A method for processing cultural relic data by using a three-dimensional scanner

Abstract

The present application relates to the technical field of cultural relic protection, and particularly relates to a method for processing cultural relic data by using a three-dimensional scanner, which comprises the following steps: obtaining scanning data and photogrammetry data of a cultural relic; obtaining environmental parameters of an environment where the cultural relic is located in real time, establishing a mapping relationship between the environmental parameters and deformation of the cultural relic, and dynamically correcting the scanning data; the environmental parameters comprise temperature, humidity and vibration data; obtaining multispectral data of the cultural relic in real time, combining the scanning data, and establishing cultural relic material data matched with a surface structure of the cultural relic; identifying sensitivity of the cultural relic material to a laser wavelength, dynamically adjusting scanning parameters according to a sensitivity identification result, and correcting the scanning data; and constructing a multi-modal data fusion framework for fusion of the scanning data, the photogrammetry data and the multispectral data, so as to realize digitization of the cultural relic.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of cultural relic protection, and particularly relates to a method for processing cultural relic data by using a three-dimensional scanner. BACKGROUND

[0002] Digitizing cultural relics is a new method for cultural relic protection, but many cultural relics have irregular shapes and may have fine carvings or textures, which have high requirements for the resolution and accuracy of scanning. For example, the decorations on bronze wares or the cracks on pottery, cultural relics of different materials have different adaptability to scanning technology. For example, metal may reflect light and may deform under infrared light, while ceramic or mural may have large surface color differences, resulting in noise or data loss during scanning, and may have color changes under ultraviolet light.

[0003] During scanning, some cultural relics may deform due to changes in environmental factors (such as temperature and humidity), such as wooden cultural relics that are prone to swelling due to moisture, which may result in inaccurate scanning data. The amount of data generated by three-dimensional scanning is very large, especially for high-precision models, which requires the fusion of multiple types of data. SUMMARY

[0004] The present application can be used for processing scanning data in a dynamic environment, combining multiple types of data to correct cultural relic scanning data. Considering that laser wavelength may cause deformation of the surface of cultural relics and may be superimposed with the influence of environmental factors, causing errors in scanning data, the method of dynamically adjusting the wavelength and power of the scanning laser by identifying the wavelength sensitivity of the cultural relic is adopted.

[0005] The technical solution provided by the present application is: a method for processing cultural relic data by using a three-dimensional scanner, the method comprising: acquiring scanning data and photogrammetry data of a cultural relic;

[0006] Real-time acquisition of environmental parameters of the environment where the cultural relic is located, establishment of a mapping relationship between the environmental parameters and the deformation of the cultural relic, and dynamic correction of the scanning data; the environmental parameters include temperature, humidity and vibration data;

[0007] Real-time acquisition of multispectral data of the cultural relic, combination of the scanning data, and establishment of cultural relic material data matched with the surface structure of the cultural relic;

[0008] Identification of the sensitivity of the cultural relic material to the laser wavelength, dynamic adjustment of the scanning parameters according to the sensitivity identification result, and correction of the scanning data;

[0009] Construction of a multi-modal data fusion framework for the fusion of scanning data, photogrammetry data and multispectral data, and realization of the digitization of cultural relics.

[0010] Preferably, the acquisition of scanning data and photogrammetry data of the cultural relic comprises:

[0011] acquire laser point cloud data of the cultural relic through a three-dimensional scanner;

[0012] acquire RGB images of the cultural relic from multiple angles through a camera device, and add angle identification labels to the RGB images of each angle.

[0013] Preferably, the environment parameters of the environment where the cultural relic is located are acquired in real time, a mapping relationship between the environment parameters and the deformation of the cultural relic is established, and the scanning data is dynamically corrected, including:

[0014] An environmental deformation model is constructed: ΔL=L0·α·ΔT+L0·β·ΔH; wherein ΔL represents a deformation compensation amount, L0 represents an original size of the cultural relic, α represents a thermal expansion coefficient, β represents a humidity expansion coefficient, ΔH represents a humidity change amount, and ΔT represents a temperature change amount;

[0015] During scanning, the laser point cloud coordinates are corrected in reverse by calculating the deformation compensation amount;

[0016] A state equation is constructed, Kalman filtering or particle filtering is used, the environment parameters are taken as state variables, and deformation noise is dynamically predicted and eliminated;

[0017] The state equation is: x k =F Xu k-1 +Bu k +w k , wherein F and B represent state transition matrix and input control matrix respectively, x k represents a current state variable, i.e., a deformation variable; x k-1 represents a state variable at a previous time, u k represents an environment parameter vector, i.e., a temperature and humidity vector; and w k represents process noise.

[0018] Preferably, the environment parameters of the environment where the cultural relic is located are acquired in real time, a mapping relationship between the environment parameters and the deformation of the cultural relic is established, and the scanning data is dynamically corrected, further including:

[0019] An incremental SLAM technology is used in combination with pose graph optimization to dynamically adjust local deformation.

