Cultural relic three-dimensional digital acquisition method and device

Abstract

The invention discloses a cultural relic three-dimensional digital acquisition method and device, and relates to the technical field of cultural relic three-dimensional digital acquisition, and the method comprises the steps: employing a laser radar LiDAR to scan a cultural relic, employing a plurality of high-resolution cameras to shoot multi-angle images of the cultural relic, and obtaining a cultural relic original data set; preprocessing the historical relic original data set to obtain a high-quality historical relic data set; establishing a three-dimensional cultural relic model based on the high-quality cultural relic data set and a multi-source data fusion algorithm, inputting the high-quality cultural relic data set into the three-dimensional cultural relic model, extracting cultural relic surface roughness and cultural relic shape deviation from the three-dimensional cultural relic model by adopting a feature extraction method, and marking the cultural relic surface roughness and the cultural relic shape deviation as key features; calculating a difference value between the high-quality cultural relic data set and the key features by adopting a mean absolute error (MAE) method; setting a threshold value according to the original data set of the cultural relics, and optimizing the three-dimensional cultural relic model by adopting a parameter adjustment method according to a difference value; and evaluating the optimized three-dimensional cultural relic model by adopting a quality inspection method.

Description

Technical Field

[0001] The present invention relates to the technical field of three-dimensional digital collection of cultural relics, and in particular to a three-dimensional digital collection method and device of cultural relics. Background Art

[0002] Three-dimensional digital acquisition of cultural relics refers to the use of modern three-dimensional scanning technology and image processing technology to carry out high-precision digital recording and reconstruction of cultural relics. Its purpose is to preserve the precise geometric shape, texture details and other information of the cultural relics to facilitate subsequent research, protection, display and restoration work. The main technical means include laser radar (LiDAR), multi-view stereoscopic vision (MVS), structured light scanning, high-resolution camera shooting, etc.

[0003] In the field of three-dimensional digital acquisition technology of cultural relics, traditional three-dimensional digital acquisition methods of cultural relics result in large data noise and many outliers due to insufficient equipment precision or environmental factors, which affects the quality of the final model. In addition, when extracting key features such as surface roughness and shape deviation of cultural relics, traditional methods lack effective calculation methods, resulting in inaccurate results. At the same time, the three-dimensional reconstruction of a single data source in the existing methods is difficult to capture all the details of the cultural relics, especially in terms of complex geometric features and surface textures. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a three-dimensional digital acquisition method and device for cultural relics to solve the problems that traditional three-dimensional digital acquisition methods of cultural relics lead to large data noise and many outliers due to insufficient equipment accuracy or environmental factors, thus affecting the quality of the final model; and traditional methods lead to inaccurate results when extracting key features such as surface roughness and shape deviation of cultural relics due to the lack of effective calculation methods.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a method for collecting three-dimensional digital cultural relics, which comprises:

[0008] The LiDAR is used to scan the cultural relics, and multi-angle images of the cultural relics are taken with multiple high-resolution cameras to obtain the original data set of the cultural relics;

[0009] Preprocess the original data set of cultural relics to obtain a high-quality data set of cultural relics;

[0010] A three-dimensional cultural relic model is established based on a high-quality cultural relic dataset and a multi-source data fusion algorithm. The high-quality cultural relic dataset is input into the three-dimensional cultural relic model. The surface roughness and shape deviation of the cultural relic are extracted from the three-dimensional cultural relic model using a feature extraction method and marked as key features.

[0011] The mean absolute error (MAE) method is used to calculate the difference between the high-quality cultural relic dataset and the key features.

[0012] Thresholds are set based on the original data set of cultural relics, and parameter adjustment methods are used to optimize the three-dimensional cultural relic model based on the difference values;

[0013] Use quality inspection methods to evaluate the optimized three-dimensional cultural relic model, obtain evaluation results, and generate a quality evaluation report based on the evaluation results

[0014] As a preferred solution of the three-dimensional digital collection method of cultural relics described in the present invention, the LiDAR is used to scan the cultural relics, and a multi-resolution camera is used to take multi-angle images of the cultural relics to obtain the original data set of the cultural relics. The specific steps are:

[0015] Deploy high-precision LiDAR equipment to conduct a comprehensive scan around the cultural relics, and obtain LiDAR point cloud data by emitting laser pulses and measuring the reflection time;

[0016] Deploy multiple high-resolution cameras around the cultural relics to photograph them from different angles and obtain cultural relic camera image data;

[0017] Project the LiDAR point cloud data onto the camera image plane through the external parameter matrix to obtain the pixel coordinates corresponding to each measurement point;

[0018] The LiDAR point cloud data is constructed into a KD tree, and the KD tree is used to locate the nearest LiDAR measurement point for each pixel coordinate. The geometric relationship between the LiDAR measurement point and the pixel coordinate is obtained by using the interpolation algorithm based on the LiDAR measurement point, and the color and depth corresponding to the pixel coordinate are obtained;

[0019] The color and depth corresponding to the pixel coordinates are combined by using a direct mapping method, and fusion data of the depth map and the color image are generated;

[0020] The fused data of the generated depth map and color image are stored in a multi-channel image to form the original dataset of artifacts.

