area.

[0090] For the front, side and back projection images of each region, calculate the corresponding regional complexity value C, C=K×j1×W1+Da×j2×W2, where K is the curvature of the regional edge point; j1 is the compensation parameter for the impact of the curvature of the regional edge point on the regional complexity value; W1 is the weight coefficient of the curvature of the regional edge point on the regional complexity value; Da is the number of regional feature points; j2 is the compensation parameter for the impact of the number of regional feature points on the regional complexity value; W2 is the weight coefficient of the number of regional feature points on the regional complexity value;

[0091] The complexity values ​​of the front, side, and back projections of each region are averaged to obtain the final complexity value of the region.

[0092] The complexity values ​​of all regions are aggregated to obtain the complexity distribution of the segmented two-dimensional image in the first section area, and the complexity value of the segmented two-dimensional image in the first section area is determined according to the complexity distribution of the segmented two-dimensional image in the first section area.

[0093] The edge detection algorithm in this embodiment is the Canny algorithm, and there is no limitation on the algorithm that can detect the curvature of the edge line.

[0094] By dividing the facial projection image into several regions and performing detailed feature extraction and complexity calculation for each region, the accuracy of facial feature recognition can be effectively improved, providing more reliable data support for applications such as facial recognition and face reconstruction. The adaptability of facial image processing is enhanced. It is suitable for facial projection images at different angles such as the front, side and back, and can comprehensively evaluate the complexity of facial features, thus improving the adaptability of facial image processing. By calculating the edge line curvature and the number of feature points, the complexity of each facial region can be analyzed quickly and efficiently, providing convenience for subsequent facial recognition and processing. The use of the Canny algorithm for edge detection is conducive to reducing the complexity of the overall algorithm and improving computational efficiency. According to the complexity distribution of each facial region, it provides targeted data support for facial beauty, plastic surgery, animation production and other fields, with high practical value.

[0095] Specifically, the data analysis module determines the laser scanning overlap height of the lower section segment according to the complexity value of the two-dimensional image of the first section segment of the target to be measured scanned in the segmented scanning mode, so as to determine the descending height of the telescopic rod, wherein the laser scanning overlap height is the overlapping scanning height of the laser scanning height of the first section segment and the laser scanning height of the lower section segment.

[0096] The data analysis module obtains the complexity value of the first segment segment two-dimensional image, and analyzes the two-dimensional image data of the target to be measured of different types and complexities based on the historical data to obtain the first standard complexity value of the segment and the second standard complexity value of the segment.

[0097] If the complexity value of the first segmented two-dimensional image is less than the first standard complexity value of the segmented image, the laser scanning overlap height is zero;

[0098] If the first standard complexity value of the segmentation is ≤ the first segmentation 2D image complexity value ≤ the second standard complexity value of the segmentation, the laser scanning overlap height is a quarter of the initial scanning height;

[0099] If the first segment segment two-dimensional image complexity value> the segment second standard complexity value, the laser scanning overlap height is one-third of the initial scanning height;

[0100] The initial scanning height is the height of the first section of the target to be measured.

[0101] According to the comparison result of the complexity value of the first segment segmented two-dimensional image and the standard complexity value, the laser scanning overlap height is intelligently adjusted, which can appropriately reduce the scanning overlap area and improve the scanning efficiency under the premise of ensuring the scanning quality. By accurately controlling the laser scanning overlap height, the amount of data that needs to be spliced ​​and corrected in subsequent data processing is reduced, thereby shortening the data processing time. The system can automatically adjust the scanning parameters according to the actual complexity of the target to be measured, enhancing the system's adaptability to targets of different types and complexities. By reducing unnecessary scanning overlap areas, the time and resource consumption in the scanning process is reduced, thereby reducing the scanning cost. The standardized scanning overlap height ensures a good connection between the data of different scanning segments and enhances the consistency of the entire measurement data set.

[0102] Specifically, the data analysis module compares the first segment segmented secondary refined morphological three-dimensional image and the lower segment segmented secondary refined morphological three-dimensional image of the target to be measured, and obtains the initial morphological three-dimensional image overlap value according to the comparison result.

