Defect detection system based on high-speed image recognition of QR codes

Abstract

The present invention discloses a high-speed image recognition defect detection system based on QR codes, which belongs to the field of image processing and is used to solve the problem that the display status of current display devices cannot be viewed by the naked eye. The system includes an image processing module, a quality classification module and a transmission analysis module. The transmission analysis module is used to analyze the transmission status of image electronic components and generate transmission abnormality signals or transmission normal signals. The image processing module is used to process image electronic components to generate display defect signals or obtain normal image grid sets and abnormal image grid sets of real-time images. If the server receives the normal image grid sets and abnormal image grid sets of real-time images, the normal image grid sets and abnormal image grid sets of real-time images are sent to the quality classification module. The quality classification module is used to classify the image quality of real-time images. The present invention analyzes specific display details when the user selects a display device, so that the user can know the display quality of the display device.

Description

Technical Field

[0001] The present invention belongs to the field of image processing and relates to image defect recognition and detection technology, specifically to an image defect recognition and detection system based on high-speed recognition of two-dimensional codes. Background Art

[0002] An image is a vivid, lifelike description or portrait of an objective object and is the most commonly used carrier of information in human social activities. Alternatively, an image is a representation of an objective object, containing relevant information about the depicted object. It is people's primary source of information. According to statistics, approximately 75% of the information a person acquires comes from vision. Broadly speaking, an image is any visual image, including those recorded on paper, film or photographs, or on televisions, projectors, or computer screens. Images can be divided into two categories based on how they are recorded: analog and digital. Analog images, such as analog television images, record brightness information through variations in the intensity of a physical quantity (such as light or electricity). Digital images, on the other hand, use computer-stored data to record the brightness of each point in the image.

[0003] When selecting a display device, factors such as product parameters and price are often considered. The specific display conditions of the display device cannot be viewed with the naked eye, especially display defects and bad pixels on the display device. Therefore, we propose a defect detection system based on high-speed image recognition of QR codes. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a defect detection system based on high-speed image recognition of QR codes.

[0005] The technical problems to be solved by the present invention are:

[0006] How to analyze and understand display details when selecting a display device.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] The defect detection system based on high-speed image recognition of QR codes includes a user terminal, a data transmission module, a display module, a data acquisition module, an image processing module, a quality classification module, a transmission analysis module, and a server. The user terminal is used to upload an input electronic image and send it to the server and the display module through the data transmission module. The data acquisition module is used to collect the transmission data of the data transmission module and the transmission time of the electronic image and send them to the server. The server sends the transmission data and transmission time to the transmission analysis module.

[0009] The transmission analysis module is used to analyze the transmission status of the image electronic component and generate a transmission abnormality signal or a transmission normal signal;

[0010] When the electronic image is successfully uploaded to the server, the display module is used to display the electronic image; the data acquisition module is used to collect standard image data of the electronic image in the server and real-time image data of the electronic image in the display module and send them to the server, and the server sends the standard image data and real-time image data to the image processing module;

[0011] The image processing module is used to process the image electronic component, obtain the generated display defect signal or the normal image grid set and the abnormal image grid set of the real-time image and feed it back to the server. If the server receives the display defect signal, it forwards the display defect signal to the corresponding user terminal. If the server receives the normal image grid set and the abnormal image grid set of the real-time image, it sends the normal image grid set and the abnormal image grid set of the real-time image to the quality classification module;

[0012] The quality classification module is used to classify the image quality of the real-time image, obtain the image quality level of the real-time image and feed it back to the server, and the server sends the image quality level of the real-time image to the corresponding user terminal.

[0013] Furthermore, the transmission data is the real-time upload speed value of the network connected to the data transmission module when transmitting the image electronically;

[0014] The transmission time is the time when the electronic image transmission starts and stops;

[0015] The real-time image data is the real-time image displayed by the image electronic component through the display module, as well as the real-time length and real-time width of the real-time image;

[0016] The standard image data is the electronic image of the electronic image part, and the standard length and standard width of the electronic image.

