Visual identification method and device for detecting mold resistance of a material

Abstract

The application relates to the field of detection technology and discloses a visual identification method and device for material mold resistance detection, wherein the visual identification method for material mold resistance detection comprises the following steps: acquiring a test area of a material to be detected; acquiring a first colony area of a culture dish; determining a second colony area of the material to be detected based on the test area and the first colony area; and determining a mold resistance grade of the material to be detected based on the test area and the second colony area. The application determines the area of the material to be detected in the culture dish before culture, determines the colony growth area in the culture dish after the material to be detected is cultured in the culture dish for a certain time, and then determines the colony growth area on the surface of the material to be detected through the previously determined test area, so that the sample edge identification is clear, the accuracy and the efficiency are improved.

Description

Technical Field

[0001] This application relates to the field of testing technology, and in particular to a visual recognition method and apparatus for testing the mold resistance of materials. Background Technology

[0002] Mold resistance refers to a material's ability to resist mold growth, and this resistance is crucial for protecting human health and safety. Specifically, using highly mold-resistant materials can prevent mold from multiplying and growing in products or the environment, thereby reducing the risk of infection.

[0003] Furthermore, the prolonged damp and high-temperature environment inside buildings can easily lead to mold growth, negatively impacting the health and comfort of residents. Testing building materials for mold resistance can ensure a hygienic and healthy interior environment.

[0004] Different materials have different requirements for their resistance to mold. For example, GB / T 1741-2020 "Determination of resistance to mold in paint films", HG / T 3950-2007(2017) "Antibacterial coatings", and ISO 21265-2021 "Sealants for buildings and civil works - Evaluation of fungal growth on sealant surfaces" have specified the resistance to mold in building materials such as coatings and sealants.

[0005] The common method for assessing the mold resistance of materials using existing technologies is to observe the growth and reproduction of mold on the material surface. However, when testing the mold resistance of materials, it is necessary to place the material in a culture medium inoculated with mold spores (the culture medium is placed in a petri dish). During the testing process, mold often grows from the periphery of the culture medium towards the center of the surface of the material being tested. When assessing the mold resistance of a material, the mold on the material surface merges with the mold on the surrounding culture medium, blurring the boundary between the material surface and the surrounding culture medium. The tester cannot accurately distinguish the area of ​​mold growth on the material surface. Moreover, sealants and similar products in building materials have high viscoelasticity, and the edges of the prepared sample materials often have a certain degree of deformation and distortion. In visual recognition schemes, it is not possible to directly apply the standard dimensions of the sample materials specified in the standard (such as 50cm*50cm). Therefore, it is also impossible to improve the accuracy and efficiency of the mold resistance test by directly pre-setting the model of the sample material's edges and area. Summary of the Invention

[0006] To improve the efficiency and accuracy of material mold resistance testing, this application provides a visual recognition method and apparatus for material mold resistance testing.

[0007] On the one hand, this application provides a visual recognition method for detecting the mildew resistance of materials, which adopts the following technical solution:

[0008] A visual recognition method for detecting the mildew resistance of materials includes:

[0009] Obtain the test area of ​​the material to be tested;

[0010] Obtain the first colony region of the petri dish;

[0011] Based on the test area and the first colony area, the second colony area of ​​the material to be tested is determined;

[0012] Based on the test area and the second colony area, the mold resistance level of the material to be tested is determined;

[0013] The test area is the area where the material to be tested is located in the petri dish, the first colony area refers to the colony growth area inside the petri dish, and the second colony area is the colony growth area on the surface of the material to be tested.

[0014] By adopting the above technical solution, when testing the mold resistance of materials, the material to be tested needs to be placed in a petri dish inoculated with mold spores. After the material to be tested is placed in the petri dish and cultured for a period of time, the mold on the surface of the material and the mold on the surrounding culture medium will merge into one piece, blurring the boundary between the surface of the material and the surrounding culture medium, making it difficult to determine the second colony area.

[0015] Therefore, when determining the mold resistance level of the material to be tested, first determining the area where the material to be tested is located in the petri dish (i.e., defining the test area) can ensure that it is easier to observe and analyze the colony growth in subsequent steps. This allows for a more accurate assessment of the colony growth on the surface of the material to be tested, thereby improving the accuracy of mold resistance testing.

