Real scene three-dimensional model information hiding method and device, equipment and storage medium

Abstract

The invention provides a live-action three-dimensional model information hiding method and device, equipment and a storage medium. Relates to the technical field of information hiding. The method comprises the following steps: acquiring live-action three-dimensional model data; wherein the live-action three-dimensional model data comprises a space coordinate, a texture coordinate and a texture picture; determining a quantized step size with constraints according to the width of the texture picture and the binary sequence bits embedded each time; according to a texture mapping principle, calculating a quantization interval in which correct texture information can still be found through mapping after modification; and on the basis of a binary sequence to be embedded generated by the multi-level identity information, modifying texture coordinates in the quantization interval to realize embedding of the multi-level identity information to obtain information-containing data. According to the method, large-capacity hiding of the multi-level identity information can be carried out under the condition that the rendering effect and the coordinate precision of the live-action three-dimensional model data are not influenced.

Description

Technical Field

[0001] The present application relates to the field of information hiding technology, and in particular to a method, device, equipment and storage medium for hiding information of a real-scene three-dimensional model. Background Art

[0002] Realistic 3D models have been widely used in fields such as digital twins and smart cities, becoming strategically valuable digital resources. However, because real-world 3D model data is a highly realistic simulation of real-world objects, its security protection is particularly important. When distributing data to users, data owners often use confidentiality agreements to constrain user behavior and hold them accountable for leaks. However, data often has multiple users, making it difficult to hold individuals accountable after a leak. Typically, only data leaks can be detected, but the specific user cannot be held accountable. Information hiding technology provides an effective solution to this problem. It can embed copyright information, identification information, or other confidential data into 3D models without compromising model quality, thus enabling data traceability.

[0003] Existing information hiding technologies for three-dimensional data can be mainly divided into two categories: spatial domain and transform domain. The spatial domain information hiding method for three-dimensional data mainly achieves information hiding by modifying the vertex coordinate values ​​or geometric features such as the angle and length between vertices. For example, the literature "Wang Gang. Research on Digital Watermarking Algorithm for Geographic Scene Point Cloud Data [D]. Nanjing Normal University, 2020." and "Wang Gang, Ren Na, Zhu Changqing, et al. Digital Watermarking Algorithm for Oblique Photography 3D Model [J]. Journal of Geo-Information Science, 2018, 20(6): 738-743." proposed a digital watermarking algorithm for oblique photography 3D models based on vertical stability. By taking advantage of the vertical upward characteristics of oblique photography 3D models, the vertices are sorted according to the vertical coordinates and the watermark information is embedded in the difference between the vertical coordinates. This algorithm can resist attacks such as rotation and translation, but it is difficult to resist scaling attacks. Embedding secret information based on the surface properties and geometric features of the 3D model is also a design idea, but such methods often have difficulty in ensuring the algorithm capacity. 3D model transform domain information hiding algorithms convert various data elements of a 3D model into frequency domain transform coefficients, such as discrete cosine transform (DCT) and discrete Fourier transform (DFT). Secret information is embedded by modifying the relevant coefficients. These algorithms exhibit a certain degree of robustness against model transformations, such as rotation, scaling, and shearing. Modifications to transform domain parameters, after inverse transformation, are robust against common point cloud data rotation, translation, and simplification attacks. The perturbations to the data are spread across the entire region, making them more difficult to crack. Existing research on 3D model information hiding has laid a solid theoretical foundation, but current research in information hiding technology focuses on algorithm robustness and display performance. Both embedding domains inevitably involve direct or indirect changes to the 3D model's coordinates, which can affect data accuracy. Real-world 3D model data often requires multi-level distribution. Embedding user information at each level ensures data traceability, but existing algorithms lack sufficient capacity. Summary of the Invention

[0004] The present application provides a method, apparatus, device and storage medium for hiding information of a real-scene three-dimensional model. By calculating the lossless modification interval of texture coordinates and utilizing the improved quantization index modulation concept, a binary sequence of multi-level identity information is mapped to the lossless modification interval of texture coordinates. In this way, large-capacity hiding of multi-level identity information can be performed without affecting the rendering effect and coordinate accuracy of the real-scene three-dimensional model data, and the method has good robustness.