[0017] Furthermore, the analysis process of the transmission analysis module is as follows:

[0018] Obtain the start transmission time and stop transmission time of the electronic image document, and set a fixed-length transmission analysis period with the start transmission time as the starting point and the stop transmission time as the end point;

[0019] Set several time points in the transmission analysis period and obtain the corresponding real-time upload speed values at several time points;

[0020] Calibrate the duration between adjacent time points to obtain several groups of time periods, and calculate the real-time upload speed change rate of the several groups of time periods;

[0021] Obtain the standard upload speed change rate stored in the server, and compare the real-time upload speed change rate with the standard upload speed change rate. If the real-time upload speed change rate is greater than the standard upload speed change rate, the corresponding time period is recorded as an abnormal time period; if the real-time upload speed change rate is less than or equal to the standard upload speed change rate, the corresponding time period is recorded as a normal time period;

[0022] The number of abnormal time periods and normal time periods is counted. If the number of abnormal time periods is greater than or equal to the number of normal time periods, a transmission abnormality signal is generated. If the number of abnormal time periods is less than the number of normal time periods, a transmission normal signal is generated.

[0023] Furthermore, the transmission analysis module feeds back the transmission abnormality signal or the transmission normal signal to the server. If the server receives the transmission normal signal, it does not perform any operation. If the server receives the transmission abnormality signal, it forwards the transmission abnormality signal to the corresponding user terminal.

[0024] Furthermore, the processing process of the image processing module is specifically as follows:

[0025] Acquire the standard length and standard width of the electronic image, and the real-time length and real-time width of the real-time image;

[0026] If the real-time length is different from the standard length or the real-time width is different from the standard width, a display defect signal is generated;

[0027] If the real-time length is the same as the standard length, and the real-time width is the same as the standard width, a coordinate system is established with the upper left corner of the electronic image and the real-time image as the origin, and then the electronic image is divided into a number of electronic image grids and the real-time image is divided into a number of real-time image grids; the coordinate position of the upper left corner of each electronic image grid and each real-time image grid is obtained, and the electronic image grid and the real-time image grid with the same upper left corner coordinate position are compared; then, pixels of different colors in the electronic image grid and the real-time image grid with the same upper left corner coordinate position are obtained, and the number of pixels of different colors is counted; if the number of pixels of different colors is the same, the real-time image grid is divided into the normal image grid set; if the number of pixels of any color is different, the real-time image grid is divided into the abnormal image grid set.

[0028] Furthermore, the division process of the quality division module is specifically as follows:

[0029] Acquire a normal image grid set and an abnormal image grid set of a real-time image;

[0030] The number of real-time image grids in the normal image grid set is counted and recorded as the number of abnormal image grids, and the number of real-time image grids in the abnormal image grid set is counted and recorded as the number of normal image grids;

[0031] If the number of abnormal image frames is less than the first abnormal number threshold, and the number of normal image frames is greater than or equal to the second normal number threshold, the image quality level of the real-time image is the high quality level;

[0032] If the number of abnormal image frames is greater than or equal to the first abnormal number threshold and less than the second abnormal number threshold, and the number of normal image frames is less than the second normal number threshold and greater than or equal to the first normal number threshold, the image quality level of the real-time image is the normal quality level;

[0033] If the number of abnormal image frames is greater than or equal to the second abnormal number threshold, and the number of normal image frames is less than the first normal number threshold, the image quality level of the real-time image is a defective quality level.