[0016] After the material to be tested has been cultured in a petri dish for a period of time, we can obtain the colony growth area in the petri dish, which is the first colony area. At this point, based on the previously determined test area, we can confirm the colony growth area on the surface of the material to be tested, which is the second colony area. This can improve both the accuracy and efficiency of mold resistance testing.

[0017] In summary, compared with previous manual identification and other visual identification methods, this application improves the accuracy and efficiency of material mold resistance testing and solves the problem of unclear sample edge identification.

[0018] For example, the test area for acquiring the material to be tested includes:

[0019] Obtain the raw data of the culture dish;

[0020] Identify the border of the culture dish and the boundary of the material to be tested in the original data;

[0021] The test area is determined based on the border of the petri dish and the boundary of the material to be tested;

[0022] The original data refers to photographs showing that no mold has formed on the surface of the petri dish and the material to be tested within it.

[0023] By employing the above technical solution, at the beginning of the experiment, raw data is obtained from the petri dishes, specifically photographs showing that no mold has formed on the surface of the petri dishes and the materials to be tested within them. These photographs can serve as the basic data for the experiment. Typically, these photographs are taken using a high-resolution camera to ensure image clarity and quality. Furthermore, to ensure consistent shooting conditions, fixed light sources and camera parameters are used.

[0024] Determining the experimental area typically requires calculating the relative position and extent of the material to be tested within the petri dish. Identifying the border of the petri dish and the boundary of the material to be tested in the raw data helps to more accurately delineate the experimental area. By using the identified border of the petri dish and the boundary of the material to be tested, the experimental area can be accurately determined, thus helping to reduce experimental errors, improve experimental repeatability, and provide a reliable basis for subsequent analysis.

[0025] In summary, by acquiring raw data and identifying the borders of the petri dishes and the boundaries of the materials to be tested, the experimental area can be divided more accurately, reducing experimental errors.

[0026] For example, the first colony region of the culture dish includes:

[0027] Obtain the culture data of the culture dish;

[0028] Identify the border of the culture dish in the culture data;

[0029] Using the border of the culture dish as a reference, the colony growth area within the culture dish is identified to determine the first colony area; wherein, the culture data is a photograph of mold growing on the surface of the material to be tested in the culture dish after the material to be tested has been placed in the culture dish for a certain period of time.

[0030] By adopting the above technical solution, after the material to be tested is placed in a petri dish for a certain period of time, we can obtain a photo of mold growing on the surface of the material to be tested in the petri dish and observe the growth of the colonies during the culture process.

[0031] Identifying the border of the culture dish helps establish a reference coordinate system identical to that of the experimental area, allowing for more accurate determination of the colony growth region. This step can be achieved using image processing techniques such as edge detection and contour extraction.

[0032] For example, determining the second colony region of the material to be tested based on the test area and the first colony region includes:

[0033] Using the border of the culture dish as a reference, the test area is mapped onto the first colony area;

[0034] Identify colony growth areas within the test area to determine the second colony area.

[0035] By employing the above technical solution, after the material to be tested has been cultured in a petri dish for a period of time, obtaining the second colony area may present the problem of difficulty in distinguishing the edges of the material. In the aforementioned steps, we have already identified the test area and the first colony area, and the reference coordinate system for both the test area and the first colony area is the border of the petri dish. This means that by simply mapping the test area to the first colony area, the colony growth area within the test area can be identified. By mapping the test area to the first colony area and identifying the colony growth area in the same coordinate system, the second colony area can be determined more accurately. This helps improve the accuracy of the mold resistance assessment of the material to be tested.

[0036] For example, determining the mold resistance level of the material to be tested based on the test area and the second colony area includes:

[0037] Calculate the area of ​​the second colony region and the area of ​​the test region;

[0038] The mold percentage is calculated based on the area of ​​the second colony region and the area of ​​the test region, and the mold resistance level of the material to be tested is determined based on the mold percentage.

[0039] By adopting the above technical solution, the mold resistance of the tested material can be objectively assessed by calculating the mold percentage, thus avoiding interference from human factors. Determining the mold resistance level based on the mold percentage quantifies the assessment process and facilitates data analysis and comparison.

[0040] For example, calculating the area of ​​the second colony region and the area of ​​the test region includes:

[0041] The culture data were preprocessed into images.