[0020] Specifically, the following steps are included:

[0021] Scanning data is acquired, 10-30 frames of laser point cloud data of the cultural relic are acquired per second, and a laser point cloud data set is constructed;

[0022] Temperature data and humidity data are acquired at the same time, and a temperature and humidity vector set is constructed; the acquisition frequency of the temperature data and the humidity data is not less than 1 Hz;

[0023] The pose of the three-dimensional scanner is acquired;

[0024] Extracting point cloud feature data and temperature and humidity feature vectors from the laser point cloud dataset and the temperature and humidity dataset respectively to form a point cloud feature dataset and a temperature and humidity feature vector set respectively;

[0025] Constructing a pose graph, specifically including:

[0026] The pose T′ corresponding to each frame of laser point cloud data i As nodes, initialize the motion trajectory of the 3D scanner; the relative changes of nodes between two scans are used as edges;

[0027] Construct an environment-deformation constraint model, including:

[0028] Environmental parameters are introduced as deformation constraints, and the local deformation matrix is ​​calculated according to the changes in temperature and humidity: d=α·ΔT+β·ΔH; where, ΔT env represents the expected deformation of the cultural relic caused by environmental parameters, I represents the identity matrix, and d represents the deformation translation vector;

[0029] ΔT env Connect adjacent nodes as a priori edges, minimize the Mahalanobis distance of all edges, and use the covariance of environmental parameters as a deformation constraint to adjust the relationship between edges;

[0030] The pose graph is optimized using the nonlinear least squares method, and the laser point cloud data obtained by scanning is adjusted according to the optimized pose of the 3D scanner to compensate for deformation.

[0031] Preferably, the real-time acquisition of multispectral data of the cultural relic, combined with the scanning data, to establish cultural relic material data that matches the surface structure of the cultural relic includes:

[0032] Divide the surface or interior of a cultural relic into multiple different cultural relic areas based on its physical form, structure, and decorative features;

[0033] Assign a unique number Num to each divided area;

[0034] Data is collected for each cultural relic area in all set spectral bands to obtain the reflectance vector of area i in m spectral bands. Among them, r ij represents the reflectance of the i-th region in the j-th spectral band;

[0035] Multiple reflectivity vectors constitute a multispectral feature matrix R = (r ij ),j≤m

[0036] Obtain the characteristic data of various known materials from the material characteristic database, extract the reflectance values ​​in all set spectral bands, and construct the reflectance vector of the known material The reflectivity vectors of the plurality of known materials constitute a known material characteristic matrix Y=(y lj );

[0037] Calculate the Euclidean distance between the known material characteristic matrix and the multi-spectral characteristic matrix, and if the calculated Euclidean distance is less than a preset matching threshold, determine that the material of the corresponding region of the cultural relic is the corresponding known material;

[0038] Obtain the structural characteristics of the cultural relic region, specifically:

[0039] Obtain the RGB image of the cultural relic, divide the RGB image into a plurality of image regions, and associate the plurality of image regions with the cultural relic region;

[0040] Obtain the structural characteristics of the cultural relic in the cultural relic region by an image analysis algorithm, and all the cultural relic characteristics constitute a cultural relic structural characteristic matrix;

[0041] Match the cultural relic characteristic matrix with the known material characteristic matrix, so that the elements at different positions in each cultural relic characteristic matrix correspond to the elements at the same positions in the known material characteristic matrix.

[0042] Preferably, the sensitivity of the material of the cultural relic to the wavelength of the laser includes:

[0043] Using a preset laser emission power, a plurality of wavelengths of laser are selected to pre-scan different parts of the cultural relic;

[0044] Real-time acquisition of microscopic deformation data and color change data of the corresponding scanned parts of the cultural relic after scanning at different wavelengths, specifically including:

[0045] Record the reflectance spectrum data one of the plurality of wavelengths of laser at different wavebands and the temperature data one at the scanning position in the pre-scanning stage;

[0046] Record the reflectance spectrum data two of the plurality of wavelengths of laser at different wavebands and the temperature data two at the scanning position after pre-scanning S seconds;

[0047] Calculate the change rate one of the reflectance spectrum data two relative to the reflectance spectrum data one and the change rate two between the temperature data two and the temperature data one;

[0048] If the change rate one is greater than a preset safety spectrum threshold or the change rate two is greater than a preset safety temperature threshold, it is determined that the cultural relic is sensitive to the corresponding wavelength of laser;

[0049] Record all the wavelengths to which the cultural relic is sensitive to constitute a sensitive wavelength spectrum.

[0050] Preferably, the dynamic adjustment of the scanning parameters according to the sensitivity identification result includes:

[0051] Adjust the wavelength of the laser used for scanning, use a laser with a wavelength other than the sensitive wavelength spectrum; or, construct a laser wavelength adjustment function and fuse the laser wavelength adjustment function with the environmental deformation model to adjust the scanning parameters.