[0021] As a preferred solution of the three-dimensional digital collection method of cultural relics described in the present invention, the steps of preprocessing the original data of cultural relics to obtain a high-quality cultural relics data set are as follows:

[0022] The LiDAR point cloud data and the cultural relic camera image data in the original data set of the cultural relic are time synchronized by a synchronization control method to obtain a time synchronized cultural relic data set;

[0023] Combining local mean filtering and local outlier detection methods, the time-synchronized cultural relics dataset is subjected to denoising and outlier detection.

[0024] Through multi-view data fusion technology, the surface texture and color of cultural relics are extracted from the cultural relics camera image data;

[0025] Fill in the missing parts in the LiDAR point cloud data and obtain the preprocessed high-quality cultural relics dataset, the expression is:

[0026]

[0027] Among them, Q represents a high-quality cultural relic dataset, Represents LiDAR point cloud data, represents a set of high-resolution camera image data taken from different perspectives, k represents different camera perspectives, K is the number of cameras, and Fusion represents the multi-perspective data fusion algorithm.

[0028] As a preferred solution of the three-dimensional digital acquisition method of cultural relics described in the present invention, wherein: the three-dimensional cultural relic model is established based on the high-quality cultural relic data set and the multi-source data fusion algorithm, the high-quality cultural relic data set is input into the three-dimensional cultural relic model, and the surface roughness and shape deviation of the cultural relic are extracted from the three-dimensional cultural relic model by a feature extraction method, and marked as key features. The specific steps are:

[0029] The multi-view stereo vision algorithm MVS and high-quality cultural relic dataset are used to establish a three-dimensional cultural relic model, which is expressed as:

[0030]

[0031] Among them, H represents the three-dimensional cultural relic model, represents the color intensity of the camera image, O represents the average illumination intensity provided by the high-quality dataset Q, α and β are parameters that control the conversion relationship between color and illumination intensity, γ is a weight factor, L(θ,ρ) represents the function of calculating the illumination effect of each point in the three-dimensional cultural relic model, dA represents an area on the surface of the real cultural relic, D represents the distance from the observation point to the surface of the cultural relic, and δ is a scaling factor;

[0032] Perform normal estimation on the three-dimensional cultural relic model to obtain the normal direction of each point;

[0033] Based on the normal direction, the principal component analysis method is used to calculate the local curvature distribution of each point in the three-dimensional cultural relic model;

[0034] According to the local curvature distribution, the surface roughness R of the cultural relic in the three-dimensional cultural relic model is calculated, and the expression is:

[0035]

[0036] Among them, Ci represents the local curvature of the i-th point involved in the calculation in the three-dimensional cultural relic model, i is the index variable of the point involved in the calculation in the three-dimensional cultural relic model, C represents the average curvature of all points, and ∝ represents the number of points for calculating the surface roughness;

[0037] The Euclidean distance measurement method is used to calculate the shape deviation S of the cultural relics in the three-dimensional cultural relics model, and the expression is:

[0038]

[0039] Among them, S represents the deviation of the shape of the cultural relic, A represents the total area of ​​the surface of the cultural relic, X, Y, Z represent the coordinates of any point on the surface of the real cultural relic, X', Y', Z' represent the coordinates of the corresponding point in the three-dimensional cultural relic model, and dA represents an area on the surface of the real cultural relic;

[0040] The artifact surface roughness R and artifact shape deviation S are marked as key features.

[0041] As a preferred solution of the three-dimensional digital acquisition method of cultural relics described in the present invention, wherein: the mean absolute error MAE method is used to calculate the difference value between the high-quality cultural relic data set and the key features, and the specific steps are:

[0042] The mean absolute error (MAE) is used to calculate the difference in the surface roughness R of the cultural relic and the difference in the shape deviation S of the cultural relic in the three-dimensional cultural relic model. The expression is:

[0043]

[0044] Among them, i represents the index variable of the point involved in the calculation in the three-dimensional cultural relic model, G R Indicates the surface roughness difference, G S represents the shape deviation difference, Q R (i) represents the surface roughness of the i-th point involved in the calculation in the high-quality artifact dataset, Q S (i) represents the shape deviation of the i-th point participating in the calculation in the high-quality cultural relic dataset, R(i) represents the surface roughness of the i-th point participating in the calculation in the three-dimensional cultural relic model, S(i) represents the shape deviation of the i-th point participating in the calculation in the three-dimensional cultural relic model, and Δ represents the number of points participating in the calculation in the three-dimensional cultural relic model;

[0045] The surface roughness difference G is calculated using the weighted average method. R and shape deviation difference G S The comprehensive difference value is expressed as:

[0046]

[0047] Among them, G represents the comprehensive difference value, wR The weight of the surface roughness difference, w S The weight representing the shape deviation difference, G R Indicates the surface roughness difference, G S Indicates the shape deviation difference.

