Vacuum cup surface defect automatic detection and classification system based on image recognition

Abstract

The invention relates to the technical field of vacuum cup surface detection, and discloses a vacuum cup surface defect automatic detection and classification system based on image recognition, which comprises a scratch recognition module, and the scratch recognition module is used for carrying out high-resolution image shooting on the surface of a produced vacuum cup by using an image acquisition device, recognizing the number, length and depth data of scratches on the surface of the vacuum cup by combining laser scanning equipment; and the defect classification module is used for obtaining a repair difficulty index according to the number, depth and length of the scratches on the surface of the vacuum cup, and comparing the repair difficulty index with a repair difficulty threshold value. According to the method, scratches are automatically detected through image recognition, manual intervention is reduced, the method is suitable for efficient quality control in a large-batch production environment, the system can accurately measure the number, length and depth of the scratches, and reliable data support is provided for evaluating the severity and repair difficulty of the scratches.

Description

Technical Field

[0001] The present invention relates to the technical field of vacuum flask surface detection, and in particular to an automatic vacuum flask surface defect detection and classification system based on image recognition. Background Art

[0002] Scratches are one of the most common defects on the surface of thermos bottles, especially in metal or coated products. Scratches can be caused by any carelessness during the manufacturing and packaging process. Therefore, identifying and controlling the generation of scratches is an important part of quality control.

[0003] During the factory production process, a small number of scratches on the surface of thermos bottles in a batch of production orders will be repaired. For minor scratches, the surface of the stainless steel thermos bottle can be restored by lightly polishing it. For deeper scratches, abrasive paste is needed to fill and smooth the scratches. However, how to identify and identify the scratches on each thermos bottle and classify them into different treatment methods still requires quality inspectors to judge and classify them, which makes the detection of scratch defects on the surface of the thermos bottle take a long time, inefficient, and may lead to misjudgments and omissions.

[0004] To this end, the present invention provides an automatic detection and classification system for surface defects of thermos cups based on image recognition. Summary of the invention

[0005] In view of the problems existing in the above-mentioned prior art, the purpose of the present invention is to provide an automatic detection and classification system for surface defects of thermos bottles based on image recognition, so as to detect and classify scratches on the surface of thermos bottles by using machine vision through image recognition technology, and help managers decide on appropriate treatment methods based on the classification results.

[0006] In order to achieve the above-mentioned purpose, the present invention provides the following technical solution: an automatic detection and classification system for surface defects of thermos cups based on image recognition, comprising:

[0007] A scratch recognition module, which is used to use an image acquisition device to take high-resolution images of the surface of the thermos cup after production, and to identify the number, length and depth of scratches on the surface of the thermos cup in combination with a laser scanning device;

[0008] A defect classification module, which is used to obtain a repair difficulty index according to the number, depth and length of scratches on the surface of the thermos cup, and compare the repair difficulty index with a repair difficulty threshold, and classify the thermos cup into a slight scratch defect or a severe scratch defect according to the comparison result;

[0009] A defect definition module, which is used to divide the thermos cup classified as having a serious scratch defect into corresponding areas according to the collected image data, and classify the thermos cup classified as having a serious scratch defect into an easily repairable thermos cup or a difficult to repair thermos cup according to the amount of areas of the thermos cup occupied by the scratches;

[0010] The result feedback module is used to compare the number of thermos cups classified as difficult to repair with the repair quantity threshold, and make a final judgment feedback based on the comparison result.

[0011] In some embodiments, a repair quantity threshold is set. After the thermos cup is classified as having a slight scratch defect or a severe scratch defect, the number of thermos cups classified as having a severe scratch defect in this production order is compared with the repair quantity threshold to determine whether to repair the defective thermos cup.

[0012] In some embodiments, when the number of thermos cups classified as having severe scratch defects is less than the repair quantity threshold, it indicates that the number of thermos cups with severe scratches on the surface in the current production batch is relatively small, and therefore a judgment is made to repair the defective thermos cups; and when the number of thermos cups classified as having severe scratch defects is greater than or equal to the repair quantity threshold, a first judgment is made not to repair the defective thermos cups.

