WO2023078254A1 - Method and apparatus for determining open/closed state of knife switch, and device, medium and product - Google Patents

Method and apparatus for determining open/closed state of knife switch, and device, medium and product Download PDF

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Publication number
WO2023078254A1
WO2023078254A1 PCT/CN2022/129042 CN2022129042W WO2023078254A1 WO 2023078254 A1 WO2023078254 A1 WO 2023078254A1 CN 2022129042 W CN2022129042 W CN 2022129042W WO 2023078254 A1 WO2023078254 A1 WO 2023078254A1
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WIPO (PCT)
Prior art keywords
knife
image
closing
position area
preset
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PCT/CN2022/129042
Other languages
French (fr)
Chinese (zh)
Inventor
方嘉聪
肖少剑
龚浩
Original Assignee
珠海优特电力科技股份有限公司
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Application filed by 珠海优特电力科技股份有限公司 filed Critical 珠海优特电力科技股份有限公司
Priority to GB2308674.7A priority Critical patent/GB2616993A/en
Priority to AU2022381656A priority patent/AU2022381656A1/en
Publication of WO2023078254A1 publication Critical patent/WO2023078254A1/en

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/22Matching criteria, e.g. proximity measures
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/50Context or environment of the image
    • G06V20/52Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/40Extraction of image or video features
    • G06V10/46Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/74Image or video pattern matching; Proximity measures in feature spaces
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/60Type of objects

Definitions

  • the present disclosure relates to the technical field of rail transit, and in particular to a method, device, equipment, medium and product for determining the opening and closing state of a knife switch.
  • the traditional monitoring and management method of switch equipment is to judge the opening and closing status of the switch through whether the electricity is connected or physical and mechanical sensors.
  • This kind of knife switch confirmation method needs to add a sensor to the equipment body. Once the sensor fails, the opening and closing status of the knife switch cannot be determined, and the operating equipment needs to be shut down during maintenance or renovation.
  • the disclosure provides a method, device, equipment, medium and product for determining the opening and closing state of a knife switch, which are used to provide a method for confirming the opening and closing state of a knife switch to solve the problem that the opening and closing state of a knife switch cannot be determined when a sensor fails.
  • the first aspect of the present disclosure provides a method for determining the opening and closing state of a knife gate, including: acquiring a knife gate monitoring image; the knife gate monitoring image is that the camera device shoots the knife gate monitoring area according to the image sending instruction sent by the knife gate control device Generated and sent; the image sending instruction is generated by the knife gate control device within a preset time period for controlling the closing or opening of the knife gate; image features of multiple preset areas in the knife gate monitoring image are extracted
  • the plurality of preset areas at least include the closed position area where the knife switch is in the closed position state and the divided position area where the knife switch is located when the knife switch is in the divided state; monitor the knife switch
  • the image features of each preset area in the image are compared with the image features of the corresponding preset area of the preset knife gate template image for structural similarity; according to the result of the structural similarity comparison, the opening and closing status of the knife gate is determined.
  • the second aspect of the present disclosure provides a device for determining the opening and closing state of a knife gate, including: an acquisition module configured to acquire a knife gate monitoring image; the knife gate monitoring image is an image sending instruction sent by the camera device according to the knife gate control device It is generated and sent by photographing the knife gate monitoring area; the image sending instruction is generated by the knife gate control device within a preset time period for controlling the knife gate to close or disconnect; the extraction module is configured to extract the knife gate monitoring The image features of multiple preset areas in the image; the multiple preset areas at least include the closed position area where the knife switch is in the closed state and the branch position where the knife switch is in the divided state.
  • comparison module configured to carry out structural similarity comparison between the image features of each of the preset areas in the knife gate monitoring image and the image features of the preset knife gate template image corresponding to the preset area; determine the module, set In order to determine the opening and closing state of the knife switch according to the result of the structural similarity comparison.
  • the third aspect of the embodiments of the present disclosure provides an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory , so as to realize the method for determining the opening and closing state of the knife switch according to any one of the first aspect.
  • the fourth aspect of the embodiments of the present disclosure provides a computer-readable storage medium, the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to implement any one of the first aspect when executed by a processor.
  • the fifth aspect of the embodiments of the present disclosure provides a computer program product, including a computer program, and when the computer program is executed by a processor, the method for determining the opening and closing state of the knife switch described in any one of the first aspect is implemented.
  • the present disclosure provides a method, device, equipment, medium and product for determining the opening and closing state of a knife gate, the method comprising: acquiring a knife gate monitoring image; the knife gate monitoring image is an image sent by a camera device according to a knife gate control device The instruction is generated and sent by taking pictures of the knife gate monitoring area; the image sending instruction is generated by the knife gate control device within the preset time period for controlling the knife gate to close or disconnect; extracting multiple images from the knife gate monitoring image
  • the image characteristics of the preset area; the plurality of preset areas at least include the closing position area where the knife switch is in the closing state and the dividing position area where the knife switch is in the dividing state; Carry out structural similarity comparison between the image features of each of the preset areas in the knife gate monitoring image and the image features of the preset knife gate template image corresponding to the preset area; determine the opening and closing state of the knife gate according to the result of the structural similarity comparison .
  • the method for determining the opening and closing state of the knife switch of the present disclosure compares the structural similarity between the preset area of the knife switch monitoring image and the preset area of the preset knife switch template image, because the preset area at least includes when the knife switch is in the closing state.
  • FIG. 1 is a scene diagram that can realize the method for determining the opening and closing state of the knife switch of the present disclosure
  • FIG. 2 is a schematic flowchart of a method for determining the opening and closing state of a knife switch provided by the first embodiment of the present disclosure
  • FIG. 3 is a schematic flowchart of a method for determining the opening and closing state of a knife switch provided by the second embodiment of the present disclosure
  • FIG. 4 is a schematic diagram of a preset area of a method for determining the opening and closing state of a knife switch provided by the second embodiment of the present disclosure
  • FIG. 5 is a schematic diagram of the image alignment process of the method for determining the opening and closing state of the knife switch provided by the third embodiment of the present disclosure
  • Fig. 6 is a schematic diagram of the interaction process of the method for determining the opening and closing state of the knife switch provided by the fourth embodiment of the present disclosure
  • FIG. 7 is a schematic diagram of the image alignment process of the method for determining the opening and closing state of the knife switch provided by the fourth embodiment of the present disclosure.
  • Fig. 8 is a schematic structural diagram of a device for determining the opening and closing state of a knife switch provided by the fifth embodiment of the present disclosure
  • FIG. 9 is a schematic structural diagram of an electronic device provided by a sixth embodiment of the present disclosure.
  • Computer vision technology is a computer simulation of human visual process, which is a synthesis of image processing, artificial intelligence and pattern recognition technologies.
  • the monitoring and management of traditional knife switch equipment in the track needs to add sensors to the equipment body. Once the sensor fails, the opening and closing status of the knife switch cannot be determined, and the operating equipment needs to be shut down during maintenance or renovation. Therefore, the rail transit field needs A new method for confirming the opening and closing state of the knife switch, combined with computer vision technology to solve the problem that the opening and closing state of the knife switch cannot be determined when the sensor fails.
  • a new method for confirming the opening and closing state of the knife gate is needed to solve the problem that the opening and closing state of the knife gate cannot be determined when the sensor fails.
  • the knife gate monitoring image generated by the camera device shooting the knife gate monitoring area is obtained, and the image features of multiple preset areas in the knife gate monitoring image are extracted.
  • the plurality of preset areas at least include the closed position area where the knife switch is in the closed position and the divided position area where the knife switch is in the divided state when the knife switch is in the divided state.
  • the structural similarity comparison is performed between the image features of each preset area in the knife gate monitoring image and the image features of the preset knife gate template image corresponding to the preset area. According to the result of structural similarity comparison, the opening and closing state of the knife switch is determined. Therefore, no matter whether the sensor is faulty or not, the opening and closing state of the knife switch can be determined according to the comparison result.
  • the inventor proposes the technical solution of the present disclosure based on the above-mentioned inventive discoveries.
  • the following introduces the application scenarios of the method for determining the opening and closing state of the knife switch provided by the present disclosure.
  • 1 is an electronic device
  • 2 is a knife switch control device
  • 3 is a knife switch device
  • 4 is a camera device.
  • the network architecture of the application scenario corresponding to the method for determining the opening and closing state of the knife switch provided in the present disclosure includes: an electronic device 1 , a knife switch control device 2 , a knife switch device 3 and a camera device 4 .
  • the knife switch control device 2 can control the closing or opening of the knife switch device 3
  • the camera device 4 can photograph the knife switch monitoring area including the knife switch device 3 .
  • the knife switch control device 2 controls the knife switch of the knife switch device 3 to close or open, the knife switch device 3 will feed back the operation information of the knife switch through the sensor set in the period.
  • the knife gate control device 2 will send an image sending instruction to the camera device 4 within a preset time period, such as 5 seconds, so that the camera device 4 will send the knife gate monitoring image generated by shooting the knife gate monitoring area to the electronic equipment 1.
  • the electronic device 1 extracts image features of multiple preset regions in the knife gate monitoring image after acquiring the knife gate monitoring image.
  • the multiple preset areas at least include the closed position area where the knife switch is in the closed position and the divided position area where the knife switch is in the divided state when the knife switch is in the divided state.
  • the electronic device 1 compares the image features of each preset area in the knife gate monitoring image with the image features of the preset knife gate template image corresponding to the preset area for structural similarity, and determines the knife gate classification according to the result of the structural similarity comparison. combined state. After the electronic device 1 determines the opening and closing state of the knife switch, it can send the opening and closing state of the knife switch to the knife control device 2 so that the knife control device 2 can further determine the opening and closing state of the knife switch according to the opening and closing state of the knife switch and the operation information of the knife switch. The gate opening and closing state.
  • Fig. 2 is a schematic flowchart of the method for determining the opening and closing state of the knife switch provided by the first embodiment of the present disclosure. As shown in Fig. The opening and closing state determination device can be integrated in the electronic device. Then the method for determining the opening and closing state of the knife switch provided in this embodiment includes the following steps:
  • Step S101 acquiring a monitoring image of a knife switch.
  • the knife gate monitoring image is generated and sent by the camera device to photograph the knife gate monitoring area according to the image sending instruction sent by the knife gate control device.
  • the image sending instruction is generated by the knife switch control device within a preset time period for controlling the closing or opening of the knife switch.
  • the photographing device may photograph the knife gate monitoring area including the knife gate in real time, or may photograph the knife gate monitoring area after receiving an image sending instruction, which is not limited in this embodiment.
  • the knife gate control device will send an image sending instruction to the shooting device, so that the shooting device will send the knife gate monitoring image generated by shooting the knife gate monitoring area to The device for determining the opening and closing state of the knife switch.
  • the preset time period can be set according to actual needs. For example, it takes 4 seconds for the knife gate to be fully closed to completely separated, then the preset time period can be set to 4 seconds or 5 seconds, etc., thereby reducing the image taken by the shooting device. is the probability that the switch is in a state between fully closed and fully open.
  • Step S102 extracting image features of a plurality of preset areas in the knife gate monitoring image.
  • the plurality of preset areas at least include the closed position area where the knife switch is in the closed position and the divided position area where the knife switch is in the divided state when the knife switch is in the divided state.
  • the extracted image feature can be extracted scale-invariant feature transform (English full name: Scale-invariant feature transform, English abbreviation: SIFT) feature, so that the extracted feature is more stable, and it can also make the follow-up and The structural similarity comparison between preset knife gate template images is more stable.
  • scale-invariant feature transform English full name: Scale-invariant feature transform, English abbreviation: SIFT
  • the closed position area where the knife switch is located when the knife switch is in the closed position refers to the position area where the knife switch is located when it is fully closed.
  • the division position area where the knife switch is located when the knife switch is in the divided state refers to the position area where the knife switch is located when the knife switch is in the complete division state.
  • the preset area is shown in dotted line boxes a and b in Fig. 4, wherein, the dotted line box a can refer to the area where the knife switch is located when the knife switch is in the divided state, and the dotted line box b can refer to the area where the knife switch is in the closed state.
  • the preset area needs to include at least the closed position area where the knife switch is in the closed state and the divided position area where the knife switch is in the divided state, so that in the subsequent and preset knife gate template When the images are compared, it is judged whether the opening and closing state of the knife switch is the closing state, the dividing state, or whether it is neither in the closing state nor in the dividing state.
  • Step S103 comparing the image features of each preset area in the knife gate monitoring image with the image features of the corresponding preset area of the preset knife gate template image for structural similarity.
  • the preset knife gate template image refers to pre-captured images of the knife gate in various states, such as the template image taken when the knife gate is in the closing state and the template image taken when the knife gate is in the dividing state. After a single configuration of the preset knife gate template image, the original configuration can be reused without model training, which improves configuration efficiency.
  • Structural similarity is used to compare the similarity between two images.
  • the English abbreviation of structural similarity is: SSIM, and the full English name is: structural similarity index, which is an index to measure the similarity of two images.
  • Step S104 determining the opening and closing state of the knife switch according to the result of the structural similarity comparison.
  • the structural similarity can determine the similarity between the knife gate monitoring image and the preset knife gate template image, and can determine whether the knife gate in the knife gate monitoring image is in the preset knife gate template image according to the similarity The status of the knife switch, so as to determine the opening and closing status of the knife switch in the monitoring image of the knife switch.
  • An embodiment of the present disclosure provides a method for determining an opening and closing state of a knife switch, the method comprising: acquiring a monitoring image of a knife switch.
  • the knife gate monitoring image is generated and sent by the camera device to photograph the knife gate monitoring area according to the image sending instruction sent by the knife gate control device.
  • the image sending instruction is generated by the knife switch control device within a preset time period for controlling the closing or opening of the knife switch.
  • the image features of multiple preset areas in the knife gate monitoring image are extracted.
  • the plurality of preset areas at least include the closed position area where the knife switch is in the closed position and the divided position area where the knife switch is in the divided state when the knife switch is in the divided state.
  • Structural similarity comparisons are made between the image features of each preset area in the knife gate monitoring image and the image features of the preset knife gate template image corresponding to the preset area. According to the result of structural similarity comparison, the opening and closing state of the knife switch is determined.
  • the method for determining the opening and closing state of the knife gate in the embodiment of the present disclosure compares the structural similarity between the preset area of the knife gate monitoring image and the preset area of the preset knife gate template image, because the preset area at least includes The close position area where the knife switch is in the state and the minute position area where the knife switch is in the split state. Therefore, no matter whether the sensor is faulty or not, the knife switch where the knife switch is located can be determined according to the comparison result. Split state.