[0005] In a first aspect, the present application provides a method for hiding information of a real-scene 3D model, comprising: Acquire real-scene 3D model data; wherein the real-scene 3D model data includes space coordinates, texture coordinates, and texture images; Determining a constrained quantization step size according to the width of the texture image and the number of bits of the binary sequence embedded each time; According to the principle of texture mapping, the quantization interval of the correct texture information can still be found through mapping after modification; Based on the binary sequence to be embedded generated by the multi-level identity information, the texture coordinates are modified within the quantization interval to achieve the embedding of the multi-level identity information and obtain the information-containing data.

[0006] In one possible design, the constrained quantization step size is determined by the following formula according to the width of the texture image and the number of bits of the binary sequence embedded each time: (1) Where, is the quantization step size, is the width of the texture image, is the number of binary bits embedded each time.

[0007] In one possible design, the quantization interval is calculated using the following formula: (2) Where, The lower bound of the range for lossless modification, The upper bound of the range of lossless modification, when the horizontal coordinate after embedding information For non-destructive modification, is the width of the texture image, The horizontal coordinate to be embedded.

[0008] In one possible design, the binary sequence to be embedded is generated by the following formula: (3) Where, is the binary sequence to be embedded, For multi-level identity information, Huffman It is a static Huffman code.

[0009] In one possible design, based on the binary sequence to be embedded generated by the multi-level identity information, the texture coordinates are modified within the quantization interval to embed the multi-level identity information, thereby obtaining information-containing data, including: Based on the texture coordinates and the height and width of the texture image, the horizontal and vertical coordinates of the image are calculated using the following formula: (4) Where, x pixel and y pixel They are the horizontal and vertical coordinates of the picture respectively. u and v are the horizontal and vertical coordinates of the texture respectively, w andh are the height and width of the texture image respectively; When modifying texture coordinates, the modified values ​​of the coordinates are made to meet the conditions shown in formula (5) to ensure lossless modification: (5) Where, and The modified values ​​of the texture's horizontal and vertical coordinates; The texture coordinates are modified within the quantization interval by the following formula to achieve the embedding of multi-level identity information: (6) Where, is the value to be embedded, is the value after quantization index modulation, is the quantization step size, is the number of bytes embedded each time, and are the upper and lower limits of the quantization interval, respectively. for The decimal integer corresponding to the binary watermark, b i is a binary sequence, i is the serial number corresponding to the binary sequence.

[0010] In one possible design, after obtaining the information-containing data, the method further includes: Calculating a range of lossless modification of coordinates based on the coordinates after the information is embedded in the information-containing data; Based on the range of losslessly modified coordinates, calculate The decimal integer corresponding to the binary watermark K ,Will K Convert to binary and get the embedded binary sequence; Combining the embedded binary sequences to obtain binary encoding of multi-level identity information; The binary code of the multi-level identity information is inversely encoded using Huffman coding to obtain the corresponding characters, and the extracted multi-level identity information is obtained using a majority voting mechanism. .

[0011] In one possible design, based on the coordinates of the embedded information in the information-containing data, the range of lossless coordinate modification is calculated using the following formula: (7) Where, are the horizontal coordinates after embedding information Determine the lower bound of the range of lossless modification, is the width of the texture image; Based on the range of lossless modification of the coordinates, it is calculated by the following formula The decimal integer corresponding to the binary watermark K : (8) Where, is the quantization step size.

[0012] In a second aspect, the present application provides a device for hiding information of a real-scene three-dimensional model, the device comprising: A data acquisition module is configured to acquire real-scene three-dimensional model data; wherein the real-scene three-dimensional model data includes space coordinates, texture coordinates and texture images; A step size calculation module is configured to determine a constrained quantization step size according to a width of the texture image and a number of bits of a binary sequence embedded each time; An interval calculation module is configured to calculate, based on the principle of texture mapping, a quantization interval that can still find correct texture information through mapping after modification; The information embedding module is configured to modify the texture coordinates within the quantization interval based on the binary sequence to be embedded generated based on the multi-level identity information to embed the multi-level identity information and obtain information-containing data.