[0048] As a preferred solution of the three-dimensional digital acquisition method of cultural relics described in the present invention, wherein: the threshold is set according to the original data set of cultural relics, and the three-dimensional cultural relic model is optimized by a parameter adjustment method according to the difference value, and the specific steps are:

[0049] Set the comprehensive difference threshold π and compare it with the comprehensive difference value G;

[0050] When G ≤ π, it means that the quality of the 3D cultural relic model is good and no further adjustment is required;

[0051] When G>π, it indicates that the three-dimensional cultural relic model has inconsistencies and problem areas, and the three-dimensional cultural relic model is optimized;

[0052] A global registration algorithm is used to capture the initial rotation matrix V and initial translation vector ∩ in the 3D cultural relic model;

[0053] The iterative optimization algorithm is used to adjust the initial rotation matrix V and initial translation vector ∩ in the three-dimensional cultural relic model to obtain the optimized three-dimensional cultural relic model, which is expressed as:

[0054] V new =V·exp(Δr);

[0055] ∩ new =∩+Δt;

[0056] Where exp(Δr) represents the exponential mapping based on the increment Δr, exp represents the exponential function, Δt represents the translation increment, V represents the initial rotation matrix, ∩ represents the initial translation vector, V new represents the optimized rotation matrix, ∩ new Represents the optimized translation vector.

[0057] As a preferred solution of the three-dimensional digital acquisition method of cultural relics described in the present invention, wherein: the optimized three-dimensional cultural relic model is analyzed by the quality inspection method to obtain the analysis results, and a quality assessment report is generated based on the analysis results. The specific steps are:

[0058] Based on the optimized three-dimensional cultural relic model, re-enter the comprehensive difference value G new , and re-align with the comprehensive difference threshold π, set the number of iterations until G is satisfied new When ≤π or the number of iterations is reached, the optimization is stopped;

[0059] The quality inspection method is used to mark all abnormal points that exceed the comprehensive difference threshold π, and the CloudCompare analysis software is run to analyze the surface roughness difference G R The distribution of the difference between the shape deviation G S , and at the same time measure the deviation value between the geometric shape of the three-dimensional cultural relic model and the reference model to obtain the analysis result;

[0060] The analysis results are summarized to obtain an evaluation report.

[0061] In a second aspect, the present invention provides a three-dimensional digital collection device for cultural relics, including: a data collection module, a data processing module, a feature extraction module, an evaluation and optimization module, and a report generation module;

[0062] The data acquisition module is used to use LiDAR to comprehensively scan the cultural relics and use a multi-resolution camera to take multi-angle images of the cultural relics to obtain the original data set of the cultural relics;

[0063] The data preprocessing module is used to preprocess the original data set of cultural relics to remove noise and outliers to obtain a high-quality cultural relics data set;

[0064] The feature extraction module is used to establish a three-dimensional cultural relic model based on a high-quality cultural relic data set and a multi-source data fusion algorithm, and to extract key features from the three-dimensional cultural relic model using a feature extraction method;

[0065] The evaluation and optimization module uses the mean absolute error (MAE) method to calculate the difference between the high-quality cultural relic data set and the key features;

[0066] The report generation module is used to perform quality inspection on the optimized three-dimensional cultural relic model, mark all abnormal points that exceed the comprehensive difference threshold, analyze the distribution of surface roughness differences and shape deviation differences, and generate a quality assessment report based on the analysis results.

[0067] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the three-dimensional digital acquisition method of cultural relics as described in the first aspect of the present invention is implemented.

[0068] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the method for three-dimensional digital acquisition of cultural relics as described in the first aspect of the present invention is implemented.

[0069] The beneficial effects of the present invention are as follows: through the combined use of LiDAR and multi-high resolution cameras, not only the accuracy and integrity of the data are improved, but also the ability to capture complex structures and subtle features is enhanced, and the risk of information omission is reduced; the use of advanced multi-source data fusion and geometric registration technology not only improves the geometric accuracy of the model, but also ensures the realism of texture mapping, so that the three-dimensional cultural relic model can truly reflect the actual form and details of the cultural relics, which is convenient for subsequent research and display; the MAE method is used to calculate the difference value, and the threshold is set for optimization and adjustment, which ensures a high degree of consistency in the geometric structure and surface features of the model, reduces inconsistencies and errors, and improves the overall quality of the model; by setting a comprehensive difference threshold and performing multiple iterative optimizations, it is ensured that the model gradually approaches the ideal state and ultimately reaches high-quality standards. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0071] Figure 1 This is a flow chart of a method for three-dimensional digital acquisition of cultural relics in Example 1.

