Image transmission security intelligent early warning system based on image processing technology

Abstract

The application relates to the technical field of image processing, and particularly discloses an image transmission safety intelligent early warning system based on an image processing technology, which comprises an image information acquisition module, an image preprocessing module, an image analysis module, an intelligent early warning module, an image comprehensive analysis module, an image transmission safety evaluation module and a user interface module; the image information data is collected and preprocessed, the image data transmission safety coefficient, the image pixel difference degree coefficient and the image structure similarity coefficient are obtained through analysis, the image transmission comprehensive safety index is obtained through further analysis, the image content is automatically recognized and early warned through the introduction of the image processing technology, the safety of the image transmission can be effectively improved, and the safety risk can be reduced; meanwhile, the research and development of the system will further promote the development of the image processing technology and the artificial intelligence technology, and provide strong support for the technical innovation in the related fields.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to an intelligent early warning system for image transmission security based on image processing technology. Background Technology

[0002] With the rapid development of information technology, image data has become an indispensable information carrier in modern society. Image data is widely used in various fields, including but not limited to social media, telemedicine, security monitoring, industrial automation, and autonomous driving. However, image data faces numerous security threats during transmission, such as data tampering, data leakage, and unauthorized access. These threats can not only compromise data integrity but also lead to serious privacy breaches and social security problems. Therefore, ensuring the security and integrity of image data during transmission is of paramount importance.

[0003] Traditional intelligent early warning systems for image transmission security mostly focus on a single security mechanism. While they can ensure basic security, they have significant limitations. They rely excessively on manual review, which is inefficient and prone to errors; their technical means are limited and cannot comprehensively defend against complex network attacks; they lack real-time capabilities, making it difficult to respond quickly to security incidents; their level of intelligence is low, lacking advanced analysis and decision-making capabilities; at the same time, they have poor adaptability to complex environments, affecting the accuracy of identification and the effectiveness of early warning; furthermore, they lack comprehensive intelligent early warning functions and cannot monitor and warn of potential security threats in real time.

[0004] Therefore, with the development of technology, there is an urgent need to develop a more intelligent, automated, and real-time image transmission security early warning system to overcome existing limitations and better ensure the security and integrity of image data during transmission. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide an intelligent early warning system for image transmission security based on image processing technology, in order to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an intelligent early warning system for image transmission security based on image processing technology, comprising an image information acquisition module, an image preprocessing module, an image analysis module, an intelligent early warning module, an image comprehensive analysis module, an image transmission security assessment module, and a user interface module.

[0007] Image information acquisition module: includes image data transmission information acquisition unit, image pixel information acquisition unit and image structure information acquisition unit. Each acquisition unit is used to acquire comprehensive parameters during image transmission and transmit the acquired comprehensive parameters to image preprocessing module;

[0008] Image preprocessing module: used to preprocess the comprehensive parameters collected by the image information acquisition module and transmit the preprocessed data to the image analysis module;

[0009] Image analysis module: includes image data transmission security analysis unit, image pixel difference analysis unit and image structure similarity analysis unit. It imports the data transmitted by the image preprocessing module into the corresponding mathematical model of the analysis unit, calculates the image data transmission security coefficient, image pixel difference coefficient and image structure similarity coefficient, and transmits the calculation results to the intelligent early warning module.

[0010] Intelligent early warning module: It is used to compare the data transmitted by the image analysis module with the preset value to determine whether there is any abnormality, and to initiate emergency response measures and issue early warning signals for abnormal data;

[0011] Image Comprehensive Analysis Module: Based on the data transmitted by the intelligent early warning module, a mathematical model is established to calculate the comprehensive security index of image transmission and transmit it to the image transmission security assessment module;

[0012] Image transmission security assessment module: This module compares and analyzes the comprehensive security index of image transmission calculated by the image comprehensive analysis module with the comprehensive threshold, obtains a judgment result, and transmits the judgment result to the user interface module.

[0013] User interface module: Used to receive the transmission status and early warning signals of monitoring image data in real time, and to provide managers with safe transmission strategies and analysis reports.