[0013] In a third aspect, an embodiment of the present application provides an electronic device comprising: at least one processor and a memory; the memory stores computer-executable instructions; the at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the real-scene three-dimensional model information hiding method described in the first aspect and various possible designs of the first aspect.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the real-scene three-dimensional model information hiding method described in the first aspect and various possible designs of the first aspect is implemented.

[0015] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the real-scene three-dimensional model information hiding method described in the first aspect and various possible designs of the first aspect.

[0016] The method, device, equipment, and storage medium for hiding information about a real-scene 3D model provided in this application have at least the following beneficial effects: This application uses the texture coordinates of a 3D model as the embedding domain, improving the embedding capacity and robustness of information while ensuring that the embedded information is invisible. Experimental results show that this application can effectively embed large amounts of information while ensuring the visual quality and geometric accuracy of the model. It has strong invisibility and anti-attack capabilities, and can be widely used in scenarios such as data traceability and copyright protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0018] Figure 1 A flowchart of a method for hiding information of a real-scene 3D model provided in an embodiment of the present application; Figure 2 This is an example diagram of a single coordinate embedding provided in an embodiment of the present application; Figure 3 A watermark embedding flowchart provided in an embodiment of the present application; Figure 4 A flowchart of multi-level identity information extraction provided in an embodiment of the present application; Figure 5 A schematic diagram of single coordinate extraction provided in an embodiment of the present application; Figure 6 A schematic diagram of experimental data of the multi-level identity information hiding method provided in an embodiment of the present application; Figure 7 SecRate experimental results provided in the examples of this application; Figure 8 Graphs showing attack experiment results provided by the embodiments of the present application; wherein, a) represents the extraction effect after a rotation attack, b) represents the extraction effect after a scaling attack, c) represents the extraction effect after a translation attack, d) represents the extraction effect after a cropping attack, and e) represents the extraction effect after a deletion attack; Figure 9 This is a structural diagram of the real-scene 3D model information hiding device provided in an embodiment of the present application.

[0019] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0020] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0021] In the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of information such as model data or user data involved comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0022] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0023] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0024] Realistic 3D models have been widely used in digital twins, smart cities and other fields. However, these models usually contain high-precision geospatial information, which, once leaked, will bring serious security risks. Therefore, information hiding technology has become an important means to protect the data security of real-life 3D models and achieve data traceability. In view of the problems of limited embedding capacity and large precision loss in existing 3D model information hiding methods, the present application provides a real-life 3D model information hiding method, such as Figure 1 , which is a flow chart of a method for hiding information of a real-scene 3D model provided in an embodiment of the present application, and the method for hiding information of a real-scene 3D model includes the following steps S100 - S400 .

[0025] S100: Acquire real-scene 3D model data; wherein the real-scene 3D model data includes space coordinates, texture coordinates, and texture images.

[0026] OSGB is a common way of expressing three-dimensional models in the surveying and mapping geographic information industry, and is also the data format specified in the Technical Outline for Realistic Three-Dimensional China Construction. Therefore, this embodiment uses OSGB data as an example of real-scene three-dimensional model data to describe in detail how the method proposed in this application solves the problem that existing three-dimensional model information hiding algorithms cannot be embedded in a large capacity without loss, and how to achieve multi-level user information and data binding without affecting data accuracy. It should be noted that OSGB data is only a category of real-scene three-dimensional model data, and does not mean that this application can only process this type of data. OSGB data is only used as an example and does not constitute a limitation to this application.

[0027] S200: Determine a constrained quantization step size according to the width of the texture image and the number of bits of the binary sequence embedded each time.

[0028] In some embodiments, the constrained quantization step size is determined according to the texture image width and the number of bits of the binary sequence embedded each time, and is calculated as shown in formula (1): (1) Where, is the quantization step size, is the width of the texture image, is the number of binary bits embedded each time.

[0029] S300: Calculating, according to the principle of texture mapping, a quantization interval in which correct texture information can still be found through mapping after modification.

[0030] In some embodiments, the interval in which the correct texture information can still be found through mapping after modification is calculated according to the principle of texture mapping, and the calculation formula is shown in Formula (2).

[0031] (2) Where, The lower bound of the range for lossless modification, The upper bound of the range of lossless modification, when the horizontal coordinate after embedding information For non-destructive modification, is the width of the texture image, The horizontal coordinate to be embedded.

