Container detection method and device, security vehicle-mounted system and security monitoring system

Abstract

The present application provides a container detection method and device, a security vehicle-mounted system and a security monitoring system. The container detection method comprises the following steps: performing a logical "AND" operation on the image pixels of a first edge image and a second edge image to synthesize a third edge image; obtaining the outer contour of the third edge image, and filtering the small contours in the third edge image to obtain a fourth edge image; obtaining the number of circumscribed rectangles of the large contour in the fourth edge image; the container detection method of the present application can fit the pixel points in the first edge image and the second edge image, accurately find all the edges in the image, and reduce missed detection and false detection; by judging the number of circumscribed rectangles of the large contour in the fourth edge image, the door status of the container can be judged, which not only improves the detection efficiency and accuracy, but also is applicable to containers of any size and model, and effectively improves the safety during container transportation.

Description

Technical Field

[0001] The present application belongs to the field of logistics monitoring technology, and more specifically, relates to a container detection method and device, a security vehicle-mounted system, and a security monitoring system. Background Art

[0002] In the logistics industry, a container is a group of tools that can carry packaged or unpackaged goods for transportation and facilitate loading and unloading with mechanical equipment. The characteristics of containers are the standardization of their products and the entire transportation system established by them. It can standardize a huge object with a load of dozens of tons, and on this basis gradually realize a logistics system that matches ships, ports, routes, roads, transfer stations, bridges, tunnels, and multimodal transport around the world.

[0003] Since the container door is locked by only one lock, if the door is opened during transportation, it cannot be detected immediately. The door can only be opened and the goods must be inspected after the container is transported to the destination, resulting in poor security.

[0004] In addition, containers are mainly used for long-distance transportation. During long-term and long-distance transportation, their logistics information is updated slowly. After arriving at the designated site or warehouse, the warehouse staff must count it into the system before receiving its logistics information. Summary of the invention

[0005] The purpose of the embodiments of the present application is to provide a container detection method and device, a security vehicle system and a security monitoring system to solve the technical problems of poor safety performance and untimely tracking of logistics information in the container transportation process in the prior art.

[0006] To achieve the above purpose, the technical solution adopted by the present application is: to provide a container detection method, comprising the following steps:

[0007] Get the rear image of the container;

[0008] Gray-scale the tail image to obtain a gray-scale image;

[0009] Performing CANNY edge detection on the grayscale image to obtain a first edge image;

[0010] Convert the RGB space of the tail image to the HSV space to obtain an HSV space image;

[0011] Extracting the H channel in the HSV spatial image to perform CANNY edge detection to obtain a second edge image;

[0012] Performing a pixel logical “AND” operation on the first edge image and the second edge image to synthesize a third edge image;

[0013] Obtaining the outer contour of the third edge image and filtering the small contours in the third edge image to obtain a fourth edge image;

[0014] Calculating the number of circumscribed rectangles of the large contour in the fourth edge image;

[0015] If the number of circumscribed rectangles of the large outline is 1, it is determined that the container is in a closed state; if the number of circumscribed rectangles of the large outline is 2, it is determined that the container is in an open state.

[0016] Preferably, after synthesizing the third edge image, the method further comprises the following steps:

[0017] Morphological image processing is performed on the third edge image, and the morphological image processing method includes at least one of dilation and erosion processing.

[0018] Preferably, the small contour is a contour whose circumscribed rectangle in the third edge image has an area less than or equal to 100 pixels, and the large contour is a contour whose circumscribed rectangle in the fourth edge image has an area greater than 100 pixels.

[0019] The present application also provides a container detection device, which is installed on a container and includes a microprocessor, a lock control switch, a mechanical lock, an image acquisition camera, a gyroscope, a solar power supply component, a wireless communication module, and an alarm device;

[0020] The lock control switch, image acquisition camera, gyroscope, solar power supply component, wireless communication module and alarm device are respectively connected to the microprocessor, and the lock control switch can control the state of the mechanical lock;

[0021] Wherein, the image acquisition camera is used to obtain the rear image of the container;

[0022] The microprocessor is used to grayscale the tail image to obtain a grayscale image;

[0023] The microprocessor is used for performing CANNY edge detection on the grayscale image to obtain a first edge image;

[0024] The microprocessor is used for converting the RGB space of the tail image into the HSV space to obtain an HSV space image;