[0103] Specifically, the data analysis module determines whether to adjust the actual secondary refinement scanning speed to obtain the target secondary refinement scanning speed according to the comparison result between the initial morphology 3D image coincidence value and the standard morphology 3D image coincidence value.

[0104] The first segment of the target to be measured is scanned for a second refinement to obtain high-resolution morphological three-dimensional image data, and the second refinement morphological three-dimensional image data of the first segment is saved. The laser scanning device is moved to the position of the next segment, and the next segment is scanned for a second refinement, and the morphological three-dimensional image data of the segment is also saved.

[0105] The data analysis module receives the secondary refined morphological three-dimensional image data of the first segment segment and the lower segment segment.

[0106] Using an image processing algorithm, the overlapping areas of the secondary refined morphological three-dimensional images of the first segment segment and the lower segment segment are compared to calculate the overlap value of the initial morphological three-dimensional image, and the overlap of the secondary refined morphological three-dimensional images of the first segment segment and the lower segment segment is analyzed to obtain the overlap value of the initial morphological three-dimensional image.

[0107] Compare the initial 3D image coincidence value with the preset standard 3D image coincidence value.

[0108] If the initial morphology 3D image coincidence value ≥ the standard morphology 3D image coincidence value, it means that the coincidence is good and there is no need to adjust the actual secondary refinement scanning speed;

[0109] If the initial morphology 3D image coincidence value is less than the standard morphology 3D image coincidence value, it means that the coincidence is insufficient and the actual secondary refinement scanning speed needs to be adjusted;

[0110] When the overlap is insufficient, the target secondary refinement scanning speed Vm, Vm=[1-(G`-G) / G`]×V1, where G` is the overlap value of the standard morphology three-dimensional image; G is the overlap value of the initial morphology three-dimensional image;

[0111] Adjust the actual secondary refinement scan speed;

[0112] According to the comparison result, the data analysis module adjusts the secondary refinement scanning speed of the lower segment area segment;

[0113] If the overlap is insufficient, the scanning speed can be reduced to improve the image quality and ensure better overlap;

[0114] Obtaining the target secondary refinement scanning speed, through adjustment, the data analysis module determines the target secondary refinement scanning speed;

[0115] Use the new scanning speed to perform a second refinement scan on the subsequent segments of the target to be measured;

[0116] In the embodiment, the image processing algorithm is an image registration algorithm, and the coincidence degree of the secondary thinned morphological three-dimensional image of the first segment segment and the lower segment segment is determined by the following steps:

[0117] Image alignment: ensure that the secondary refined morphological 3D images of the first segment segmentation and the second segment segmentation are spatially aligned for comparison;

[0118] Feature matching: identifying and matching the corresponding feature points in the secondary thinned morphological 3D images of the first segment segment and the lower segment segment;

[0119] Calculation of coincidence degree: By comparing the positions and numbers of matching feature points, the coincidence degree of the secondary refined morphological three-dimensional images of the first segment segment and the next segment segment is calculated.

[0120] By performing a secondary refinement scan of the first segment segment and the lower segment segment, high-resolution morphological three-dimensional image data can be obtained, thereby improving the overall accuracy of the scan. By comparing the overlapping areas of the two morphological three-dimensional images and calculating the overlap, the scanning speed can be intelligently adjusted, the scanning process can be optimized, and unnecessary scanning time can be reduced. The use of the image registration algorithm ensures that the morphological three-dimensional images of the first segment segment and the lower segment segment are aligned in space, thereby ensuring the consistency of the scan data. By automatically adjusting the scanning speed, the manual intervention required in subsequent data processing is reduced, and the data processing efficiency and automation level are improved. By reducing the overlapping scanning area and improving the scanning efficiency, the resource consumption in the scanning process is reduced, thereby reducing the scanning cost. By accurately controlling the scanning speed, the scanning error is reduced and the reliability and repeatability of the scanning results are improved.