[0034] Furthermore, the value of the first abnormal number threshold is smaller than the value of the second abnormal number threshold, and the value of the first normal number threshold is smaller than the value of the second normal number threshold.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] The present invention uploads an input image electronic component through a user terminal and sends it to a server and a display module. First, a transmission analysis module is used to analyze the transmission status of the image electronic component, and a transmission abnormality signal or a transmission normal signal is generated and fed back to the corresponding user terminal. When the image electronic component is successfully uploaded to the server, the display module displays the image electronic component, and an image processing module is used to process the image electronic component to generate a display defect signal or obtain a normal image grid set and an abnormal image grid set of a real-time image. The display defect signal is sent to the corresponding user terminal, and the normal image grid set and the abnormal image grid set of the real-time image are sent to a quality classification module. The image quality of the real-time image is then divided by the quality classification module to obtain the image quality level of the real-time image and feed it back to the corresponding user terminal. The present invention analyzes specific display details when the user selects a display device, so that the user can know the display quality of the display device. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] To facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0038] Figure 1 is a block diagram of the overall system of the present invention;

[0039] Figure 2 This is another system block diagram of the present invention. DETAILED DESCRIPTION

[0040] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0041] Example 1

[0042] See also Figure 1 As shown, the defect detection system based on QR code high-speed recognition and image recognition includes a user terminal, a data transmission module, a display module, a data acquisition module, an image processing module, a quality classification module, an image review module, a transmission analysis module and a server;

[0043] In this embodiment, the user terminal is used for the user to register and log in to the system by scanning the QR code and entering personal information, and the personal information is sent to the server for storage; the personal information includes the user's real name, real-name authenticated mobile phone number, etc.

[0044] In a specific implementation, after the user registers and logs in, the user terminal is used to upload the electronic copy of the input image and send the electronic copy of the image to the server and display module through the data transmission module;

[0045] In an embodiment of the present invention, the data acquisition module is used to collect the transmission data of the data transmission module and the transmission time of the electronic image component, and send the transmission data and transmission time to the server, and the server sends the transmission data and transmission time to the transmission analysis module;

[0046] It should be noted that the transmission data refers to the real-time upload speed and the real-time download speed of the network connected to the data transmission module when transmitting the electronic image; the transmission time refers to the start time and the stop time of the transmission of the electronic image;

[0047] The transmission analysis module is used to analyze the transmission status of the electronic image. In this embodiment, the parameter of the real-time upload network speed is used. In a specific implementation, the real-time download network speed can also be used. The analysis process is as follows:

[0048] Step S1: Obtain the start transmission time and stop transmission time of the electronic image document, and set a fixed-length transmission analysis period with the start transmission time as the starting point and the stop transmission time as the end point;

[0049] Step S2: setting a number of time points in the transmission analysis period, and obtaining corresponding real-time upload speed values at the time points;

[0050] Step S3: Calibrate the duration between adjacent time points to obtain several groups of time periods, and calculate the real-time upload speed change rate of the several groups of time periods, specifically:

[0051] For example, if the time points are t1, t2, and t3, the real-time upload speed values corresponding to the time points t1, t2, and t3 are divided into SSWt1, SSWt2, and SSWt3. The time point from t1 to t2 is a time period, and the time point from t2 to t3 is a time period. The real-time upload speed change rate of the two time periods is obtained using the formulas |SSWt2-SSWt1| / (t2-t1) and |SSWt3-SSWt2| / (t3-t2).

[0052] Step S4: Obtain the standard upload speed change rate stored in the server, and compare the real-time upload speed change rate with the standard upload speed change rate;

[0053] If the real-time upload speed change rate is greater than the standard upload speed change rate, the corresponding time period is recorded as an abnormal time period. If the real-time upload speed change rate is less than or equal to the standard upload speed change rate, the corresponding time period is recorded as a normal time period.

[0054] Step S5: Count the number of abnormal time periods and normal time periods. If the number of abnormal time periods is greater than or equal to the number of normal time periods, generate a transmission abnormality signal. If the number of abnormal time periods is less than the number of normal time periods, generate a transmission normal signal.

[0055] The transmission analysis module feeds back the transmission abnormality signal or the transmission normal signal to the server. If the server receives the transmission normal signal, it does not perform any operation. If the server receives the transmission abnormality signal, it forwards the transmission abnormality signal to the corresponding user terminal.