[0072] Figure 2 This is a schematic diagram of the three-dimensional digital acquisition device for cultural relics in Example 1. DETAILED DESCRIPTION

[0073] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0074] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0075] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0076] Example 1, reference Figure 1 and Figure 2, which is the first embodiment of the present invention, provides a method for collecting three-dimensional digital cultural relics, comprising the following steps:

[0077] S1. Scan the cultural relics using LiDAR and use multiple high-resolution cameras to take multi-angle images of the cultural relics to obtain the original data set of the cultural relics;

[0078] Furthermore, high-precision LiDAR equipment is deployed to conduct a comprehensive scan around the cultural relics, and LiDAR point cloud data is obtained by emitting laser pulses and measuring the reflection time;

[0079] Deploy multiple high-resolution cameras around the cultural relics to photograph them from different angles and obtain cultural relic camera image data;

[0080] Project the LiDAR point cloud data onto the camera image plane through the external parameter matrix to obtain the pixel coordinates corresponding to each measurement point;

[0081] The LiDAR point cloud data is constructed into a KD tree, and the KD tree is used to locate the nearest LiDAR measurement point for each pixel coordinate. The geometric relationship between the LiDAR measurement point and the pixel coordinate is obtained by using the interpolation algorithm based on the LiDAR measurement point, and the color and depth corresponding to the pixel coordinate are obtained;

[0082] The color and depth corresponding to the pixel coordinates are combined by using a direct mapping method, and fusion data of the depth map and the color image are generated;

[0083] The fused data of the generated depth map and color image are stored in a multi-channel image to form an original data set of cultural relics;

[0084] It should be noted that by fusing LiDAR point cloud data with multi-view camera image data, it is ensured that each pixel contains not only color but also accurate depth. The fusion method can effectively improve the integrity and accuracy of the data, which is especially important when dealing with complex geometric shapes and cultural relics with rich textures. In addition, the use of direct mapping method to combine depth and color simplifies the data processing process, improves efficiency, and ensures data consistency and reliability.

[0085] S2, preprocessing the original data set of cultural relics to obtain a high-quality cultural relics data set;

[0086] Furthermore, the LiDAR point cloud data and the cultural relic camera image data in the original data set of the cultural relic are time synchronized by a synchronization control method to obtain a time synchronized cultural relic data set;

[0087] Combining local mean filtering and local outlier detection methods, the time-synchronized cultural relics dataset is subjected to denoising and outlier detection.

[0088] Through multi-view data fusion technology, the surface texture and color of cultural relics are extracted from the cultural relics camera image data;

[0089] Fill in the missing parts in the LiDAR point cloud data and obtain the preprocessed high-quality cultural relics dataset, the expression is:

[0090]

[0091] Among them, Q represents a high-quality cultural relic dataset, Represents LiDAR point cloud data, represents a collection of high-resolution camera image data taken from different viewpoints, k represents different camera viewpoints, K is the number of cameras, and Fusion represents a multi-view data fusion algorithm;

[0092] It should be noted that time synchronization ensures the temporal consistency of LiDAR data and camera images, reducing errors caused by asynchrony. Local mean filtering and outlier detection effectively remove noise and outliers, improving the quality of LiDAR data and cultural relics camera image data. Multi-view data fusion technology further supplements the missing parts in the LiDAR point cloud, making the high-quality cultural relics data set more complete and accurate, providing a solid foundation for subsequent three-dimensional reconstruction.

[0093] S3. Building a three-dimensional cultural relic model based on a high-quality cultural relic dataset and a multi-source data fusion algorithm, inputting the high-quality cultural relic dataset into the three-dimensional cultural relic model, and using a feature extraction method to extract the surface roughness and shape deviation of the cultural relic from the three-dimensional cultural relic model, marking them as key features;

[0094] Furthermore, a multi-view stereo vision algorithm MVS and a high-quality cultural relic dataset are used to build a three-dimensional cultural relic model, which is expressed as:

[0095]

[0096] Among them, H represents the three-dimensional cultural relic model, represents the color intensity of the camera image, O represents the average illumination intensity provided by the high-quality dataset Q, α and β are parameters that control the conversion relationship between color and illumination intensity, γ is a weight factor, L(θ,ρ) represents the function of calculating the illumination effect of each point in the three-dimensional cultural relic model, dA represents an area on the surface of the real cultural relic, D represents the distance from the observation point to the surface of the cultural relic, and δ is a scaling factor;

[0097] Perform normal estimation on the three-dimensional cultural relic model to obtain the normal direction of each point;

[0098] Based on the normal direction, the principal component analysis method is used to calculate the local curvature distribution of each point in the three-dimensional cultural relic model;