[0025] The microprocessor is used to extract the H channel in the HSV spatial image to perform CANNY edge detection to obtain a second edge image;

[0026] The microprocessor is used for performing an image pixel logic “AND” operation on the first edge image and the second edge image to synthesize a third edge image;

[0027] The microprocessor is used to obtain the outer contour of the third edge image and filter the small contours in the third edge image to obtain a fourth edge image;

[0028] The microprocessor is used to obtain the number of circumscribed rectangles of the large outline in the fourth edge image. If the number of circumscribed rectangles of the large outline is 1, it is determined that the container is in a closed state. If the number of circumscribed rectangles of the large outline is 2, it is determined that the container is in an open state, so that the alarm device sounds.

[0029] Preferably, the solar power supply component includes a solar panel, a rechargeable battery and a power management module, the solar panel and the rechargeable battery are respectively connected to the power management module, and the power management module is connected to the microprocessor.

[0030] Preferably, the mechanical lock is provided with a magnet, and the magnet is used to be adsorbed on the container.

[0031] Preferably, the container detection device comprises a keyboard, and the keyboard is connected to the microprocessor.

[0032] Preferably, the container detection device comprises a display screen, and the display screen is connected to the microprocessor.

[0033] Preferably, the container detection device comprises an indicator light, and the indicator light is connected to the microprocessor.

[0034] Preferably, the container detection device comprises a GPS module, and the GPS module is connected to the microprocessor.

[0035] Preferably, the container detection device comprises an infrared camera, and the infrared camera is connected to the microprocessor.

[0036] The present application also provides a vehicle-mounted security system, which includes a vehicle-mounted central control system and the container detection device as described above, and the vehicle-mounted central control system is connected to the container detection device via a wireless communication module.

[0037] The present application also provides a security monitoring system, which includes a background client, a smart phone and the container detection device as described above, and the background client, the smart phone and the container detection device are connected via a wireless communication module.

[0038] The beneficial effects of the container detection method provided by the present application are as follows: compared with the prior art, by performing a logical "AND" operation on the image pixels of the first edge image and the second edge image, the pixel points in the first edge image and the second edge image can be fitted, all the edges in the image can be accurately found, and missed detections and false detections can be reduced; by judging the number of circumscribed rectangles of the large outline in the fourth edge image, the door status of the container can be judged, which not only improves the detection efficiency and accuracy, but also is applicable to containers of any size and model, effectively improving the safety during container transportation.

[0039] The beneficial effects of the container detection device provided by the present application are as follows: compared with the prior art, the solar power supply component is used for power supply, which is energy-saving and environmentally friendly, and improves the endurance; the gyroscope is used to sense the vibration of the container, which can work intermittently and save energy and electricity; the image of the tail of the container can be obtained by the image acquisition camera, and the microprocessor determines the state of the container door through image processing, realizes the anti-theft alarm function, can be remotely monitored, and improves the safety of the container.

[0040] The beneficial effect of the security vehicle-mounted system provided by the present application is that, compared with the prior art, the vehicle-mounted central control system is connected to the container detection device through a wireless communication module, the container status can be monitored by the vehicle-mounted central control system, and the vehicle-mounted safety is improved.

[0041] The beneficial effect of the security monitoring system provided by the present application is that, compared with the prior art, the background client, the smart phone and the container detection device are connected through a wireless communication module, and the user can remotely monitor the container status through the background client and the smart phone, thereby improving the safety, reliability, convenience and flexibility of logistics transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0043] Figure 1 A flowchart of a container detection method provided in an embodiment of the present application;

[0044] Figure 2 for Figure 1 A simplified flow chart of the container detection method in FIG.

[0045] Figure 3A partial schematic diagram of a closed door in a tail image provided in an embodiment of the present application;

[0046] Figure 4 A partial schematic diagram of a door in an open state in a tail image provided in an embodiment of the present application;

[0047] Figure 5 A schematic diagram of the three-dimensional structure of the container detection device provided in an embodiment of the present application when used on a container;

[0048] Figure 6 for Figure 5 A schematic diagram of the system module structure of the container detection device;

[0049] Figure 7 for Figure 5 A schematic diagram of the three-dimensional structure of the container detection device;

[0050] Figure 8 for Figure 5 A schematic diagram of a system module structure of another embodiment of a container detection device;

[0051] Fig. 9 A schematic diagram of a three-dimensional structure of an application scenario of a security vehicle system provided in an embodiment of the present application;

[0052] Fig.10 A schematic diagram of the application environment of the security monitoring system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0054] It should be noted that when an element is referred to as being "fixed to" or "disposed on" another element, it can be directly on the other element or indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or indirectly connected to the other element.