[0056] When the electronic image is successfully uploaded to the server, the display module is used to display the electronic image. In a specific implementation, the display module is specifically a plurality of display devices;

[0057] The data acquisition module is used to collect standard image data of the image electronic component in the server and real-time image data of the image electronic component in the display module and send them to the server, and the server sends the standard image data and real-time image data to the image processing module;

[0058] It should be specifically noted that the real-time image data refers to the real-time image displayed by the image electronic component through the display module, as well as the real-time length and real-time width of the real-time image; the standard image data refers to the electronic image of the image electronic component, as well as the standard length and standard width of the electronic image;

[0059] The image processing module is used to process the image electronic components. The processing process is as follows:

[0060] Step S100: Acquire the standard length and standard width of the electronic image, and the real-time length and real-time width of the real-time image;

[0061] Step S200: If the real-time length is the same as the standard length, and the real-time width is the same as the standard width, proceed to the next step;

[0062] If the real-time length is different from the standard length or the real-time width is different from the standard width, a display defect signal is generated;

[0063] Step S300: establishing a coordinate system with the upper left corner of the electronic image and the real-time image as the origin, and then dividing the electronic image into a plurality of electronic image grids and the real-time image into a plurality of real-time image grids;

[0064] Step S400: Obtain the coordinate position of the upper left corner of each electronic image grid and each real-time image grid, and compare the electronic image grid and the real-time image grid with the same upper left corner coordinate position;

[0065] Step S500: obtaining pixels of different colors in the electronic image grid and the real-time image grid with the same upper left corner coordinate position, and counting the number of pixels of different colors;

[0066] If the number of pixels of different colors is the same, the real-time image grid is divided into the normal image grid set; if the number of pixels of any color is different, the real-time image grid is divided into the abnormal image grid set;

[0067] The image processing module feeds back the generated normal image grid set and abnormal image grid set showing the defect signal or real-time image to the server;

[0068] In this embodiment, the coordinate system is established with the upper left corner of the electronic image or real-time image as the origin. This is only a preferred method. In actual setting and processing, the coordinate system can also be established with the upper right corner, lower left corner, or lower right corner of the electronic image or real-time image as the origin, without specific limitation.

[0069] If the server receives a display defect signal, it forwards the display defect signal to the corresponding user terminal;

[0070] If the server receives the normal image grid set and the abnormal image grid set of the real-time image, the server sends the normal image grid set and the abnormal image grid set of the real-time image to the quality classification module;

[0071] The quality classification module is used to classify the image quality of the real-time image. The classification process is as follows:

[0072] Step SS1: obtaining a normal image grid set and an abnormal image grid set of a real-time image;

[0073] Step SS2: Count the number of real-time image grids in the normal image grid set and record it as the number of abnormal image grids; count the number of real-time image grids in the abnormal image grid set and record it as the number of normal image grids;

[0074] Step SS3: If the number of abnormal image frames is less than the first abnormal number threshold, and the number of normal image frames is greater than or equal to the second normal number threshold, the image quality level of the real-time image is a high-quality quality level;

[0075] If the number of abnormal image frames is greater than or equal to the first abnormal number threshold and less than the second abnormal number threshold, and the number of normal image frames is less than the second normal number threshold and greater than or equal to the first normal number threshold, the image quality level of the real-time image is the normal quality level;

[0076] If the number of abnormal image frames is greater than or equal to the second abnormal number threshold, and the number of normal image frames is less than the first normal number threshold, the image quality level of the real-time image is a defective quality level; wherein the value of the first abnormal number threshold is less than the value of the second abnormal number threshold, and the value of the first normal number threshold is less than the value of the second normal number threshold;

[0077] The quality classification module feeds back the image quality level of the real-time image to the server, and the server sends the image quality level of the real-time image to the corresponding user terminal. The user at the user terminal understands the display quality of the display module based on the image quality level.