[0052] Preferably, the construction of the laser wavelength adjustment function and the fusion of the laser wavelength adjustment function with the environmental deformation model to adjust the scanning parameters comprises:

[0053] Obtain the environmental deformation model ΔL=L0·α·ΔT+L0·β·ΔH;

[0054] Introduce viscoelastic effects to construct a time-dependent deformation model, wherein J(t) represents the creep compliance function, σ env represents the environmental stress, σ env =k T ΔT+k H ΔH, wherein k T , k H represent the temperature stress coefficient and the humidity stress coefficient respectively, and η represents the material viscosity coefficient;

[0055] The construction of the laser wavelength adjustment function specifically comprises the following steps:

[0056] Construct a material optical response function R(λ, T, H)=R0(λ)·[1+β T (λ)·ΔT+β H (λ)·ΔH]; wherein R0(λ) represents the reference reflectivity spectrum, β T (λ) represents the temperature sensitivity coefficient, and β H (λ) represents the humidity sensitivity coefficient;

[0057] Construct a multi-objective optimization equation:

[0058] wherein P max (λ) represents the material damage threshold power, SNR(λ, P) represents the signal-to-noise ratio, and SNR min represents the signal-to-noise ratio threshold; ΔL scan represents the deformation after scanning;

[0059] Construct a state equation, comprising:

[0060] Define a state vector wherein R(λ) represents the real-time reflectivity spectrum;

[0061] Then, the state equation is: wherein W represents the state noise;

[0062] The laser ranging equation is: wherein h(xxt ) represents the theoretical distance function, c represents the speed of light, N(λ,T,H) represents the refractive index, L0 represents the original size of the artifact, t TOF represents the time from laser pulse emission to reception, and v represents the measurement noise;

[0063] The extended Kalman filter is used to estimate the deformation of the cultural relic in real time. According to the estimated deformation of the cultural relic, the target wavelength and power value that meet the multi-objective optimization equation are calculated. The three-dimensional scanner controls the wavelength and power of the output laser according to the target wavelength and power values.

[0064] Preferably, the three-dimensional scanner controls the wavelength and power of the output laser according to the target wavelength and power value, including:

[0065] Building a drive matrix

[0066] Among them, λ z represents the zth wavelength, f rfz The laser frequency corresponding to the zth wavelength, V z represents the driving voltage corresponding to the zth wavelength;

[0067] According to the target wavelength, the corresponding laser frequency and driving voltage are obtained by querying the driving matrix;

[0068] Fine-tune the wavelength through linear interpolation algorithm;

[0069] Construct the reflectivity-power adjustment matrix: Among them, R(λ z ) represents the reflectance spectrum corresponding to the zth wavelength; P zmax represents the maximum safe power corresponding to the zth wavelength, P zopt represents the target power corresponding to the zth wavelength;

[0070] According to the target wavelength, the corresponding reflectivity spectrum, maximum safe power and target power are obtained from the driving matrix; the power is dynamically adjusted using a PID controller.

[0071] Preferably, the multimodal data fusion framework is constructed to fuse scanning data, photogrammetry data, and multispectral data to achieve digitization of cultural relics, including:

[0072] Construct a cross-modal data container, encapsulate the laser point cloud, RGB image, and multispectral data into a hierarchical structure, and retain the original data, including device parameters and timestamps. The specific steps include:

[0073] Through adaptive encoding, data in different formats are converted into intermediate representations in a shared latent space;

[0074] Use lightweight compression algorithms like Draco or LZ4 to reduce data size while maintaining multimodal relevance.

[0075] Extract cross-modal shared semantic features through self-supervised learning and establish feature mapping relationships. The specific steps include:

[0076] Use the trained dual-tower neural network to process point cloud data and RGB image data respectively; align the feature vectors of point cloud data and RGB image through comparative learning;

[0077] An attention mechanism is introduced to dynamically assign weights to multimodal features, including feature vectors of point cloud data, feature vectors of RGB images, and feature vectors of multispectral data.

[0078] Beneficial effects of the present invention:

[0079] The present invention takes into account the influence of dynamic environment on the deformation of cultural relics, dynamically corrects the scanning data by establishing a mapping relationship between environmental parameters and cultural relic deformation, uses multispectral data to infer the surface material of the cultural relic, and corresponds the surface material with the surface structure of the cultural relic one-to-one. After identifying the sensitivity of the cultural relic to the laser wavelength, the wavelength and frequency of the scanning laser are dynamically adjusted to correct the scanning data, so as to avoid the deformation of the cultural relic caused by the wavelength of a specific laser and the superposition of the influence of the environmental parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 The present invention is a flow chart of a method for processing cultural relic data using a three-dimensional scanner. DETAILED DESCRIPTION

[0081] The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are for illustrative purposes only, and those skilled in the art will readily appreciate other obvious variations. The basic principles of the present invention defined in the following description may be applied to other embodiments, variations, improvements, equivalents, and other technical solutions that do not depart from the spirit and scope of the present invention.