  • Figure 3 is a schematic flow chart of the method for determining the opening and closing state of the knife switch provided by the second embodiment of the present disclosure. As shown in Figure 3, the method for determining the opening and closing state of the knife switch provided by this embodiment is provided in the previous embodiment of the present disclosure. On the basis of the determination method of the opening and closing state of the knife switch, each step is further refined. Then, the method for determining the opening and closing state of the knife switch provided in this embodiment includes the following steps.
  • Step S201 acquiring a monitoring image of a knife switch.
  • the knife gate monitoring image is generated and sent by the camera device to photograph the knife gate monitoring area according to the image sending instruction sent by the knife gate control device.
  • the image sending instruction is generated by the knife switch control device within a preset time period for controlling the closing or opening of the knife switch.
  • step 201 is similar to the implementation manner of step 101 in the previous embodiment of the present disclosure, and will not be repeated here.
  • Step S202 obtaining the coordinate range of each preset area in the preset knife gate template image in the preset knife gate template image.
  • the preset knife switch template image is a pre-shot closing template image when the knife switch is in a closing state and a dividing template image when the knife switch is in a separating state.
  • the closing template image includes the closing position area when the knife switch is in the closing state and the dividing position area when the knife switch is in the closing state.
  • the divider template image includes the closing position area when the knife switch is in the divider state and the divider position area when the knife switch is in the divider state.
  • each preset area when configuring the preset knife gate template image, each preset area will be represented in the form of a coordinate range.
  • the preset area can be in the form of a square area, as shown by dashed boxes a and b in FIG. 4 , or it can be set in a circle or other shapes.
  • the closing template image may further include: an image of the closing position area when the knife switch is in the closing position area, and an image of the dividing position area when the knife switch is in the closing position area.
  • the dividing template image may also include: an image of the closing position area when the knife switch is in the dividing position area, and an image of the dividing position area when the knife switch is in the dividing position area.
  • Step S203 extracting image features corresponding to preset areas in the knife gate monitoring image according to each coordinate range.
  • the corresponding preset area in the knife gate monitoring image can be extracted according to each coordinate range of the preset knife gate template image. Image features of the set area.
  • the image feature corresponding to the preset area in the knife gate monitoring image may also be extracted in other ways, which is not limited in this embodiment.
  • the preset area is the closed position area where the knife switch is in the closed state and the divided position area where the knife switch is in the divided state when the knife switch is in the closed state.
  • Step S204 comparing the closing position area in the knife gate monitoring image with the closing position area in the closing template image and the closing position area in the quantization template image respectively, so as to determine the closing position area comparison result.
  • the purpose of comparing the structural similarity of the closing position area in the knife gate monitoring image with the closing position area in the closing template image and the closing position area in the sub-position template image is to determine the Whether there is a knife switch in the closed position area in the image.
  • the dotted line box b area is the close position area in the preset area. When the knife switch is in the close position state, there is a knife switch in the dotted line box b area, and when the knife switch is in the split state, the dotted line There is no knife switch in the box b area.
  • Structural similarity is expressed in numerical form, generally the value is between 0 and 1, and the larger the value, the higher the degree of similarity.
  • structural similarity between the closing position area in the knife gate monitoring image and the closing position area in the closing template image is greater, it means that there is a knife gate in the closing position area.
  • Step S205 performing structural similarity comparison between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image and the quantile position area in the quantile template image, so as to determine the quantile position area comparison result.
  • the structural similarity comparison between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image and the quantile position area in the quantizing template image is to determine the Whether there is a knife gate in the quantile position area in the image.
  • the dotted line box a area is the division position area in the preset area. When the knife switch is in the division state, there is a knife switch in the dotted line box a area, and when the knife switch is in the close position, the dotted line There is no knife gate in the box a area.
  • the quantile position area is determined in a similar way to the close position area.
  • the structural similarity between the quantile position area in the knife gate monitoring image and the quantile position area in the quantile template image is greater, it represents the quantile position.
  • Step S206 determining the opening and closing state of the knife switch according to the comparison result of the closed position area and the comparison result of the divided position area.
  • the determination of the opening and closing state of the knife switch according to the comparison result of the closing position area and the comparison result of the dividing position area can be specifically as follows:
  • the comparison result of the closing position area is that there is a knife switch in the closing position area, and the comparison result of the closing position area is that there is no knife switch in the closing position area, then it is determined that the knife switch is in the closing state.
  • the comparison result of the close position area is that there is no knife switch in the close position area
  • the comparison result of the split position area is that there is a knife switch in the split position area
  • the comparison result of the closing position area is that there is no knife switch in the closing position area, and the comparison result of the closing position area is that there is no knife switch in the closing position area, then it is determined that the knife switch state is in a non-separating and non-closing state.
  • Step S207 sending the opening and closing state of the knife switch to the knife switch control device, so that the knife switch control device determines the opening and closing state of the knife switch for a second time according to the opening and closing state of the knife switch and the operation information of the knife switch fed back by the sensor.
  • the opening and closing state of the knife switch can be sent to the knife switch control device, so that the knife switch control device can determine the opening and closing state of the knife switch according to the opening and closing state of the knife switch and the knife switch operation information fed back by the sensor, so as to improve the certainty.
  • the accuracy and stability of the opening and closing state of the knife switch can be sent to the knife switch control device, so that the knife switch control device can determine the opening and closing state of the knife switch according to the opening and closing state of the knife switch and the knife switch operation information fed back by the sensor, so as to improve the certainty.
  • FIG. 5 is a schematic diagram of the image alignment process of the method for determining the opening and closing state of the knife switch provided by the third embodiment of the present disclosure. As shown in FIG. Based on the method for determining the opening and closing state of the knife gate provided in the example, an image alignment process is added, and the image alignment process includes the following steps.
  • Step S301 extracting the image features of the monitor image of the knife gate and the image features of the preset knife gate template image.
  • the SIFT feature is preferable for extracting the image feature of the knife gate monitoring image, which can better improve the matching degree of the image feature pair and the stability of the transformation matrix.
  • Step S302 matching the image features of the monitor image of the knife gate with the image features of the preset knife gate template image to generate a plurality of image feature pairs.
  • An image feature pair is a feature pair consisting of two image features that match.
  • the matching method can use FLANN (Chinese: fast nearest neighbor search package, English full name: Fast Library for Approximate Nearest Neighbors) or BF (Chinese is violence, English full name: Brute Force) algorithm to further improve the accuracy of matching image feature pairs sex and stability.
  • FLANN Fast nearest neighbor search package, English full name: Fast Library for Approximate Nearest Neighbors
  • BF Chiinese is violence, English full name: Brute Force
  • step S303 a transformation matrix between the knife gate monitoring image and the preset knife gate template image is determined according to a plurality of image feature pairs and a preset projection transformation algorithm.
  • the preset projection transformation algorithm can use the RANSAC robust solution algorithm, which is called Random Sample Consensus in English, so as to determine a more stable and accurate transformation matrix.
  • the transformation matrix between the knife gate monitoring image and the preset knife gate template image is determined according to the multiple image feature pairs and a preset projection transformation algorithm.
  • the matching degree between the knife gate monitoring image and the preset knife gate template image is too low, and the next knife gate monitoring image can be used for image alignment.
  • Step S304 correcting the monitoring image of the knife gate according to the transformation matrix, so that the corrected monitoring image of the knife gate is aligned with the preset knife gate template image.
  • the correcting process is performed on the monitoring image of the knife gate because the rail vehicle is likely to generate relatively large vibrations during actual operation, thereby causing an angle deviation of the photographing device. If the shooting device produces an angular offset, the captured knife switch monitoring image will also have an angle offset problem, which will affect the subsequent determination of the opening and closing status of the knife switch. Therefore, the problem of angular deviation of the shooting device can be solved by correcting the monitoring image of the knife gate.
  • the second determination of the status of the knife switch by the knife switch control device is used as an example for illustration.
  • the knife switch control device adopts the control device in the commonly used one-key sequence control system, which is represented by one-key sequence control in the figure.
  • the photographing device adopted in this embodiment is a camera.
  • the one-button sequential control system sends a signal to control the closing or opening of the knife switch, and after waiting for a few seconds, the knife switch moves in place, and the sensor in the knife switch device will feedback the operation information of the knife switch, that is, whether it is closed or divided.
  • the one-button sequential control system will send an image sending command to the camera, so that the camera can transmit the captured knife switch monitoring image to the knife switch opening and closing state determination device to judge the knife switch opening and closing state, and return the result to the one-button sequence control system.
  • the one-button sequential control system integrates the status discrimination information of the sensor and the switch opening and closing status determination device, and obtains the opening and closing status of the switch comprehensively, and completes the double confirmation of the opening and closing of the switch.
  • the images of the knife switch in the opening and closing positions are intercepted for labeling configuration. After a single configuration is completed, the original configuration can be reused without model training.
  • the device for determining the opening and closing state of the knife gate obtains the knife gate monitoring image that needs to determine the knife gate state from the camera, extracts the SIFT feature of the image, and then uses the FLANN or BF algorithm to match the SIFT features of the knife gate monitoring image and the template image, Get pairs of feature points. At this time, judge whether the number of feature point pairs is greater than or equal to 10, if not, wait for the next image input by the camera, if so, use the RANSAC robust solution algorithm to find the knife gate monitoring
  • the transformation matrix M of the image to the template image Perform affine or projective transformation on the knife gate monitoring image according to M, align the two images, correct the angle offset of the camera, and complete the image alignment.
  • the structural similarity comparison is carried out between the knife gate monitoring image and the template image.
  • SSIM similarity comparison it is obtained whether there is a knife switch in the a and b areas, so as to judge the opening and closing status of the knife switch. Discrimination of the opening and closing state is shown in Table 1.
  • the device for determining the opening and closing state of the knife switch After reading the corresponding state from Table 1, the device for determining the opening and closing state of the knife switch sends the opening and closing state of the knife switch to the one-key sequence control system.
  • Fig. 8 is a schematic structural diagram of the device for determining the opening and closing state of the knife switch provided by the fifth embodiment of the present disclosure.
  • the device 400 for determining the opening and closing state of the knife switch includes:
  • the obtaining module 401 is configured to obtain the monitoring image of the knife gate.
  • the knife gate monitoring image is generated and sent by the camera device to photograph the knife gate monitoring area according to the image sending instruction sent by the knife gate control device.
  • the image sending instruction is generated by the knife switch control device within a preset time period for controlling the closing or opening of the knife switch.
  • the extraction module 402 is configured to extract image features of multiple preset areas in the knife gate monitoring image.
  • the plurality of preset areas at least include the closed position area where the knife switch is in the closed position and the divided position area where the knife switch is in the divided state when the knife switch is in the divided state.
  • the comparison module 403 is configured to perform structural similarity comparison between the image features of each preset area in the knife gate monitoring image and the image features of the preset knife gate template image corresponding to the preset area.
  • the determination module 404 is configured to determine the opening and closing state of the knife switch according to the result of the structural similarity comparison.
  • the device for determining the opening and closing state of the knife switch provided in this embodiment can implement the technical solution of the method embodiment shown in FIG. 2 , and its realization principle and technical effect are similar to those of the method embodiment shown in FIG. 2 , so details will not be repeated here.
  • the device for determining the opening and closing state of the knife switch provided in the present disclosure further refines the device for determining the opening and closing state of the knife switch 400 on the basis of the device for determining the opening and closing state of the knife switch provided in the previous embodiment.
  • the extraction module 402 is specifically set as:
  • the coordinate range of each preset area in the preset knife gate template image in the preset knife gate template image is acquired.
  • the image features corresponding to the preset area in the knife gate monitoring image are extracted according to each coordinate range.
  • the preset area includes the closed position area where the knife switch is in the closed state and the divided position area where the knife switch is in the divided state when the knife switch is in the divided state.
  • the preset knife gate template image is a pre-shot closing template image when the knife gate is in a closing state and a dividing template image when the knife gate is in a dividing state.
  • the closing template image includes the closing position area when the knife switch is in the closing state and the dividing position area when the knife switch is in the closing state.
  • the divider template image includes the closing position area when the knife switch is in the divider state and the divider position area when the knife switch is in the divider state.
  • the comparison module 403 is set to:
  • Structural similarity comparisons were carried out between the closing position area in the knife gate monitoring image and the closing position area in the closing template image and the closing position area in the quantized template image, so as to determine the comparison result of the closing position area.
  • Structural similarity comparisons are made between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image and the quantile position area in the quantile template image to determine the comparison result of the quantile position area.
  • the comparison module 403 compares the closing position area in the knife gate monitoring image with the closing position area in the closing template image and the closing position area in the sub-positioning template image respectively in a similar structure. Sex comparison to determine the zygomatic position area comparison result, set to:
  • the structural similarity between the closing position area in the knife gate monitoring image and the closing position area in the closing template image is greater than the closing position area in the knife gate monitoring image and the closing position area in the split template image If there is structural similarity between them, it is determined that there is a knife switch in the closing position area as a result of the comparison of the closing position area. If the structural similarity between the closing position area in the knife gate monitoring image and the closing position area in the closing template image is smaller than the closing position area in the knife gate monitoring image and the closing position area in the split template image If there is structural similarity between them, it is determined that there is no knife gate in the closing position area as a result of the comparison.
  • the comparison module 403 compares the quantile position area in the knife gate monitoring image with the quantile position area in the closing template image and the quantile position area in the quantizing template image.
  • the specific settings are:
  • the structural similarity between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image is greater than the quantile position area in the knife gate monitoring image and the quantile position area in the quantizing template image If there is structural similarity between them, it is determined that there is no knife gate in the quantile position area as a result of the comparison. If the structural similarity between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image is smaller than the quantile position area in the knife gate monitoring image and the quantile position area in the quantizing template image If there is structural similarity between them, it is determined that there is a knife gate in the quantile position area as a result of the comparison of the quantile position area.
  • the determining module 404 is set to:
  • the comparison result of the closing position area is that there is a knife switch in the closing position area, and the comparison result of the closing position area is that there is no knife switch in the closing position area, then it is determined that the knife switch is in the closing state. If the comparison result of the close position area is that there is no knife switch in the close position area, and the comparison result of the split position area is that there is a knife switch in the split position area, then it is determined that the knife switch state is in the split state. If the comparison result of the closing position area is that there is no knife switch in the closing position area, and the comparison result of the closing position area is that there is no knife switch in the closing position area, then it is determined that the knife switch state is in a non-separating and non-closing state.
  • the device 400 for determining the opening and closing state of the knife switch further includes:
  • the image alignment module is configured to extract the image features of the monitor image of the knife gate and the image features of the preset knife gate template image. Match the image features of the knife gate monitoring image with the image features of the preset knife gate template image to generate multiple image feature pairs.
  • a transformation matrix between the knife gate monitoring image and the preset knife gate template image is determined according to a plurality of image feature pairs and a preset projection transformation algorithm.
  • the knife gate monitoring image is corrected according to the transformation matrix, so that the corrected knife gate monitoring image is aligned with the preset knife gate template image.