[0099] According to the local curvature distribution, the surface roughness R of the cultural relic in the three-dimensional cultural relic model is calculated, and the expression is:

[0100]

[0101] Among them, C i represents the local curvature of the i-th point involved in the calculation in the three-dimensional cultural relic model, i is the index variable of the point involved in the calculation in the three-dimensional cultural relic model, C represents the average curvature of all points, and ∝ represents the number of points for calculating the surface roughness;

[0102] The Euclidean distance measurement method is used to calculate the shape deviation S of the cultural relics in the three-dimensional cultural relics model, and the expression is:

[0103]

[0104] Among them, S represents the deviation of the shape of the cultural relic, A represents the total area of ​​the surface of the cultural relic, X, Y, Z represent the coordinates of any point on the surface of the real cultural relic, X', Y', Z' represent the coordinates of the corresponding point in the three-dimensional cultural relic model, and dA represents an area on the surface of the real cultural relic;

[0105] Mark the artifact surface roughness R and artifact shape deviation S as key features;

[0106] It should be noted that the three-dimensional cultural relic model established by combining the multi-view stereo vision algorithm with a high-quality cultural relic dataset reconstructs the true three-dimensional structure of the cultural relic by fusing image information from different perspectives. Normal estimation and principal component analysis rely on the data of the surrounding point cloud when calculating the local curvature distribution of each point, which helps to identify tiny features on the surface of the cultural relic. The Euclidean distance measurement method is used to evaluate the shape deviation of the cultural relic, which provides a method to directly compare the three-dimensional cultural relic model with the actual geometric morphology of the cultural relic. The extracted surface roughness and shape deviation of the cultural relic are key features, which are crucial for the condition assessment, protection and restoration of the cultural relic.

[0107] S4. Use feature extraction method to extract the surface roughness and shape deviation of cultural relics from the three-dimensional cultural relic model as key features, and use mean absolute error (MAE) method to calculate the difference between the high-quality cultural relic data set and the key features;

[0108] Furthermore, the mean absolute error (MAE) is used to calculate the difference in the surface roughness R of the cultural relic and the difference in the shape deviation S of the cultural relic in the three-dimensional cultural relic model. The expression is:

[0109]

[0110] Among them, i represents the index variable of the point involved in the calculation in the three-dimensional cultural relic model, G R Indicates the surface roughness difference, G S represents the shape deviation difference, Q R (i) represents the surface roughness of the i-th point involved in the calculation in the high-quality artifact dataset, Q S (i) represents the shape deviation of the i-th point involved in the calculation in the high-quality cultural relic dataset, R(i) represents the surface roughness of the i-th point involved in the calculation in the three-dimensional cultural relic model, S(i) represents the shape deviation of the i-th point involved in the calculation in the three-dimensional cultural relic model, Indicates the number of points involved in the calculation in the three-dimensional cultural relic model;

[0111] The surface roughness difference G is calculated using the weighted average method. R and shape deviation difference G S The comprehensive difference value is expressed as:

[0112]

[0113] Among them, G represents the comprehensive difference value, w R The weight of the surface roughness difference, w S The weight representing the shape deviation difference, G R Indicates the surface roughness difference, G S Indicates shape deviation differences;

[0114] It should be noted that by calculating the difference values ​​of surface roughness and shape deviation respectively, and combining the differences in these two aspects using the weighted average method, a more comprehensive evaluation index can be obtained. The comprehensive difference value not only reflects the degree of similarity between the three-dimensional cultural relic model and the original cultural relic, but also reflects the importance of different features to the overall representation of the cultural relic.

[0115] S5, setting a threshold value according to the original data set of cultural relics, and optimizing the three-dimensional cultural relic model by using a parameter adjustment method according to the difference value;

[0116] Furthermore, a comprehensive difference threshold π is set based on the original data set of cultural relics and compared with the comprehensive difference value G;

[0117] When G ≤ π, it means that the quality of the 3D cultural relic model is good and no further adjustment is required;

[0118] When G>π, it indicates that the three-dimensional cultural relic model has inconsistencies and problem areas, and the three-dimensional cultural relic model is optimized;

[0119] A global registration algorithm is used to capture the initial rotation matrix V and initial translation vector ∩ in the 3D cultural relic model;

[0120] The iterative optimization algorithm is used to adjust the initial rotation matrix V and initial translation vector ∩ in the three-dimensional cultural relic model to obtain the optimized three-dimensional cultural relic model, which is expressed as:

[0121] V new =V·exp(Δr);

[0122] ∩ new =∩+Δt;

[0123] Where exp(Δr) represents the exponential mapping based on the increment Δr, exp represents the exponential function, Δt represents the translation increment, V represents the initial rotation matrix, ∩ represents the initial translation vector, V new represents the optimized rotation matrix, ∩ new represents the optimized translation vector;

[0124] It should be noted that setting a comprehensive difference threshold and comparing it with the comprehensive difference value is an important means to ensure the quality of the three-dimensional cultural relic model. When the three-dimensional cultural relic model meets the expected standard, no further adjustment is required; when there is inconsistency, adjustment is made through the geometric alignment ICP algorithm and the iterative optimization algorithm to gradually improve the accuracy of the three-dimensional cultural relic model. This not only ensures the quality of the three-dimensional cultural relic model, but also improves the efficiency of the optimization process, avoids the problem of over-optimization or under-optimization, and ensures that the three-dimensional cultural relic model meets high standards.