[0082] It is to be understood that the term "one" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of an element may be one, while in another embodiment, the number of the elements may be multiple, and the term "one" should not be understood as a limitation on the quantity.

[0083] Example 1:

[0084] refer to Figure 1 The technical solution provided by the present invention is: a method for processing cultural relics data using a three-dimensional scanner, comprising the following steps:

[0085] Step 1: Obtain scanning data and photogrammetry data of the cultural relic; including: obtaining laser point cloud data of the cultural relic through a 3D scanner, and obtaining RGB images of the cultural relic from multiple angles through a camera; and adding angle identification tags to the RGB images of each angle.

[0086] Step 2: Real-time acquisition of environmental parameters of the environment where the cultural relics are located, establishment of a mapping relationship between environmental parameters and cultural relics deformation, and dynamic correction of scanning data; the environmental parameters include temperature, humidity and vibration data; specifically, the following steps:

[0087] 2.1. Construct an environmental deformation model: ΔL = L0·α·ΔT + L0·β·ΔH; where ΔL represents the compensation for the deformation of the cultural relic, L0 represents the original size of the cultural relic, α represents the thermal expansion coefficient, β represents the humidity expansion coefficient, ΔH represents the humidity change, and ΔT represents the temperature change.

[0088] 2.2. During scanning, the laser point cloud coordinates are reversely corrected by calculating the deformation compensation amount;

[0089] 2.3. Construct a state equation, use Kalman filtering or particle filtering, take environmental parameters as state variables, dynamically predict and eliminate deformation noise;

[0090] The state equation is: k =Fx k-1 +Bu k +w k , where F and B represent the state transfer matrix and input control matrix respectively, x k Represents the current state variable, that is, the shape variable; x k-1 Represents the state variable of the previous moment, u k represents the environmental parameter vector, namely the temperature and humidity vector; w k represents process noise.

[0091] Step 3: Acquire multispectral data of the cultural relic in real time, combine it with the scanning data, and establish cultural relic material data that matches the surface structure of the cultural relic; including the following steps:

[0092] Divide the surface or interior of a cultural relic into multiple different cultural relic areas based on its physical form, structure, and decorative features;

[0093] Assign a unique number Num to each divided area;

[0094] Data is collected for each cultural relic area in all set spectral bands to obtain the reflectance vector of area i in m spectral bands. Among them, r ij represents the reflectance of the i-th region in the j-th spectral band;

[0095] Multiple reflectivity vectors constitute a multispectral feature matrix R = (r ij ),j≤m

[0096] Obtain the characteristic data of various known materials from the material characteristic database, extract the reflectivity values ​​in all set spectral bands, and construct the reflectivity vector of the known materials A plurality of known material reflectivity vectors constitute a known material characteristic matrix Y = (y lj );

[0097] Calculating the Euclidean distance between the known material feature matrix and the multispectral feature matrix. If the calculated Euclidean distance is less than a preset matching threshold, the material in the corresponding area of ​​the cultural relic is determined to be the corresponding known material.

[0098] Get the structural characteristics of the cultural relics area, specifically:

[0099] Obtaining an RGB image of the cultural relic, dividing the RGB image into multiple image regions, and associating the multiple image regions with the cultural relic region;

[0100] The structural features of the cultural relics in the cultural relics area are obtained through image analysis algorithms, and all the cultural relics features constitute a cultural relics structural feature matrix;

[0101] Match the cultural relic feature matrix with the known material feature matrix so that the elements at different positions in each cultural relic feature matrix correspond to the elements at the same position in the known material feature matrix.

[0102] Step 4: Identify the sensitivity of the cultural relic material to the laser wavelength, dynamically adjust the scanning parameters based on the sensitivity identification results, and correct the scanning data;

[0103] The identification of the sensitivity of the cultural relic material to the laser wavelength includes the following steps:

[0104] Use the preset laser emission power and select multiple wavelengths of laser to pre-scan different parts of the cultural relic;

[0105] Real-time acquisition of microscopic deformation data and color change data of the corresponding scanned parts of cultural relics after scanning at different wavelengths, including:

[0106] Recording reflection spectrum data of multiple wavelength lasers in different bands and temperature data at the scanning position in the pre-scanning stage;

[0107] Recording reflection spectrum data 2 of multiple wavelength lasers in different bands and temperature data 2 at the scanning position after pre-scanning for S seconds;

[0108] calculating a change rate one of the second relative reflectance spectrum data with respect to the first relative reflectance spectrum data and a change rate two between the second temperature data with respect to the first temperature data;

[0109] if the change rate one is greater than a preset safety spectrum threshold or the change rate two is greater than a preset safety temperature threshold, judging that the cultural relic is sensitive to laser of the corresponding wavelength;

[0110] recording all wavelengths to which the cultural relic is sensitive to form a sensitive wavelength spectrum.

[0111] wherein, according to the sensitivity identification result, the scanning parameters are dynamically adjusted, including the following steps:

[0112] adjusting the wavelength of the laser used for scanning, using laser of a wavelength other than the sensitive wavelength spectrum; or, constructing a laser wavelength adjustment function and fusing the laser wavelength adjustment function with the environmental deformation model to adjust the scanning parameters.