  • the image alignment module determines the transformation matrix between the knife gate monitoring image and the preset knife gate template image according to a plurality of image feature pairs and a preset projection transformation algorithm, it is set as:
  • the transformation matrix between the knife gate monitoring image and the preset knife gate template image is determined according to the multiple image feature pairs and a preset projection transformation algorithm.
  • the device 400 for determining the opening and closing state of the knife switch further includes:
  • the secondary determination module is configured to send the opening and closing state of the knife switch to the knife switch control device, so that the knife switch control device can secondarily determine the opening and closing state of the knife switch according to the opening and closing state of the knife switch and the operation information of the knife switch fed back by the sensor.
  • the device for determining the opening and closing state of the knife switch provided in this embodiment can implement the technical solution of the method embodiment shown in Fig. 2-Fig. 7, and its realization principle and technical effect are similar to those of the method embodiment shown in Fig. 2-Fig. Let me repeat them one by one.
  • the present disclosure also provides an electronic device, a computer-readable storage medium, and a computer program product.
  • FIG. 9 is a schematic structural diagram of an electronic device provided by a sixth embodiment of the present disclosure.
  • the electronic device is intended to be in various forms of digital computers suitable for knife-opening state determination training, such as laptop computers, personal digital assistants, and other suitable computers.
  • digital computers suitable for knife-opening state determination training, such as laptop computers, personal digital assistants, and other suitable computers.
  • the components shown herein, their connections and relationships, and their functions, are by way of example only, and are not intended to limit implementations of the disclosure described and/or claimed herein.
  • the electronic device includes: a processor 501 and a memory 502 .
  • the various components are interconnected using different buses and can be mounted on a common motherboard or otherwise as desired.
  • a processor may process instructions for execution within an electronic device.
  • the memory 502 is a non-transitory computer-readable storage medium provided in the present disclosure.
  • the memory stores instructions executable by at least one processor, so that at least one processor executes the method for determining the opening and closing state of the knife switch provided in the present disclosure.
  • the non-transitory computer-readable storage medium of the present disclosure stores computer instructions, and the computer instructions are used to make the computer execute the method for determining the opening and closing state of the knife switch provided in the present disclosure.
  • the memory 502 as a non-transitory computer-readable storage medium, can be configured to store non-transitory software programs, non-transitory computer-executable programs and modules, such as program instructions/ modules (for example, the acquisition module 401, the extraction module 402, the comparison module 403 and the determination module 404 shown in FIG. 8).
  • the processor 501 executes various functional applications and data processing of the server by running non-transient software programs, instructions and modules stored in the memory 502, that is, implements the method for determining the opening and closing state of the switch in the above method embodiments.
  • this embodiment also provides a computer product.
  • the electronic device can execute the method for determining the opening and closing state of the knife switch in the above embodiment.

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Abstract

The present disclosure provides a method and apparatus for determining the open/closed state of a knife switch, and a device, a medium and a product. The method comprises: acquiring a knife switch monitoring image; extracting image features of a plurality of preset regions in the knife switch monitoring image, wherein the plurality of preset regions at least comprise a closing position region in which a knife switch is located when same is in a closing position state and an opening position region in which the knife switch is located when same is in an opening position state; performing structural similarity comparison on the image features of the preset regions in the knife switch monitoring image with an image feature of a preset region corresponding to a preset knife switch template image; and determining the open/closed state of the knife switch according to a structural similarity comparison result.

Description

刀闸分合状态确定方法、装置、设备、介质及产品Method, device, equipment, medium and product for determining opening and closing state of knife switch
本公开要求于2021年11月08日提交中国专利局、申请号为202111314122.4、发明名称“刀闸分合状态确定方法、装置、设备、介质及产品”的中国专利申请的优先权,其全部内容通过引用结合在本公开中。This disclosure claims the priority of the Chinese patent application with the application number 202111314122.4 and the title of the invention "method, device, equipment, medium and product for determining the opening and closing state of the knife gate" submitted to the China Patent Office on November 08, 2021, and its entire content Incorporated by reference in this disclosure.
技术领域technical field
本公开涉及轨道交通技术领域,尤其涉及一种刀闸分合状态确定方法、装置、设备、介质及产品。The present disclosure relates to the technical field of rail transit, and in particular to a method, device, equipment, medium and product for determining the opening and closing state of a knife switch.
背景技术Background technique
在轨道交通领域中,轨道内设备状态管理与轨道交通的安全息息相关。其中,轨道中刀闸设备的监控管理是其中较为重要的一环。In the field of rail transit, the status management of in-track equipment is closely related to the safety of rail transit. Among them, the monitoring and management of the knife switch equipment in the track is a more important part.
传统的刀闸设备的监控管理方式是通过电气是否连通,或物理力学传感器等判别刀闸分合状态。这种刀闸确认方式需要在设备本体中添加传感器,一旦传感器故障将无法确定刀闸分合状态,且在使用维修或改造时需要关停运作设备。The traditional monitoring and management method of switch equipment is to judge the opening and closing status of the switch through whether the electricity is connected or physical and mechanical sensors. This kind of knife switch confirmation method needs to add a sensor to the equipment body. Once the sensor fails, the opening and closing status of the knife switch cannot be determined, and the operating equipment needs to be shut down during maintenance or renovation.
因此,轨道交通领域需要一种新的刀闸分合状态确认方法,以解决传感器故障时无法确定刀闸分合状态的问题。Therefore, a new method for confirming the opening and closing state of the knife switch is needed in the field of rail transit to solve the problem that the opening and closing state of the knife switch cannot be determined when the sensor fails.
发明内容Contents of the invention
本公开提供一种刀闸分合状态确定方法、装置、设备、介质及产品,用以提供一种刀闸分合状态确认方法,以解决传感器故障时无法确定刀闸分合状态的问题。The disclosure provides a method, device, equipment, medium and product for determining the opening and closing state of a knife switch, which are used to provide a method for confirming the opening and closing state of a knife switch to solve the problem that the opening and closing state of a knife switch cannot be determined when a sensor fails.
本公开的第一方面提供了一种刀闸分合状态确定方法,包括:获取刀闸监控图像;所述刀闸监控图像为摄像装置根据刀闸控制装置发送的图像发送指令拍摄刀闸监控区域生成并发送的;所述图像发送指令为所述刀闸 控制装置在控制刀闸闭合或断开的预设时间段内生成的;提取所述刀闸监控图像中多个预设区域的图像特征;所述多个预设区域至少包括刀闸处于合位状态时刀闸所处的合位位置区域和刀闸处于分位状态时刀闸所处的分位位置区域;将所述刀闸监控图像中各所述预设区域的图像特征与预设刀闸模板图像对应预设区域的图像特征进行结构相似性比较;根据结构相似性比较的结果确定刀闸分合状态。The first aspect of the present disclosure provides a method for determining the opening and closing state of a knife gate, including: acquiring a knife gate monitoring image; the knife gate monitoring image is that the camera device shoots the knife gate monitoring area according to the image sending instruction sent by the knife gate control device Generated and sent; the image sending instruction is generated by the knife gate control device within a preset time period for controlling the closing or opening of the knife gate; image features of multiple preset areas in the knife gate monitoring image are extracted The plurality of preset areas at least include the closed position area where the knife switch is in the closed position state and the divided position area where the knife switch is located when the knife switch is in the divided state; monitor the knife switch The image features of each preset area in the image are compared with the image features of the corresponding preset area of the preset knife gate template image for structural similarity; according to the result of the structural similarity comparison, the opening and closing status of the knife gate is determined.
本公开的第二方面提供了一种刀闸分合状态确定装置,包括:获取模块,设置为获取刀闸监控图像;所述刀闸监控图像为摄像装置根据刀闸控制装置发送的图像发送指令拍摄刀闸监控区域生成并发送的;所述图像发送指令为所述刀闸控制装置在控制刀闸闭合或断开的预设时间段内生成的;提取模块,设置为提取所述刀闸监控图像中多个预设区域的图像特征;所述多个预设区域至少包括刀闸处于合位状态时刀闸所处的合位位置区域和刀闸处于分位状态时刀闸所处的分位位置区域;比较模块,设置为将所述刀闸监控图像中各所述预设区域的图像特征与预设刀闸模板图像对应预设区域的图像特征进行结构相似性比较;确定模块,设置为根据结构相似性比较的结果确定刀闸分合状态。The second aspect of the present disclosure provides a device for determining the opening and closing state of a knife gate, including: an acquisition module configured to acquire a knife gate monitoring image; the knife gate monitoring image is an image sending instruction sent by the camera device according to the knife gate control device It is generated and sent by photographing the knife gate monitoring area; the image sending instruction is generated by the knife gate control device within a preset time period for controlling the knife gate to close or disconnect; the extraction module is configured to extract the knife gate monitoring The image features of multiple preset areas in the image; the multiple preset areas at least include the closed position area where the knife switch is in the closed state and the branch position where the knife switch is in the divided state. bit position area; comparison module, configured to carry out structural similarity comparison between the image features of each of the preset areas in the knife gate monitoring image and the image features of the preset knife gate template image corresponding to the preset area; determine the module, set In order to determine the opening and closing state of the knife switch according to the result of the structural similarity comparison.
本公开实施例第三方面提供一种电子设备,包括:处理器,以及与所述处理器通信连接的存储器;所述存储器存储计算机执行指令;所述处理器执行所述存储器存储的计算机执行指令,以实现如第一方面任一项所述的刀闸分合状态确定方法。The third aspect of the embodiments of the present disclosure provides an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory , so as to realize the method for determining the opening and closing state of the knife switch according to any one of the first aspect.
本公开实施例第四方面提供一种计算机可读存储介质,所述计算机可读存储介质中存储有计算机执行指令,所述计算机执行指令被处理器执行时用于实现第一方面任一项所述的刀闸分合状态确定方法。The fourth aspect of the embodiments of the present disclosure provides a computer-readable storage medium, the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to implement any one of the first aspect when executed by a processor. The method for determining the opening and closing state of the knife switch described above.
本公开实施例第五方面提供一种计算机程序产品,包括计算机程序,该计算机程序被处理器执行时实现第一方面任一项所述的刀闸分合状态确定方法。The fifth aspect of the embodiments of the present disclosure provides a computer program product, including a computer program, and when the computer program is executed by a processor, the method for determining the opening and closing state of the knife switch described in any one of the first aspect is implemented.
本公开提供的一种刀闸分合状态确定方法、装置、设备、介质及产品,该方法包括:获取刀闸监控图像;所述刀闸监控图像为摄像装置根据刀闸控制装置发送的图像发送指令拍摄刀闸监控区域生成并发送的;所述图像发送指令为所述刀闸控制装置在控制刀闸闭合或断开的预设时间段内生成的;提取所述刀闸监控图像中多个预设区域的图像特征;所述多个预设区域至少包括刀闸处于合位状态时刀闸所处的合位位置区域和刀闸处于分位状态时刀闸所处的分位位置区域;将所述刀闸监控图像中各所述预设区域的图像特征与预设刀闸模板图像对应预设区域的图像特征进行结构相似性比较;根据结构相似性比较的结果确定刀闸分合状态。本公开的刀闸分合状态确定方法,对刀闸监控图像的预设区域和预设刀闸模板图像的预设区域进行结构相似性比较,由于预设区域至少包括刀闸处于合位状态时刀闸所处的合位位置区域和刀闸处于分位状态时刀闸所处的分位位置区域,因而,不管传感器是否故障,都可以根据比较结果确定出刀闸所处的刀闸分合状态。The present disclosure provides a method, device, equipment, medium and product for determining the opening and closing state of a knife gate, the method comprising: acquiring a knife gate monitoring image; the knife gate monitoring image is an image sent by a camera device according to a knife gate control device The instruction is generated and sent by taking pictures of the knife gate monitoring area; the image sending instruction is generated by the knife gate control device within the preset time period for controlling the knife gate to close or disconnect; extracting multiple images from the knife gate monitoring image The image characteristics of the preset area; the plurality of preset areas at least include the closing position area where the knife switch is in the closing state and the dividing position area where the knife switch is in the dividing state; Carry out structural similarity comparison between the image features of each of the preset areas in the knife gate monitoring image and the image features of the preset knife gate template image corresponding to the preset area; determine the opening and closing state of the knife gate according to the result of the structural similarity comparison . The method for determining the opening and closing state of the knife switch of the present disclosure compares the structural similarity between the preset area of the knife switch monitoring image and the preset area of the preset knife switch template image, because the preset area at least includes when the knife switch is in the closing state The closed position area where the knife switch is located and the divided position area where the knife switch is located when the knife switch is in the split state. Therefore, no matter whether the sensor is faulty or not, the opening and closing position of the knife switch can be determined according to the comparison result. state.
附图说明Description of drawings
此处的附图被并入说明书中并构成本说明书的一部分,示出了符合本公开的实施例,并与说明书一起用于解释本公开的原理。The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description serve to explain the principles of the disclosure.
图1为可以实现本公开的刀闸分合状态确定方法的场景图;FIG. 1 is a scene diagram that can realize the method for determining the opening and closing state of the knife switch of the present disclosure;
图2为本公开第一实施例提供的刀闸分合状态确定方法的流程示意图;FIG. 2 is a schematic flowchart of a method for determining the opening and closing state of a knife switch provided by the first embodiment of the present disclosure;
图3为本公开第二实施例提供的刀闸分合状态确定方法的流程示意图;FIG. 3 is a schematic flowchart of a method for determining the opening and closing state of a knife switch provided by the second embodiment of the present disclosure;
图4为本公开第二实施例提供的刀闸分合状态确定方法的预设区域示意图;FIG. 4 is a schematic diagram of a preset area of a method for determining the opening and closing state of a knife switch provided by the second embodiment of the present disclosure;
图5为本公开第三实施例提供的刀闸分合状态确定方法的图像对齐流程示意图;FIG. 5 is a schematic diagram of the image alignment process of the method for determining the opening and closing state of the knife switch provided by the third embodiment of the present disclosure;
图6为本公开第四实施例提供的刀闸分合状态确定方法的交互流程示 意图;Fig. 6 is a schematic diagram of the interaction process of the method for determining the opening and closing state of the knife switch provided by the fourth embodiment of the present disclosure;
图7为本公开第四实施例提供的刀闸分合状态确定方法的图像对齐流程示意图;FIG. 7 is a schematic diagram of the image alignment process of the method for determining the opening and closing state of the knife switch provided by the fourth embodiment of the present disclosure;
图8为本公开第五实施例提供的刀闸分合状态确定装置的结构示意图;Fig. 8 is a schematic structural diagram of a device for determining the opening and closing state of a knife switch provided by the fifth embodiment of the present disclosure;
图9为本公开第六实施例提供的电子设备的结构示意图。FIG. 9 is a schematic structural diagram of an electronic device provided by a sixth embodiment of the present disclosure.