[0032] S400: Based on the binary sequence to be embedded generated by the multi-level identity information, modify the texture coordinates within the quantization interval to achieve the embedding of the multi-level identity information and obtain information-containing data.

[0033] In some embodiments, in order to facilitate the embedding of multi-level identity information, it can be converted into the form of binary numbers. Common binary encoding methods include UTF-8, ASCII code, etc., among which the shortest encoding is 7 binary numbers to represent one character. This type of common encoding method will have a lot of redundancy, resulting in a long encoding sequence and easy to crack. Therefore, this embodiment constructs a coding method. Considering that the coordinate numbers in the multi-level identity information are often the main part of the multi-level identity information, a static Huffman coding method with a higher proportion of numbers and a lower proportion of letters is constructed. Taking into account the actual situation, the static Huffman coding method is adopted, that is, after the coding table is generated only once, the fixed coding table remains unchanged. The process of static Huffman coding is recorded as: (3) Where, is the binary sequence to be embedded, For multi-level identity information, Huffman It is a static Huffman code.

[0034] In some embodiments, taking OSGB data as an example, OSGB data uses a texture mapping mechanism to obtain textures. Texture coordinates and texture images are stored separately. When rendering, the color information of different points is determined by calculating the mapping value of the texture coordinates. The texture mapping mechanism is as shown in formula (4). When rendering, the texture coordinates corresponding to the spatial coordinates are taken ( u , v ), and then get the height of the texture image h He Kuan w , calculate the image coordinates in real time x pixel and y pixel .

[0035] (4) In the formula is the floor symbol, and then according to x pixel and y pixel Get the pixel value in the texture image.

[0036] If you modify the texture coordinates ( u , v ) when ensuring x pixel and y pixel If the pixel coordinates ( u , v ) is within the range of 0 to 1, then lossless modification can be guaranteed as long as the conditions in formula (5) are met: (5) In the formula and is the modified value of the corresponding coordinate.

[0037] Based on this mechanism, this embodiment combines the concept of quantization index modulation to design a multi-level identity information hiding algorithm based on texture mapping. Quantization index modulation (QIM) is a technique that maps information to different quantization levels by modifying the data quantization index. It is a commonly used technical method in information hiding research. As shown in Equation (9), the core of QIM is to achieve information hiding through different quantization indices: (9) Where, is the value to be embedded, is the value after quantization index modulation, is the quantization step size. QIM affects the accuracy of the data carrier and each value can only be embedded in one byte, which does not meet the requirements of the method proposed in this application.

[0038] Considering the data characteristics of the texture mapping being studied, directly using quantization index modulation (QIM) can lead to errors in texture mapping values. Therefore, this embodiment improves the QIM mechanism, constrains the modification interval, and proposes a Constraint-Aware QIM (CA-QIM) technique. The main idea is to first calculate the constrained quantization step size and constrained quantization interval to ensure that the modulated structure meets the constraints; then, a multi-byte embedding mechanism is incorporated to expand the number of bytes that can be embedded in each coordinate. As shown in Equation (6), the CA-QIM formula is shown below.

[0039] (6) Where, is the value to be embedded, is the value after quantization index modulation, is the quantization step size, is the number of bytes embedded each time, and are the upper and lower bounds of the constraints, b i is a binary sequence, i is the serial number corresponding to the binary sequence.

[0040] In some embodiments, the watermark information is embedded using the CA-QIM concept. The texture coordinates are modified within the range calculated in step 2 to achieve the embedding of multi-level identity information. Taking the horizontal coordinate of the texture as an example, the calculation formula is as follows: (10) in for The decimal integer corresponding to the binary watermark. , the sequence to be embedded is 11, then a single coordinate embedding example is as follows Figure 2 shown.