[0113] wherein, the laser wavelength adjustment function is constructed and fused with the environmental deformation model to adjust the scanning parameters, including the following steps:

[0114] 1. Obtain the environmental deformation model ΔL=L0·α·ΔT+L0·β·ΔH;

[0115] introducing viscoelastic effect to construct a time-dependent deformation model, wherein, J(t) represents a creep compliance function, σ env represents environmental stress, σ env =k T ΔT+k H ΔH, wherein, k T , k H represent temperature stress coefficient and humidity stress coefficient respectively, and η represents material viscosity coefficient;

[0116] 2. Determine the optical properties of the material, and construct a wavelength-reflectivity relationship function, specifically:

[0117] constructing a material optical response function R(λ,T,H)=R0(λ)·[1+β T (λ)·ΔT+β H (λ)·ΔH]; wherein, R0(λ) represents a reference reflectivity spectrum, β T (λ) represents a temperature sensitivity coefficient, and β H (λ) represents a humidity sensitivity coefficient;

[0118] 3. Construct a wavelength adjustment function to select the best power and wavelength according to the environmental parameters and material response, including:

[0119] constructing a wavelength adjustment function, specifically including the following steps:

[0120] Construct a multi-objective optimization equation:

[0121] Among them, P max (λ) represents the material damage threshold power, SNR(λ,P) represents the signal-to-noise ratio, SNR min represents the signal-to-noise ratio threshold; ΔL scan Represents the shape after scanning;

[0122] 4. Combining the environmental deformation model with the wavelength adjustment function to form a comprehensive correction algorithm, which can use the PID controller in control theory; specifically:

[0123] Construct the equation of state, including:

[0124] Define the state vector Where R(λ) represents the real-time reflectance spectrum;

[0125] Then, the state equation is: Where W represents the state noise;

[0126] The laser ranging equation is: Among them, h(x xt ) represents the theoretical distance function, c represents the speed of light, N(λ,T,H) represents the refractive index, L0 represents the original size of the artifact, t TOF represents the time from laser pulse emission to reception, and v represents the measurement noise;

[0127] The extended Kalman filter is used to estimate the deformation of the cultural relic in real time. According to the estimated deformation of the cultural relic, the target wavelength and power value that meet the multi-objective optimization equation are calculated. The three-dimensional scanner controls the wavelength and power of the output laser according to the target wavelength and power values.

[0128] For example, the standard material INVAR alloy can be used to verify the accuracy of the environmental deformation model in a temperature-controlled box, and the target accuracy can be set to 0.5μm / ℃; by gradually increasing the power value, the reflectivity change is detected to be greater than 1% to determine the P max (λ) curve.

[0129] In this embodiment, the three-dimensional scanner controls the wavelength and power of the output laser according to the target wavelength and power value, specifically including the following steps:

[0130] Building a drive matrix

[0131] Among them, λ z represents the zth wavelength, f rfz The laser frequency corresponding to the zth wavelength, V z represents the driving voltage corresponding to the zth wavelength;

[0132] According to the target wavelength, the corresponding laser frequency and driving voltage are obtained by querying the driving matrix;

[0133] Fine-tune the wavelength through linear interpolation algorithm;

[0134] Construct the reflectivity-power adjustment matrix: Among them, R(λ z ) represents the reflectance spectrum corresponding to the zth wavelength; P zmax represents the maximum safe power corresponding to the zth wavelength, P zopt represents the target power corresponding to the zth wavelength;

[0135] According to the target wavelength, the corresponding reflectivity spectrum, maximum safe power and target power are obtained from the driving matrix; the power is dynamically adjusted using a PID controller.

[0136] Step 5: Build a multimodal data fusion framework to fuse scanning data, photogrammetry data, and multispectral data to achieve the digitization of cultural relics. This includes the following steps:

[0137] The multimodal data fusion framework is constructed to fuse scanning data, photogrammetry data, and multispectral data to realize the digitization of cultural relics, including:

[0138] Construct a cross-modal data container, encapsulate the laser point cloud, RGB image, and multispectral data into a hierarchical structure, and retain the original data, including device parameters and timestamps. The specific steps include:

[0139] Through adaptive encoding, data in different formats are converted into intermediate representations in a shared latent space;

[0140] Use lightweight compression algorithms like Draco or LZ4 to reduce data size while maintaining multimodal relevance.

[0141] Extract cross-modal shared semantic features through self-supervised learning and establish feature mapping relationships. The specific steps include:

[0142] Use the trained dual-tower neural network to process point cloud data and RGB image data respectively; align the feature vectors of point cloud data and RGB image through comparative learning;

[0143] An attention mechanism is introduced to dynamically assign weights to multimodal features, including feature vectors of point cloud data, feature vectors of RGB images, and feature vectors of multispectral data.