[0125] S6. Evaluate the optimized three-dimensional cultural relic model using a quality inspection method to obtain an evaluation result, and generate a quality evaluation report based on the evaluation result;

[0126] Furthermore, based on the optimized three-dimensional cultural relic model, the comprehensive difference value G is re-entered new , and re-align with the comprehensive difference threshold π, set the number of iterations until G is satisfied new When ≤π or the number of iterations is reached, the optimization is stopped;

[0127] The quality inspection method is used to mark all abnormal points that exceed the comprehensive difference threshold π, and the CloudCompare analysis software is run to analyze the surface roughness difference G R The distribution of the difference between the shape deviation G S , and simultaneously measure the deviation value between the geometric shape of the three-dimensional cultural relic model and the reference model, and obtain the analysis results, including the location, number, deviation value, spatial distribution map of the abnormal points, surface roughness and shape deviation;

[0128] Summarize the analysis results and obtain an evaluation report;

[0129] It should be noted that by re-entering the comprehensive difference expression and setting the number of iterations, the optimization process is terminated when the expected standard or the maximum number of iterations is reached to prevent unnecessary repeated calculations. The quality inspection method is used to mark abnormal points that exceed the comprehensive difference threshold and analyze the distribution of surface roughness differences and shape deviation differences to provide detailed analysis results. The final summary evaluation report not only reflects the quality status of the three-dimensional cultural relic model, but also provides an important reference for subsequent research and protection work, ensuring the effectiveness and reliability of the three-dimensional digital acquisition method of cultural relics.

[0130] This embodiment also provides a three-dimensional digital collection device for cultural relics, including: a data collection module, a data processing module, a feature extraction module, an evaluation and optimization module, and a report generation module;

[0131] The data acquisition module is used to use LiDAR to comprehensively scan the cultural relics and use multiple high-resolution cameras to take multi-angle images of the cultural relics to obtain the original data set of the cultural relics;

[0132] The data preprocessing module is used to preprocess the original data set of cultural relics to remove noise and outliers and obtain a high-quality cultural relics data set;

[0133] A feature extraction module is used to establish a three-dimensional cultural relic model based on a high-quality cultural relic data set and a multi-source data fusion algorithm, and to extract key features from the three-dimensional cultural relic model using a feature extraction method;

[0134] The evaluation and optimization module uses the mean absolute error (MAE) method to calculate the difference between the high-quality cultural relic dataset and the key features;

[0135] Report generation module, used to check the quality of the optimized 3D cultural relic model, mark all abnormal points that exceed the comprehensive difference threshold, analyze the distribution of surface roughness difference and shape deviation difference, and generate a quality assessment report based on the analysis results

[0136] This embodiment also provides a computer device, which is applicable to a three-dimensional digital collection method of cultural relics, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement a three-dimensional digital collection method of cultural relics as proposed in the above embodiment.

[0137] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0138] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, a three-dimensional digital acquisition method of cultural relics as proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination of them, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0139] In summary, the present invention not only improves the accuracy and integrity of the data through the combined use of LiDAR and multi-high resolution cameras, but also enhances the ability to capture complex structures and subtle features, reduces the risk of information omission, and adopts advanced multi-source data fusion and geometric registration technology, which not only improves the geometric accuracy of the model, but also ensures the realism of texture mapping, so that the three-dimensional cultural relic model can truly reflect the actual form and details of the cultural relics, which is convenient for subsequent research and display. The MAE method is used to calculate the difference value, and the threshold is set for optimization and adjustment, which ensures the high consistency of the model in geometric structure and surface features, reduces inconsistency and errors, and improves the overall quality of the model. By setting a comprehensive difference threshold and performing multiple iterative optimizations, it is ensured that the model gradually approaches the ideal state and finally reaches the high quality standard.