[0041] The above steps S100 to S400 implement the watermark embedding process, which embeds the watermark to achieve the hiding of the real scene 3D model information. Figure 3 As shown, it is a watermark embedding flow chart provided by an embodiment of the present application. When embedding the watermark, identity information and original data are first obtained, wherein the original data is the real-scene three-dimensional model data. For identity information, multi-level identity information can be obtained by information grouping, and a group coding encapsulation combination is obtained after static Huffman coding, which includes a binary sequence to be embedded. For the original data, texture coordinates and texture images are extracted respectively, and the embedding parameter k is determined according to the texture coordinates, where k is the number of binary bits embedded each time, and the quantization step size is calculated. The image size, including height and width, is extracted according to the texture image, which is used to calculate the lossless embedding range, wherein the height and width are used to determine the lossless embedding range of the texture vertical coordinate and horizontal coordinate respectively. Finally, according to the group coding encapsulation combination, quantization supplement and lossless embedding range, quantization embedding is performed to obtain information-containing data.

[0042] In some embodiments, the real scene 3D model information hiding method further includes a multi-level identity information extraction step, such as Figure 4 The figure shows a multi-stage identity information extraction flow chart provided by an embodiment of the present application. Based on the information-containing data obtained in steps S100 to S400 above, texture coordinates and texture images are extracted, the embedding parameter k is obtained based on the texture coordinates, and the quantization step size is calculated. The image size is extracted based on the texture image and the lossless embedding range is calculated. Quantization extraction is performed based on the quantization step size and lossless embedding range to obtain a group coding combination. After regular expression search, static Huffman inverse coding, and majority voting mechanism processing, the identity information is obtained.

[0043] In some embodiments, the horizontal coordinate of the embedded texture coordinate is For example, the extraction process of multi-level identity information is as follows: Step 1: Calculate the quantization step size according to formula (1).

[0044] Step 2: According to formula (7), calculate the range of lossless coordinate modification.

[0045] (7) Where, are the horizontal coordinates after embedding information Determine the lower bound of the range of lossless modification, The width of the texture image.

[0046] Step 3: Extract multi-level identity information. Calculation The watermark information is obtained in the interval, and the calculation formula is as follows: (8) Where, is the quantization step size.

[0047] Will Convert to binary and you can get the embedded binary sequence. Figure 2 , a single coordinate extraction diagram is as follows Figure 5 shown.

[0048] Step 4: Combine the above binary sequences to obtain the binary encoding of multi-level identity information. Since the embedding is multiple times, the extracted information is , j is The number of times to embed repeatedly.

[0049] Step 6: Use Huffman coding to reverse the binary code of the matching code information to obtain the corresponding characters, and use the majority voting mechanism to obtain multi-level identity information .

[0050] In order to verify the performance of the method proposed in this application, this application selected three data sets with different file sizes and ranges as experimental data. The relevant information of the data is as follows: Figure 6 shown.

[0051] This embodiment designs two major categories of experiments: functional experiments and robustness experiments. Functional experiments include: invisibility experiments, losslessness experiments, independence experiments, and watermark capacity experiments. Robustness experiments include rotation attack experiments, scaling attack experiments, translation attack experiments, and deletion attack experiments. The experimental categories and experimental contents are shown in Table 1: Table 1 Experimental categories and contents of multi-level identity information hiding methods

[0052] Experiment 1: Invisibility experiment.

[0053] Objective experiments are generally performed by calculating the rate of change of coordinates after information embedding. In combination with the characteristics of the data in this paper, the error rate of texture information settlement is selected for calculation. The calculation formula is as follows: (11) in CER is the error rate, N e The number of texture calculation errors for the coordinates, N The above data are embedded and the statistical results are shown in Table 2: Table 2 Texture coordinate solution error rate

[0054] It can be seen that after the multi-level identity information is embedded, the display effect does not change from a subjective point of view, and the rendering effect before and after embedding is exactly the same. CER All are 0, indicating that each spatial coordinate obtains the same pixel coordinate through the texture coordinate. Since the texture image has not changed, each spatial coordinate can obtain the correct coordinate. Since the purpose of the design of this application method is to hide multi-level identity information, the basic requirement is to ensure that the rendering effect of the data remains unchanged. This application method embeds information by using improved quantization index modulation in the lossless interval to ensure that it does not affect the model rendering. In summary, the embedding of multi-level identity information does not affect the rendering effect of the real-life three-dimensional model.

[0055] Experiment 2: Non-destructive experiment.