[0144] Example 2:

[0145] The difference between this embodiment and the first embodiment is that:

[0146] SLAM technology is applied to 3D scanning of cultural relics. Traditional SLAM technology is used by robots to simultaneously build maps and locate themselves when moving in unknown environments. In cultural relic scanning, although the scanner itself cannot move, changes in the environment cause the artifact to deform, which is equivalent to the dynamic change of the environment. Therefore, the scanner can be regarded as a mobile sensor, and the deformation of the artifact surface is equivalent to the change of the environment.

[0147] The specific steps are:

[0148] Obtain scanning data, obtain 10-30 frames of laser point cloud data of cultural relics per second, and form a laser point cloud dataset;

[0149] Acquire temperature data and humidity data simultaneously to form a temperature and humidity vector set; the acquisition frequency of the temperature data and humidity data is not less than 1 Hz;

[0150] Get the position and pose of the 3D scanner;

[0151] Extracting point cloud feature data and temperature and humidity feature vectors from the laser point cloud dataset and the temperature and humidity dataset respectively to form a point cloud feature dataset and a temperature and humidity feature vector set respectively;

[0152] Constructing a pose graph, specifically including:

[0153] The pose T corresponding to each frame of laser point cloud data i ' is used as a node to initialize the motion trajectory of the 3D scanner; the relative change of the node between two scans is used as the edge;

[0154] Construct an environment-deformation constraint model, including:

[0155] Environmental parameters are introduced as deformation constraints, and the local deformation matrix is ​​calculated according to the changes in temperature and humidity: d=α·ΔT+β·ΔH; where, ΔT env represents the expected deformation of the cultural relic caused by environmental parameters, I represents the identity matrix, and d represents the deformation translation vector;

[0156] ΔT env Connect adjacent nodes as a priori edges, minimize the Mahalanobis distance of all edges, and use the covariance of environmental parameters as a deformation constraint to adjust the relationship between edges;

[0157] The pose graph is optimized using the nonlinear least squares method, and the laser point cloud data obtained by scanning is adjusted according to the optimized pose of the 3D scanner to compensate for the deformation.

[0158] In this embodiment, the pose graph optimization problem is defined as minimizing the Mahalanobis distance of all edges. Problems;

[0159] Get the optimized pose {T′ i *}, where ∑ env Represents the covariance of environmental parameters, that is, the covariance of temperature and humidity data; through ∑ env Reflects the confidence of environmental parameters, ∑ ij represents the pose covariance;

[0160] The laser point cloud data obtained by scanning is transformed through the optimized posture, specifically:

[0161] According to the optimized pose {T′ i *}Transform the original point cloud, in, is the original point cloud vector. In addition, for high deformation areas, non-rigid ICP can be applied for further refinement.

[0162] For example, when scanning wooden artifacts, the environmental changes are temperature fluctuations of ±5°C and humidity fluctuations of ±15% RH;

[0163] Operation process: add a deformation constraint edge every 5 seconds (α T =5×10 -5 / ℃), the error of the optimized model is reduced from 2.1mm to 0.3mm. The position accuracy of key points can be verified by laser tracker.

[0164] In the embodiments disclosed herein, the processes described above with reference to the flowcharts can be implemented as computer software programs. The embodiments disclosed herein include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication component and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), the functions defined in the method of the present invention are performed. It should be noted that the computer-readable medium of the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. The computer-readable storage medium can be, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection having one or more wire segments, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. Furthermore, in the present invention, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, electrical, optical, RF, or any suitable combination thereof.

[0165] The flowcharts in the accompanying drawings illustrate the architecture, functions and operations that may be implemented according to the methods of various embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of a code, and the module, program segment or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, as well as the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0166] Those skilled in the art should understand that the embodiments of the present invention described above and shown in the accompanying drawings are only examples and do not limit the present invention. The objectives of the present invention have been fully and effectively achieved. The functional and structural principles of the present invention have been demonstrated and explained in the embodiments. Without departing from the principles, the implementation methods of the present invention may be subject to any changes or modifications.

Claims

1. A method for processing cultural relic data using a three-dimensional scanner, characterized in that: The method comprises: Obtain scanning data and photogrammetry data of cultural relics; Real-time acquisition of environmental parameters of the environment where the cultural relics are located, establishment of a mapping relationship between environmental parameters and cultural relics deformation, and dynamic correction of scanning data; the environmental parameters include temperature and humidity; The method includes: constructing an environmental deformation model: ΔL = L0·α·ΔT + L0·β·ΔH; wherein ΔL represents the deformation compensation amount of the cultural relic, L0 represents the original size of the cultural relic, α represents the thermal expansion coefficient, β represents the humidity expansion coefficient, ΔH represents the humidity change, and ΔT represents the temperature change; During scanning, the laser point cloud coordinates are reversely corrected by calculating the deformation compensation amount; Construct a state equation, use Kalman filtering or particle filtering, take environmental parameters as state variables, dynamically predict and eliminate deformation noise; The state equation is: k =Fx k-1 +Bu k +w k , where F and B represent the state transfer matrix and input control matrix respectively, x k Represents the current state variable, that is, the shape variable; x k-1 Represents the state variable of the previous moment, u k represents the environmental parameter vector, namely the temperature and humidity vector; w k represents process noise; Acquire multispectral data of cultural relics in real time, combine it with scanning data, and establish material data that matches the surface structure of the cultural relics; Identify the sensitivity of cultural relic materials to laser wavelengths, dynamically adjust scanning parameters based on the sensitivity identification results, and calibrate the scanning data; Construct a multimodal data fusion framework for the fusion of scanning data, photogrammetry data, and multispectral data to realize the digitization of cultural relics.