[0014] Preferably, the image data transmission information acquisition unit is used to acquire image data transmission information parameters including the number of lost image data packets, the total number of sent image data packets, the amount of retransmitted data, the amount of original transmitted data, the key length, the amount of encrypted data, the encryption time, and the image data transmission delay time; the image pixel information acquisition unit is used to acquire image pixel parameters including the total number of pixels in the image, the pixel values ​​of the original image, and the pixel values ​​of the transmitted image; the image structure information acquisition unit is used to acquire image structure parameters including the set of pixel values ​​of the original image, the set of pixel values ​​of the transmitted image, and the dynamic range of the image pixel values.

[0015] Preferably, the image preprocessing module preprocesses the data by using existing filtering techniques to denoise, enhance, and compress the acquired images.

[0016] Preferably, the calculation steps for the image data transmission security factor are as follows:

[0017] A1: Calculate the packet loss rate of image data. The calculation model is as follows:

[0018]

[0019] Where Ldp represents the number of lost image data packets, and Tdp represents the total number of image data packets sent;

[0020] A2: Calculate the image data retransmission rate using the following model:

[0021]

[0022] Where Rdv represents the amount of retransmitted data and Odv represents the amount of original transmitted data;

[0023] A3: Calculate the encryption strength index. The calculation model is as follows:

[0024] Esi=α×log2(2 Kl ),

[0025] Where Kl represents the key length, with the unit of key length being bits, log represents the logarithmic function, and α represents a constant;

[0026] A4: Calculate the image data transmission security factor. The calculation model is as follows:

[0027]

[0028] Where TSC represents the security factor for image data transmission, Esi represents the encryption strength index, Edv represents the amount of encrypted data, Et represents the encryption time, Plr represents the image data packet loss rate, Esi represents the image data retransmission rate, and Dt represents the image data transmission delay time.

[0029] Preferably, the calculation model for the image pixel difference coefficient is as follows:

[0030]

[0031] Where PDC represents the image pixel difference coefficient, N represents the total number of pixels in the image, P1(i) represents the pixel value at position i in the original image, and P2(i) represents the pixel value at position i after image transmission.

[0032] Preferably, the calculation steps for the image structural similarity coefficient are as follows:

[0033] B1: Calculate image brightness similarity using the following model:

[0034]

[0035] Where L(x, y) represents the brightness similarity between the original image and the transmitted image, x represents the set of pixel values ​​in the original image, y represents the set of pixel values ​​in the transmitted image, and μx Let μ be the mean of the original image x. y Let C1 be the mean of the transmitted image y, and let C1 be a small positive constant, where C1 = (k1 × L). 2 L represents the dynamic range of the image pixel values, and k1 represents a constant much smaller than 1, where k1 takes the values ​​0.01 or 0.03.

[0036] B2: Calculate image contrast similarity using the following model:

[0037]

[0038] Where C(x, y) represents the contrast similarity between the original image and the transmitted image, σ x The variance, σ, is expressed as the variance of the original image x. y Let C2 be the variance of the transmitted image y, and let C2 be a small positive constant, where C2 = (k2 × L). 2 k2 represents a constant much smaller than 1, and the values ​​of k2 and k1 are similar.

[0039] B3: Calculate image structural similarity using the following model:

[0040]

[0041] Where S(x, y) represents the structural similarity between the original image and the transmitted image, σ xy Let C3 be the covariance of the original image x and the transmitted image y, and let C3 be a small positive constant.

[0042] B4: Calculate the image structure similarity coefficient. The calculation model is as follows:

[0043] SSC=L(x,y)×C(x,y)×S(x,y),

[0044] Wherein, SSC represents the image structure similarity coefficient, L(x,y) represents the brightness similarity between the original image and the transmitted image, C(x,y) represents the contrast similarity between the original image and the transmitted image, and S(x,y) represents the structural similarity between the original image and the transmitted image.

[0045] Preferably, the intelligent early warning module compares the data transmitted by the image analysis module with preset values ​​in the following specific way:

[0046] Extracting the image data transmission security factor, we obtain the formula for the image data transmission security change fluctuation coefficient: If the image data transmission security factor is less than the preset value TSC 预If the error is detected, it indicates that there is an abnormality in the image data transmission. The abnormal result will be sent to the management personnel, and emergency response measures will be initiated and an early warning signal will be issued. Otherwise, it indicates that there is no abnormality in the image data transmission.