[0013] In some embodiments, the specific method for obtaining the repair difficulty index is: obtaining the number, length and depth data of the scratches on the surface of the thermos cup, and the depth data is the maximum depth of the scratches, and obtaining the repair difficulty index The calculation method is as follows: ,in, Indicates the number of scratches on the thermos cup. Indicates The length of the scratch, Indicates The maximum depth of a scratch, , and is the weight coefficient, which is used to adjust the impact of each factor on the overall repair difficulty.

[0014] In some embodiments, the specific method of dividing the thermos cup classified as having severe scratch defects into areas is: based on the collected image data, the thermos cup is divided into a cup body area and a cup lid area, the cup body area is then divided into a cup body front area and a cup body back area, and the cup lid area is divided into a cup lid front area and a cup lid back area.

[0015] In some embodiments, the specific method of classifying a thermos cup classified as having severe scratch defects as an easily repairable thermos cup or a difficult to repair thermos cup is as follows: the amount of area occupied by the scratches in the thermos cup is compared with the easy to repair threshold; if the amount of area occupied by the scratches in the thermos cup is less than or equal to the easy to repair threshold, the thermos cup is classified as an easily repairable thermos cup; if the amount of area occupied by the scratches in the thermos cup is greater than the easy to repair threshold, the thermos cup is classified as a difficult to repair thermos cup.

[0016] In some embodiments, the specific method of judging feedback is: when the number of thermos cups that are difficult to repair is less than the repair quantity threshold, a judgment is made to repair the defective thermos cups; and when the number of thermos cups that are difficult to repair is greater than or equal to the repair quantity threshold, a judgment is made not to repair the defective thermos cups, and the defective thermos cups are re-produced or retrieved from inventory according to the number of defective thermos cups.

[0017] In some embodiments, after the scratch recognition module identifies the number of thermos cups with scratch defects on the surface, the total number of thermos cups required to be produced in the current production batch is obtained. When the number of thermos cups with scratches on the surface is identified to exceed the scratch defect threshold, the system directly feedbacks the results of the production line inspection, and re-produces or retrieves from inventory the same number of thermos cups as those with scratch defects to obtain the total number of thermos cups required by the order; when the number of thermos cups with scratches on the surface is identified to not exceed the scratch defect threshold, the next step of the defect classification module operation is executed.

[0018] In some embodiments, the specific method for obtaining the data of the number, length and depth of scratches on the surface of the thermos cup is:

[0019] Use image acquisition equipment to take high-resolution images of the surface of the thermos cup after production, and use edge detection algorithms to identify the boundaries of scratches on the surface of the thermos cup in the image. After extracting the contours of all scratches on the surface of the thermos cup, the total number of scratches is obtained, and the length of each scratch is measured using the image coordinate system. At the same time, a laser scanning device is used to emit a laser beam to measure the distance of the thermos cup surface, and the maximum depth of each scratch is measured by comparing the height difference between the scratch area and the surrounding normal surface.

[0020] The present invention further provides a computer-readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the above-mentioned automatic detection and classification system for surface defects of thermos cups based on image recognition.

[0021] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0022] Firstly, the present invention automatically detects scratches through image recognition, reduces human intervention, and reduces the risk of false detection and missed detection. It is suitable for efficient quality control in mass production environments. The system can accurately measure the number, length and depth of scratches, providing reliable data support for evaluating the severity of scratches and the difficulty of repair.

[0023] Secondly, after the present invention classifies the severity of scratches on the surface of the thermos cup for the first time, it allows the scratch classification to be dynamically adjusted according to the concentration of scratches on the surface area of ​​the thermos cup, so that the system can formulate repair and processing strategies more flexibly and accurately.