[0042] Separate the experimental area from the culture data;

[0043] Count the total number of first pixels in the test area, and convert the total number of first pixels into the area of ​​the test area;

[0044] The total number of second pixels in the second colony region is counted, and the total number of second pixels is converted into the area of ​​the second colony region.

[0045] By adopting the above technical solutions, image preprocessing and segmentation techniques can improve the accuracy of calculating the area of ​​the experimental area and the second colony area, thereby ensuring the correctness of subsequent mold percentage calculations. Utilizing computer vision technology for image processing and area calculation can automate the analysis process, improve efficiency, and reduce manual intervention. By converting the total number of first and second pixels into actual areas, image information can be quantified, facilitating data analysis and comparison.

[0046] An apparatus for detecting the mold resistance of auxiliary materials, employing the aforementioned visual recognition method for detecting the mold resistance of materials, the apparatus comprising:

[0047] The data acquisition module is used to acquire raw data and culture data;

[0048] The data processing module is used to preprocess the raw data and the culture data;

[0049] The data recognition module is used to identify the test area, the first colony area, and the second colony area.

[0050] The rating module is used to calculate the area of ​​the test area and the second colony area to determine the mold resistance rating of the material to be tested.

[0051] By employing the above technical solution, the data acquisition module is responsible for collecting raw and culture data, which can be images, videos, or other formats. The data processing module is responsible for preprocessing the raw and culture data, including noise reduction, filtering, and histogram equalization. This helps improve image quality, reduce errors, and thus ensure the accuracy and reliability of subsequent analysis. The data recognition module is responsible for identifying the test area, the first colony area, and the second colony area. This can be achieved through computer vision techniques, such as image segmentation and feature extraction. Through these techniques, the device can accurately identify and locate different colony areas, providing crucial data for subsequent mold resistance assessment. The grading module is responsible for calculating the area of ​​the test area and the second colony area to determine the mold resistance grade of the material to be tested. This process includes counting the total number of first pixels, counting the total number of second pixels, calculating the mold percentage, and judging the mold resistance grade according to predetermined standards or thresholds. This enables the device to objectively, quantitatively, and accurately assess the mold resistance of the material to be tested.

[0052] In summary, this application can accurately identify and locate different colony regions, thereby ensuring the accuracy of mold resistance assessment, automating the mold resistance assessment process of the tested materials, improving analytical efficiency, and reducing manual intervention.

[0053] For example, the data acquisition module includes a colony culture unit and a data acquisition unit. The colony culture unit includes an incubator with a petri dish holder for placing petri dishes. The data acquisition unit includes an acquisition slide rail and an image acquisition device slidably mounted on the acquisition slide rail for acquiring data.

[0054] By employing the above technical solutions, the incubator provides a constant temperature, humidity, and suitable environment for bacterial colony growth, which helps obtain reliable colony growth data. The petri dish holder facilitates the placement of petri dishes and maintains their stability, which is beneficial for subsequent data acquisition. The acquisition rail ensures that the image acquisition device moves smoothly and accurately during data acquisition, improving the precision of data acquisition. The image acquisition device, slidingly mounted on the acquisition rail, can capture information from the surface of the material being tested, such as colony growth, providing crucial data for subsequent analysis.

[0055] For example, the acquisition slide rail includes a first slide rail, a second slide rail, and a third slide rail. The first slide rail includes two rails, which are vertically arranged and respectively disposed on two opposite side walls of the incubator. The second slide rail is used to slide along the length direction of the first slide rail, and its two ends are slidably connected to the two first slide rails respectively. The third slide rail is used to slide along the length direction of the second slide rail, with one end slidably connected to the second slide rail and the other end extending in a direction opposite to the length direction of the second slide rail. The image acquisition device is slidably connected to the third slide rail and is used to slide along the length direction of the third slide rail.

[0056] By adopting the above technical solution, it is possible to achieve precise movement of the image acquisition device in three directions, thereby improving the accuracy of data acquisition. This setup enhances the stability, flexibility, accuracy, and automation of the device for testing the mold resistance of materials in terms of data acquisition, providing support for evaluating different types of materials.

[0057] For example, a storage compartment is provided on the second slide rail for accommodating the image acquisition device. A ventilation component for ventilation is provided in the storage compartment. A position sensor is provided on the surface of the storage compartment for the image acquisition device to enter and exit. The position sensor is used to transmit a position signal to the controller of the ventilation component. The controller turns the ventilation component on or off based on the position signal.