[0047] Extract the image pixel difference coefficient to obtain the formula for the image pixel variation fluctuation coefficient: If the image pixel difference coefficient is greater than the preset value PDC 预 If the result is positive, it indicates that there is an anomaly in the transmitted image pixels. The anomaly result is sent to the management personnel, and emergency response measures are initiated to issue an early warning signal. Otherwise, it indicates that there is no anomaly in the transmitted image pixels.

[0048] Extracting the image structure similarity coefficient yields the formula for the image structure change fluctuation coefficient: If the image structure similarity coefficient is less than the preset value SSC 预 If the result is positive, it indicates that there is an anomaly in the image structure. The anomaly result is sent to the management personnel, and emergency response measures are initiated to issue an early warning signal. Otherwise, it indicates that there is no anomaly in the image structure.

[0049] Preferably, the calculation model for the comprehensive security index of image transmission is as follows:

[0050]

[0051] Wherein, TCSI represents the comprehensive security index of image transmission, TSC represents the security coefficient of image data transmission, PDC represents the image pixel difference coefficient, SSC represents the image structure similarity coefficient, and β represents other influencing factors of the comprehensive security index of image transmission.

[0052] Preferably, the image transmission security assessment module uses the following comparative analysis method:

[0053] The overall security index of image transmission is compared with the overall threshold. If the overall security index of image transmission is less than the overall threshold, it indicates that there is a security anomaly in the image transmission process. An analysis report is generated for the abnormal data and sent to the relevant management personnel for review and a warning signal is issued. Conversely, if the overall security index of image transmission is greater than the overall threshold, it indicates that there is no security anomaly in the image transmission process.

[0054] The technical effects and advantages of this invention are as follows:

[0055] 1. This invention acquires and preprocesses image information data, analyzes and obtains image data transmission security coefficient, image pixel difference coefficient, and image structure similarity coefficient, and further analyzes and obtains a comprehensive image transmission security index. By introducing image processing technology, it achieves automatic recognition and early warning of image content, which can effectively improve the security of image transmission and reduce security risks. At the same time, the development of this system will also promote the further development of image processing technology and artificial intelligence technology, providing strong support for technological innovation in related fields.

[0056] 2. By integrating advanced image processing technology and intelligent analysis algorithms, this invention can detect and warn of potential security threats during image transmission in real time, effectively reducing the risk of image information being illegally used and ensuring the integrity and confidentiality of image data;

[0057] 3. This invention can significantly improve the security and reliability of image transmission, reduce the risk of data leakage, and improve transmission efficiency. At the same time, it has a good user experience and regulatory compliance, providing users with an efficient, safe and reliable image transmission solution. Attached Figure Description

[0058] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0059] Figure 1 This is a schematic diagram of the overall system structure of the present invention.

[0060] Figure 2 This is a schematic diagram of the acquisition unit structure of the image information acquisition module of the present invention. Detailed Implementation

[0061] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] Please see Figure 1-2 As shown, the present invention provides an intelligent early warning system for image transmission security based on image processing technology, including an image information acquisition module, an image preprocessing module, an image analysis module, an intelligent early warning module, an image comprehensive analysis module, an image transmission security assessment module, and a user interface module.

[0063] The output of the image information acquisition module is electrically connected to the input of the image preprocessing module. The output of the image preprocessing module is electrically connected to the input of the image analysis module. The output of the image analysis module is electrically connected to the input of the intelligent early warning module. The output of the intelligent early warning module is electrically connected to both the input of the image comprehensive analysis module and the input of the user interface module. The output of the image comprehensive analysis module is electrically connected to both the input of the image transmission security assessment module and the input of the user interface module. The output of the image transmission security assessment module is electrically connected to the input of the user interface module.

[0064] The image information acquisition module includes an image data transmission information acquisition unit, an image pixel information acquisition unit, and an image structure information acquisition unit. Each acquisition unit is used to acquire comprehensive parameters during the image transmission process and transmit the acquired comprehensive parameters to the image preprocessing module.

[0065] In this embodiment, it should be specifically noted that the image data transmission information acquisition unit is used to acquire image data transmission information parameters including the number of lost image data packets, the total number of sent image data packets, the amount of retransmitted data, the amount of original transmitted data, the key length, the amount of encrypted data, the encryption time, and the image data transmission delay time; the image pixel information acquisition unit is used to acquire image pixel parameters including the total number of pixels in the image, the pixel values ​​of the original image, and the pixel values ​​of the transmitted image; the image structure information acquisition unit is used to acquire image structure parameters including the set of pixel values ​​of the original image, the set of pixel values ​​of the transmitted image, and the dynamic range of the image pixel values.