[0024] Third, through the refined detection and classification process, the detailed data collected by the present invention can be used to analyze and optimize the production process, identify and reduce the root causes of scratch defects, and improve the quality stability of future production. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a module schematic diagram of the automatic detection and classification system of the surface defects of the thermos cup based on image recognition of the present invention;

[0026] Figure 2 The figure is a schematic diagram of the working principle of the automatic detection and classification system for surface defects of thermos cups based on image recognition according to the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] It is to be understood that the term "one" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of an element may be one, while in another embodiment, the number of the element may be multiple, and the term "one" should not be understood as a limitation on the quantity.

[0029] See also Figure 1-Figure 2 , the present invention provides an automatic detection and classification system for surface defects of thermos cups based on image recognition, the system comprising a scratch recognition module, a defect classification module, a defect definition module and a result feedback module;

[0030] The scratch recognition module is used to use an image acquisition device to take high-resolution images of the surface of the thermos cup after production, ensuring that the entire surface of the thermos cup can be clearly seen, and use an edge detection algorithm to identify the scratch boundaries on the surface of the thermos cup in the image. After extracting the outlines of all scratches on the surface of the thermos cup, the total amount of scratches is obtained, and the length of each scratch is measured using the image coordinate system. At the same time, the laser scanning device emits a laser beam to measure the distance of the surface of the thermos cup, and the maximum depth of each scratch can be measured by comparing the height difference between the scratch area and the surrounding normal surface. The laser scanning data is combined with the image data, and the image data can be processed in real time to quickly screen and identify scratches and determine the areas that need to be analyzed in detail. The laser scanning can only perform a deep scan on the key areas, provide accurate depth information of these areas, and supplement the three-dimensional data that the image cannot provide. The combination of the two can achieve a more comprehensive scratch analysis, ensuring both speed and accuracy, thereby identifying the number, length and depth data of scratches on the surface of the thermos cup.

[0031] At the same time, after identifying the number of thermos cups with scratch defects on the surface, the total number of thermos cups required to be produced in the current production batch is obtained. When the number of thermos cups with scratch defects on the surface is identified to exceed the scratch defect threshold, it indicates that the raw materials or semi-finished products were not properly handled during the production process of this batch of orders, or the machinery and equipment used were improperly maintained and adjusted. The production line should be checked, and the same number of thermos cups with scratch defects as those with scratch defects should be re-produced or transferred from the inventory to obtain the total number of thermos cups required by the order. For example, the total number of thermos cups required to be produced in the current production batch is set to 100, and the scratch defect threshold is 10. When the number of thermos cups with scratch defects on the surface is 11, the same number of thermos cups with scratch defects as those with scratch defects should be re-produced or transferred from the inventory. When the number of thermos cups with scratch defects on the surface does not exceed the scratch defect threshold, the next step of the defect classification module is executed.

[0032] The defect classification module includes setting a repair difficulty threshold and a repair quantity threshold. The repair quantity threshold is half of the scratch defect threshold. When the number of thermos cups with scratches on the surface is identified to be less than the scratch defect threshold, a repair difficulty index is obtained based on the number, depth and length of scratches on the surface of the thermos cup, and the repair difficulty index is compared with the repair difficulty threshold. Based on the comparison result, the thermos cup is classified as a minor scratch defect or a severe scratch defect. Next, the number of thermos cups classified as severe scratch defects in this production order is compared with the repair quantity threshold to determine whether to repair the defective thermos cup.

[0033] Specifically, when the number of thermos cups classified as having severe scratch defects is less than the repair quantity threshold, it means that the number of thermos cups with severe scratches on the surface in this production batch is relatively small, and the corresponding defect repair time required is relatively short. Therefore, a judgment can be made to repair the defective thermos cups; and when the number of thermos cups classified as having severe scratch defects is greater than or equal to the repair quantity threshold, it means that at least half of the thermos cups in this production batch have severe surface scratches, and the repair process requires more energy and time of the staff. Comprehensive repair of the thermos cups with scratch defects may cause delayed delivery of the entire batch of orders. Therefore, a first judgment can be made not to repair the defective thermos cups.