[0055] It should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0056] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0057] Please also read Figures 1 to 4 , the container detection method provided in the embodiment of the present application is now described. The container detection method comprises the following steps:

[0058] Step S1, obtaining a rear image of a container;

[0059] Step S2, graying the tail image to obtain a grayscale image;

[0060] Step S3, performing CANNY edge detection on the grayscale image to obtain a first edge image;

[0061] Step S4, converting the RGB space of the tail image into the HSV space to obtain an HSV space image;

[0062] Step S5, extracting the H channel in the HSV spatial image to perform CANNY edge detection to obtain a second edge image;

[0063] Step S6, performing a pixel logical “AND” operation on the first edge image and the second edge image to synthesize a third edge image;

[0064] Step S7, obtaining the outer contour of the third edge image, and filtering the small contours in the third edge image to obtain a fourth edge image;

[0065] Step S8, obtaining the number of circumscribed rectangles of the large contour in the fourth edge image;

[0066] Step S9: if the number of circumscribed rectangles of the large outline is 1, it is determined that the container is in a closed state; if the number of circumscribed rectangles of the large outline is 2, it is determined that the container is in an open state.

[0067] It can be understood that, in step S1, the image of the rear of the container can be understood as an image of the entire surface of the rear of the container, or can be understood as a local image of the rear of the container, in order to obtain the size of the door seam at the rear of the container, and then through subsequent image processing, determine whether the door at the rear of the container is opened.

[0068] Preferably, the rear image of the container is a partial image of the rear of the container, because the partial image of the rear of the container is easier to obtain and can obtain a clearer image of the container door, thereby improving recognition accuracy.

[0069] It is understandable that in step S2, the tail image is grayed to obtain a grayscale image. Among them, each pixel of the grayscale image only needs one byte to store the grayscale value (also known as intensity value, brightness value), and the grayscale range is 0-255. The grayscale image is usually obtained by measuring the brightness of each pixel in a single electromagnetic wave spectrum (such as visible light). The grayscale image used for display is usually saved with a nonlinear scale of 8 bits per sampled pixel, so that there can be 256 levels of grayscale. This accuracy is just enough to avoid visible banding distortion and is very easy to program.

[0070] Therefore, in step S3, after the tail image is grayed, CANNY edge detection is performed on the gray image, which can avoid stripe distortion and improve the quality of the first edge image.

[0071] It can be understood that in steps S4 to S5, the RGB space of the tail image is first converted to the HSV space, and then the H channel in the HSV space image is extracted for CANNY edge detection, which can avoid the interference of saturation (S) and brightness (V), while reducing the amount of calculation during CANNY edge detection, improving the calculation speed, and improving the quality of the second edge image.

[0072] It can be understood that in step S6, performing a logical "AND" operation on the image pixels of the first edge image and the second edge image can fit the pixel points in the first edge image and the second edge image, accurately find all the edges in the image, and reduce missed detections and false detections.

[0073] It can be understood that in step S7, after performing the image pixel logic “AND” operation, there are many impurities in the third edge image. By filtering the small contours in the third edge image, the impurity components can be removed to avoid interference.

[0074] In addition, if the image of the container's tail is an image of the entire surface of the container's tail, the outer contour is the edge contour of the container's tail. If the image of the container's tail is a partial image of the container's tail, the outer contour is the edge contour in the partial image.

[0075] It can be understood that in steps S8 to S9, if the number of circumscribed rectangles of the large outline is 1, it means that the container has not been opened, the door is tightly closed, and there is no door gap in the middle. At this time, the container is safe; if the number of circumscribed rectangles of the large outline is 2, it means that the container has been opened, and a door gap has been generated in the middle of the door. Because of the existence of the door gap, there is a blank area in the fourth edge image, and the blank area will be located between the two large outlines. At this time, the container is dangerous and an alarm is triggered.