[0121] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0122] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A laser measuring device for measuring human body morphology, characterized in that: include, A base, used to carry the object to be measured; A telescopic rod, one end of which is connected to the base and the other end of which is connected to the connecting rod, for controlling the measuring height of the laser measuring assembly; An annular guide rail connected to the connecting rod, used to enable the laser measurement assembly to slide and scan around a human body; A laser measurement assembly, which is composed of an annular guide rail and a searchlight, wherein the annular guide rail is used for the laser scanning device to perform laser scanning around the target to be measured; A laser scanning device, which is slidably connected to the annular guide rail and is used to scan the shape of the target to be measured; An image generation module, used for generating a three-dimensional image of the morphology of the target to be measured; A control module, used to control the telescopic length of the telescopic rod; and control the scanning speed and scanning height of the laser scanning device; A data analysis module, which is connected to the image generation module, the image conversion module and the control module, and is used to analyze the morphological three-dimensional image of the target to be detected collected by the image generation module to obtain an initial morphological three-dimensional image; The image conversion module generates a two-dimensional image according to the initial three-dimensional image, wherein the two-dimensional image includes a front projection image, a side projection image, and a rear projection image; The data analysis module is further used to: determine the actual two-dimensional image complexity value according to the two-dimensional image area and the number of feature points, determine the secondary refinement scanning difficulty level according to the two-dimensional image actual complexity value, determine the actual secondary refinement scanning speed according to the secondary refinement scanning difficulty level to obtain a secondary refinement scanning result, and obtain a secondary refinement morphological three-dimensional image according to the secondary refinement scanning result; Determine the scanning mode of the laser scanning device according to the difficulty level of the secondary refinement scanning; determine the complexity value of each segmented two-dimensional image according to the curvature of the edge line of each projection image and the number of segmented feature points; According to the complexity value of the first segment segment two-dimensional image of the target to be measured scanned in the segmented scanning mode, the laser scanning overlap height of the lower segment segment is judged to determine the descending height of the telescopic rod, wherein the laser scanning overlap height of the lower segment segment is the overlap scanning height of the laser scanning height of the first segment segment and the laser scanning height of the lower segment segment; Compare the segmented secondary refined morphological three-dimensional image of the first segment area and the segmented secondary refined morphological three-dimensional image of the lower segment area of ​​the target to be measured, and obtain the overlap value of the initial morphological three-dimensional image according to the comparison result; The target secondary refinement scanning speed is obtained based on the comparison result of the initial morphology three-dimensional image coincidence value and the standard morphology three-dimensional image coincidence value.

2. The laser measuring device for measuring human body shape according to claim 1, characterized in that: The height of the telescopic rod can be adjusted according to the height of the target to be measured, and can be shortened from top to bottom to meet the measurement height of the target to be measured.

3. The laser measuring device for measuring human body shape according to claim 2, characterized in that: The data analysis module performs segmentation scanning on the laser scanning area of ​​the three-dimensional image of the target morphology to be measured according to a first differentiation method, wherein the first differentiation method is to differentiate the segments of the target to be measured according to anatomical divisions.

4. The laser measuring device for measuring human body shape according to claim 3, characterized in that: The data analysis module determines a scanning mode of the laser scanning device according to the difficulty level of the secondary refinement scanning. The scanning mode is divided into an overall scanning mode and a segmented scanning mode. The overall scanning mode is a scanning mode in which the data analysis module determines an initial scanning speed of the laser scanning device according to the difficulty level of the secondary refinement scanning. The segmented scanning mode is a scanning mode in which the initial scanning speed of the laser scanning device in each zone is adjusted according to the complexity value of the two-dimensional image of each zone of the target to be measured.

5. The laser measuring device for measuring human body shape according to claim 4, characterized in that: The data analysis module obtains the front projection image, the side projection image and the back projection image of each segment of the two-dimensional image of the target to be measured, and determines the complexity value of the segmented two-dimensional image of each area according to the curvature of the edge line of each projection image and the number of segment feature points.

6. The laser measuring device for measuring human body shape according to claim 5, characterized in that: The data analysis module determines whether to adjust the actual secondary refinement scanning speed to obtain the target secondary refinement scanning speed according to the comparison result between the initial form three-dimensional image coincidence value and the standard form three-dimensional image coincidence value.

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