[0056] As a means of transmitting information, multi-level identity information hiding methods should not only be more secure than file-based multi-level identity information transmission, but should also have no impact on spatial coordinates or keep the impact within a controllable range. To verify the impact of the multi-level identity information hiding algorithm on spatial coordinates, quantitative indicators such as root mean square error (RMSE) and coordinate error (Er) are used to represent it. The RMSE is calculated as follows: (12) in n The number of bit coordinates, and Respectively The coordinate values ​​of the coordinates before and after the watermark is embedded. RMSE can represent the impact of the information hiding algorithm on the coordinates of the data space. The smaller the value, the smaller the impact. Er The calculation formula is as follows: (13) in n is the number of coordinates, and Respectively The coordinate values ​​of a coordinate before and after the watermark is embedded. This indicator needs to be calculated for each coordinate point separately. The smaller the Er, the smaller the error, so the most representative Max(Er) and Min(Er) are selected to represent it.

[0057] After information hiding, the RMSE and Er of the above three data are calculated respectively. The results are shown in Table 3: Table 3 Nondestructive test results

[0058] Since the embedding domain of information hiding is independent of the spatial coordinates, the method of the present application does not affect the accuracy of the spatial coordinates at all.

[0059] Experiment 3: Embedding capacity experiment.

[0060] There is a key parameter in the multi-level identity information hiding algorithm k , represents the number of binary bits embedded in each coordinate. This parameter directly affects the algorithm capacity. In order to ensure that multi-level identity information can be fully embedded and there can be a sufficient number of repeated embedding times, k It can be as large as possible if the data allows. k Let's discuss and find the maximum value while ensuring the bit error rate (BER) is 0. The bit error rate calculation formula is as follows: (14) Where, E Indicates the number of error bits, A is the total number of bits.

[0061] To ensure the accuracy of multi-level identity information transmission and the effectiveness of the algorithm, k The value of starts from 1 and increases in sequence. Each data is embedded a sufficient number of times (more than 3000 times). k Under the value of , the proportion of multi-level identity information with an average bit error rate BER = 0 is SecRate. The experimental results are as follows Figure 7 As shown: According to experimental results, when k is less than 15, the bit error rate of all embedded information is 0, and when k is greater than or equal to 15, the phenomenon of incorrect embedding and extraction begins to occur.

[0062] Experiment 4: Robustness Experiment The multi-level identity information hiding method should be resistant to common operations on real-life 3D model data, including rotation, scaling, translation, cropping, and deletion, to ensure that the multi-level identity information is not lost during normal use. This embodiment regards these operations as attacks and extracts multi-level identity information from the data after the attack to verify the robustness of the method. This embodiment uses the NC value of the multi-level identity information extracted from the data after the attack to evaluate the robustness of the algorithm. The calculation formula of the NC value is shown in Equation (15): (15) Where: is the length of the data, and The corresponding values, .

[0063] The model data containing multi-level identity information are attacked separately: rotated 10° to 180°; scaled in the ratio of 1:0.1 to 1:5; translated 10m to 100m; cropped 10% to 50%; and randomly deleted files in the ratio of 10% to 50%. Then the NC value of the extracted multi-level identity information sequence is calculated as follows: Figure 8 As shown, from the above experiments, it can be obtained that the method of the present application has strong robustness and good resistance to rotation, translation, scaling, cropping and deletion attacks. The method in this embodiment is independent of the spatial coordinates and can completely resist spatial attacks. The technical effect is consistent with the experimental results. This also shows that the multi-level identity information will always exist in the data. First, the multi-level identity information will not be destroyed due to user behavior. The stable embedding of the multi-level identity information in the data protects the data from being illegally disseminated to a certain extent; secondly, the data will not be lost due to related operations in the normal use of the user, resulting in the problem of subsequent inability to decrypt, which provides the availability of the access control system.

[0064] According to the experimental results of Experiments 1 to 4 above, when k is less than 15, the bit error rate of all embedded information is 0. k When the number is greater than or equal to 15, the phenomenon of incorrect embedding and extraction begins to occur. k When the number is increased to 18, there are still groups that can be extracted completely correctly. Combining the principle of the method of this application, the following analysis is made on this phenomenon: From formula (1) and formula (10), we can get: (16) in K Determined by the embedded sequence and . Then after any identical coordinates are embedded into two different sequences, the coordinate difference is: (17) In the formula are the coordinate values ​​after embedding, and are the lower bounds of the range allowed to be modified, The decimal integers corresponding to the binary sequences to be embedded. Since the osgb data allows the data to be stored with a precision of ,like , due to the characteristics of the data, it has exceeded the data accuracy that can be saved, then , similar sequences cannot be distinguished. In summary, let , this is the most extreme case, k The value of is shown in formula (18): (18) After simplifying formula (18), we can get: (19) Where, , ,because Common sizes are 256, 512, and 1024, all of which are powers of 2, corresponding to k The maximum values ​​of are 17, 16, and 15, respectively. It is impossible to guarantee that the extraction is completely correct and consistent with the experimental results.