[0140] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for collecting three-dimensional digital images of cultural relics, characterized in that: include: The LiDAR is used to scan the cultural relics, and multi-angle images of the cultural relics are taken with multiple high-resolution cameras to obtain the original data set of the cultural relics; Preprocess the original data set of cultural relics to obtain a high-quality data set of cultural relics; A three-dimensional cultural relic model is established based on a high-quality cultural relic dataset and a multi-source data fusion algorithm. The high-quality cultural relic dataset is input into the three-dimensional cultural relic model. The surface roughness and shape deviation of the cultural relic are extracted from the three-dimensional cultural relic model using a feature extraction method and marked as key features. The mean absolute error (MAE) method is used to calculate the difference between the high-quality cultural relic dataset and the key features. Thresholds are set based on the original data set of cultural relics, and parameter adjustment methods are used to optimize the three-dimensional cultural relic model based on the difference values; The optimized three-dimensional cultural relic model is evaluated using a quality inspection method to obtain evaluation results, and a quality assessment report is generated based on the evaluation results.

2. The method for collecting three-dimensional digital cultural relics according to claim 1, characterized in that: The LiDAR is used to scan the cultural relics, and a multi-resolution camera is used to take multi-angle images of the cultural relics to obtain the original data set of the cultural relics. The specific steps are as follows: Deploy high-precision LiDAR equipment to conduct a comprehensive scan around the cultural relics, and obtain LiDAR point cloud data by emitting laser pulses and measuring the reflection time; Deploy multiple high-resolution cameras around the cultural relics to photograph them from different angles and obtain cultural relic camera image data; Project the LiDAR point cloud data onto the camera image plane through the external parameter matrix to obtain the pixel coordinates corresponding to each measurement point; The LiDAR point cloud data is constructed into a KD tree, and the KD tree is used to locate the nearest LiDAR measurement point for each pixel coordinate. The geometric relationship between the LiDAR measurement point and the pixel coordinate is obtained by using the interpolation algorithm based on the LiDAR measurement point, and the color and depth corresponding to the pixel coordinate are obtained; The color and depth corresponding to the pixel coordinates are combined by using a direct mapping method, and fusion data of the depth map and the color image are generated; The fused data of the generated depth map and color image are stored in a multi-channel image to form the original dataset of artifacts.

3. The method for collecting three-dimensional digital cultural relics according to claim 2, characterized in that: The raw data of cultural relics are preprocessed to obtain a high-quality cultural relics data set, and the specific steps are as follows: The LiDAR point cloud data and the cultural relic camera image data in the original data set of the cultural relic are time synchronized by a synchronization control method to obtain a time synchronized cultural relic data set; Combining local mean filtering and local outlier detection methods, the time-synchronized cultural relics dataset is subjected to denoising and outlier detection. Through multi-view data fusion technology, the surface texture and color of cultural relics are extracted from the cultural relics camera image data; Fill in the missing parts in the LiDAR point cloud data and obtain the preprocessed high-quality cultural relics dataset, the expression is: Among them, Q represents a high-quality cultural relic dataset, Represents LiDAR point cloud data, represents a set of high-resolution camera image data taken from different perspectives, k represents different camera perspectives, K is the number of cameras, and Fusion represents the multi-perspective data fusion algorithm.

4. The method for collecting three-dimensional digital cultural relics according to claim 3, characterized in that: The three-dimensional cultural relic model is established based on the high-quality cultural relic data set and the multi-source data fusion algorithm, the high-quality cultural relic data set is input into the three-dimensional cultural relic model, and the surface roughness and shape deviation of the cultural relic are extracted from the three-dimensional cultural relic model by the feature extraction method, and marked as key features. The specific steps are as follows: The multi-view stereo vision algorithm MVS and high-quality cultural relic dataset are used to establish a three-dimensional cultural relic model, which is expressed as: Among them, H represents the three-dimensional cultural relic model, represents the color intensity of the camera image, O represents the average illumination intensity provided by the high-quality dataset Q, α and β are parameters that control the conversion relationship between color and illumination intensity, γ is a weight factor, L(θ,ρ) represents the function of calculating the illumination effect of each point in the three-dimensional cultural relic model, dA represents an area on the surface of the real cultural relic, D represents the distance from the observation point to the surface of the cultural relic, and δ is a scaling factor; Perform normal estimation on the three-dimensional cultural relic model to obtain the normal direction of each point; Based on the normal direction, the principal component analysis method is used to calculate the local curvature distribution of each point in the three-dimensional cultural relic model; According to the local curvature distribution, the surface roughness R of the cultural relic in the three-dimensional cultural relic model is calculated, and the expression is: Among them, C i It represents the local curvature of the i-th point involved in the calculation in the three-dimensional cultural relic model. i is the index variable of the point involved in the calculation in the three-dimensional cultural relic model. represents the average curvature of all points, ∝ represents the number of points for calculating surface roughness; The Euclidean distance measurement method is used to calculate the shape deviation S of the cultural relics in the three-dimensional cultural relics model, and the expression is: Among them, S represents the deviation of the shape of the cultural relic, A represents the total area of ​​the surface of the cultural relic, X, Y, Z represent the coordinates of any point on the surface of the real cultural relic, X', Y', Z' represent the coordinates of the corresponding point in the three-dimensional cultural relic model, and dA represents an area on the surface of the real cultural relic; The artifact surface roughness R and artifact shape deviation S are marked as key features.