[0058] By adopting the above technical solution, the incubator is kept in a humid state for a long time. When not collecting data, the image acquisition device is placed in the storage compartment, which can isolate the moisture in the incubator and prevent the image acquisition device from being damaged.

[0059] In summary, this application includes at least one of the following beneficial technical effects:

[0060] 1. When determining the mold resistance level of the test material, first identifying the area of ​​the material in the petri dish ensures easier observation and analysis of colony growth in subsequent steps. This allows for a more accurate assessment of colony growth on the surface of the test material, thereby improving the accuracy of mold resistance testing. After the test material has been cultured in the petri dish for a period of time, the colony growth area in the petri dish is obtained. Based on the previously identified test area, the colony growth area on the surface of the test material can then be confirmed as the secondary colony area, further improving the efficiency of mold resistance testing.

[0061] 2. By acquiring raw data and identifying the borders of the petri dishes and the boundaries of the materials to be tested, the test area can be delineated more accurately, reducing experimental errors. Accurately determining the test area helps in observing and analyzing colony growth in subsequent steps, providing accurate data support for mold resistance testing. Attached Figure Description

[0062] Figure 1 This is a flowchart of the steps involved in a visual recognition method for testing the mold resistance of materials.

[0063] Figure 2 Figure a in the figure is a schematic diagram of the raw data of the test material with regular edges in a petri dish.

[0064] Figure 2 Figure b in the figure is a schematic diagram of the raw data of the material to be tested with irregular edges in a petri dish.

[0065] Figure 3 Figure a in the figure is a schematic diagram of the culture data of the test material with regular edges in a petri dish.

[0066] Figure 3 Figure b in the figure is a schematic diagram of the culture data of the test material with irregular edges in a petri dish.

[0067] Figure 3 Figure c in the figure is a schematic diagram of the second colony area of ​​the test material with regular edges.

[0068] Figure 3 Figure d in the figure is a schematic diagram of the second colony area of ​​the material to be tested with irregular edges.

[0069] Figure 4 This is a flowchart of step S1 in a visual recognition method for detecting the mold resistance of materials according to an embodiment of this application.

[0070] Figure 5 This is a flowchart of step S2 in a visual recognition method for detecting the mold resistance of materials in an embodiment of this application.

[0071] Figure 6 This is a flowchart of step S3 in a visual recognition method for detecting the mold resistance of materials in an embodiment of this application.

[0072] Figure 7 This is a flowchart of step S4 in a visual recognition method for detecting the mold resistance of materials in an embodiment of this application.

[0073] Figure 8 This is a flowchart of step S41 in a visual recognition method for detecting the mold resistance of materials in an embodiment of this application.

[0074] Figure 9 This is a schematic diagram of a device for testing the mold resistance of auxiliary materials in an embodiment of this application.

[0075] Figure 10 This is a schematic diagram of the structure of an auxiliary material mold resistance testing device in an embodiment of this application.

[0076] Figure 11 This is a schematic diagram of the internal structure of an auxiliary material mildew resistance testing device according to an embodiment of this application. Figure 1 .

[0077] Figure 12 This is a schematic diagram of the internal structure of an auxiliary material mildew resistance testing device according to an embodiment of this application. Figure 2 .

[0078] Explanation of reference numerals in the attached figures:

[0079] 1. Material to be tested; 2. Petri dish; 3. Test area; 4. First colony area; 5. Second colony area; 6. Data acquisition module; 61. Colony culture unit; 611. Incubator; 612. Petri dish support; 62. Data acquisition unit; 621. Acquisition rail; 6211. First rail; 6212. Second rail; 6213. Third rail; 622. Image acquisition device; 63. Storage compartment; 631. Partition; 632. Ventilation component; 64. Light strip; 7. Data processing module; 8. Data recognition module; 9. Grading module. Detailed Implementation

[0080] The present application will be further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the application and are not intended to limit the scope of the application.