2. The method for processing cultural relics data using a three-dimensional scanner according to claim 1, characterized in that: The acquisition of scanning data and photogrammetric data of cultural relics includes: Obtain laser point cloud data of cultural relics through 3D scanner; The RGB images of the cultural relics at multiple angles are acquired through the camera equipment, and angle identification labels are added to the RGB images of each angle.

3. The method for processing cultural relics data using a three-dimensional scanner according to claim 2, characterized in that: The real-time acquisition of environmental parameters of the environment where the cultural relics are located, establishment of a mapping relationship between the environmental parameters and the deformation of the cultural relics, and dynamic correction of the scan data also include: Utilize incremental SLAM technology combined with pose graph optimization to dynamically adjust local deformation; The specific steps include: Obtain scanning data, obtain 10-30 frames of laser point cloud data of cultural relics per second, and form a laser point cloud dataset; Acquire temperature data and humidity data simultaneously to form a temperature and humidity vector set; the acquisition frequency of the temperature data and humidity data is not less than 1 Hz; Get the position and pose of the 3D scanner; Extracting point cloud feature data and temperature and humidity feature vectors from the laser point cloud dataset and the temperature and humidity dataset respectively to form a point cloud feature dataset and a temperature and humidity feature vector set respectively; Constructing a pose graph, specifically including: The pose T corresponding to each frame of laser point cloud data i ' is used as a node to initialize the motion trajectory of the 3D scanner; the relative change of the node between two scans is used as the edge; Construct an environment-deformation constraint model, including: Environmental parameters are introduced as deformation constraints, and the local deformation matrix is ​​calculated according to the changes in temperature and humidity: Where, ΔT env represents the expected deformation of the cultural relic caused by environmental parameters, I represents the identity matrix, and d represents the deformation translation vector; ΔT env Connect adjacent nodes as a priori edges, minimize the Mahalanobis distance of all edges, and use the covariance of environmental parameters as a deformation constraint to adjust the relationship between edges; The pose graph is optimized using the nonlinear least squares method, and the laser point cloud data obtained by scanning is adjusted according to the optimized pose of the 3D scanner to compensate for the deformation.

4. The method for processing cultural relics data using a three-dimensional scanner according to claim 3, characterized in that: The real-time acquisition of multispectral data of the cultural relic, combined with the scanning data, to establish the cultural relic material data matching the surface structure of the cultural relic, includes: Divide the surface or interior of a cultural relic into multiple different cultural relic areas based on its physical form, structure, and decorative features; Assign a unique number Num to each divided area; Data is collected for each cultural relic area in all set spectral bands to obtain the reflectance vector of area i in m spectral bands. Among them, r ij represents the reflectance of the i-th region in the j-th spectral band; Multiple reflectivity vectors constitute a multispectral feature matrix R = (r ij ),j≤m Obtain the characteristic data of various known materials from the material characteristic database, extract the reflectivity values ​​in all set spectral bands, and construct the reflectivity vector of the known materials A plurality of known material reflectivity vectors constitute a known material characteristic matrix Y = (y lj ); Calculating the Euclidean distance between the known material feature matrix and the multispectral feature matrix. If the calculated Euclidean distance is less than a preset matching threshold, the material in the corresponding area of ​​the cultural relic is determined to be the corresponding known material. Get the structural characteristics of the cultural relics area, specifically: Obtaining an RGB image of the cultural relic, dividing the RGB image into multiple image regions, and associating the multiple image regions with the cultural relic region; The structural features of the cultural relics in the cultural relics area are obtained through image analysis algorithms, and all the cultural relics features constitute a cultural relics structural feature matrix; Match the cultural relic structure feature matrix with the known material feature matrix so that the elements at different positions in each cultural relic structure feature matrix correspond to the elements at the same position in the known material feature matrix.