通过上述附图,已示出本公开明确的实施例,后文中将有更详细的描述。这些附图和文字描述并不是为了通过任何方式限制本公开构思的范围,而是通过参考特定实施例为本领域技术人员说明本公开的概念。By means of the above-mentioned drawings, certain embodiments of the present disclosure have been shown and will be described in more detail hereinafter. These drawings and written description are not intended to limit the scope of the disclosed concept in any way, but to illustrate the disclosed concept for those skilled in the art by referring to specific embodiments.
具体实施方式Detailed ways
这里将详细地对示例性实施例进行说明,其示例表示在附图中。下面的描述涉及附图时,除非另有表示,不同附图中的相同数字表示相同或相似的要素。以下示例性实施例中所描述的实施方式并不代表与本公开相一致的所有实施方式。相反,它们仅是与如所附权利要求书中所详述的、本公开的一些方面相一致的装置和方法的例子。Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present disclosure as recited in the appended claims.
下面以具体地实施例对本公开的技术方案进行详细说明。下面这几个具体的实施例可以相互结合,对于相同或相似的概念或过程可能在某些实施例中不再赘述。下面将结合附图,对本公开的实施例进行描述。The technical solution of the present disclosure will be described in detail below with specific embodiments. The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present disclosure will be described below with reference to the accompanying drawings.
为了清楚理解本公开的技术方案,首先对现有技术的方案进行详细介绍。计算机视觉技术是计算机模拟人类的视觉过程,是图像处理、人工智能和模式识别等技术的综合。随着轨道交通的不断发展,计算机视觉技术在轨道内设备状态管理的应用也越来越多。传统的轨道中刀闸设备的监控管理由于需要在设备本体中添加传感器,一旦传感器故障将无法确定刀闸分合状态,且在使用维修或改造时需要关停运作设备,因而,轨道交通领域需要一种新的刀闸分合状态确认方法,结合计算机视觉技术来解决传感器故障时无法确定刀闸分合状态的问题。In order to clearly understand the technical solutions of the present disclosure, the solutions of the prior art are first introduced in detail. Computer vision technology is a computer simulation of human visual process, which is a synthesis of image processing, artificial intelligence and pattern recognition technologies. With the continuous development of rail transit, the application of computer vision technology in the status management of equipment in the track is also increasing. The monitoring and management of traditional knife switch equipment in the track needs to add sensors to the equipment body. Once the sensor fails, the opening and closing status of the knife switch cannot be determined, and the operating equipment needs to be shut down during maintenance or renovation. Therefore, the rail transit field needs A new method for confirming the opening and closing state of the knife switch, combined with computer vision technology to solve the problem that the opening and closing state of the knife switch cannot be determined when the sensor fails.
所以针对现有技术中轨道交通领域需要一种新的刀闸分合状态确认方法,以解决传感器故障时无法确定刀闸分合状态的问题,发明人在研究中发现,为了解决该问题,可以获取监控刀闸设备运作状态的摄像装置所拍摄的刀闸监控图像,并根据刀闸监控图像和预设刀闸模板图像确定刀闸分合状态。Therefore, in the field of rail transit in the prior art, a new method for confirming the opening and closing state of the knife gate is needed to solve the problem that the opening and closing state of the knife gate cannot be determined when the sensor fails. The inventor found in the research that in order to solve this problem, the Obtain the monitoring image of the knife switch taken by the camera device for monitoring the operating state of the knife switch equipment, and determine the opening and closing state of the knife switch according to the monitoring image of the knife switch and the preset knife switch template image.
具体为,在刀闸控制装置控制刀闸设备闭合或断开时,获取摄像装置拍摄刀闸监控区域生成的刀闸监控图像,并提取刀闸监控图像中多个预设区域的图像特征。多个预设区域至少包括刀闸处于合位状态时刀闸所处的合位位置区域和刀闸处于分位状态时刀闸所处的分位位置区域。然后,将刀闸监控图像中各预设区域的图像特征与预设刀闸模板图像对应预设区域的图像特征进行结构相似性比较。根据结构相似性比较的结果确定刀闸分合状态。从而,不管传感器是否故障,都可以根据比较结果确定出刀闸所处的刀闸分合状态。Specifically, when the knife gate control device controls the knife gate equipment to be closed or disconnected, the knife gate monitoring image generated by the camera device shooting the knife gate monitoring area is obtained, and the image features of multiple preset areas in the knife gate monitoring image are extracted. The plurality of preset areas at least include the closed position area where the knife switch is in the closed position and the divided position area where the knife switch is in the divided state when the knife switch is in the divided state. Then, the structural similarity comparison is performed between the image features of each preset area in the knife gate monitoring image and the image features of the preset knife gate template image corresponding to the preset area. According to the result of structural similarity comparison, the opening and closing state of the knife switch is determined. Therefore, no matter whether the sensor is faulty or not, the opening and closing state of the knife switch can be determined according to the comparison result.
发明人基于上述的创造性发现,提出了本公开的技术方案。The inventor proposes the technical solution of the present disclosure based on the above-mentioned inventive discoveries.
下面对本公开提供的刀闸分合状态确定方法的应用场景进行介绍。如图1所示,其中,1为电子设备,2为刀闸控制装置,3为刀闸设备,4为摄像装置。本公开提供的刀闸分合状态确定方法对应的应用场景的网络架构中包括:电子设备1、刀闸控制装置2、刀闸设备3和摄像装置4。刀闸控制装置2可以控制刀闸设备3的刀闸闭合或断开,摄像装置4可以拍摄包括刀闸设备3在内的刀闸监控区域。The following introduces the application scenarios of the method for determining the opening and closing state of the knife switch provided by the present disclosure. As shown in FIG. 1 , 1 is an electronic device, 2 is a knife switch control device, 3 is a knife switch device, and 4 is a camera device. The network architecture of the application scenario corresponding to the method for determining the opening and closing state of the knife switch provided in the present disclosure includes: an electronic device 1 , a knife switch control device 2 , a knife switch device 3 and a camera device 4 . The knife switch control device 2 can control the closing or opening of the knife switch device 3 , and the camera device 4 can photograph the knife switch monitoring area including the knife switch device 3 .
在刀闸控制装置2控制刀闸设备3的刀闸闭合或断开后,刀闸设备3会通过设置在期内的传感器反馈刀闸运行信息。同时,刀闸控制装置2会在预设时间段内,如5秒,发送图像发送指令至摄像装置4,以使摄像装置4将拍摄刀闸监控区域所生成的刀闸监控图像发送至电子设备1。电子设备1在获取刀闸监控图像后,提取刀闸监控图像中多个预设区域的图像特征。该多个预设区域至少包括刀闸处于合位状态时刀闸所处的合位位置 区域和刀闸处于分位状态时刀闸所处的分位位置区域。同时,电子设备1将刀闸监控图像中各预设区域的图像特征与预设刀闸模板图像对应预设区域的图像特征进行结构相似性比较,并根据结构相似性比较的结果确定刀闸分合状态。电子设备1在确定出刀闸分合状态后,可以将刀闸分合状态发送至刀闸控制装置2以使刀闸控制装置2可以根据刀闸分合状态和刀闸运行信息进一步的确定刀闸分合状态。After the knife switch control device 2 controls the knife switch of the knife switch device 3 to close or open, the knife switch device 3 will feed back the operation information of the knife switch through the sensor set in the period. At the same time, the knife gate control device 2 will send an image sending instruction to the camera device 4 within a preset time period, such as 5 seconds, so that the camera device 4 will send the knife gate monitoring image generated by shooting the knife gate monitoring area to the electronic equipment 1. The electronic device 1 extracts image features of multiple preset regions in the knife gate monitoring image after acquiring the knife gate monitoring image. The multiple preset areas at least include the closed position area where the knife switch is in the closed position and the divided position area where the knife switch is in the divided state when the knife switch is in the divided state. At the same time, the electronic device 1 compares the image features of each preset area in the knife gate monitoring image with the image features of the preset knife gate template image corresponding to the preset area for structural similarity, and determines the knife gate classification according to the result of the structural similarity comparison. combined state. After the electronic device 1 determines the opening and closing state of the knife switch, it can send the opening and closing state of the knife switch to the knife control device 2 so that the knife control device 2 can further determine the opening and closing state of the knife switch according to the opening and closing state of the knife switch and the operation information of the knife switch. The gate opening and closing state.
下面结合说明书附图对本公开实施例进行介绍。Embodiments of the present disclosure will be described below in conjunction with the accompanying drawings.
图2为本公开第一实施例提供的刀闸分合状态确定方法的流程示意图,如图2所示,本实施例中,本公开的执行主体为刀闸分合状态确定装置,该刀闸分合状态确定装置可以集成在电子设备中。则本实施例提供的刀闸分合状态确定方法包括以下几个步骤:Fig. 2 is a schematic flowchart of the method for determining the opening and closing state of the knife switch provided by the first embodiment of the present disclosure. As shown in Fig. The opening and closing state determination device can be integrated in the electronic device. Then the method for determining the opening and closing state of the knife switch provided in this embodiment includes the following steps:
步骤S101,获取刀闸监控图像。刀闸监控图像为摄像装置根据刀闸控制装置发送的图像发送指令拍摄刀闸监控区域生成并发送的。图像发送指令为刀闸控制装置在控制刀闸闭合或断开的预设时间段内生成的。Step S101, acquiring a monitoring image of a knife switch. The knife gate monitoring image is generated and sent by the camera device to photograph the knife gate monitoring area according to the image sending instruction sent by the knife gate control device. The image sending instruction is generated by the knife switch control device within a preset time period for controlling the closing or opening of the knife switch.
本实施例中,拍摄装置可以实时拍摄包括刀闸在内的刀闸监控区域,也可以在接收到图像发送指令后再拍摄刀闸监控区域,本实施例对此不作限定。在刀闸控制装置控制刀闸闭合或断开的预设时间段内,刀闸控制装置会发送图像发送指令至拍摄装置,以使拍摄装置将拍摄刀闸监控区域生成的刀闸监控图像发送至刀闸分合状态确定装置。In this embodiment, the photographing device may photograph the knife gate monitoring area including the knife gate in real time, or may photograph the knife gate monitoring area after receiving an image sending instruction, which is not limited in this embodiment. During the preset period of time during which the knife gate control device controls the knife gate to close or disconnect, the knife gate control device will send an image sending instruction to the shooting device, so that the shooting device will send the knife gate monitoring image generated by shooting the knife gate monitoring area to The device for determining the opening and closing state of the knife switch.
该预设时间段内可以根据实际需求进行设置,如刀闸从完全闭合到完全分开需要4秒时间,则可以将预设时间段设为4秒或5秒等,从而降低拍摄装置拍摄的图像是刀闸正处于完全闭合与完全分开之间状态的概率。The preset time period can be set according to actual needs. For example, it takes 4 seconds for the knife gate to be fully closed to completely separated, then the preset time period can be set to 4 seconds or 5 seconds, etc., thereby reducing the image taken by the shooting device. is the probability that the switch is in a state between fully closed and fully open.
步骤S102,提取刀闸监控图像中多个预设区域的图像特征。多个预设区域至少包括刀闸处于合位状态时刀闸所处的合位位置区域和刀闸处于分位状态时刀闸所处的分位位置区域。Step S102, extracting image features of a plurality of preset areas in the knife gate monitoring image. The plurality of preset areas at least include the closed position area where the knife switch is in the closed position and the divided position area where the knife switch is in the divided state when the knife switch is in the divided state.
本实施例中,提取的图像特征可以是提取尺度不变特征变换(英文全称为:Scale-invariant feature transform,英文简称为:SIFT)特征,使提取出的特征更为稳定,也可以使后续与预设刀闸模板图像之间进行结构相似性比较时更为稳定。In this embodiment, the extracted image feature can be extracted scale-invariant feature transform (English full name: Scale-invariant feature transform, English abbreviation: SIFT) feature, so that the extracted feature is more stable, and it can also make the follow-up and The structural similarity comparison between preset knife gate template images is more stable.
刀闸处于合位状态时刀闸所处的合位位置区域指刀闸在完全合位时,所处的位置区域。刀闸处于分位状态时刀闸所处的分位位置区域指刀闸在完全分位时,所处的位置区域。The closed position area where the knife switch is located when the knife switch is in the closed position refers to the position area where the knife switch is located when it is fully closed. The division position area where the knife switch is located when the knife switch is in the divided state refers to the position area where the knife switch is located when the knife switch is in the complete division state.
预设区域如图4中a、b虚线框所示,其中,a虚线框可以指代刀闸处于分位状态时刀闸所处的分位位置区域,b虚线框可以指代刀闸处于合位状态时刀闸所处的合位位置区域。该预设区域需要至少包括刀闸处于合位状态时刀闸所处的合位位置区域和刀闸处于分位状态时刀闸所处的分位位置区域,从而在后续与预设刀闸模板图像比较时,判断出刀闸分合状态是合位状态、分位状态还是即不处于合位状态又不处于分位状态。The preset area is shown in dotted line boxes a and b in Fig. 4, wherein, the dotted line box a can refer to the area where the knife switch is located when the knife switch is in the divided state, and the dotted line box b can refer to the area where the knife switch is in the closed state. The closing position area where the knife switch is in the bit state. The preset area needs to include at least the closed position area where the knife switch is in the closed state and the divided position area where the knife switch is in the divided state, so that in the subsequent and preset knife gate template When the images are compared, it is judged whether the opening and closing state of the knife switch is the closing state, the dividing state, or whether it is neither in the closing state nor in the dividing state.
步骤S103,将刀闸监控图像中各预设区域的图像特征与预设刀闸模板图像对应预设区域的图像特征进行结构相似性比较。Step S103 , comparing the image features of each preset area in the knife gate monitoring image with the image features of the corresponding preset area of the preset knife gate template image for structural similarity.
本实施例中,预设刀闸模板图像指预先拍摄的刀闸处于各种状态的图像,比如处于合位状态时,拍摄的模板图像以及处于分位状态时,拍摄的模板图像。单次配置预设刀闸模板图像后可重复使用原有配置,无需进行模型训练,提高了配置效率。In this embodiment, the preset knife gate template image refers to pre-captured images of the knife gate in various states, such as the template image taken when the knife gate is in the closing state and the template image taken when the knife gate is in the dividing state. After a single configuration of the preset knife gate template image, the original configuration can be reused without model training, which improves configuration efficiency.
结构相似性用于比较两幅图像的相似程度,结构相似性英文简称为:SSIM,英文全称为:structural similarity index,是一种衡量两幅图像相似度的指标。Structural similarity is used to compare the similarity between two images. The English abbreviation of structural similarity is: SSIM, and the full English name is: structural similarity index, which is an index to measure the similarity of two images.
步骤S104,根据结构相似性比较的结果确定刀闸分合状态。Step S104, determining the opening and closing state of the knife switch according to the result of the structural similarity comparison.