[0081] Embodiment 1 of this application discloses a visual recognition method for detecting the mold resistance of materials. (Refer to...) Figure 1 A visual recognition method for detecting the mold resistance of materials includes the following steps:

[0082] S1. Obtain the test area 3 of the material to be tested 1;

[0083] Specifically, refer to Figure 2 and Figure 3 Test area 3 is the area where the test material 1 is located in petri dish 2. When testing the mold resistance of materials, the test material 1 needs to be placed in petri dish 2 inoculated with mold spores. After the test material 1 is placed in petri dish 2 and incubated for a period of time, colonies will grow on the test material 1. During growth, the colonies will cover the edges of the test material 1, making it difficult to determine the second colony area 5. Furthermore, it is difficult to prepare standard-shaped samples of building materials such as paints and sealants, i.e., it is impossible to obtain regular edges, and therefore it is impossible to test them using a pre-set template. When determining the mold resistance level of the test material 1, first determining the area where the test material 1 is located in petri dish 2 ensures that the colony growth is easier to observe and analyze in subsequent steps. This allows for a more accurate assessment of the colony growth on the surface of the test material 1, thereby improving the accuracy of the mold resistance test. (It is worth mentioning that...) Figure 3 The colony distribution shown is for illustrative purposes only and does not represent colony density. In practical applications, colonies will not be evenly distributed in the area.

[0084] Reference Figure 4 In different embodiments, different methods can be used to obtain the test area 3 of the material to be tested 1 in S1 above. Specifically, but not limited to, one method includes the following steps:

[0085] S11. Obtain the raw data for petri dish 2;

[0086] Specifically, the raw data consists of photographs or videos of petri dish 2 and the surface of the material to be tested 1 within petri dish 2 before mold growth occurs. These photographs or videos can serve as baseline data for the experiment. Typically, these photographs are taken using a high-resolution camera to ensure image clarity and quality. Furthermore, to ensure consistency in the photographing conditions for different materials to be tested 1, fixed light sources and camera parameters are used.

[0087] S12. Identify the border of petri dish 2 and the boundary of material 1 to be tested in the original data;

[0088] Identifying the border of petri dish 2 and the boundary of the material to be tested 1 in the raw data helps to more accurately delineate the test area 3.

[0089] S13. Determine the test area 3 based on the border of the petri dish 2 and the boundary of the material to be tested 1;

[0090] By identifying the border of the petri dish 2 and the boundary of the material to be tested 1, the test area 3 can be accurately determined, which helps to reduce experimental errors and provides a reliable basis for subsequent analysis.

[0091] S2. Obtain the first colony region 4 of petri dish 2;

[0092] Specifically, refer to Figure 3 The first colony area 4 refers to the colony growth area within the petri dish 2.

[0093] Reference Figure 5 In different embodiments, the first colony region 4 of the petri dish 2 can be obtained by different methods. As an example, the above-described S2 for obtaining the first colony region 4 of the petri dish 2 includes the following steps:

[0094] S21. Obtain the culture data of petri dish 2;

[0095] Among them, the culture data are photos of mold growing on the surface of the material to be tested 1 after it has been placed in the culture dish 2 for a certain period of time.

[0096] S22. Identify the border of culture dish 2 in the culture data;

[0097] S23. Using the border of petri dish 2 as a reference, identify the colony growth area within petri dish 2 to determine the first colony area 4; identifying the border of petri dish 2 helps to establish a reference coordinate system that is the same as the reference coordinate system of the test area 3, so as to more accurately determine the colony growth area. Specifically, the border of petri dish 2 can be identified by edge detection, contour extraction and other techniques.

[0098] S3. Based on test area 3 and first colony area 4, determine the second colony area 5 of the material to be tested 1;

[0099] Specifically, the second colony area 5 is the colony growth area on the surface of the material to be tested 1. (Refer to...) Figure 6 In different embodiments, the second colony region 5 can be determined in different ways. As an example, the process of determining the second colony region 5 includes the following steps:

[0100] S31. Using the border of the petri dish 2 as a reference, map the test area 3 onto the first colony area 4;

[0101] S32. Identify the colony growth areas in test area 3 to determine the second colony area 5.

[0102] After the material to be tested 1 has been cultured in the petri dish 2 for a period of time, it may be difficult to distinguish the edge of the material to be tested 1 when trying to obtain the second colony area 5. In the aforementioned steps, we have already identified the test area 3 and the first colony area 4, and the reference coordinate system of the test area 3 and the first colony area 4 is the border of the petri dish 2. This means that as long as the mapping between the test area 3 and the first colony area 4 is completed, the colony growth area in the test area 3 can be identified.