[0066] In this embodiment, it should be specifically noted that in a grayscale image, each pixel has a grayscale value, which is usually an integer between 0 and 255 (for an 8-bit grayscale image); therefore, the pixel set of a grayscale image is a set of these grayscale values, for example: {50, 100, 150, 200, ...}, which contains the grayscale values ​​of all pixels in the image.

[0067] For a color image, each pixel is represented by the values ​​of three color channels: red (R), green (G), and blue (B). These three values ​​are usually integers between 0 and 255 (for 8-bit color channels). Therefore, the set of pixels in a color image is actually a set of triplets, where each triplet represents the color information of a pixel. For example: {(100, 150, 200), (50, 100, 150), ...}, where each triplet (R, G, B) represents the color of a pixel.

[0068] The image preprocessing module is used to preprocess the comprehensive parameters collected by the image information acquisition module and transmit the preprocessed data to the image analysis module.

[0069] In this embodiment, it should be specifically explained that the image preprocessing module preprocesses the data by using existing filtering techniques to denoise, enhance, and compress the acquired images.

[0070] The image analysis module includes an image data transmission security analysis unit, an image pixel difference analysis unit, and an image structure similarity analysis unit. It imports the data transmitted by the image preprocessing module into the corresponding mathematical model of the analysis unit, calculates the image data transmission security coefficient, the image pixel difference coefficient, and the image structure similarity coefficient, and transmits the calculation results to the intelligent early warning module.

[0071] In this embodiment, the calculation steps for the image data transmission security factor need to be specifically explained as follows:

[0072] A1: Calculate the packet loss rate of image data. The calculation model is as follows:

[0073]

[0074] Where Ldp represents the number of lost image data packets, and Tdp represents the total number of image data packets sent;

[0075] A2: Calculate the image data retransmission rate using the following model:

[0076]

[0077] Where Rdv represents the amount of retransmitted data and Odv represents the amount of original transmitted data;

[0078] A3: Calculate the encryption strength index. The calculation model is as follows:

[0079] Esi=α×log2(2 Kl ),

[0080] Where Kl represents the key length, with the unit of key length being bits, log represents the logarithmic function, and α represents a constant;

[0081] A4: Calculate the image data transmission security factor. The calculation model is as follows:

[0082]

[0083] Where TSC represents the security factor for image data transmission, Esi represents the encryption strength index, Edv represents the amount of encrypted data, Et represents the encryption time, Plr represents the image data packet loss rate, Esi represents the image data retransmission rate, and Dt represents the image data transmission delay time.

[0084] In this embodiment, it should be specifically noted that the image data transmission security factor is an important input parameter of the intelligent early warning system method. A high security factor in image data transmission can significantly reduce the risk of data being stolen, tampered with, or lost during transmission.

[0085] In this embodiment, it should be specifically explained that the calculation model for the image pixel difference coefficient is as follows:

[0086]

[0087] Where PDC represents the image pixel difference coefficient, N represents the total number of pixels in the image, P1(i) represents the pixel value at position i in the original image, and P2(i) represents the pixel value at position i after image transmission.

[0088] In this embodiment, it is important to note that during image transmission, the system calculates the pixel difference coefficient between the received image and the original image to monitor in real time whether the image has been tampered with or damaged during transmission. Monitoring using the image pixel difference coefficient increases the sensitivity to image tampering, making even the slightest alteration difficult to escape the system's detection, thereby improving the security of image transmission. Furthermore, analyzing the image pixel difference coefficient allows for a direct assessment of the image transmission quality. A smaller difference coefficient indicates that the image is more intact during transmission, resulting in higher transmission quality and greater security. This helps in the timely detection and resolution of problems during transmission.