[0065] Therefore, this application proposes a method for losslessly hiding multi-level identity information based on improved quantization index modulation for texture coordinates. By calculating the lossless modification interval of texture coordinates and utilizing the concept of improved quantization index modulation, the multi-level identity information binary sequence is mapped to the lossless modification interval of texture coordinates. This method can hide large amounts of multi-level identity information without affecting the rendering effect and coordinate accuracy of the real-life 3D model data, and it also has good robustness.

[0066] The embodiment of the present application also provides a real scene three-dimensional model information hiding device, such as Figure 9 As shown, the real scene 3D model information hiding device includes: The data acquisition module 901 is configured to acquire real-scene 3D model data; wherein the real-scene 3D model data includes space coordinates, texture coordinates and texture images; A step size calculation module 902 is configured to determine a constrained quantization step size according to the width of the texture image and the number of bits of the binary sequence embedded each time; The interval calculation module 903 is configured to calculate the quantization interval that can still find the correct texture information through mapping after modification based on the principle of texture mapping; The information embedding module 904 is configured to modify the texture coordinates within the quantization interval based on the binary sequence to be embedded generated by the multi-level identity information to embed the multi-level identity information and obtain information-containing data.

[0067] An embodiment of the present application provides an electronic device, which may include a processor and a memory, wherein the processor and the memory can communicate with each other; illustratively, the processor and the memory communicate with each other via a communication bus.

[0068] The processor executes the computer-executable instructions stored in the memory, so that the processor implements the solutions in the above embodiments. The processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0069] The communication bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. System buses can be categorized as address buses, data buses, and control buses. Transceivers facilitate communication between the database access device and other computers (e.g., clients, read-write libraries, and read-only libraries). Memory may include random access memory (RAM) or non-volatile memory.

[0070] The electronic device provided in the embodiment of the present application may be the terminal device of the above embodiment.

[0071] An embodiment of the present application further provides a computer-readable storage medium, in which computer instructions are stored. When the computer instructions are executed on a computer, the computer executes the technical solution of the real-scene three-dimensional model information hiding method of the above embodiment.

[0072] An embodiment of the present application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When at least one processor executes the computer program, it can implement the technical solution of the real-scene three-dimensional model information hiding method in the above embodiment.

[0073] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of modules is only a logical function division. In actual implementation, there may be other division methods, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or module, which can be electrical, mechanical or other forms.

[0074] Modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of these modules may be selected to implement the solution of this embodiment based on actual needs.

[0075] In addition, the functional modules in the various embodiments of the present application may be integrated into a single processing unit, or each module may exist physically separately, or two or more modules may be integrated into a single unit. The above-mentioned modules may be implemented in the form of hardware or hardware plus software functional units.

[0076] The integrated modules implemented in the form of software function modules can be stored in a computer-readable storage medium. The software function modules stored in a storage medium include a number of instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute some of the steps of the methods of various embodiments of the present application.

[0077] It should be understood that the processor described above may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules within the processor.

[0078] The memory may include a high-speed RAM memory, and may also include non-volatile storage NVM, such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a magnetic disk or an optical disk.

[0079] A bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be divided into address buses, data buses, and control buses.

[0080] The storage medium may be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium may be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0081] An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic control unit or a main control device.

[0082] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for hiding information of a real-scene 3D model, characterized in that: The method comprises: Acquire real-scene 3D model data; wherein the real-scene 3D model data includes space coordinates, texture coordinates, and texture images; Determining a constrained quantization step size according to the width of the texture image and the number of bits of the binary sequence embedded each time; According to the principle of texture mapping, the quantization interval of the correct texture information can still be found through mapping after modification; Based on the binary sequence to be embedded generated by the multi-level identity information, the texture coordinates are modified within the quantization interval to achieve the embedding of the multi-level identity information and obtain the information-containing data.