[0076] Compared with the prior art, the container detection method provided by the present application performs a logical "AND" operation on the image pixels of the first edge image and the second edge image, which can fit the pixel points in the first edge image and the second edge image, accurately find all the edges in the image, and reduce missed detection and false detection; by judging the number of circumscribed rectangles of the large outline in the fourth edge image, the door status of the container can be judged, which not only improves the detection efficiency and accuracy, but also is applicable to containers of any size and model, effectively improving the safety during container transportation.

[0077] In another embodiment of the present application, please refer to Figure 2 In step S6, after synthesizing the third edge image, the method further comprises the following steps:

[0078] S6.1, performing morphological image processing on the third edge image, wherein the morphological image processing method includes at least one of dilation and erosion processing.

[0079] For example, in morphological image processing, dilation of the highlight part in the third edge image is an operation to find the local maximum value, which can eliminate some small dark spots and dark lines. Erosion of the highlight part in the third edge image is an operation to find the local minimum value, which can eliminate some small bright spots and bright lines. Erosion followed by dilation can eliminate some small bright spots and bright lines and smooth the boundaries of larger objects without significantly changing their areas. Dilation followed by erosion can eliminate some small dark spots and dark lines without significantly changing their areas.

[0080] In another embodiment of the present application, please refer to Figure 3 In steps S7 to S8, the small contour is a contour whose circumscribed rectangle in the third edge image has an area less than or equal to 100 pixels, and the large contour is a contour whose circumscribed rectangle in the fourth edge image has an area greater than 100 pixels.

[0081] It can be understood that by setting a critical value and dividing the small contour and the large contour by the area of ​​the circumscribed rectangular area, all impurities can be filtered out at one time, the large contour can be extracted, unnecessary contour points can be deleted, and the large contour can be retained, thereby avoiding the situation in step S9 where the number of circumscribed rectangles is greater than 2.

[0082] If the pixels in the tail image are high, the critical value can be changed according to the actual situation. Under normal circumstances, after experimental testing, 100 pixels can be used as the critical value, which can meet the requirements of conventional image processing algorithms.

[0083] See also Figures 5 to 7 The present application also provides a container detection device 100, which is installed on a container and includes a microprocessor 10, a lock control switch 20, a mechanical lock 30, an image acquisition camera 40, a gyroscope 50, a solar power supply component 60, a wireless communication module 70 and an alarm device 80.

[0084] Specifically, the lock control switch 20 , the image acquisition camera 40 , the gyroscope 50 , the solar power supply component 60 , the wireless communication module 70 and the alarm device 80 are respectively connected to the microprocessor 10 , and the lock control switch 20 can control the state of the mechanical lock 30 .

[0085] Wherein, the image acquisition camera 40 is used to obtain the rear image of the container;

[0086] The microprocessor 10 is used to grayscale the tail image to obtain a grayscale image;

[0087] The microprocessor 10 is used to perform CANNY edge detection on the grayscale image to obtain a first edge image;

[0088] The microprocessor 10 is used to convert the RGB space of the tail image into the HSV space to obtain an HSV space image;

[0089] The microprocessor 10 is used to extract the H channel in the HSV spatial image to perform CANNY edge detection to obtain a second edge image;

[0090] The microprocessor 10 is used to perform an image pixel logical “AND” operation on the first edge image and the second edge image to synthesize a third edge image;

[0091] The microprocessor 10 is used to obtain the outer contour of the third edge image and filter the small contours in the third edge image to obtain a fourth edge image;

[0092] The microprocessor 10 is used to obtain the number of circumscribed rectangles of the large outline in the fourth edge image. If the number of circumscribed rectangles of the large outline is 1, it is determined that the container is in a closed state. If the number of circumscribed rectangles of the large outline is 2, it is determined that the container is in an open state, so that the alarm device 80 sounds.

[0093] It can be understood that the solar power supply assembly 60 is used to convert solar energy into electrical energy to power the container detection device 100, which is energy-saving and environmentally friendly and improves endurance.

[0094] The gyroscope 50 is used to sense vibration. If the amplitude is greater than a set threshold, the system is awakened. The image of the rear of the container can be obtained through the image acquisition camera 40. The microprocessor 10 processes the image of the rear of the container to determine the door gap at the rear of the container, and then determines the state of the container door. If the container is found to be closed, the alarm device 80 sounds to prevent theft. When the gyroscope 50 does not sense vibration, the system is in a dormant state and works intermittently, saving energy and power.