[0089] In this embodiment, it should be specifically explained that the calculation steps for the image structure similarity coefficient are as follows:

[0090] B1: Calculate image brightness similarity using the following model:

[0091]

[0092] Where L(x, y) represents the brightness similarity between the original image and the transmitted image, x represents the set of pixel values ​​in the original image, y represents the set of pixel values ​​in the transmitted image, and μ x Let μ be the mean of the original image x. y Let C1 be the mean of the transmitted image y, and let C1 be a small positive constant, where C1 = (k1 × L). 2L represents the dynamic range of the image pixel values, and k1 represents a constant much smaller than 1, usually taking the value 0.01 or 0.03.

[0093] B2: Calculate image contrast similarity using the following model:

[0094]

[0095] Where C(x, y) represents the contrast similarity between the original image and the transmitted image, σ x The variance, σ, is expressed as the variance of the original image x. y Let C2 be the variance of the transmitted image y, and let C2 be a small positive constant, where C2 = (k2 × L). 2 k2 represents a constant much smaller than 1, and k2 usually takes a value similar to k1;

[0096] B3: Calculate image structural similarity using the following model:

[0097]

[0098] Where S(x, y) represents the structural similarity between the original image and the transmitted image, σ xy Let C3 be the covariance of the original image x and the transmitted image y, and let C3 be a small positive constant.

[0099] In this embodiment, it should be specifically noted that C1, C2, and C3 are set to small positive numbers to avoid the denominator being zero and to increase numerical stability. L represents the dynamic range of the image pixel values; for example, for an 8-bit image, L = 255.

[0100] B4: Calculate the image structure similarity coefficient. The calculation model is as follows:

[0101] SSC=L(x,y)×C(x,y)×S(x,y),

[0102] Wherein, SSC represents the image structure similarity coefficient, L(x,y) represents the brightness similarity between the original image and the transmitted image, C(x,y) represents the contrast similarity between the original image and the transmitted image, and S(x,y) represents the structural similarity between the original image and the transmitted image.

[0103] In this embodiment, it should be specifically noted that the image structure similarity coefficient, as an important indicator for measuring image quality, can assess the similarity between two images. Its value ranges from 0 to 1; the closer the value is to 1, the more similar the two images are in structure; conversely, the greater the difference.

[0104] By calculating the structural similarity coefficient between the original image and the transmitted image, the system can assess whether significant quality loss has occurred during transmission. This helps to promptly identify and resolve problems in the transmission link, ensuring the integrity and accuracy of image information. When the system detects a significant degradation in the quality of the transmitted image, it may indicate a security vulnerability in the transmission link, such as tampering, interception, or interference. In this case, the system can automatically trigger a security warning mechanism, alerting relevant personnel to take timely measures to address the potential security threat.

[0105] The intelligent early warning module is used to compare the data transmitted by the image analysis module with preset values ​​to determine whether an anomaly has occurred, and to initiate emergency response measures and issue an early warning signal for abnormal data.

[0106] In this embodiment, it should be specifically explained that the intelligent early warning module compares the data transmitted by the image analysis module with the preset value in the following way:

[0107] Extracting the image data transmission security factor, we obtain the formula for the image data transmission security change fluctuation coefficient: If the image data transmission security factor is less than the preset value TSC 预 If the error is detected, it indicates that there is an abnormality in the image data transmission. The abnormal result will be sent to the management personnel, and emergency response measures will be initiated and an early warning signal will be issued. Otherwise, it indicates that there is no abnormality in the image data transmission.

[0108] Extract the image pixel difference coefficient to obtain the formula for the image pixel variation fluctuation coefficient: If the image pixel difference coefficient is greater than the preset value PDC 预 If the result is positive, it indicates that there is an anomaly in the transmitted image pixels. The anomaly result is sent to the management personnel, and emergency response measures are initiated to issue an early warning signal. Otherwise, it indicates that there is no anomaly in the transmitted image pixels.

[0109] Extracting the image structure similarity coefficient yields the formula for the image structure change fluctuation coefficient: If the image structure similarity coefficient is less than the preset value SSC 预 If the result is positive, it indicates that there is an anomaly in the image structure. The anomaly result is sent to the management personnel, and emergency response measures are initiated to issue an early warning signal. Otherwise, it indicates that there is no anomaly in the image structure.

[0110] In this embodiment, it should be specifically explained that the emergency response measures are: automatically cutting off the abnormal transmission channel and recording and saving the abnormal data for subsequent analysis.