[0103] S4. Based on test area 3 and the second colony area 5, determine the mold resistance level of the material to be tested 1;

[0104] Reference Figure 7 Furthermore, determining the mold resistance level of the tested material 1 based on test area 3 and the second colony area 5 also includes the following steps:

[0105] S41. Calculate the area of ​​the second colony region 5 and the area of ​​the test region 3;

[0106] In different embodiments, different methods can be used to calculate the area of ​​the second colony region 5, and different methods can be used to calculate the area of ​​the test region 3, as referred to... Figure 8 As an example, the area of ​​the second colony region 5 and the area of ​​the test region 3 are calculated using the following method:

[0107] S411. Perform image preprocessing on the culture data;

[0108] Image preprocessing of culture data includes denoising, filtering, grayscale conversion, and binarization. This helps improve image quality, reduce errors, and thus ensure the accuracy and reliability of subsequent analysis. Image processing of culture data can also make colony growth areas more prominent.

[0109] S412. Separate experimental region 3 from the culture data;

[0110] The second colony region 5 is located above the test region 3. The test region 3 was mapped into the first colony region 4 during the identification of the second colony region 5. Separating the test region 3 from the culture data means that the second colony region 5 is also separated from the culture data.

[0111] S413. Count the total number of first pixels in test area 3, and convert the total number of first pixels into the area of ​​test area 3;

[0112] S414. Count the total number of second pixels in the second colony region 5, and convert the total number of second pixels into the area of ​​the second colony region 5.

[0113] By converting the total number of first and second pixels into actual area, image information can be quantified, facilitating data analysis and comparison. Utilizing computer vision technology for image processing and area calculation can automate the analysis process, improve efficiency, and reduce manual intervention.

[0114] S42. Calculate the mold percentage based on the area of ​​the second colony area 5 and the area of ​​the test area 3, and determine the mold resistance level of the material 1 to be tested based on the mold percentage.

[0115] Determining the mold resistance level based on the percentage of mold is a quantifiable method for assessing mold resistance, which is beneficial for data analysis and comparison. Specifically, in this application, the mold resistance level of the material 1 to be tested is classified according to the following table:

[0116] Mold growth on specimens Mold percentage Level / Class No growth 0 0 Trace growth ＜10 1 Small amount of growth ≥10 and <30 2 Moderate growth ≥30 and <60 3 Severe growth ≥60 4

[0117] Embodiment 2 of this application discloses an apparatus for testing the mold resistance of auxiliary materials. (Refer to...) Figure 9 and Figure 10 An apparatus for testing the mold resistance of auxiliary materials, employing the aforementioned visual recognition method for testing the mold resistance of materials, specifically includes a data acquisition module 6, a data processing module 7, a data recognition module 8, and a grade evaluation module 9. The data acquisition module 6 acquires raw data and culture data. The data processing module 7 preprocesses the raw data and culture data. The data recognition module 8 identifies the test area 3, the first colony area 4, and the second colony area 5. The grade evaluation module 9 calculates the area of ​​the test area 3 and the second colony area 5 to determine the mold resistance grade of the material 1 to be tested.

[0118] Specifically, the data acquisition module 6 is responsible for collecting raw data and culture data, which can be images, videos, or other formats. As an example, the data acquisition module 6 includes a colony culture unit 61 and a data acquisition unit 62. The colony culture unit 61 includes an incubator 611, which contains a culture dish support 612 for placing the culture dish 2. The data acquisition unit 62 includes a data acquisition rail 621 and an image acquisition device 622 slidably mounted on the data acquisition rail 621 for data acquisition.

[0119] Furthermore, the incubator 611 provides a constant temperature, constant humidity, and suitable growth environment for the colonies, which helps to obtain reliable colony growth data. The petri dish holder 612 facilitates the placement of petri dishes 2, maintains the stability of the petri dishes 2, and is beneficial for subsequent data collection. In this embodiment, multiple petri dishes 2 containing the same bacterial species can be placed on the petri dish holder 612, with different test materials 1 placed in the multiple petri dishes 2, so as to test the tolerance of different test materials 1 to the same bacterial species within the same environmental humidity, temperature, and cycle. Alternatively, multiple petri dishes 2 containing different bacterial species can be placed, with the same test material 1 placed in the multiple petri dishes 2, so as to test the tolerance of the same material to different bacterial species.