[0034] For example, the total number of thermos cups to be produced in the current production batch is set to 100, the scratch defect threshold is 10, and the repair quantity threshold is 5. If the image acquisition device captures 11 produced thermos cups with scratch defects on their surfaces, the scratch defect threshold is exceeded, and the production line should be checked, and the defective thermos cups should be re-produced or retrieved from inventory;

[0035] If the image acquisition device captures 9 produced thermos cups with scratch defects on their surfaces, these 9 thermos cups will be classified as slight scratch defects or severe scratch defects. Set the number of thermos cups classified as slight scratch defects to 4 and the number of thermos cups classified as severe scratch defects to 5. Since the number of thermos cups classified as severe scratch defects is equal to the repair quantity threshold, the first judgment can be made not to repair the defective thermos cups, and the next step can be performed.

[0036] The defect definition module is used to divide the thermos cup classified as having severe scratch defects into corresponding areas according to the collected image data after it is determined for the first time that the defective thermos cup will not be repaired. For example, the thermos cup can be divided into a cup body area and a cup cover area, and the cup body area and the cup cover area are each divided into two, specifically, the cup body area is divided into a cup body front area and a cup body back area, and the cup cover area is divided into a cup cover front area and a cup cover back area, a total of four areas. After the area is divided, the image data is used to check whether the scratch appears in the corresponding area, and the thermos cup classified as having severe scratch defects is classified as an easy-to-repair thermos cup or a difficult-to-repair thermos cup according to the amount of area occupied by the scratch.

[0037] The specific reason for dividing the areas is that when polishing and repairing scratches on the surface of a thermos bottle, even if there are multiple scratches to be repaired in the same area, the same repair tools and materials can be concentratedly used. There is no need to frequently adjust the position of the thermos bottle or replace the repair tools. Repairs in more concentrated areas can reduce the difficulty of repairs and the time required.

[0038] The specific method of classifying a thermos cup with serious scratch defects as an easy-to-repair thermos cup or a difficult-to-repair thermos cup is as follows: compare the number of areas of the thermos cup occupied by scratches with the easy-to-repair threshold. If the number of areas of the thermos cup occupied by scratches is less than or equal to the easy-to-repair threshold, the thermos cup is classified as an easy-to-repair thermos cup; if the number of areas of the thermos cup occupied by scratches is greater than the easy-to-repair threshold, the thermos cup is classified as a difficult-to-repair thermos cup. For example, the thermos cup is divided into 4 areas, and the easy-to-repair threshold is 2. When the scratch only occupies 1 area of ​​the thermos cup, the thermos cup is classified as an easy-to-repair thermos cup, and when the scratch occupies 3 areas of the thermos cup, the thermos cup is classified as a difficult-to-repair thermos cup.

[0039] The result feedback module is used to compare the number of thermos cups classified as difficult to repair with the repair quantity threshold, and make a final judgment feedback based on the comparison result. Specifically, the number of thermos cups classified as difficult to repair is compared with the repair quantity threshold. When the number of thermos cups difficult to repair is less than the repair quantity threshold, it means that most of the scratches on the surface of the thermos cups in this production batch are easy to repair, and a judgment is made to repair the defective thermos cups; and when the number of thermos cups difficult to repair is greater than or equal to the repair quantity threshold, it means that there are many thermos cups in this production batch with scratches on the surface that are difficult to repair. In order to avoid time-consuming repairs and delayed delivery of the entire batch of orders, a judgment is made not to repair the defective thermos cups, and they are re-produced or retrieved from inventory according to the number of defective thermos cups.

[0040] The specific method for obtaining the repair difficulty index is:

[0041] Get the number, length and depth of scratches on the surface of the thermos cup. It should be noted that the depth here is the maximum depth of the scratches, and get the repair difficulty index The calculation method is:

[0042]

[0043] in, Indicates the number of scratches on the thermos cup. Indicates The length of the scratch, Indicates The maximum depth of a scratch, , and is the weight coefficient, which is used to adjust the impact of each factor on the overall repair difficulty.