本实施例中,结构相似性可以确定刀闸监控图像和预设刀闸模板图像之间的相似度,根据相似度可以确定刀闸监控图像中的刀闸是否处于与预 设刀闸模板图像中刀闸所处状态,从而确定刀闸监控图像中的刀闸分合状态。In this embodiment, the structural similarity can determine the similarity between the knife gate monitoring image and the preset knife gate template image, and can determine whether the knife gate in the knife gate monitoring image is in the preset knife gate template image according to the similarity The status of the knife switch, so as to determine the opening and closing status of the knife switch in the monitoring image of the knife switch.
本公开实施例提供的一种刀闸分合状态确定方法,该方法包括:获取刀闸监控图像。刀闸监控图像为摄像装置根据刀闸控制装置发送的图像发送指令拍摄刀闸监控区域生成并发送的。图像发送指令为刀闸控制装置在控制刀闸闭合或断开的预设时间段内生成的。提取刀闸监控图像中多个预设区域的图像特征。多个预设区域至少包括刀闸处于合位状态时刀闸所处的合位位置区域和刀闸处于分位状态时刀闸所处的分位位置区域。将刀闸监控图像中各预设区域的图像特征与预设刀闸模板图像对应预设区域的图像特征进行结构相似性比较。根据结构相似性比较的结果确定刀闸分合状态。An embodiment of the present disclosure provides a method for determining an opening and closing state of a knife switch, the method comprising: acquiring a monitoring image of a knife switch. The knife gate monitoring image is generated and sent by the camera device to photograph the knife gate monitoring area according to the image sending instruction sent by the knife gate control device. The image sending instruction is generated by the knife switch control device within a preset time period for controlling the closing or opening of the knife switch. The image features of multiple preset areas in the knife gate monitoring image are extracted. The plurality of preset areas at least include the closed position area where the knife switch is in the closed position and the divided position area where the knife switch is in the divided state when the knife switch is in the divided state. Structural similarity comparisons are made between the image features of each preset area in the knife gate monitoring image and the image features of the preset knife gate template image corresponding to the preset area. According to the result of structural similarity comparison, the opening and closing state of the knife switch is determined.
本公开实施例的刀闸分合状态确定方法,对刀闸监控图像的预设区域和预设刀闸模板图像的预设区域进行结构相似性比较,由于预设区域至少包括刀闸处于合位状态时刀闸所处的合位位置区域和刀闸处于分位状态时刀闸所处的分位位置区域,因而,不管传感器是否故障,都可以根据比较结果确定出刀闸所处的刀闸分合状态。The method for determining the opening and closing state of the knife gate in the embodiment of the present disclosure compares the structural similarity between the preset area of the knife gate monitoring image and the preset area of the preset knife gate template image, because the preset area at least includes The close position area where the knife switch is in the state and the minute position area where the knife switch is in the split state. Therefore, no matter whether the sensor is faulty or not, the knife switch where the knife switch is located can be determined according to the comparison result. Split state.
图3为本公开第二实施例提供的刀闸分合状态确定方法的流程示意图,如图3所示,本实施例提供的刀闸分合状态确定方法,是在本公开上一实施例提供的刀闸分合状态确定方法的基础上,对各个步骤进行了进一步的细化。则本实施例提供的刀闸分合状态确定方法包括以下步骤。Figure 3 is a schematic flow chart of the method for determining the opening and closing state of the knife switch provided by the second embodiment of the present disclosure. As shown in Figure 3, the method for determining the opening and closing state of the knife switch provided by this embodiment is provided in the previous embodiment of the present disclosure. On the basis of the determination method of the opening and closing state of the knife switch, each step is further refined. Then, the method for determining the opening and closing state of the knife switch provided in this embodiment includes the following steps.
步骤S201,获取刀闸监控图像。刀闸监控图像为摄像装置根据刀闸控制装置发送的图像发送指令拍摄刀闸监控区域生成并发送的。图像发送指令为刀闸控制装置在控制刀闸闭合或断开的预设时间段内生成的。Step S201, acquiring a monitoring image of a knife switch. The knife gate monitoring image is generated and sent by the camera device to photograph the knife gate monitoring area according to the image sending instruction sent by the knife gate control device. The image sending instruction is generated by the knife switch control device within a preset time period for controlling the closing or opening of the knife switch.
本实施例中,步骤201的实现方式与本公开上一实施例中的步骤101的实现方式类似,在此不再一一赘述。In this embodiment, the implementation manner of step 201 is similar to the implementation manner of step 101 in the previous embodiment of the present disclosure, and will not be repeated here.
步骤S202,获取预设刀闸模板图像中各预设区域在预设刀闸模板图像中的坐标范围。其中,预设刀闸模板图像为预先拍摄的刀闸处于合位状态时的合位模板图像和刀闸处于分位状态时的分位模板图像。合位模板图像包括刀闸处于合位状态时的合位位置区域和刀闸处于合位状态时的分位位置区域。分位模板图像包括刀闸处于分位状态时的合位位置区域和刀闸处于分位状态时的分位位置区域。Step S202, obtaining the coordinate range of each preset area in the preset knife gate template image in the preset knife gate template image. Wherein, the preset knife switch template image is a pre-shot closing template image when the knife switch is in a closing state and a dividing template image when the knife switch is in a separating state. The closing template image includes the closing position area when the knife switch is in the closing state and the dividing position area when the knife switch is in the closing state. The divider template image includes the closing position area when the knife switch is in the divider state and the divider position area when the knife switch is in the divider state.
本实施例中,在配置预设刀闸模板图像时,每个预设区域都会以坐标范围的形式表示。预设区域可以为方形区域的形式,如图4中虚线框a和b所示,也可以设置为圆形或其他形状。In this embodiment, when configuring the preset knife gate template image, each preset area will be represented in the form of a coordinate range. The preset area can be in the form of a square area, as shown by dashed boxes a and b in FIG. 4 , or it can be set in a circle or other shapes.
本实施例中,合位模板图像还可以包括:刀闸处于合位位置区域时合位位置区域的图像和刀闸处于合位位置区域时分位位置区域的图像。分位模板图像还可以包括:刀闸处于分位位置区域时合位位置区域的图像和刀闸处于分位位置区域时分位位置区域的图像。In this embodiment, the closing template image may further include: an image of the closing position area when the knife switch is in the closing position area, and an image of the dividing position area when the knife switch is in the closing position area. The dividing template image may also include: an image of the closing position area when the knife switch is in the dividing position area, and an image of the dividing position area when the knife switch is in the dividing position area.
步骤S203,根据各坐标范围提取刀闸监控图像中对应预设区域的图像特征。Step S203, extracting image features corresponding to preset areas in the knife gate monitoring image according to each coordinate range.
本实施例中,由于刀闸监控图像的预设区域与预设刀闸模板图像的预设区域相对应,因而,可以根据预设刀闸模板图像的各坐标范围提取刀闸监控图像中对应预设区域的图像特征。也可以通过其他方式来提取刀闸监控图像中对应预设区域的图像特征,本实施例对此不作限定。In this embodiment, since the preset area of the knife gate monitoring image corresponds to the preset area of the preset knife gate template image, the corresponding preset area in the knife gate monitoring image can be extracted according to each coordinate range of the preset knife gate template image. Image features of the set area. The image feature corresponding to the preset area in the knife gate monitoring image may also be extracted in other ways, which is not limited in this embodiment.
需要说明的是,预设区域为刀闸处于合位状态时刀闸所处的合位位置区域和刀闸处于分位状态时刀闸所处的分位位置区域。It should be noted that the preset area is the closed position area where the knife switch is in the closed state and the divided position area where the knife switch is in the divided state when the knife switch is in the closed state.
步骤S204,将刀闸监控图像中的合位位置区域分别与合位模板图像中的合位位置区域以及分位模板图像中的合位位置区域进行结构相似性比较,以确定合位位置区域比较结果。Step S204, comparing the closing position area in the knife gate monitoring image with the closing position area in the closing template image and the closing position area in the quantization template image respectively, so as to determine the closing position area comparison result.
本实施例中,将刀闸监控图像中的合位位置区域分别与合位模板图像 中的合位位置区域以及分位模板图像中的合位位置区域进行结构相似性比较是为了确定刀闸监控图像中的合位位置区域是否存在刀闸。如图4所示,虚线框b区域是预设区域中的合位位置区域,当刀闸处于合位状态时,虚线框b区域中存在刀闸,而在刀闸处于分位状态时,虚线框b区域中不存在刀闸。In this embodiment, the purpose of comparing the structural similarity of the closing position area in the knife gate monitoring image with the closing position area in the closing template image and the closing position area in the sub-position template image is to determine the Whether there is a knife switch in the closed position area in the image. As shown in Figure 4, the dotted line box b area is the close position area in the preset area. When the knife switch is in the close position state, there is a knife switch in the dotted line box b area, and when the knife switch is in the split state, the dotted line There is no knife switch in the box b area.
同时,具体的结构相似性比较流程如下:At the same time, the specific structural similarity comparison process is as follows:
若刀闸监控图像中的合位位置区域与合位模板图像中的合位位置区域之间的结构相似性大于刀闸监控图像中的合位位置区域与分位模板图像中的合位位置区域之间的结构相似性,则确定合位位置区域比较结果为合位位置区域存在刀闸。If the structural similarity between the closing position area in the knife gate monitoring image and the closing position area in the closing template image is greater than the closing position area in the knife gate monitoring image and the closing position area in the split template image If there is structural similarity between them, it is determined that there is a knife switch in the closing position area as a result of the comparison of the closing position area.
若刀闸监控图像中的合位位置区域与合位模板图像中的合位位置区域之间的结构相似性小于刀闸监控图像中的合位位置区域与分位模板图像中的合位位置区域之间的结构相似性,则确定合位位置区域比较结果为合位位置区域不存在刀闸。If the structural similarity between the closing position area in the knife gate monitoring image and the closing position area in the closing template image is smaller than the closing position area in the knife gate monitoring image and the closing position area in the split template image If there is structural similarity between them, it is determined that there is no knife gate in the closing position area as a result of the comparison.
结构相似性以数值的形式表示,一般数值为0-1之间,数值越大代表相似程度越高。当刀闸监控图像中的合位位置区域与合位模板图像中的合位位置区域之间的结构相似性更大时,代表合位位置区域存在刀闸。Structural similarity is expressed in numerical form, generally the value is between 0 and 1, and the larger the value, the higher the degree of similarity. When the structural similarity between the closing position area in the knife gate monitoring image and the closing position area in the closing template image is greater, it means that there is a knife gate in the closing position area.
步骤S205,将刀闸监控图像中的分位位置区域分别与合位模板图像中的分位位置区域以及分位模板图像中的分位位置区域进行结构相似性比较,以确定分位位置区域比较结果。Step S205, performing structural similarity comparison between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image and the quantile position area in the quantile template image, so as to determine the quantile position area comparison result.
本实施例中,将刀闸监控图像中的分位位置区域分别与合位模板图像中的分位位置区域以及分位模板图像中的分位位置区域进行结构相似性比较是为了确定刀闸监控图像中的分位位置区域是否存在刀闸。如图4所示,虚线框a区域是预设区域中的分位位置区域,当刀闸处于分位状态时,虚线框a区域中存在刀闸,而在刀闸处于合位状态时,虚线框a区域中不 存在刀闸。In this embodiment, the structural similarity comparison between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image and the quantile position area in the quantizing template image is to determine the Whether there is a knife gate in the quantile position area in the image. As shown in Figure 4, the dotted line box a area is the division position area in the preset area. When the knife switch is in the division state, there is a knife switch in the dotted line box a area, and when the knife switch is in the close position, the dotted line There is no knife gate in the box a area.
同时,具体的结构相似性比较流程如下:At the same time, the specific structural similarity comparison process is as follows:
若刀闸监控图像中的分位位置区域与合位模板图像中的分位位置区域之间的结构相似性大于刀闸监控图像中的分位位置区域与分位模板图像中的分位位置区域之间的结构相似性,则确定分位位置区域比较结果为分位位置区域不存在刀闸。If the structural similarity between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image is greater than the quantile position area in the knife gate monitoring image and the quantile position area in the quantizing template image If there is structural similarity between them, it is determined that there is no knife gate in the quantile position area as a result of the comparison.
若刀闸监控图像中的分位位置区域与合位模板图像中的分位位置区域之间的结构相似性小于刀闸监控图像中的分位位置区域与分位模板图像中的分位位置区域之间的结构相似性,则确定分位位置区域比较结果为分位位置区域存在刀闸。If the structural similarity between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image is smaller than the quantile position area in the knife gate monitoring image and the quantile position area in the quantizing template image If there is structural similarity between them, it is determined that there is a knife gate in the quantile position area as a result of the comparison of the quantile position area.
分位位置区域与合位位置区域的判定方式类似,当刀闸监控图像中的分位位置区域与分位模板图像中的分位位置区域之间的结构相似性更大时,代表分位位置区域存在刀闸。The quantile position area is determined in a similar way to the close position area. When the structural similarity between the quantile position area in the knife gate monitoring image and the quantile position area in the quantile template image is greater, it represents the quantile position. There are knife gates in the area.
步骤S206,根据合位位置区域比较结果和分位位置区域比较结果确定刀闸分合状态。Step S206, determining the opening and closing state of the knife switch according to the comparison result of the closed position area and the comparison result of the divided position area.
本实施例中,根据合位位置区域比较结果和分位位置区域比较结果确定刀闸分合状态可以具体为:In this embodiment, the determination of the opening and closing state of the knife switch according to the comparison result of the closing position area and the comparison result of the dividing position area can be specifically as follows:
若合位位置区域比较结果为合位位置区域存在刀闸,分位位置区域比较结果为分位位置区域不存在刀闸,则确定刀闸状态为处于合位状态。If the comparison result of the closing position area is that there is a knife switch in the closing position area, and the comparison result of the closing position area is that there is no knife switch in the closing position area, then it is determined that the knife switch is in the closing state.
若合位位置区域比较结果为合位位置区域不存在刀闸,分位位置区域比较结果为分位位置区域存在刀闸,则确定刀闸状态为处于分位状态。If the comparison result of the close position area is that there is no knife switch in the close position area, and the comparison result of the split position area is that there is a knife switch in the split position area, then it is determined that the knife switch state is in the split state.
若合位位置区域比较结果为合位位置区域不存在刀闸,分位位置区域比较结果为分位位置区域不存在刀闸,则确定刀闸状态为处于非分位且非合位状态。If the comparison result of the closing position area is that there is no knife switch in the closing position area, and the comparison result of the closing position area is that there is no knife switch in the closing position area, then it is determined that the knife switch state is in a non-separating and non-closing state.