[0120] Reference Figure 11 and Figure 12The acquisition rail 621 ensures that the image acquisition device 622 moves smoothly and accurately during data acquisition, improving the accuracy of data acquisition. The image acquisition device 622, slidably mounted on the acquisition rail 621, can capture information from the surface of the material 1 to be tested, such as the colony growth, providing crucial data for subsequent analysis. The acquisition slide rail 621 and the image acquisition device 622 can be slidably connected in different ways. As an example, the acquisition slide rail 621 includes a first slide rail 6211, a second slide rail 6212, and a third slide rail 6213. The first slide rail 6211 includes two slide rails, which are arranged vertically and respectively on two opposite side walls of the incubator 611. The second slide rail 6212 is used to slide along the length direction of the first slide rail 6211, and both ends of the second slide rail 6212 are slidably connected to the two first slide rails 6211. The third slide rail 6213 is used to slide along the length direction of the second slide rail 6212. One end of the third slide rail 6213 is slidably connected to the second slide rail 6212, and the other end extends in a direction away from the length direction of the second slide rail 6212. The image acquisition device 622 is slidably connected to the third slide rail 6213 and is used to slide along the length direction of the third slide rail 6213. This configuration helps to achieve precise movement of the image acquisition unit 622 in three directions, thereby improving the accuracy of data acquisition. Furthermore, the first slide rail 6211, the second slide rail 6212, and the third slide rail 6213 can all be motorized slide rails, controlled by the same slide rail controller.

[0121] Furthermore, the incubator 611 is used to test the mold resistance of the material 1 to be tested. The environment is usually relatively humid, and the image acquisition device 622 is easily damaged if it is in a humid environment for a long time. In order to protect the image acquisition device 622, a storage compartment 63 is specifically, but not limited to, proposed. The storage compartment 63 is set on the second slide rail 6212 and is used to accommodate the image acquisition device 622. The storage compartment 63 is provided with a ventilation component 632 for ventilation. A position sensor is provided on the surface of the storage compartment 63 for the image acquisition device 622 to enter and exit. The position sensor is used to transmit a position signal to the controller of the ventilation component 632. The controller of the ventilation component 632 turns the ventilation component 632 on or off based on the position signal.

[0122] Specifically, the image acquisition device 622 is equipped with a partition 631 that mates with the surface of the storage compartment 63 for the image acquisition device 622 to enter and exit. When the image acquisition device 622 enters the storage compartment 63, the partition 631 mates with the storage compartment 63, making the interior of the storage compartment 63 a sealed space. At this time, opening the ventilation component 632 will not affect the temperature and humidity inside the incubator 611. When the image acquisition device 622 leaves the storage compartment 63, the controller of the ventilation component 632 shuts off the ventilation component 632 to prevent ventilation from affecting the temperature and humidity inside the incubator 611. The ventilation component 632 can be a fan or an electric door. In this embodiment, the ventilation component 632 is an electric door. When the electric door is opened, the storage compartment 63 can be connected to the outside world to achieve the effect of ventilation.

[0123] To improve the accuracy of the detection, an ultraviolet lamp can also be installed in the incubator 611. This lamp is used to sterilize the incubator 611 before detection to prevent interference from bacteria in the detection data, and also to sterilize the incubator 611 after detection to maintain the environment inside the incubator. It is worth mentioning that, to improve the clarity of the collected raw and cultured data, an acquisition lamp can also be installed in the incubator 611. The acquisition lamp can be fixedly connected to the image acquisition unit 622 and slides along with it. It is activated when the image acquisition unit 622 is working and is turned off when the image acquisition unit 622 returns to the storage compartment 63.

[0124] Furthermore, a light strip 64 that has both ultraviolet lamp and incandescent lamp functions can also be used. Before testing, the light strip 64 activates the ultraviolet lamp function for sterilization, and when collecting data, the light strip 64 activates the incandescent lamp function.