[0078] Example 2

[0079] In another embodiment, see Figure 2 As shown, the server further includes an image review module, which is used to perform image repetition inspection on real-time images at a defective quality level. The specific working process is as follows:

[0080] Send the image electronic parts to different display modules, and then use the data acquisition module to display the real-time image data of the image electronic parts in the module;

[0081] The real-time image data of the image electronic component is sent to the image processing module for processing, and the processing result is sent to the quality classification module, so as to obtain the image quality level of the real-time image corresponding to the image electronic component again;

[0082] If the image quality level obtained again is the same as the image quality level obtained last time, a recognition correct signal is generated; otherwise, a recognition abnormal signal is generated;

[0083] The image re-inspection signal will feed back the correct identification signal or the abnormal identification signal to the server. If the server receives the correct identification signal, no operation will be performed. If the server receives the abnormal identification signal, the image electronic component will be re-identified for image defects.

[0084] Example 3

[0085] In this embodiment, the working method of the defect detection system based on high-speed image recognition of QR codes is as follows:

[0086] In step S101, the user terminal uploads an electronic image and transmits it to the server and display module via the data transmission module. The data acquisition module collects the transmission data and the transmission time of the electronic image from the data transmission module and transmits the transmission data and transmission time to the server. The server transmits the transmission data and transmission time to the transmission analysis module.

[0087] Step S102, analyze the transmission status of the electronic image document through the transmission analysis module, obtain the start transmission time and stop transmission time of the electronic image document, set a fixed-length transmission analysis period with the start transmission time as the starting point and the stop transmission time as the end point, set several time points in the transmission analysis period, and obtain the corresponding real-time upload network speed values at several time points, calibrate the time between adjacent time points to obtain several groups of time periods, calculate the real-time upload network speed change rate of several groups of time periods, and then obtain the standard upload network speed change rate stored in the server, compare the real-time upload network speed change rate with the standard upload network speed change rate, and if the real-time upload network speed change rate is If the rate is greater than the standard upload speed change rate, the corresponding time period is recorded as an abnormal time period. If the real-time upload speed change rate is less than or equal to the standard upload speed change rate, the corresponding time period is recorded as a normal time period. The number of abnormal time periods and normal time periods is counted. If the number of abnormal time periods is greater than or equal to the number of normal time periods, a transmission abnormality signal is generated. If the number of abnormal time periods is less than the number of normal time periods, a transmission normal signal is generated. The transmission analysis module feeds back the transmission abnormality signal or the transmission normal signal to the server. If the server receives the transmission normal signal, no operation is performed. If the server receives the transmission abnormality signal, it forwards the transmission abnormality signal to the corresponding user terminal.

[0088] Step S103: When the electronic image is successfully uploaded to the server, the display module displays the electronic image. The data acquisition module collects standard image data of the electronic image in the server and real-time image data of the electronic image in the display module and sends them to the server. The server sends the standard image data and real-time image data to the image processing module.

[0089] Step S104, using the image processing module to process the electronic component of the image, obtain the standard length and standard width of the electronic image, and the real-time length and real-time width of the real-time image, if the real-time length is different from the standard length or the real-time width is different from the standard width, then generate a display defect signal, if the real-time length is the same as the standard length, and the real-time width is the same as the standard width, then establish a coordinate system with the upper left corner of the electronic image and the real-time image as the origin, then divide the electronic image into a number of electronic image grids and the real-time image into a number of real-time image grids, then obtain the coordinate position of the upper left corner of each electronic image grid and each real-time image grid, compare the electronic image grid and the real-time image grid with the same upper left corner coordinate position, and finally obtain For pixels of different colors in the electronic image grid and the real-time image grid with the same upper left corner coordinate position, the number of pixels of different colors is counted. If the number of pixels of different colors is the same, the real-time image grid is divided into a normal image grid set. If the number of pixels of any color is different, the real-time image grid is divided into an abnormal image grid set. The image processing module feeds back the generated display defect signal or the normal image grid set and the abnormal image grid set of the real-time image to the server. If the server receives the display defect signal, it forwards the display defect signal to the corresponding user terminal. If the server receives the normal image grid set and the abnormal image grid set of the real-time image, it sends the normal image grid set and the abnormal image grid set of the real-time image to the quality classification module.