5. The method for collecting three-dimensional digital cultural relics according to claim 4, characterized in that: The mean absolute error (MAE) method is used to calculate the difference between the high-quality cultural relic data set and the key features. The specific steps are as follows: The mean absolute error (MAE) is used to calculate the difference in the surface roughness R of the cultural relic and the difference in the shape deviation S of the cultural relic in the three-dimensional cultural relic model. The expression is: Among them, i represents the index variable of the point involved in the calculation in the three-dimensional cultural relic model, G R Indicates the surface roughness difference, G S represents the shape deviation difference, Q R (i) represents the surface roughness of the i-th point involved in the calculation in the high-quality artifact dataset, Q S (i) represents the shape deviation of the i-th point involved in the calculation in the high-quality cultural relic dataset, R(i) represents the surface roughness of the i-th point involved in the calculation in the three-dimensional cultural relic model, S(i) represents the shape deviation of the i-th point involved in the calculation in the three-dimensional cultural relic model, Indicates the number of points involved in the calculation in the three-dimensional cultural relic model; The surface roughness difference G is calculated using the weighted average method. R and shape deviation difference G S The comprehensive difference value is expressed as: Among them, G represents the comprehensive difference value, W R The weight of the surface roughness difference, w S The weight representing the shape deviation difference, G R Indicates the surface roughness difference, G S Indicates the shape deviation difference.

6. The method for collecting three-dimensional digital cultural relics according to claim 5, characterized in that: The threshold is set according to the original data set of cultural relics, and the parameter adjustment method is used to optimize the three-dimensional cultural relics model according to the difference value. The specific steps are: Set the comprehensive difference threshold π and compare it with the comprehensive difference value G; When G ≤ π, it means that the quality of the 3D cultural relic model is good and no further adjustment is required; When G>π, it indicates that the three-dimensional cultural relic model has inconsistencies and problem areas, and the three-dimensional cultural relic model is optimized; A global registration algorithm is used to capture the initial rotation matrix V and initial translation vector ∩ in the 3D cultural relic model; The iterative optimization algorithm is used to adjust the initial rotation matrix V and initial translation vector ∩ in the three-dimensional cultural relic model to obtain the optimized three-dimensional cultural relic model, which is expressed as: V new =V·exp(△r); ∩ new ＝∩+△t； Where exp(△r) represents the exponential mapping based on the increment Δr, exp represents the exponential function, Δt represents the translation increment, V represents the initial rotation matrix, ∩ represents the initial translation vector, V new represents the optimized rotation matrix, ∩ new Represents the optimized translation vector.

7. The method for collecting three-dimensional digital images of cultural relics as claimed in claim 6, characterized in that: The quality inspection method is used to analyze the optimized three-dimensional cultural relic model to obtain analysis results, and a quality assessment report is generated based on the analysis results. The specific steps are: Based on the optimized three-dimensional cultural relic model, re-enter the comprehensive difference value G new , and re-align with the comprehensive difference threshold π, set the number of iterations until G is satisfied new When ≤π or the number of iterations is reached, the optimization is stopped; The quality inspection method is used to mark all abnormal points that exceed the comprehensive difference threshold π, and the CloudCompare analysis software is run to analyze the surface roughness difference G R The distribution of the difference between the shape deviation G S , and at the same time measure the deviation value between the geometric shape of the three-dimensional cultural relic model and the reference model to obtain the analysis result; The analysis results are summarized to obtain an evaluation report.

8. A three-dimensional digital collection device for cultural relics, based on a three-dimensional digital collection method for cultural relics according to any one of claims 1 to 7, characterized in that: It includes data acquisition module, data processing module, feature extraction module, evaluation and optimization module and report generation module; The data acquisition module is used to use LiDAR to comprehensively scan the cultural relics and use a multi-resolution camera to take multi-angle images of the cultural relics to obtain the original data set of the cultural relics; The data preprocessing module is used to preprocess the original data set of cultural relics to remove noise and outliers to obtain a high-quality cultural relics data set; The feature extraction module is used to establish a three-dimensional cultural relic model based on a high-quality cultural relic data set and a multi-source data fusion algorithm, and to extract key features from the three-dimensional cultural relic model using a feature extraction method; The evaluation and optimization module uses the mean absolute error (MAE) method to calculate the difference between the high-quality cultural relic data set and the key features; The report generation module is used to perform quality inspection on the optimized three-dimensional cultural relic model, mark all abnormal points that exceed the comprehensive difference threshold, analyze the distribution of surface roughness differences and shape deviation differences, and generate a quality assessment report based on the analysis results.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the three-dimensional digital acquisition method of cultural relics 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 three-dimensional digital acquisition method of cultural relics described in any one of claims 1 to 7 are implemented.

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