[0044] As a preferred embodiment, it is possible to set two scratches on the surface of the thermos cup, with lengths of 20 mm and 25 mm, and maximum depths of 0.1 mm and 0.2 mm, respectively. , and ,but , it can be obtained that the repair difficulty index of the thermos cup is 8. The repair difficulty threshold is set to 10. Since the repair difficulty index of the thermos cup is less than the repair difficulty threshold, the system will classify the thermos cup as a thermos cup with slight scratch defects.

[0045] In general, the present invention aims to design an automatic detection and classification system for surface defects of thermos cups based on image recognition, in order to address the current problems of insufficient efficiency in the detection and classification of scratch defects on the surface of thermos cups, and the lack of means to take corresponding measures according to the difficulty of defect repair. The present invention obtains the specific number, length and depth data of scratches on the surface of the thermos cup through an image acquisition device, and judges whether the scratch defects of the thermos cup are easy to repair based on these data. When it is judged for the first time that it is not easy to repair, the thermos cup in the image data is further divided into regions, and each region represents an area where scratch repair can be concentrated. When the scratches that need to be repaired are concentrated in some areas, the thermos cups classified as severe scratch defects can be dynamically reclassified into easily repairable thermos cups, and the system can once again give feedback on the judgment result of whether the thermos cup needs to be repaired, so that after the thermos cup is produced, it can be repaired according to the severity of the actual scratch defects. The system can identify the situation and quickly give reasonable response measures. Compared with traditional manual inspection, which is time-consuming and easily affected by human factors, this system greatly improves the inspection speed and efficiency through automated image recognition and inspection, making quality control in mass production more efficient. The system can accurately obtain the number, length and depth data of scratches, and provide objective data support for subsequent repair decisions. Through these data, the severity of defects and the difficulty of repair can be more accurately assessed. The system can dynamically adjust the classification of scratches, and according to the concentration of the area, it allows severe scratches to be reclassified as easily repaired scratches. This flexibility enables the production line to make further decisions better.

[0046] The embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. The embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part, and or or installed from a removable medium. When the computer program is executed by the central processing unit, the above functions defined in the method of the present application are executed. It should be noted that the computer-readable medium mentioned above in the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, a system, device or device of an electrical, magnetic, optical, electromagnetic, infrared segment, or semiconductor, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wire segments, a portable computer disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical fiber, a portable compact disk read-only memory, an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless segments, wire segments, optical cables, RF, etc., or any suitable combination of the above.

[0047] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or the flow chart, and the combination of the square boxes in the block diagram and / or the flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0048] Those skilled in the art should understand that the above description is only a specific implementation mode of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.

Claims

1. The automatic detection and classification system of surface defects of thermos cups based on image recognition is characterized by: include: A scratch recognition module, which is used to use an image acquisition device to take high-resolution images of the surface of the thermos cup after production, and to identify the number, length and depth of scratches on the surface of the thermos cup in combination with a laser scanning device; A defect classification module, which is used to obtain a repair difficulty index according to the number, depth and length of scratches on the surface of the thermos cup, and compare the repair difficulty index with a repair difficulty threshold, and classify the thermos cup into a slight scratch defect or a severe scratch defect according to the comparison result; A defect definition module, which is used to divide the thermos cup classified as having a serious scratch defect into corresponding areas according to the collected image data, and classify the thermos cup classified as having a serious scratch defect into an easily repairable thermos cup or a difficult to repair thermos cup according to the amount of areas of the thermos cup occupied by the scratches; The result feedback module is used to compare the number of thermos cups classified as difficult to repair with the repair quantity threshold, and make a final judgment feedback based on the comparison result.

2. The automatic detection and classification system for surface defects of thermos cups based on image recognition according to claim 1 is characterized in that: Set a repair quantity threshold. After classifying the thermos cup as having a minor scratch defect or a severe scratch defect, compare the number of thermos cups classified as having a severe scratch defect in this production order with the repair quantity threshold to determine whether to repair the defective thermos cup.