[0090] Step S105: The image quality of the real-time image is divided by the quality classification module, and a normal image grid set and an abnormal image grid set of the real-time image are obtained. The number of real-time image grids in the normal image grid set is counted and recorded as the abnormal image grid number, and the number of real-time image grids in the abnormal image grid set is counted and recorded as the normal image grid number. If the number of abnormal image grids is less than a first abnormal number threshold and the number of normal image grids is greater than or equal to a second normal number threshold, the image quality level of the real-time image is a high-quality quality level. If the number of abnormal image grids is greater than or equal to the first abnormal number threshold and less than the second abnormal number threshold, and the number of normal image grids is less than the second normal number threshold and greater than or equal to the first normal number threshold, the image quality level of the real-time image is a normal quality level. If the number of abnormal image grids is greater than or equal to the second abnormal number threshold and the number of normal image grids is less than the first normal number threshold, the image quality level of the real-time image is a defective quality level. The quality classification module feeds back the image quality level of the real-time image to the server. The server sends the image quality level of the real-time image to the corresponding user terminal. The user terminal understands the display quality of the display module based on the image quality level.

[0091] Step S106. At the same time, the server also includes an image review module, which uses the image review module to perform repeated image inspection on the real-time image at the defective quality level, and sends the image electronic component to different display modules. Then, the data acquisition module is used to display the real-time image data of the image electronic component in the module. The real-time image data of the image electronic component is sent to the image processing module for processing, and the processing result is sent to the quality classification module, so as to obtain the image quality level of the real-time image corresponding to the image electronic component again. If the image quality level obtained again is the same as the image quality level obtained last time, a correct recognition signal is generated, otherwise an abnormal recognition signal is generated. The image review signal will feed back the correct recognition signal or the abnormal recognition signal to the server. If the server receives the correct recognition signal, no operation is performed. If the server receives the abnormal recognition signal, the image defect recognition of the image electronic component is re-performed.

[0092] The above formulas are all dimensionless and numerically calculated. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The size of the weight coefficient and the proportional coefficient is to quantify each parameter to obtain a specific value, which is convenient for subsequent comparison. Regarding the size of the weight coefficient and the proportional coefficient, as long as it does not affect the proportional relationship between the parameter and the quantized value, it is fine.

[0093] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. Based on the high-speed image recognition defect detection system of QR code, it is characterized by: The system comprises a user terminal, a data transmission module, a display module, a data acquisition module, an image processing module, a quality classification module, a transmission analysis module, and a server. The user terminal is used to upload an input electronic image and send it to the server and the display module via the data transmission module. The data acquisition module is used to collect transmission data from the data transmission module and the transmission time of the electronic image and send them to the server. The server sends the transmission data and transmission time to the transmission analysis module. The transmission analysis module is used to analyze the transmission status of the image electronic component and generate a transmission abnormality signal or a transmission normal signal; When the electronic image is successfully uploaded to the server, the display module is used to display the electronic image; the data acquisition module is used to collect standard image data of the electronic image in the server and real-time image data of the electronic image in the display module and send them to the server, and the server sends the standard image data and real-time image data to the image processing module; The image processing module is used to process the image electronic component, obtain the generated display defect signal or the normal image grid set and the abnormal image grid set of the real-time image and feed it back to the server. If the server receives the display defect signal, it forwards the display defect signal to the corresponding user terminal. If the server receives the normal image grid set and the abnormal image grid set of the real-time image, it sends the normal image grid set and the abnormal image grid set of the real-time image to the quality classification module; The quality classification module is used to classify the image quality of the real-time image, obtain the image quality level of the real-time image and feed it back to the server, and the server sends the image quality level of the real-time image to the corresponding user terminal.

2. The defect detection system based on high-speed image recognition of two-dimensional codes according to claim 1 is characterized in that: The transmission data is the real-time upload speed value of the network connected to the data transmission module when transmitting image electrons; The transmission time is the time when the electronic image transmission starts and stops; The real-time image data is the real-time image displayed by the image electronic component through the display module, as well as the real-time length and real-time width of the real-time image; The standard image data is the electronic image of the electronic image part, and the standard length and standard width of the electronic image.