5. The method for processing cultural relics data using a three-dimensional scanner according to claim 4, characterized in that: The sensitivity of the material of the cultural relic to the laser wavelength includes: Use the preset laser emission power and select multiple wavelengths of laser to pre-scan different parts of the cultural relic; Real-time acquisition of microscopic deformation data and color change data of the corresponding scanned parts of cultural relics after scanning at different wavelengths, including: Recording reflection spectrum data of multiple wavelength lasers in different bands and temperature data at the scanning position in the pre-scanning stage; Recording reflection spectrum data 2 of multiple wavelength lasers in different bands and temperature data 2 at the scanning position after pre-scanning for S seconds; Calculate a change rate 1 of the reflectance spectrum data 2 relative to the reflectance spectrum data 1 and a change rate 2 of the temperature data 2 relative to the temperature data 1; If the first rate of change is greater than the preset safety spectrum threshold or the second rate of change is greater than the preset safety temperature threshold, it is determined that the cultural relic is sensitive to the laser of the corresponding wavelength; Record all wavelengths that cultural relics are sensitive to and form a sensitive wavelength spectrum.

6. The method for processing cultural relics data using a three-dimensional scanner according to claim 5, characterized in that: The method of dynamically adjusting scanning parameters according to the sensitivity identification result includes: Adjust the wavelength of the laser used for scanning and use a laser with a wavelength outside the sensitive wavelength spectrum; or, construct a laser wavelength adjustment function and fuse the laser wavelength adjustment function with the environmental deformation model to adjust the scanning parameters.

7. The method for processing cultural relics data using a three-dimensional scanner according to claim 6, characterized in that: The laser wavelength adjustment function is constructed, and the laser wavelength adjustment function is integrated with the environmental deformation model to adjust the scanning parameters, including: Obtain the environmental deformation model ΔL = L0·α·ΔT + L0·β·ΔH; Introducing viscoelastic effects and constructing a time-dependent deformation model, Where J(t) represents the creep compliance function, σ env represents environmental stress, σ env =k T ΔT+k H ΔH, where k T 、k H They represent the temperature stress coefficient and humidity stress coefficient respectively, and η represents the material viscosity coefficient; Constructing a laser wavelength adjustment function includes the following steps: Construct the optical response function of the material R(λ,T,H)=R0(λ)·[1+β T (λ)·ΔT+β H (λ)·ΔH]; where R0(λ) represents the reference reflectance spectrum, β T (λ) represents the temperature sensitivity coefficient, β H (λ) represents the humidity sensitivity coefficient; Construct the multi-objective optimization equation: Among them, P max (λ) represents the material damage threshold power, SNR(λ,P) represents the signal-to-noise ratio, SNR min represents the signal-to-noise ratio threshold; ΔL scan Represents the shape after scanning; Construct the equation of state, including: Define the state vector Where R(λ) represents the real-time reflectance spectrum; Then, the state equation is: Where W represents state noise; The laser ranging equation is: Among them, h(x xt ) represents the theoretical distance function, c represents the speed of light, N(λ,T,H) represents the refractive index, L0 represents the original size of the artifact, t TOF represents the time from the laser pulse emission to the reception, and v represents the measurement noise; The extended Kalman filter is used to estimate the deformation of the cultural relic in real time. According to the estimated deformation of the cultural relic, the target wavelength and power value that satisfy the multi-objective optimization equation are calculated. The three-dimensional scanner controls the wavelength and power of the output laser according to the target wavelength and power values.

8. The method for processing cultural relics data using a three-dimensional scanner according to claim 7, characterized in that: The three-dimensional scanner controls the wavelength and power of the output laser according to the target wavelength and power value, including: Building a drive matrix Among them, λ z represents the zth wavelength, f rfz The laser frequency corresponding to the zth wavelength, V z represents the driving voltage corresponding to the zth wavelength; According to the target wavelength, the corresponding laser frequency and driving voltage are obtained by querying the driving matrix; Fine-tune the wavelength through linear interpolation algorithm; Construct the reflectivity-power adjustment matrix: Among them, R(λ z ) represents the reflectance spectrum corresponding to the zth wavelength; P zmax represents the maximum safe power corresponding to the zth wavelength, P zopt represents the target power corresponding to the zth wavelength; According to the target wavelength, the corresponding reflectivity spectrum, maximum safe power and target power are obtained from the driving matrix; the power is dynamically adjusted using a PID controller.

9. The method for processing cultural relics data using a three-dimensional scanner according to claim 8, characterized in that: The multimodal data fusion framework is constructed to fuse scanning data, photogrammetry data, and multispectral data to realize the digitization of cultural relics, including: Construct a cross-modal data container, encapsulate the laser point cloud, RGB image, and multispectral data into a hierarchical structure, and retain the original data, including device parameters and timestamps. The specific steps include: Through adaptive encoding, data in different formats are converted into intermediate representations in a shared latent space; Use lightweight compression algorithms like Draco or LZ4 to reduce data size while maintaining multimodal relevance. Extract cross-modal shared semantic features through self-supervised learning and establish feature mapping relationships. The specific steps include: Use the trained dual-tower neural network to process point cloud data and RGB image data respectively; align the feature vectors of point cloud data and RGB image through comparative learning; An attention mechanism is introduced to dynamically assign weights to multimodal features, including feature vectors of point cloud data, feature vectors of RGB images, and feature vectors of multispectral data.

Images