[0095] In addition, the microprocessor 10 can also control the lock control switch 20 to open the mechanical lock 30 so that the staff can open the container. The wireless communication module 70 is convenient for transmitting data to the background server in real time to achieve remote monitoring.

[0096] It is worth mentioning that the wireless communication module 70 is preferably a 5G network communication module, which has a fast transmission speed and can improve the speed of information transmission.

[0097] Compared with the prior art, the container detection device 100 provided in the present application adopts the solar power supply component 60 for power supply, which is energy-saving and environmentally friendly, and improves the endurance; the gyroscope 50 is used to sense the vibration of the container, which can work intermittently and save energy and electricity; the image of the tail of the container can be obtained through the image acquisition camera 40, and the microprocessor 10 determines the state of the container door through image processing, realizes the anti-theft alarm function, can be remotely monitored, and improves the safety of the container.

[0098] In another embodiment of the present application, please refer to Figure 8 The solar power supply component 60 includes a solar panel 61, a rechargeable battery 62 and a power management module 63. The solar panel 61 and the rechargeable battery 62 are respectively connected to the power management module 63, and the power management module 63 is connected to the microprocessor 10.

[0099] It can be understood that the solar panel 61 is used to convert solar energy into electrical energy, the power management module 63 is used to adjust the voltage and charge the rechargeable battery 62, and when the rechargeable battery 62 is used as a power output, the power management module 63 can play a voltage stabilizing role.

[0100] In another embodiment of the present application, please refer to Figure 7 The mechanical lock 30 is provided with a magnet 31, and the magnet 31 is used to be adsorbed on the container.

[0101] It is understandable that when the magnet 31 is adsorbed on the container, the entire container detection device 100 can remain stationary relative to the container, ensuring that the image quality of the image of the rear of the container taken by the image acquisition camera 40 is clear.

[0102] In another embodiment of the present application, please refer to Figures 7 and 8 The container detection device 100 includes a keyboard 90 , and the keyboard 90 is connected to the microprocessor 10 .

[0103] It is understandable that a password can be input through the keyboard 90 , and the lock control switch 20 can be controlled by the password to open the mechanical lock 30 .

[0104] In another embodiment of the present application, please refer to Figures 7 and 8 The container detection device 100 includes a display screen 91 , and the display screen 91 is connected to the microprocessor 10 .

[0105] It is understandable that the display screen 91 can display human-computer interaction interface information, making it convenient for staff to input instructions and display status.

[0106] In another embodiment of the present application, please refer to Figures 7 and 8 The container detection device 100 includes an indicator light 92 , and the indicator light 92 is connected to the microprocessor 10 .

[0107] It is understandable that the indicator light 92 can provide an indication function, such as when the door is open, the indicator light 92 is red; when the door is closed, the indicator light 92 is green.

[0108] In another embodiment of the present application, please refer to Figure 8 The container detection device 100 includes a GPS module 94 , and the GPS module 94 is connected to the microprocessor 10 .

[0109] It is understandable that the position of the container can be located in real time through the GPS module 94, and the positioning information can be sent to the back-end server through the wireless communication module 70, so as to facilitate real-time remote monitoring and remote tracking by back-end personnel.

[0110] In another embodiment of the present application, please refer to Figures 7 and 8 The container detection device 100 includes an infrared camera 93 , and the infrared camera 93 is connected to the microprocessor 10 .

[0111] It can be understood that the infrared camera 93 senses people approaching the container, and if it senses that someone is approaching, the system is quickly activated to ensure the safety of the container.

[0112] See also Fig. 9 The present application also provides a security vehicle-mounted system 200 , which includes a vehicle-mounted central control system and the container detection device 100 as described above, and the vehicle-mounted central control system is connected to the container detection device 100 via a wireless communication module 70 .

[0113] Compared with the prior art, the security vehicle-mounted system 200 provided in the present application connects the vehicle-mounted central control system with the container detection device 100 via a wireless communication module 70, and the container status can be monitored by the vehicle-mounted central control system, thereby improving the safety of the vehicle.