3. The defect detection system based on high-speed image recognition of two-dimensional codes according to claim 1 is characterized in that: The analysis process of the transmission analysis module is as follows: Obtain the start transmission time and stop transmission time of the electronic image document, and set a fixed-length transmission analysis period with the start transmission time as the starting point and the stop transmission time as the end point; Set several time points in the transmission analysis period and obtain the corresponding real-time upload speed values at several time points; Calibrate the duration between adjacent time points to obtain several groups of time periods, and calculate the real-time upload speed change rate of the several groups of time periods; Obtain the standard upload speed change rate stored in the server, and compare the real-time upload speed change rate with the standard upload speed change rate. If the real-time upload speed change rate is greater than the standard upload speed change rate, the corresponding time period is recorded as an abnormal time period; if the real-time upload speed change rate is less than or equal to the standard upload speed change rate, the corresponding time period is recorded as a normal time period; The number of abnormal time periods and normal time periods is counted. If the number of abnormal time periods is greater than or equal to the number of normal time periods, a transmission abnormality signal is generated. If the number of abnormal time periods is less than the number of normal time periods, a transmission normal signal is generated.

4. The defect detection system based on high-speed image recognition of two-dimensional codes according to claim 3 is characterized in that: The transmission analysis module feeds back the transmission abnormality signal or the transmission normal signal to the server. If the server receives the transmission normal signal, it does not perform any operation. If the server receives the transmission abnormality signal, it forwards the transmission abnormality signal to the corresponding user terminal.

5. The defect detection system based on high-speed image recognition of two-dimensional codes according to claim 1 is characterized in that: The processing process of the image processing module is as follows: Acquire the standard length and standard width of the electronic image, and the real-time length and real-time width of the real-time image; If the real-time length is different from the standard length or the real-time width is different from the standard width, a display defect signal is generated; If the real-time length is the same as the standard length, and the real-time width is the same as the standard width, a coordinate system is established with the upper left corner of the electronic image and the real-time image as the origin, and then the electronic image is divided into a number of electronic image grids and the real-time image is divided into a number of real-time image grids; the coordinate position of the upper left corner of each electronic image grid and each real-time image grid is obtained, and the electronic image grid and the real-time image grid with the same upper left corner coordinate position are compared; then, pixels of different colors in the electronic image grid and the real-time image grid with the same upper left corner coordinate position are obtained, and the number of pixels of different colors is counted; if the number of pixels of different colors is the same, the real-time image grid is divided into the normal image grid set; if the number of pixels of any color is different, the real-time image grid is divided into the abnormal image grid set.

6. The defect detection system based on high-speed image recognition of two-dimensional codes according to claim 1 is characterized in that: The division process of the quality division module is as follows: Acquire a normal image grid set and an abnormal image grid set of a real-time image; The number of real-time image grids in the normal image grid set is counted and recorded as the number of abnormal image grids, and the number of real-time image grids in the abnormal image grid set is counted and recorded as the number of normal image grids; If the number of abnormal image frames is less than the first abnormal number threshold, and the number of normal image frames is greater than or equal to the second normal number threshold, the image quality level of the real-time image is the high quality level; If the number of abnormal image frames is greater than or equal to the first abnormal number threshold and less than the second abnormal number threshold, and the number of normal image frames is less than the second normal number threshold and greater than or equal to the first normal number threshold, the image quality level of the real-time image is the normal quality level; If the number of abnormal image frames is greater than or equal to the second abnormal number threshold, and the number of normal image frames is less than the first normal number threshold, the image quality level of the real-time image is a defective quality level.

7. The defect detection system based on high-speed image recognition of two-dimensional codes according to claim 6 is characterized in that: The value of the first abnormal number threshold is smaller than the value of the second abnormal number threshold, and the value of the first normal number threshold is smaller than the value of the second normal number threshold.

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