2. The method for hiding information of a real-scene 3D model according to claim 1, characterized in that: According to the width of the texture image and the number of bits of the binary sequence embedded each time, the constrained quantization step size is determined by the following formula: （1） Where, is the quantization step size, is the width of the texture image, is the number of binary bits embedded each time.

3. The method for hiding information of a real-scene 3D model according to claim 1, wherein: The quantization interval is calculated by the following formula: （2） Where, The lower bound of the range for lossless modification, The upper bound of the range of lossless modification, when the horizontal coordinate after embedding information For non-destructive modification, is the width of the texture image, The horizontal coordinate to be embedded.

4. The method for hiding information of a real-scene 3D model according to claim 1, wherein: Generate the binary sequence to be embedded using the following formula: （3） Where, is the binary sequence to be embedded, For multi-level identity information, Huffman It is a static Huffman code.

5. The method for hiding information of a real-scene 3D model according to claim 1, wherein: Based on the binary sequence to be embedded generated by the multi-level identity information, the texture coordinates are modified within the quantization interval to achieve the embedding of the multi-level identity information, and the information-containing data is obtained, including: Based on the texture coordinates and the height and width of the texture image, the horizontal and vertical coordinates of the image are calculated using the following formula: （4） Where, x pixel and y pixel They are the horizontal and vertical coordinates of the picture respectively. u and v are the horizontal and vertical coordinates of the texture respectively, w and h are the height and width of the texture image respectively; When modifying texture coordinates, the modified values ​​of the coordinates are made to meet the conditions shown in formula (5) to ensure lossless modification: （5） Where, and The modified values ​​of the texture's horizontal and vertical coordinates; The texture coordinates are modified within the quantization interval by the following formula to achieve the embedding of multi-level identity information: （6） Where, is the value to be embedded, is the value after quantization index modulation, is the quantization step size, is the number of bytes embedded each time, and are the upper and lower limits of the quantization interval, respectively. for The decimal integer corresponding to the binary watermark, b i is a binary sequence, i is the serial number corresponding to the binary sequence.

6. The method for hiding information of a real-scene 3D model according to any one of claims 1 to 5, characterized in that: After obtaining the information-containing data, the method further includes: Calculating a range of lossless modification of coordinates based on the coordinates after the information is embedded in the information-containing data; Based on the range of losslessly modified coordinates, calculate The decimal integer corresponding to the binary watermark K ,Will K Convert to binary and get the embedded binary sequence; Combining the embedded binary sequences to obtain binary encoding of multi-level identity information; The binary code of the multi-level identity information is inversely encoded using Huffman coding to obtain the corresponding characters, and the extracted multi-level identity information is obtained using a majority voting mechanism. .

7. The method for hiding information of a real-scene 3D model according to claim 6, wherein: Based on the coordinates of the embedded information in the information-containing data, the range of lossless modification of the coordinates is calculated using the following formula: （7） Where, are the horizontal coordinates after embedding information Determine the lower bound of the range of lossless modification, is the width of the texture image; Based on the range of lossless modification of the coordinates, it is calculated by the following formula The decimal integer corresponding to the binary watermark K : （8） Where, is the quantization step size.

8. A real-scene three-dimensional model information hiding device, characterized in that: The device comprises: A data acquisition module is configured to acquire real-scene three-dimensional model data; wherein the real-scene three-dimensional model data includes space coordinates, texture coordinates and texture images; A step size calculation module is configured to determine a constrained quantization step size according to a width of the texture image and a number of bits of a binary sequence embedded each time; An interval calculation module is configured to calculate, based on the principle of texture mapping, a quantization interval that can still find correct texture information through mapping after modification; The information embedding module is configured to modify the texture coordinates within the quantization interval based on the binary sequence to be embedded generated based on the multi-level identity information to embed the multi-level identity information and obtain information-containing data.

9. An electronic device, characterized in that: include: a processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the real-scene three-dimensional model information hiding method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method for hiding information of a real-scene three-dimensional model according to any one of claims 1 to 7.

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