[0111] The image comprehensive analysis module, based on the data transmitted by the intelligent early warning module, establishes a mathematical model to calculate the comprehensive security index of image transmission and transmits it to the image transmission security assessment module.

[0112] In this embodiment, it should be specifically explained that the calculation model for the comprehensive security index of image transmission is as follows:

[0113]

[0114] Wherein, TCSI represents the comprehensive security index of image transmission, TSC represents the security coefficient of image data transmission, PDC represents the image pixel difference coefficient, SSC represents the image structure similarity coefficient, and β represents other influencing factors of the comprehensive security index of image transmission.

[0115] The image transmission security assessment module is used to compare and analyze the comprehensive image transmission security index calculated by the image comprehensive analysis module with the comprehensive threshold, obtain a judgment result, and transmit the judgment result to the user interface module.

[0116] In this embodiment, it should be specifically explained that the image transmission security assessment module uses the following comparative analysis method:

[0117] The overall security index of image transmission is compared with the overall threshold. If the overall security index of image transmission is less than the overall threshold, it indicates that there is a security anomaly in the image transmission process. An analysis report is generated for the abnormal data and sent to the relevant management personnel for review and a warning signal is issued. Conversely, if the overall security index of image transmission is greater than the overall threshold, it indicates that there is no security anomaly in the image transmission process.

[0118] The user interface module is used to receive the transmission status and early warning signals of the monitoring image data in real time, and to provide managers with safe transmission strategies and analysis reports.

[0119] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0120] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An intelligent early warning system for image transmission security based on image processing technology, characterized in that, include: Image information acquisition module: includes image data transmission information acquisition unit, image pixel information acquisition unit and image structure information acquisition unit. Each acquisition unit is used to acquire comprehensive parameters during image transmission and transmit the acquired comprehensive parameters to image preprocessing module; Image preprocessing module: used to preprocess the comprehensive parameters collected by the image information acquisition module and transmit the preprocessed data to the image analysis module; Image analysis module: includes image data transmission security analysis unit, image pixel difference analysis unit and image structure similarity analysis unit. It imports the data transmitted by the image preprocessing module into the corresponding mathematical model of the analysis unit, calculates the image data transmission security coefficient, image pixel difference coefficient and image structure similarity coefficient, and transmits the calculation results to the intelligent early warning module. Intelligent early warning module: It is used to compare the data transmitted by the image analysis module with the preset value to determine whether there is any abnormality, and to initiate emergency response measures and issue early warning signals for abnormal data; Image Comprehensive Analysis Module: Based on the data transmitted by the intelligent early warning module, a mathematical model is established to calculate the comprehensive security index of image transmission and transmit it to the image transmission security assessment module; Image transmission security assessment module: This module compares and analyzes the comprehensive security index of image transmission calculated by the image comprehensive analysis module with the comprehensive threshold, obtains a judgment result, and transmits the judgment result to the user interface module. User interface module: used to receive the transmission status and early warning signals of monitoring image data in real time, and to provide managers with safe transmission strategies and analysis reports; The image data transmission information acquisition unit is used to acquire image data transmission information parameters including the number of lost image data packets, the total number of sent image data packets, the amount of retransmitted data, the amount of original transmitted data, the key length, the amount of encrypted data, the encryption time, and the image data transmission delay time. The image pixel information acquisition unit is used to acquire image pixel parameters including the total number of pixels in the image, the pixel values ​​of the original image, and the pixel values ​​of the transmitted image; the image structure information acquisition unit is used to acquire image structure parameters including the set of pixel values ​​of the original image, the set of pixel values ​​of the transmitted image, and the dynamic range of the image pixel values. The image preprocessing module preprocesses the data by using existing filtering techniques to denoise, enhance, and compress the acquired images. The steps for calculating the security factor of the image data transmission are as follows: A1: Calculate the packet loss rate of image data. The calculation model is as follows: Where Ldp represents the number of lost image data packets, and Tdp represents the total number of image data packets sent; A2: Calculate the image data retransmission rate. The calculation model is as follows: Where Rdv represents the amount of retransmitted data and Odv represents the amount of original transmitted data; A3: Calculate the encryption strength index. The calculation model is as follows: Esi=α×log2(2 Kl ), Where Kl represents the key length, with the unit of key length being bits, log represents the logarithmic function, and α represents a constant; A4: Calculate the image data transmission security factor. The calculation model is as follows: Where TSC represents the security factor for image data transmission, Esi represents the encryption strength index, Edv represents the amount of encrypted data, Et represents the encryption time, Plr represents the image data packet loss rate, Esi represents the image data retransmission rate, and Dt represents the image data transmission delay time. The calculation model for the image pixel difference coefficient is as follows: Where PDC represents the image pixel difference coefficient, N represents the total number of pixels in the image, P1(i) represents the pixel value at position i in the original image, and P2(i) represents the pixel value at position i after image transmission. The steps for calculating the image structural similarity coefficient are as follows: B1: Calculate image brightness similarity using the following model: Where L(x, y) represents the brightness similarity between the original image and the transmitted image, x represents the set of pixel values ​​in the original image, y represents the set of pixel values ​​in the transmitted image, and μ x Let μ be the mean of the original image x. y Let C1 be the mean of the transmitted image y, and let C1 be a small positive constant, where C1 = (k1 × L). 2 L represents the dynamic range of the image pixel values, and k1 represents a constant much smaller than 1, where k1 takes the values ​​0.01 or 0.