[0114] See also Fig.10 The present application also provides a security monitoring system 300, which includes a background client 301, a smart phone 302 and the container detection device 100 as described above, and the background client 301, the smart phone 302 and the container detection device 100 are connected via a wireless communication module 70.

[0115] Compared with the prior art, the security monitoring system 300 provided in the present application is connected to the container detection device 100 through the background client 301 and the smart phone 302 via the wireless communication module 70. The user can remotely monitor the container status through the background client 301 and the smart phone 302, thereby improving the safety, reliability, convenience and flexibility of logistics transportation.

[0116] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A container detection method, characterized in that: The following steps are involved: Get the rear image of the container; Gray-scale the tail image to obtain a gray-scale image; Performing CANNY edge detection on the grayscale image to obtain a first edge image; Convert the RGB space of the tail image to the HSV space to obtain an HSV space image; Extracting the H channel in the HSV spatial image to perform CANNY edge detection to obtain a second edge image; Performing a pixel logical AND operation on the first edge image and the second edge image to synthesize a third edge image; Obtaining the outer contour of the third edge image and filtering the small contours in the third edge image to obtain a fourth edge image; Calculating the number of circumscribed rectangles of the large contour in the fourth edge image; If the number of circumscribed rectangles of the large outline is 1, it is determined that the container is in a closed state; if the number of circumscribed rectangles of the large outline is 2, it is determined that the container is in an open state.

2. The container detection method according to claim 1, characterized in that: After synthesizing the third edge image, the method further comprises the following steps: Morphological image processing is performed on the third edge image, and the morphological image processing method includes at least one of dilation and erosion processing.

3. The container detection method according to claim 1, characterized in that: The small contour is a contour whose circumscribed rectangle in the third edge image has an area less than or equal to 100 pixels, and the large contour is a contour whose circumscribed rectangle in the fourth edge image has an area greater than 100 pixels.

4. A container detection device, installed on a container, characterized in that: It includes a microprocessor, a lock control switch, a mechanical lock, an image acquisition camera, a gyroscope, a solar power supply component, a wireless communication module and an alarm device; The lock control switch, image acquisition camera, gyroscope, solar power supply component, wireless communication module and alarm device are respectively connected to the microprocessor, and the lock control switch can control the state of the mechanical lock; Wherein, the image acquisition camera is used to obtain the rear image of the container; The microprocessor is used to grayscale the tail image to obtain a grayscale image; The microprocessor is used for performing CANNY edge detection on the grayscale image to obtain a first edge image; The microprocessor is used for converting the RGB space of the tail image into the HSV space to obtain an HSV space image; The microprocessor is used to extract the H channel in the HSV spatial image to perform CANNY edge detection to obtain a second edge image; The microprocessor is used to perform an image pixel logical “AND” operation on the first edge image and the second edge image to synthesize a third edge image; The microprocessor is used to obtain the outer contour of the third edge image and filter the small contours in the third edge image to obtain a fourth edge image; The microprocessor is used to obtain the number of circumscribed rectangles of the large outline in the fourth edge image. If the number of circumscribed rectangles of the large outline is 1, it is determined that the container is in a closed state. If the number of circumscribed rectangles of the large outline is 2, it is determined that the container is in an open state, so that the alarm device sounds.

5. The container detection device according to claim 4, characterized in that: The solar power supply component includes a solar panel, a rechargeable battery and a power management module. The solar panel and the rechargeable battery are respectively connected to the power management module, and the power management module is connected to the microprocessor.

6. The container detection device according to claim 4, characterized in that: The mechanical lock is provided with a magnet, and the magnet is used to be adsorbed on the container.

7. The container detection device according to claim 4, characterized in that: The container detection device comprises a GPS module, and the GPS module is connected to the microprocessor.

8. The container detection device according to claim 4, characterized in that: The container detection device comprises an infrared camera, and the infrared camera is connected to the microprocessor.

9. A security vehicle system, characterized in that: It comprises a vehicle-mounted central control system and a container detection device according to any one of claims 4 to 8, wherein the vehicle-mounted central control system is connected to the container detection device via a wireless communication module.

10. A security monitoring system, characterized in that: It comprises a background client, a smart phone and a container detection device as described in any one of claims 4 to 8, wherein the background client, the smart phone and the container detection device are connected via a wireless communication module.

Images