[0125] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A visual recognition method for detecting mold resistance of a material, characterized by, The method comprises: acquiring a test area (3) of the material to be detected (1); acquiring a first colony area (4) of the culture dish (2); determining a second colony area (5) of the material to be detected (1) based on the test area (3) and the first colony area (4); determining a mold resistance grade of the material to be detected (1) based on the test area (3) and the second colony area (5); wherein the test area (3) is an area where the material to be detected (1) is located in the culture dish (2), the first colony area (4) refers to a colony growth area in the culture dish (2), and the second colony area (5) is an area where colonies grow on the surface of the material to be detected (1); the acquisition of the test area (3) of the material to be detected (1) comprises: acquiring original data of the culture dish (2); identifying the frame of the culture dish (2) and the boundary of the material to be detected (1) in the original data; determining the test area (3) based on the frame of the culture dish (2) and the boundary of the material to be detected (1); wherein the original data is a photo of the culture dish (2) and the material to be detected (1) in the culture dish (2) without mold; the acquisition of the first colony area (4) of the culture dish (2) comprises: acquiring culture data of the culture dish (2); identifying the frame of the culture dish (2) in the culture data; identifying the colony growth area in the culture dish (2) based on the frame of the culture dish (2) to determine the first colony area (4); wherein the culture data is a photo of the surface of the material to be detected (1) in the culture dish (2) generating mold after the material to be detected (1) is placed in the culture dish (2) for a certain period of time; the determination of the second colony area (5) of the material to be detected (1) based on the test area (3) and the first colony area (4) comprises: mapping the test area (3) in the first colony area (4) based on the frame of the culture dish (2); identifying the colony growth area in the test area (3) to determine the second colony area (5).

2. The method of visual recognition of the detection of the resistance of materials to mold according to claim 1, characterized in that, the determination of the mold resistance grade of the material to be detected (1) based on the test area (3) and the second colony area (5) comprises: calculating the area of the second colony area (5) and the area of the test area (3); calculating the mold proportion based on the area of the second colony area (5) and the area of the test area (3), and determining the mold resistance grade of the material to be detected (1) according to the mold proportion.

3. The method of visual recognition of the detection of the resistance of materials to mold according to claim 2, characterized by the fact that, the calculation of the area of the second colony area (5) and the area of the test area (3) comprises: image preprocessing of the culture data; segmenting the test area (3) from the culture data; counting the first total number of pixels of the test area (3) and converting the first total number of pixels into the area of the test area (3); counting the second total number of pixels of the second colony area (5) and converting the second total number of pixels into the area of the second colony area (5).

4. A device for assisting in the detection of the mold resistance of a material, characterized in that, The application discloses a visual identification method for detecting the mold resistance of a material, and a device for assisting in detecting the mold resistance of the material. The data acquisition module (6) is used for acquiring original data and culture data; The data processing module (7) is used for preprocessing the original data and the culture data; The data identification module (8) is used for identifying a test area (3), a first colony area (4) and a second colony area (5); The grade evaluation module (9) is used for calculating the areas of the test area (3) and the second colony area (5) to determine the mold resistance grade of the material (1) to be detected.

5. The device for testing the mold resistance of an auxiliary material according to claim 4, wherein The data acquisition module (6) comprises a colony culture unit (61) and a data acquisition unit (62), the colony culture unit (61) comprises a culture box (611), the culture box (611) is provided with a culture dish support (612) for placing a culture dish (2), and the data acquisition unit (62) comprises an acquisition sliding rail (621) and an image collector (622) slidably arranged on the acquisition sliding rail (621) and used for acquiring data.

6. The device for detecting the mold resistance of an auxiliary material according to claim 5, wherein The acquisition sliding rail (621) comprises a first sliding rail (6211), a second sliding rail (6212) and a third sliding rail (6213), the first sliding rail (6211) comprises two first sliding rails (6211) which are vertically arranged and are arranged on opposite two side walls of the culture box (611), the second sliding rail (6212) is used for sliding along the length direction of the first sliding rail (6211), two ends of the second sliding rail (6212) are slidably connected with the two first sliding rails (6211) respectively, the third sliding rail (6213) is used for sliding along the length direction of the second sliding rail (6212), one end of the third sliding rail (6213) is slidably connected with the second sliding rail (6212), the other end extends away from the length direction of the second sliding rail (6212), and the image collector (622) is slidably connected with the third sliding rail (6213) and is used for sliding along the length direction of the third sliding rail (6213).

7. The device for testing the mold resistance of an auxiliary material according to claim 6, wherein The second sliding rail (6212) is provided with a storage bin (63), the storage bin (63) is used for containing the image collector (622), the storage bin (63) is provided with a ventilation piece (632) for ventilation, a position sensor is arranged on the surface of the storage bin (63) through which the image collector (622) enters or exits, the position sensor is used for transmitting a position signal to a controller of the ventilation piece (632), and the controller opens or closes the ventilation piece (632) based on the position signal.

Images