03. B2: Calculate image contrast similarity using the following model: Where C(x, y) represents the contrast similarity between the original image and the transmitted image, σ x The variance, σ, is expressed as the variance of the original image x. y Let C2 be the variance of the transmitted image y, and let C2 be a small positive constant, where C2 = (k2 × L). 2 k2 represents a constant much smaller than 1, and the values ​​of k2 and k1 are similar. B3: Calculate image structural similarity using the following model: Where S(x, y) represents the structural similarity between the original image and the transmitted image, σ xy Let C3 be the covariance of the original image x and the transmitted image y, and let C3 be a small positive constant. B4: Calculate the image structure similarity coefficient. The calculation model is as follows: SSC=L(x,y)×C(x,y)×S(x,y), Where SSC represents the image structure similarity coefficient, L(x,y) represents the brightness similarity between the original image and the transmitted image, C(x,y) represents the contrast similarity between the original image and the transmitted image, and S(x,y) represents the structural similarity between the original image and the transmitted image. The intelligent early warning module compares the data transmitted by the image analysis module with preset values ​​in the following specific way: Extracting the image data transmission security factor, we obtain the formula for the image data transmission security change fluctuation coefficient: If the image data transmission security factor is less than the preset value TSC 预 If the error is detected, it indicates that there is an abnormality in the image data transmission. The abnormal result will be sent to the management personnel, and emergency response measures will be initiated and an early warning signal will be issued. Otherwise, it indicates that there is no abnormality in the image data transmission. Extract the image pixel difference coefficient to obtain the formula for the image pixel variation fluctuation coefficient: If the image pixel difference coefficient is greater than the preset value PDC 预 If the result is positive, it indicates that there is an anomaly in the transmitted image pixels. The anomaly result is sent to the management personnel, and emergency response measures are initiated to issue an early warning signal. Otherwise, it indicates that there is no anomaly in the transmitted image pixels. Extracting the image structure similarity coefficient yields the formula for the image structure change fluctuation coefficient: If the image structure similarity coefficient is less than the preset value SSC 预 If the result is positive, it indicates that there is an anomaly in the image structure. The anomaly result is sent to the management personnel, and emergency response measures are initiated to issue an early warning signal. Otherwise, it indicates that there is no anomaly in the image structure. The calculation model for the comprehensive security index of image transmission is as follows: Wherein, TCSI represents the comprehensive security index of image transmission, TSC represents the security coefficient of image data transmission, PDC represents the image pixel difference coefficient, SSC represents the image structure similarity coefficient, and β represents other influencing factors of the comprehensive security index of image transmission.

2. The image transmission security intelligent early warning system based on image processing technology according to claim 1, characterized in that: The specific method for comparative analysis in the image transmission security assessment module is as follows: The overall security index of image transmission is compared with the overall threshold. If the overall security index of image transmission is less than the overall threshold, it indicates that there is a security anomaly in the image transmission process. An analysis report is generated for the abnormal data and sent to the relevant management personnel for review and a warning signal is issued. Conversely, if the overall security index of image transmission is greater than the overall threshold, it indicates that there is no security anomaly in the image transmission process.

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