3. The automatic detection and classification system for surface defects of thermos cups based on image recognition according to claim 2 is characterized in that: When the number of thermos cups classified as having severe scratch defects is less than the repair quantity threshold, it means that the number of thermos cups with severe scratches on the surface in this production batch is small, so a judgment is made to repair the defective thermos cups; when the number of thermos cups classified as having severe scratch defects is greater than or equal to the repair quantity threshold, the first judgment is made not to repair the defective thermos cups.

4. The automatic detection and classification system for surface defects of thermos cups based on image recognition according to claim 1 is characterized in that: The specific method for obtaining the repair difficulty index is: obtain the number, length and depth data of scratches on the surface of the thermos cup, and the depth data is the maximum depth of the scratches to obtain the repair difficulty index The calculation method is as follows: ,in, Indicates the number of scratches on the thermos cup. Indicates The length of the scratch, Indicates The maximum depth of a scratch, , and is the weight coefficient, which is used to adjust the impact of each factor on the overall repair difficulty.

5. The automatic detection and classification system for surface defects of thermos cups based on image recognition according to claim 1 is characterized in that: The specific method of dividing the thermos cup classified as having severe scratch defects into areas is: based on the collected image data, the thermos cup is divided into a cup body area and a cup lid area, the cup body area is then divided into a cup body front area and a cup body back area, and the cup lid area is divided into a cup lid front area and a cup lid back area.

6. The automatic detection and classification system for surface defects of thermos cups based on image recognition according to claim 1 is characterized in that: The specific method of classifying the thermos cup classified as a serious scratch defect as an easy-to-repair thermos cup or a difficult-to-repair thermos cup is as follows: the amount of area occupied by the scratches on the thermos cup is compared with the easy-to-repair threshold. If the amount of area occupied by the scratches on the thermos cup is less than or equal to the easy-to-repair threshold, the thermos cup is classified as an easy-to-repair thermos cup; If the area occupied by the scratches on the thermos cup is greater than the easy-to-repair threshold, the thermos cup is classified as a difficult-to-repair thermos cup.

7. The automatic detection and classification system for surface defects of thermos cups based on image recognition according to claim 6 is characterized in that: The specific method of judging feedback is: when the number of thermos cups that are difficult to repair is less than the repair quantity threshold, a judgment is made to repair the defective thermos cups; and when the number of thermos cups that are difficult to repair is greater than or equal to the repair quantity threshold, a judgment is made not to repair the defective thermos cups, and they are re-produced or retrieved from inventory according to the number of defective thermos cups.

8. The automatic detection and classification system for surface defects of thermos cups based on image recognition according to claim 1 is characterized in that: After the scratch recognition module identifies the number of thermos cups with scratch defects on the surface, the total number of thermos cups required to be produced in the current production batch is obtained. When the number of thermos cups with scratches on the surface is identified to exceed the scratch defect threshold, the system directly feedbacks the result that the production line needs to be checked, and re-produces or calls out the same number of thermos cups with scratch defects from the inventory to obtain the total number of thermos cups required by the order; When the number of thermos cups with scratches on the surface is identified to be less than the scratch defect threshold, the next step of the defect classification module is executed.

9. The automatic detection and classification system for surface defects of thermos cups based on image recognition according to claim 1 is characterized in that: The specific method of obtaining the scratch quantity, length and depth data on the surface of the thermos cup is: Use image acquisition equipment to take high-resolution images of the surface of the thermos cup after production, and use edge detection algorithms to identify the boundaries of scratches on the surface of the thermos cup in the image. After extracting the contours of all scratches on the surface of the thermos cup, the total number of scratches is obtained, and the length of each scratch is measured using the image coordinate system. At the same time, a laser scanning device is used to emit a laser beam to measure the distance of the thermos cup surface, and the maximum depth of each scratch is measured by comparing the height difference between the scratch area and the surrounding normal surface.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the automatic detection and classification system for surface defects of thermos cups based on image recognition as described in any one of claims 1 to 9.

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