步骤S207,向刀闸控制装置发送刀闸分合状态,以使刀闸控制装置根据刀闸分合状态和传感器反馈的刀闸运行信息二次确定刀闸分合状态。Step S207, sending the opening and closing state of the knife switch to the knife switch control device, so that the knife switch control device determines the opening and closing state of the knife switch for a second time according to the opening and closing state of the knife switch and the operation information of the knife switch fed back by the sensor.
本实施例中,可以通过向刀闸控制装置发送刀闸分合状态,使刀闸控制装置可以根据刀闸分合状态和传感器反馈的刀闸运行信息二次确定刀闸分合状态,提高确定刀闸分合状态的精确性和稳定性。In this embodiment, the opening and closing state of the knife switch can be sent to the knife switch control device, so that the knife switch control device can determine the opening and closing state of the knife switch according to the opening and closing state of the knife switch and the knife switch operation information fed back by the sensor, so as to improve the certainty. The accuracy and stability of the opening and closing state of the knife switch.
图5为本公开第三实施例提供的刀闸分合状态确定方法的图像对齐流程示意图,如图5所示,本实施例提供的刀闸分合状态确定方法,是在本公开上一实施例提供的刀闸分合状态确定方法的基础上,增加了图像对齐流程,图像对齐流程包括以下步骤。FIG. 5 is a schematic diagram of the image alignment process of the method for determining the opening and closing state of the knife switch provided by the third embodiment of the present disclosure. As shown in FIG. Based on the method for determining the opening and closing state of the knife gate provided in the example, an image alignment process is added, and the image alignment process includes the following steps.
步骤S301,提取刀闸监控图像的图像特征和预设刀闸模板图像的图像特征。Step S301, extracting the image features of the monitor image of the knife gate and the image features of the preset knife gate template image.
本实施例中,提取刀闸监控图像的图像特征以SIFT特征为佳,可以更好地提高图像特征对的匹配度以及变换矩阵的稳定性。In this embodiment, the SIFT feature is preferable for extracting the image feature of the knife gate monitoring image, which can better improve the matching degree of the image feature pair and the stability of the transformation matrix.
步骤S302,将刀闸监控图像的图像特征与预设刀闸模板图像的图像特征进行匹配,以生成多个图像特征对。Step S302, matching the image features of the monitor image of the knife gate with the image features of the preset knife gate template image to generate a plurality of image feature pairs.
图像特征对是由匹配的两个图像特征组成的特征对。An image feature pair is a feature pair consisting of two image features that match.
匹配方式可以采用FLANN(中文为:快速最近邻搜索包,英文全称为:Fast Library for Approximate Nearest Neighbors)或BF(中文为暴力,英文全称为:Brute Force)算法,进一步提高匹配图像特征对的精确性和稳定性。The matching method can use FLANN (Chinese: fast nearest neighbor search package, English full name: Fast Library for Approximate Nearest Neighbors) or BF (Chinese is violence, English full name: Brute Force) algorithm to further improve the accuracy of matching image feature pairs sex and stability.
步骤S303,根据多个图像特征对和预设的投影变换算法确定刀闸监控图像与预设刀闸模板图像之间的变换矩阵。In step S303, a transformation matrix between the knife gate monitoring image and the preset knife gate template image is determined according to a plurality of image feature pairs and a preset projection transformation algorithm.
预设的投影变换算法可以采用RANSAC鲁棒求解算法,其英文全称为:Random Sample Consensus,从而确定出更稳定、精确度更高的变换矩阵。The preset projection transformation algorithm can use the RANSAC robust solution algorithm, which is called Random Sample Consensus in English, so as to determine a more stable and accurate transformation matrix.
同时,在根据多个图像特征对和预设的投影变换算法确定刀闸监控图像与预设刀闸模板图像之间的变换矩阵时,可以先判断多个图像特征对数量是否大于或等于预设阈值。At the same time, when determining the transformation matrix between the knife gate monitoring image and the preset knife gate template image according to multiple image feature pairs and the preset projection transformation algorithm, it is possible to first judge whether the number of multiple image feature pairs is greater than or equal to the preset threshold.
若确定多个图像特征对数量大于或等于预设阈值,则根据多个图像特征对和预设的投影变换算法确定刀闸监控图像与预设刀闸模板图像之间的变换矩阵。If it is determined that the number of multiple image feature pairs is greater than or equal to the preset threshold, the transformation matrix between the knife gate monitoring image and the preset knife gate template image is determined according to the multiple image feature pairs and a preset projection transformation algorithm.
若确定多个图像特征对数量小于预设阈值,可以确定刀闸监控图像与预设刀闸模板图像之间匹配度太低,可以采用下一个刀闸监控图像进行图像对齐的流程。If it is determined that the number of image feature pairs is less than the preset threshold, it can be determined that the matching degree between the knife gate monitoring image and the preset knife gate template image is too low, and the next knife gate monitoring image can be used for image alignment.
步骤S304,根据变换矩阵对刀闸监控图像进行矫正,以使矫正后的刀闸监控图像与预设刀闸模板图像对齐。Step S304, correcting the monitoring image of the knife gate according to the transformation matrix, so that the corrected monitoring image of the knife gate is aligned with the preset knife gate template image.
本实施例中,对刀闸监控图像进行矫正处理是由于轨道车辆实际运行时,容易产生较大的震动,从而使拍摄装置产生角度偏移的问题。如果拍摄装置产生角度偏移会导致拍摄出来的刀闸监控图像也存在角度偏移问题,影响后续刀闸分合状态的确定。因而,可以通过对刀闸监控图像进行矫正,解决拍摄装置的角度偏移问题。In this embodiment, the correcting process is performed on the monitoring image of the knife gate because the rail vehicle is likely to generate relatively large vibrations during actual operation, thereby causing an angle deviation of the photographing device. If the shooting device produces an angular offset, the captured knife switch monitoring image will also have an angle offset problem, which will affect the subsequent determination of the opening and closing status of the knife switch. Therefore, the problem of angular deviation of the shooting device can be solved by correcting the monitoring image of the knife gate.
同时,为了更好的理解本公开的刀闸分合状态确定方法,下面将结合附图进一步的说明。如图6所示,本实施例中,以刀闸控制装置二次确定刀闸状态来进行举例说明。刀闸控制装置采用常用的一键顺控系统中的控制装置,在图中以一键顺控表示。本实施例采用的拍摄装置为摄像头。At the same time, in order to better understand the method for determining the opening and closing state of the knife switch of the present disclosure, further description will be given below in conjunction with the accompanying drawings. As shown in FIG. 6 , in this embodiment, the second determination of the status of the knife switch by the knife switch control device is used as an example for illustration. The knife switch control device adopts the control device in the commonly used one-key sequence control system, which is represented by one-key sequence control in the figure. The photographing device adopted in this embodiment is a camera.
总体流程为:一键顺控系统发出信号控制刀闸闭合或断开,等待若干秒后刀闸动作到位,刀闸设备中的传感器会反馈刀闸运行信息,即是否合位或分位。同时,一键顺控系统会发送图像发送指令至摄像头,以使摄像头传输拍摄的刀闸监控图像至刀闸分合状态确定装置,以判别刀闸分合状态,将结果返回一键件顺控系统。一键顺控系统综合传感器和刀闸分合状 态确定装置的状态判别信息,综合得出刀闸分合状态,完成刀闸分合闸的双确认。The overall process is: the one-button sequential control system sends a signal to control the closing or opening of the knife switch, and after waiting for a few seconds, the knife switch moves in place, and the sensor in the knife switch device will feedback the operation information of the knife switch, that is, whether it is closed or divided. At the same time, the one-button sequential control system will send an image sending command to the camera, so that the camera can transmit the captured knife switch monitoring image to the knife switch opening and closing state determination device to judge the knife switch opening and closing state, and return the result to the one-button sequence control system. The one-button sequential control system integrates the status discrimination information of the sensor and the switch opening and closing status determination device, and obtains the opening and closing status of the switch comprehensively, and completes the double confirmation of the opening and closing of the switch.
具体流程:specific process:
在确定刀闸分合状态分析前,截取刀闸处于分位与合位的图像,进行标注配置。在单次配置完成后可重复使用原有配置,无需进行模型训练。Before determining the opening and closing state analysis of the knife switch, the images of the knife switch in the opening and closing positions are intercepted for labeling configuration. After a single configuration is completed, the original configuration can be reused without model training.
具体的,首先,保存两张刀闸分别处于分位与合位的照片作为模板图像。并在其中标记刀闸活动连接处所在位置a和b两个虚线框,如图4中所示,图4上方为合位时的状态,下方为分位时的状态。由此,可以得到4张匹配模板,分别是合位(有刀闸)、合位(无刀闸)、分位(有刀闸)与分位(无刀闸)。这4个区域将用于刀闸分合状态的识别。Specifically, firstly, two photos of the knife switch in the split position and the closing position are saved as template images. And mark the two dotted line boxes at the position a and b of the active connection of the knife switch, as shown in Figure 4, the upper part of Figure 4 is the state when it is closed, and the lower part is the state when it is divided. In this way, four matching templates can be obtained, namely close position (with knife switch), close position (without knife switch), separate position (with knife switch) and separate position (without knife switch). These 4 areas will be used to identify the opening and closing state of the knife switch.
然后,如图7所示,先对刀闸监控图像进行摄像头角度的矫正,使刀闸监控图像与模板图像对齐。具体为:刀闸分合状态确定装置从摄像头处取得需要确定刀闸状态的刀闸监控图像,提取该图像的SIFT特征,然后通过FLANN或BF算法匹配刀闸监控图像与模板图像的SIFT特征,得到成对的特征点。此时,判断该特征点对数量是否大于或等于10,若否,则等待下一次摄像头输入的图像,若是,则按照仿射或投影变换关系,利用RANSAC鲁棒求解算法,求出刀闸监控图像到模板图像的变换矩阵M。将刀闸监控图像根据M进行仿射或投影变换,对齐两个图像,纠正摄像头的角度偏移,完成图像对齐。Then, as shown in FIG. 7 , the angle of the camera is corrected on the monitor image of the knife gate, so that the monitor image of the knife gate is aligned with the template image. Specifically: the device for determining the opening and closing state of the knife gate obtains the knife gate monitoring image that needs to determine the knife gate state from the camera, extracts the SIFT feature of the image, and then uses the FLANN or BF algorithm to match the SIFT features of the knife gate monitoring image and the template image, Get pairs of feature points. At this time, judge whether the number of feature point pairs is greater than or equal to 10, if not, wait for the next image input by the camera, if so, use the RANSAC robust solution algorithm to find the knife gate monitoring The transformation matrix M of the image to the template image. Perform affine or projective transformation on the knife gate monitoring image according to M, align the two images, correct the angle offset of the camera, and complete the image alignment.
在完成图像对齐后,对刀闸监控图像和模板图像进行结构相似性比较。首先,根据模板图像虚线框区域a和b的坐标,选取对齐后刀闸监控图像上的对应虚线框区域a与b,来与保存的模板图像的虚线框区域a与b作比较。通过SSIM相似性比较,得出a、b区域是否存在刀闸,从而判断刀闸的分合状态。分合状态判别如表1刀闸分合位状态表所示。After the image alignment is completed, the structural similarity comparison is carried out between the knife gate monitoring image and the template image. First, according to the coordinates of the dotted frame areas a and b of the template image, select the corresponding dotted frame areas a and b on the knife gate monitor image after alignment to compare with the dotted frame areas a and b of the saved template image. Through SSIM similarity comparison, it is obtained whether there is a knife switch in the a and b areas, so as to judge the opening and closing status of the knife switch. Discrimination of the opening and closing state is shown in Table 1.
表1 刀闸分合位状态表Table 1 Knife switch opening and closing status table
a区域状态a area state b区域状态b area status 刀闸状态Knife status
无刀闸No knife gate 有刀闸With knife switch 合位fit together
有刀闸With knife switch 无刀闸No knife gate 分位quantile
无刀闸No knife gate 无刀闸No knife gate 动作不到位The action is not in place
有刀闸With knife switch 有刀闸With knife switch 分析出错analysis error
从表1读取对应状态后,刀闸分合状态确定装置将刀闸分合状态发送到一键顺控系统。After reading the corresponding state from Table 1, the device for determining the opening and closing state of the knife switch sends the opening and closing state of the knife switch to the one-key sequence control system.
图8为本公开第五实施例提供的刀闸分合状态确定装置的结构示意图,如图8所示,本实施例中,该刀闸分合状态确定装置400包括:Fig. 8 is a schematic structural diagram of the device for determining the opening and closing state of the knife switch provided by the fifth embodiment of the present disclosure. As shown in Fig. 8, in this embodiment, the device 400 for determining the opening and closing state of the knife switch includes:
获取模块401,设置为获取刀闸监控图像。刀闸监控图像为摄像装置根据刀闸控制装置发送的图像发送指令拍摄刀闸监控区域生成并发送的。图像发送指令为刀闸控制装置在控制刀闸闭合或断开的预设时间段内生成的。The obtaining module 401 is configured to obtain the monitoring image of the knife gate. The knife gate monitoring image is generated and sent by the camera device to photograph the knife gate monitoring area according to the image sending instruction sent by the knife gate control device. The image sending instruction is generated by the knife switch control device within a preset time period for controlling the closing or opening of the knife switch.
提取模块402,设置为提取刀闸监控图像中多个预设区域的图像特征。多个预设区域至少包括刀闸处于合位状态时刀闸所处的合位位置区域和刀闸处于分位状态时刀闸所处的分位位置区域。The extraction module 402 is configured to extract image features of multiple preset areas in the knife gate monitoring image. The plurality of preset areas at least include the closed position area where the knife switch is in the closed position and the divided position area where the knife switch is in the divided state when the knife switch is in the divided state.
比较模块403,设置为将刀闸监控图像中各预设区域的图像特征与预设刀闸模板图像对应预设区域的图像特征进行结构相似性比较。The comparison module 403 is configured to perform structural similarity comparison between the image features of each preset area in the knife gate monitoring image and the image features of the preset knife gate template image corresponding to the preset area.
确定模块404,设置为根据结构相似性比较的结果确定刀闸分合状态。The determination module 404 is configured to determine the opening and closing state of the knife switch according to the result of the structural similarity comparison.
本实施例提供的刀闸分合状态确定装置可以执行图2所示方法实施例的技术方案,其实现原理和技术效果与图2所示方法实施例类似,在此不再一一赘述。The device for determining the opening and closing state of the knife switch provided in this embodiment can implement the technical solution of the method embodiment shown in FIG. 2 , and its realization principle and technical effect are similar to those of the method embodiment shown in FIG. 2 , so details will not be repeated here.
同时,本公开提供的刀闸分合状态确定装置在上一实施例提供的刀闸分合状态确定装置的基础上,对刀闸分合状态确定装置400进行了进一步的细化。At the same time, the device for determining the opening and closing state of the knife switch provided in the present disclosure further refines the device for determining the opening and closing state of the knife switch 400 on the basis of the device for determining the opening and closing state of the knife switch provided in the previous embodiment.
可选的,本实施例中,提取模块402具体设置为:Optionally, in this embodiment, the extraction module 402 is specifically set as:
获取预设刀闸模板图像中各预设区域在预设刀闸模板图像中的坐标范围。根据各坐标范围提取刀闸监控图像中对应预设区域的图像特征。The coordinate range of each preset area in the preset knife gate template image in the preset knife gate template image is acquired. The image features corresponding to the preset area in the knife gate monitoring image are extracted according to each coordinate range.
可选的,本实施例中,预设区域包括刀闸处于合位状态时刀闸所处的合位位置区域和刀闸处于分位状态时刀闸所处的分位位置区域。Optionally, in this embodiment, the preset area includes the closed position area where the knife switch is in the closed state and the divided position area where the knife switch is in the divided state when the knife switch is in the divided state.
预设刀闸模板图像为预先拍摄的刀闸处于合位状态时的合位模板图像和刀闸处于分位状态时的分位模板图像。合位模板图像包括刀闸处于合位状态时的合位位置区域和刀闸处于合位状态时的分位位置区域。分位模板图像包括刀闸处于分位状态时的合位位置区域和刀闸处于分位状态时的分位位置区域。The preset knife gate template image is a pre-shot closing template image when the knife gate is in a closing state and a dividing template image when the knife gate is in a dividing state. The closing template image includes the closing position area when the knife switch is in the closing state and the dividing position area when the knife switch is in the closing state. The divider template image includes the closing position area when the knife switch is in the divider state and the divider position area when the knife switch is in the divider state.
比较模块403设置为:The comparison module 403 is set to:
将刀闸监控图像中的合位位置区域分别与合位模板图像中的合位位置区域以及分位模板图像中的合位位置区域进行结构相似性比较,以确定合位位置区域比较结果。将刀闸监控图像中的分位位置区域分别与合位模板图像中的分位位置区域以及分位模板图像中的分位位置区域进行结构相似性比较,以确定分位位置区域比较结果。Structural similarity comparisons were carried out between the closing position area in the knife gate monitoring image and the closing position area in the closing template image and the closing position area in the quantized template image, so as to determine the comparison result of the closing position area. Structural similarity comparisons are made between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image and the quantile position area in the quantile template image to determine the comparison result of the quantile position area.
可选的,本实施例中,比较模块403在将刀闸监控图像中的合位位置区域分别与合位模板图像中的合位位置区域以及分位模板图像中的合位位置区域进行结构相似性比较,以确定合位位置区域比较结果时,设置为:Optionally, in this embodiment, the comparison module 403 compares the closing position area in the knife gate monitoring image with the closing position area in the closing template image and the closing position area in the sub-positioning template image respectively in a similar structure. Sex comparison to determine the zygomatic position area comparison result, set to:
若刀闸监控图像中的合位位置区域与合位模板图像中的合位位置区域之间的结构相似性大于刀闸监控图像中的合位位置区域与分位模板图像中的合位位置区域之间的结构相似性,则确定合位位置区域比较结果为 合位位置区域存在刀闸。若刀闸监控图像中的合位位置区域与合位模板图像中的合位位置区域之间的结构相似性小于刀闸监控图像中的合位位置区域与分位模板图像中的合位位置区域之间的结构相似性,则确定合位位置区域比较结果为合位位置区域不存在刀闸。If the structural similarity between the closing position area in the knife gate monitoring image and the closing position area in the closing template image is greater than the closing position area in the knife gate monitoring image and the closing position area in the split template image If there is structural similarity between them, it is determined that there is a knife switch in the closing position area as a result of the comparison of the closing position area. If the structural similarity between the closing position area in the knife gate monitoring image and the closing position area in the closing template image is smaller than the closing position area in the knife gate monitoring image and the closing position area in the split template image If there is structural similarity between them, it is determined that there is no knife gate in the closing position area as a result of the comparison.
可选的,本实施例中,比较模块403在将刀闸监控图像中的分位位置区域分别与合位模板图像中的分位位置区域以及分位模板图像中的分位位置区域进行结构相似性比较,以确定分位位置区域比较结果时,具体设置为:Optionally, in this embodiment, the comparison module 403 compares the quantile position area in the knife gate monitoring image with the quantile position area in the closing template image and the quantile position area in the quantizing template image. To determine the quantile position area comparison results, the specific settings are:
若刀闸监控图像中的分位位置区域与合位模板图像中的分位位置区域之间的结构相似性大于刀闸监控图像中的分位位置区域与分位模板图像中的分位位置区域之间的结构相似性,则确定分位位置区域比较结果为分位位置区域不存在刀闸。若刀闸监控图像中的分位位置区域与合位模板图像中的分位位置区域之间的结构相似性小于刀闸监控图像中的分位位置区域与分位模板图像中的分位位置区域之间的结构相似性,则确定分位位置区域比较结果为分位位置区域存在刀闸。If the structural similarity between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image is greater than the quantile position area in the knife gate monitoring image and the quantile position area in the quantizing template image If there is structural similarity between them, it is determined that there is no knife gate in the quantile position area as a result of the comparison. If the structural similarity between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image is smaller than the quantile position area in the knife gate monitoring image and the quantile position area in the quantizing template image If there is structural similarity between them, it is determined that there is a knife gate in the quantile position area as a result of the comparison of the quantile position area.
可选的,本实施例中,确定模块404设置为:Optionally, in this embodiment, the determining module 404 is set to:
若合位位置区域比较结果为合位位置区域存在刀闸,分位位置区域比较结果为分位位置区域不存在刀闸,则确定刀闸状态为处于合位状态。若合位位置区域比较结果为合位位置区域不存在刀闸,分位位置区域比较结果为分位位置区域存在刀闸,则确定刀闸状态为处于分位状态。若合位位置区域比较结果为合位位置区域不存在刀闸,分位位置区域比较结果为分位位置区域不存在刀闸,则确定刀闸状态为处于非分位且非合位状态。If the comparison result of the closing position area is that there is a knife switch in the closing position area, and the comparison result of the closing position area is that there is no knife switch in the closing position area, then it is determined that the knife switch is in the closing state. If the comparison result of the close position area is that there is no knife switch in the close position area, and the comparison result of the split position area is that there is a knife switch in the split position area, then it is determined that the knife switch state is in the split state. If the comparison result of the closing position area is that there is no knife switch in the closing position area, and the comparison result of the closing position area is that there is no knife switch in the closing position area, then it is determined that the knife switch state is in a non-separating and non-closing state.
可选的,本实施例中,刀闸分合状态确定装置400还包括:Optionally, in this embodiment, the device 400 for determining the opening and closing state of the knife switch further includes:
图像对齐模块,设置为提取刀闸监控图像的图像特征和预设刀闸模板图像的图像特征。将刀闸监控图像的图像特征与预设刀闸模板图像的图像 特征进行匹配,以生成多个图像特征对。根据多个图像特征对和预设的投影变换算法确定刀闸监控图像与预设刀闸模板图像之间的变换矩阵。根据变换矩阵对刀闸监控图像进行矫正,以使矫正后的刀闸监控图像与预设刀闸模板图像对齐。The image alignment module is configured to extract the image features of the monitor image of the knife gate and the image features of the preset knife gate template image. Match the image features of the knife gate monitoring image with the image features of the preset knife gate template image to generate multiple image feature pairs. A transformation matrix between the knife gate monitoring image and the preset knife gate template image is determined according to a plurality of image feature pairs and a preset projection transformation algorithm. The knife gate monitoring image is corrected according to the transformation matrix, so that the corrected knife gate monitoring image is aligned with the preset knife gate template image.
可选的,本实施例中,图像对齐模块在根据多个图像特征对和预设的投影变换算法确定刀闸监控图像与预设刀闸模板图像之间的变换矩阵时,设置为:Optionally, in this embodiment, when the image alignment module determines the transformation matrix between the knife gate monitoring image and the preset knife gate template image according to a plurality of image feature pairs and a preset projection transformation algorithm, it is set as:
判断多个图像特征对数量是否大于或等于预设阈值。若确定多个图像特征对数量大于或等于预设阈值,则根据多个图像特征对和预设的投影变换算法确定刀闸监控图像与预设刀闸模板图像之间的变换矩阵。It is judged whether the number of multiple image feature pairs is greater than or equal to a preset threshold. If it is determined that the number of multiple image feature pairs is greater than or equal to the preset threshold, the transformation matrix between the knife gate monitoring image and the preset knife gate template image is determined according to the multiple image feature pairs and a preset projection transformation algorithm.
可选的,本实施例中,刀闸分合状态确定装置400还包括:Optionally, in this embodiment, the device 400 for determining the opening and closing state of the knife switch further includes:
二次确定模块,设置为向刀闸控制装置发送刀闸分合状态,以使刀闸控制装置根据刀闸分合状态和传感器反馈的刀闸运行信息二次确定刀闸分合状态。The secondary determination module is configured to send the opening and closing state of the knife switch to the knife switch control device, so that the knife switch control device can secondarily determine the opening and closing state of the knife switch according to the opening and closing state of the knife switch and the operation information of the knife switch fed back by the sensor.
本实施例提供的刀闸分合状态确定装置可以执行图2-图7所示方法实施例的技术方案,其实现原理和技术效果与图2-图7所示方法实施例类似,在此不再一一赘述。The device for determining the opening and closing state of the knife switch provided in this embodiment can implement the technical solution of the method embodiment shown in Fig. 2-Fig. 7, and its realization principle and technical effect are similar to those of the method embodiment shown in Fig. 2-Fig. Let me repeat them one by one.
本公开还提供了一种电子设备、一种计算机可读存储介质和一种计算机程序产品。The present disclosure also provides an electronic device, a computer-readable storage medium, and a computer program product.
如图9所示,图9是本公开第六实施例提供的电子设备的结构示意图。电子设备旨在各种形式适用于刀闸分合状态确定训练的数字计算机,诸如,膝上型计算机、个人数字助理、和其它适合的计算机。本文所示的部件、它们的连接和关系、以及它们的功能仅仅作为示例,并且不意在限制本文中描述的和/或者要求的本公开的实现。As shown in FIG. 9 , FIG. 9 is a schematic structural diagram of an electronic device provided by a sixth embodiment of the present disclosure. The electronic device is intended to be in various forms of digital computers suitable for knife-opening state determination training, such as laptop computers, personal digital assistants, and other suitable computers. The components shown herein, their connections and relationships, and their functions, are by way of example only, and are not intended to limit implementations of the disclosure described and/or claimed herein.
如图9所示,该电子设备包括:处理器501、存储器502。各个部件 利用不同的总线互相连接,并且可以被安装在公共主板上或者根据需要以其它方式安装。处理器可以对在电子设备内执行的指令进行处理。As shown in FIG. 9 , the electronic device includes: a processor 501 and a memory 502 . The various components are interconnected using different buses and can be mounted on a common motherboard or otherwise as desired. A processor may process instructions for execution within an electronic device.
存储器502即为本公开所提供的非瞬时计算机可读存储介质。其中,存储器存储有可由至少一个处理器执行的指令,以使至少一个处理器执行本公开所提供的刀闸分合状态确定方法。本公开的非瞬时计算机可读存储介质存储计算机指令,该计算机指令用于使计算机执行本公开所提供的刀闸分合状态确定方法。The memory 502 is a non-transitory computer-readable storage medium provided in the present disclosure. Wherein, the memory stores instructions executable by at least one processor, so that at least one processor executes the method for determining the opening and closing state of the knife switch provided in the present disclosure. The non-transitory computer-readable storage medium of the present disclosure stores computer instructions, and the computer instructions are used to make the computer execute the method for determining the opening and closing state of the knife switch provided in the present disclosure.
存储器502作为一种非瞬时计算机可读存储介质,可设置为存储非瞬时软件程序、非瞬时计算机可执行程序以及模块,如本公开实施例中的刀闸分合状态确定方法对应的程序指令/模块(例如,附图8所示的获取模块401、提取模块402、比较模块403和确定模块404)。处理器501通过运行存储在存储器502中的非瞬时软件程序、指令以及模块,从而执行服务器的各种功能应用以及数据处理,即实现上述方法实施例中的刀闸分合状态确定方法。The memory 502, as a non-transitory computer-readable storage medium, can be configured to store non-transitory software programs, non-transitory computer-executable programs and modules, such as program instructions/ modules (for example, the acquisition module 401, the extraction module 402, the comparison module 403 and the determination module 404 shown in FIG. 8). The processor 501 executes various functional applications and data processing of the server by running non-transient software programs, instructions and modules stored in the memory 502, that is, implements the method for determining the opening and closing state of the switch in the above method embodiments.
同时,本实施例还提供一种计算机产品,当该计算机产品中的指令由电子设备的处理器执行时,使得电子设备能够执行上述实施例的刀闸分合状态确定方法。At the same time, this embodiment also provides a computer product. When the instructions in the computer product are executed by the processor of the electronic device, the electronic device can execute the method for determining the opening and closing state of the knife switch in the above embodiment.
本领域技术人员在考虑说明书及实践这里公开的发明后,将容易想到本公开实施例的其它实施方案。本公开旨在涵盖本公开实施例的任何变型、用途或者适应性变化,这些变型、用途或者适应性变化遵循本公开实施例的一般性原理并包括本公开实施例未公开的本技术领域中的公知常识或惯用技术手段。说明书和实施例仅被视为示例性的。Other implementations of the disclosed embodiments will be readily apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. The present disclosure is intended to cover any modification, use or adaptation of the embodiments of the present disclosure. These modifications, uses or adaptations follow the general principles of the embodiments of the present disclosure and include those in the technical field not disclosed by the embodiments of the present disclosure. Common knowledge or common technical means. The specification and examples are to be considered as illustrative only.
应当理解的是,本公开实施例并不局限于上面已经描述并在附图中示出的精确结构,并且可以在不脱离其范围进行各种修改和改变。本公开实施例的范围仅由所附的权利要求书来限制。It should be understood that the embodiments of the present disclosure are not limited to the precise structures that have been described above and shown in the accompanying drawings, and various modifications and changes may be made without departing from the scope thereof. The scope of the disclosed embodiments is limited only by the appended claims.

Claims (14)

  1. 一种刀闸分合状态确定方法,包括:A method for determining the opening and closing state of a knife switch, comprising:
    获取刀闸监控图像;所述刀闸监控图像为摄像装置根据刀闸控制装置发送的图像发送指令拍摄刀闸监控区域生成并发送的;所述图像发送指令为所述刀闸控制装置在控制刀闸闭合或断开的预设时间段内生成的;Obtain the knife gate monitoring image; the knife gate monitoring image is generated and sent by the camera device according to the image sending instruction sent by the knife gate control device to shoot the knife gate monitoring area; the image sending instruction is that the knife gate control device is controlling the knife Generated within a preset period of time when the gate is closed or opened;
    提取所述刀闸监控图像中多个预设区域的图像特征;所述多个预设区域至少包括刀闸处于合位状态时刀闸所处的合位位置区域和刀闸处于分位状态时刀闸所处的分位位置区域;Extracting the image features of a plurality of preset areas in the monitor image of the knife switch; the multiple preset areas at least include the closed position area where the knife switch is in the closed position and the closed position area when the knife switch is in the split state The sub-position area where the knife switch is located;
    将所述刀闸监控图像中各所述预设区域的图像特征与预设刀闸模板图像对应预设区域的图像特征进行结构相似性比较,其中,所述预设刀闸模板图像为预先拍摄的刀闸处于合位状态时的合位模板图像和刀闸处于分位状态时的分位模板图像;所述合位模板图像包括:存在刀闸的合位位置区域和不存在刀闸的分位位置区域;所述分位模板图像包括不存在刀闸的合位位置区域和存在刀闸的分位位置区域;Comparing the image features of each preset area in the knife gate monitoring image with the image features of the preset knife gate template image corresponding to the preset area for structural similarity, wherein the preset knife gate template image is a pre-shot The closing template image when the knife switch is in the closed position and the sub-position template image when the knife switch is in the sub-position state; the closing template image includes: the closing position area where there is a knife switch and the sub-position area where there is no knife switch Bit position area; the sub-position template image includes a position area where there is no knife switch and a bit position area where there is a knife switch;
    根据结构相似性比较的结果确定刀闸分合状态。According to the result of structural similarity comparison, the opening and closing state of the knife switch is determined.
  2. 根据权利要求1所述的方法,其中,所述提取所述刀闸监控图像中多个预设区域的图像特征,包括:The method according to claim 1, wherein said extracting image features of a plurality of preset areas in said knife gate monitoring image comprises:
    获取所述预设刀闸模板图像中各所述预设区域在所述预设刀闸模板图像中的坐标范围;Obtain the coordinate range of each preset area in the preset knife gate template image in the preset knife gate template image;
    根据各所述坐标范围提取所述刀闸监控图像中对应预设区域的图像特征。Image features corresponding to preset areas in the knife gate monitoring image are extracted according to each of the coordinate ranges.
  3. 根据权利要求1所述的方法,其中,所述将所述刀闸监控图像中各所述预设区域的图像特征与预设刀闸模板图像对应预设区域的图像特征进行结构相似性比较,包括:The method according to claim 1, wherein the structural similarity comparison is performed between the image features of each preset area in the knife gate monitoring image and the image features of the preset knife gate template image corresponding to the preset area, include:
    将所述刀闸监控图像中的合位位置区域分别与所述合位模板图像中的合位位置区域以及所述分位模板图像中的合位位置区域进行结构相似性比较,以确定合位位置区域比较结果;Comparing the closing position area in the knife gate monitoring image with the closing position area in the closing template image and the closing position area in the sub-position template image respectively to determine the closing position location area comparison results;
    将所述刀闸监控图像中的分位位置区域分别与所述合位模板图像中的分位位置区域以及所述分位模板图像中的分位位置区域进行结构相似性比较,以确定分位位置区域比较结果。Structural similarity comparisons are performed between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image and the quantile position area in the quantile template image to determine the quantile position Location area comparison results.
  4. 根据权利要求3所述的方法,其中,所述将所述刀闸监控图像中的合位位置区域分别与所述合位模板图像中的合位位置区域以及所述分位模板图像中的合位位置区域进行结构相似性比较,以确定合位位置区域比较结果,包括:The method according to claim 3, wherein said combining the closing position area in the knife gate monitoring image with the closing position area in the closing template image and the closing position area in the dividing template image respectively Structural similarity comparison of zygomatic location regions to determine the comparison results of zygomatic location regions, including:
    若刀闸监控图像中的合位位置区域与所述合位模板图像中的合位位置区域之间的结构相似性大于刀闸监控图像中的合位位置区域与所述分位模板图像中的合位位置区域之间的结构相似性,则确定合位位置区域比较结果为合位位置区域存在刀闸;If the structural similarity between the closing position area in the knife gate monitoring image and the closing position area in the closing template image is greater than the closing position area in the knife gate monitoring image and the dividing template image, If there is structural similarity between the closing position areas, it is determined that the comparison result of the closing position areas is that there is a knife gate in the closing position areas;
    若刀闸监控图像中的合位位置区域与所述合位模板图像中的合位位置区域之间的结构相似性小于刀闸监控图像中的合位位置区域与所述分位模板图像中的合位位置区域之间的结构相似性,则确定合位位置区域比较结果为合位位置区域不存在刀闸。If the structural similarity between the closing position area in the knife gate monitoring image and the closing position area in the closing template image is smaller than the closing position area in the knife gate monitoring image and the dividing template image, If the structural similarity between the closing position areas is determined, the comparison result of the closing position areas is determined to be that there is no knife gate in the closing position areas.
  5. 根据权利要求4所述的方法,其中,所述将所述刀闸监控图像中的分位位置区域分别与所述合位模板图像中的分位位置区域以及所述分位模板图像中的分位位置区域进行结构相似性比较,以确定分位位置区域比较结果,包括:The method according to claim 4, wherein said combining the grading position area in the knife gate monitoring image with the grading position area in the closing template image and the grading position area in the grading template image respectively Structural similarity comparison of the quantile position area to determine the quantile position area comparison results, including:
    若刀闸监控图像中的分位位置区域与所述合位模板图像中的分位位置区域之间的结构相似性大于刀闸监控图像中的分位位置区域与所述分位模板图像中的分位位置区域之间的结构相似性,则确定分位位置 区域比较结果为分位位置区域不存在刀闸;If the structural similarity between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image is greater than the fractional position area in the knife gate monitoring image and the quantizing template image If the structural similarity between the quantile position areas is determined, the comparison result of the quantile position areas is determined to be that there is no knife gate in the quantile position areas;
    若刀闸监控图像中的分位位置区域与所述合位模板图像中的分位位置区域之间的结构相似性小于刀闸监控图像中的分位位置区域与所述分位模板图像中的分位位置区域之间的结构相似性,则确定分位位置区域比较结果为分位位置区域存在刀闸。If the structural similarity between the quantile position area in the knife gate monitoring image and the quantile position area in the closing template image is smaller than the fractional position area in the knife gate monitoring image and the quantizing template image If the structural similarity between the quantile position areas is determined, the comparison result of the quantile position areas is determined to be that there is a knife gate in the quantile position area.
  6. 根据权利要求5所述的方法,其中,所述根据结构相似性比较的结果确定刀闸分合状态,包括:The method according to claim 5, wherein said determining the opening and closing state of the knife switch according to the result of the structural similarity comparison comprises:
    若合位位置区域比较结果为合位位置区域存在刀闸,分位位置区域比较结果为分位位置区域不存在刀闸,则确定刀闸状态为处于合位状态;If the comparison result of the closing position area is that there is a knife switch in the closing position area, and the comparison result of the minute position area is that there is no knife switch in the closing position area, then it is determined that the knife switch state is in the closing state;
    若合位位置区域比较结果为合位位置区域不存在刀闸,分位位置区域比较结果为分位位置区域存在刀闸,则确定刀闸状态为处于分位状态;If the comparison result of the close position area is that there is no knife switch in the close position area, and the comparison result of the split position area is that there is a knife switch in the split position area, then it is determined that the knife switch state is in the split state;
    若合位位置区域比较结果为合位位置区域不存在刀闸,分位位置区域比较结果为分位位置区域不存在刀闸,则确定刀闸状态为处于非分位且非合位状态。If the comparison result of the closing position area is that there is no knife switch in the closing position area, and the comparison result of the closing position area is that there is no knife switch in the closing position area, then it is determined that the knife switch state is in a non-separating and non-closing state.
  7. 根据权利要求1至6任一项所述的方法,其中,所述提取所述刀闸监控图像中多个预设区域的图像特征之前,还包括:The method according to any one of claims 1 to 6, wherein, before extracting the image features of a plurality of preset areas in the knife gate monitoring image, further comprising:
    提取所述刀闸监控图像的图像特征和预设刀闸模板图像的图像特征;Extracting the image features of the monitor image of the knife gate and the image features of the preset knife gate template image;
    将所述刀闸监控图像的图像特征与预设刀闸模板图像的图像特征进行匹配,以生成多个图像特征对;Matching the image features of the knife gate monitoring image with the image features of the preset knife gate template image to generate a plurality of image feature pairs;
    根据所述多个图像特征对和预设的投影变换算法确定所述刀闸监控图像与所述预设刀闸模板图像之间的变换矩阵;determining a transformation matrix between the knife gate monitoring image and the preset knife gate template image according to the plurality of image feature pairs and a preset projection transformation algorithm;
    根据所述变换矩阵对所述刀闸监控图像进行矫正,以使矫正后的刀闸监控图像与预设刀闸模板图像对齐。The knife gate monitoring image is corrected according to the transformation matrix, so that the corrected knife gate monitoring image is aligned with a preset knife gate template image.
  8. 根据权利要求7所述的方法,其中,所述根据所述多个图像特征对和预设的投影变换算法确定所述刀闸监控图像与所述预设刀闸模板图像之间的变换矩阵,包括:The method according to claim 7, wherein the transformation matrix between the knife gate monitoring image and the preset knife gate template image is determined according to the plurality of image feature pairs and a preset projection transformation algorithm, include:
    判断所述多个图像特征对数量是否大于或等于预设阈值;judging whether the number of image feature pairs is greater than or equal to a preset threshold;
    若确定所述多个图像特征对数量大于或等于预设阈值,则根据所述多个图像特征对和预设的投影变换算法确定所述刀闸监控图像与所述预设刀闸模板图像之间的变换矩阵。If it is determined that the number of the multiple image feature pairs is greater than or equal to the preset threshold, then determine the difference between the knife gate monitoring image and the preset knife gate template image according to the multiple image feature pairs and the preset projection transformation algorithm. Transformation matrix between.
  9. 根据权利要求7所述的方法,其中,所述根据所述变换矩阵对所述刀闸监控图像进行矫正,以使矫正后的刀闸监控图像与预设刀闸模板图像对齐,包括:The method according to claim 7, wherein the correcting the knife gate monitoring image according to the transformation matrix so that the corrected knife gate monitoring image is aligned with the preset knife gate template image comprises:
    根据所述变换矩阵对所述刀闸监控图像进行仿射或投影变换,以使仿射或投影变换后的刀闸监控图像与预设刀闸模板图像对齐。Affine or projective transformation is performed on the knife gate monitoring image according to the transformation matrix, so that the knife gate monitoring image after the affine or projective transformation is aligned with the preset knife gate template image.
  10. 根据权利要求1所述的方法,其中,所述根据结构相似性比较的结果确定刀闸分合状态之后,还包括:The method according to claim 1, wherein, after determining the opening and closing state of the knife switch according to the result of the structural similarity comparison, further comprising:
    向所述刀闸控制装置发送刀闸分合状态,以使所述刀闸控制装置根据所述刀闸分合状态和传感器反馈的刀闸运行信息二次确定刀闸分合状态。Sending the opening and closing state of the knife switch to the control device of the knife switch, so that the control device of the knife switch determines the opening and closing state of the knife switch for a second time according to the opening and closing state of the knife switch and the operation information of the knife switch fed back by the sensor.
  11. 一种刀闸分合状态确定装置,包括:A device for determining the opening and closing state of a knife switch, comprising:
    获取模块,设置为获取刀闸监控图像;所述刀闸监控图像为摄像装置根据刀闸控制装置发送的图像发送指令拍摄刀闸监控区域生成并发送的;所述图像发送指令为所述刀闸控制装置在控制刀闸闭合或断开的预设时间段内生成的;The acquisition module is configured to acquire the knife gate monitoring image; the knife gate monitoring image is generated and sent by the camera device according to the image sending instruction sent by the knife gate control device to capture the knife gate monitoring area; the image sending instruction is the knife gate Generated by the control device within the preset time period for controlling the closing or opening of the knife switch;
    提取模块,设置为提取所述刀闸监控图像中多个预设区域的图像特征;所述多个预设区域至少包括刀闸处于合位状态时刀闸所处的合位位 置区域和刀闸处于分位状态时刀闸所处的分位位置区域;The extraction module is configured to extract the image features of multiple preset areas in the knife switch monitoring image; the multiple preset areas include at least the closed position area where the knife switch is in the closed state and the knife switch The divisional position area where the knife switch is located when it is in the divisional state;
    比较模块,设置为将所述刀闸监控图像中各所述预设区域的图像特征与预设刀闸模板图像对应预设区域的图像特征进行结构相似性比较,其中,所述预设刀闸模板图像为预先拍摄的刀闸处于合位状态时的合位模板图像和刀闸处于分位状态时的分位模板图像;所述合位模板图像包括:存在刀闸的合位位置区域和不存在刀闸的分位位置区域;所述分位模板图像包括:不存在刀闸的合位位置区域和存在刀闸的分位位置区域;The comparison module is configured to perform structural similarity comparison between the image features of each preset area in the knife gate monitoring image and the image features of the preset knife gate template image corresponding to the preset area, wherein the preset knife gate The template image is the closing template image taken in advance when the knife switch is in the closed position and the sub-position template image when the knife switch is in the sub-position state; There is a sub-position area of a knife switch; the sub-position template image includes: a closing position area without a knife switch and a sub-position area with a knife switch;
    确定模块,设置为根据结构相似性比较的结果确定刀闸分合状态。The determination module is configured to determine the opening and closing state of the knife switch according to the result of the structural similarity comparison.
  12. 一种电子设备,包括:处理器,以及与所述处理器通信连接的存储器;An electronic device, comprising: a processor, and a memory communicatively connected to the processor;
    所述存储器存储计算机执行指令;the memory stores computer-executable instructions;
    所述处理器执行所述存储器存储的计算机执行指令,以实现如权利要求1至10任一项所述的刀闸分合状态确定方法。The processor executes the computer-executed instructions stored in the memory, so as to realize the method for determining the opening and closing state of the knife switch according to any one of claims 1 to 10.
  13. 一种计算机可读存储介质,所述计算机可读存储介质中存储有计算机执行指令,所述计算机执行指令被处理器执行时用于实现如权利要求1至10任一项所述的刀闸分合状态确定方法。A computer-readable storage medium, wherein computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, they are used to realize the knife-gate separation according to any one of claims 1 to 10 A method for determining the state of fit.
  14. 一种计算机程序产品,包括计算机程序,该计算机程序被处理器执行时实现权利要求1至10任一项所述的刀闸分合状态确定方法。A computer program product, including a computer program, when the computer program is executed by a processor, the method for determining the opening and closing state of a switch according to any one of claims 1 to 10 is realized.
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