Lightweight instrument automatic identification system
By using a lightweight instrument automatic identification system to collect and identify dashboard data in real time, the problem of not being able to know the dashboard display parameters in real time is solved, enabling real-time data acquisition and remote transmission, and supporting enterprise management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TSINGHUA UNIVERSITY
- Filing Date
- 2023-02-20
- Publication Date
- 2026-06-02
Smart Images
Figure CN116109810B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of image processing technology, and in particular to a lightweight automatic instrument recognition system. Background Technology
[0002] In the field of mechanical engineering, instrument panels are generally used to display performance parameters of machinery during use, providing users with a basis for control operations. However, due to limitations in human energy, memory, and analytical abilities, control operations can generally only be performed based on the parameters currently displayed on the instrument panel. It is impossible to collect and understand information such as the overall usage status, fatigue level, and malfunctions of the machinery based solely on the displayed parameters, thus limiting the applicability of the instrument panel's parameters. Summary of the Invention
[0003] This invention aims to at least partially solve one of the technical problems in related technologies. Therefore, the objective of this invention is to propose a lightweight automatic instrument identification system that can collect and identify data displayed on the instrument panel in real time, thereby achieving real-time acquisition of the data displayed on the instrument panel and facilitating timely monitoring of the machine's operating status.
[0004] To achieve the above objectives, embodiments of the present invention propose a lightweight automatic instrument identification system, comprising:
[0005] The acquisition unit includes an instrument image field acquisition device, which is used to acquire instrument images in real time.
[0006] The processing unit includes a front-end module, an instrument preprocessing module, an instrument alignment processing module, and an instrument recognition module, which are used to process the instrument image to identify the instrument data in the instrument image.
[0007] The transmission unit includes a transmission module and an instrument data module, used to remotely transmit the instrument data identified in the instrument image to the database of the management department;
[0008] The operation and maintenance unit is used to provide remote operation and maintenance services for the acquisition unit, the processing unit and the transmission unit.
[0009] The lightweight instrument automatic identification system according to an embodiment of the present invention can realize the real-time acquisition and automatic identification of data displayed on the instrument panel, thereby realizing the real-time acquisition, identification, transmission and remote operation and maintenance of data displayed on the instrument panel, providing data support and information services for modern enterprise management.
[0010] In addition, the lightweight instrument automatic identification system described above may also have the following additional technical features:
[0011] According to one embodiment of the present invention, the instrument image field acquisition device is a lightweight camera device, which is fixed within a preset range around the lightweight instrument and is used to acquire images of the instrument panel embedded in the front end of the engineering vehicle's operating console in real time to obtain the corresponding instrument image.
[0012] According to one embodiment of the present invention, the front-end module is connected to the instrument image field acquisition device and is used to receive and store the instrument image, wherein the front-end module includes the user interface and system setting parameters of the instrument automatic identification system;
[0013] The instrument preprocessing module is connected to the front-end module and is used to perform environmental recognition, instrument noise reduction, and light reflection preprocessing on the instrument image to obtain the instrument U1 image.
[0014] The instrument alignment processing module is connected to the instrument preprocessing module and is used to perform instrument selection, positioning, and image stabilization processing based on the instrument U1 image obtained by the instrument preprocessing module to obtain the instrument U2 image.
[0015] The instrument recognition module is connected to the instrument alignment processing module and is used to identify the instrument pointer reading based on the instrument U2 image obtained by the instrument alignment processing module to obtain the instrument data.
[0016] According to one embodiment of the present invention, the instrument preprocessing module includes an environment recognition submodule, an instrument noise reduction submodule, and a light reflection filtering submodule;
[0017] The environmental recognition submodule is connected to the front-end module and is used to process the environment of the image acquired by the instrument image field acquisition device, determine the target instrument, and obtain the instrument U11 image.
[0018] The instrument denoising submodule is connected to the environment recognition submodule and is used to denoise the instrument U11 image to obtain the instrument U12 image.
[0019] The light reflection filtering submodule is connected to the instrument denoising submodule and is used to perform specular reflection filtering on the instrument U12 image to obtain the instrument U1 image.
[0020] The environment recognition submodule is specifically used for:
[0021] The target instrument is determined from the image acquired by the instrument image field acquisition device using a first preset method to obtain the instrument U11 image. The first preset method includes SIFT feature point matching and information filtering methods, but is not limited to these methods. The target instrument is determined from the first image acquired by the instrument acquisition unit to obtain the instrument U11 image.
[0022] The instrument noise reduction submodule is specifically used for:
[0023] The second preset method is used to denoise the instrument U11 image. The second preset method includes Gaussian filtering algorithm, median filtering algorithm, NLM algorithm, bilateral filtering algorithm, nonlocal mean filter, WLS filter, Sobel edge-preserving filtering algorithm, but is not limited to these methods. The third acquired image of the instrument is denoised.
[0024] The light reflection filtering submodule is specifically used for:
[0025] The instrument U12 image is subjected to specular reflection filtering using a third preset method. The third preset method includes polarizing filter CPL algorithm, layered filtering method, and adaptive histogram equalization algorithm, but is not limited to these methods. The instrument's third acquired image is subjected to specular reflection filtering.
[0026] Using an improved dark channel algorithm (see...) Figure 2 The process includes: dark channel processing, white balance processing, global illumination processing, image erosion and dilation processing, dark channel smoothing correction, and image reflection elimination. It also performs specular reflection filtering on the instrument U12 image, but is not limited to these methods. The instrument alignment processing module includes an instrument positioning submodule, an instrument alignment submodule, and an instrument anti-shake submodule.
[0027] The instrument positioning submodule is connected to the instrument preprocessing module and is used to select one from multiple instrument U1 images and determine the position of the target instrument panel in the selected instrument U1 image to obtain the instrument U21 image;
[0028] The instrument alignment submodule is connected to the instrument positioning submodule and is used to rotate, translate, and adjust the instrument U21 image to obtain the instrument U22 corrected image.
[0029] The instrument anti-shake submodule is connected to the instrument alignment submodule and is used to perform spatial angle transformation on the instrument U22 correction image to correct the image blur caused by the shaking of the instrument image field acquisition device and obtain the instrument U2 image.
[0030] The instrument positioning submodule is specifically used for:
[0031] The position of the instrument panel in the selected instrument U1 image is determined by the fourth preset method to obtain the instrument U21 image. The fourth preset method includes circle detection algorithm, Hough gradient method, Hough ellipse detection algorithm, and contour detection algorithm, but is not limited to these methods. The position of the instrument panel in the selected instrument first U1 image is determined to obtain the U21 image.
[0032] The instrument alignment submodule is specifically used for:
[0033] The instrument U21 image is rotated, translated, and adjusted using the fifth preset method to obtain the instrument U22 rectified image. The fifth preset method includes coordinate transformation method, checkerboard calibration method, ORB feature extraction algorithm, and feature point matching method, but is not limited to these methods. The selected instrument first U21 image is rotated, translated, and adjusted to obtain the U22 image.
[0034] The instrument anti-shake submodule is specifically used for:
[0035] The instrument U22 is image stabilized using a sixth preset method to eliminate image jitter and improve the robustness of the recognition algorithm. The image captured by the camera with a certain degree of shaking is transformed by spatial angle to correct the blur caused by camera jitter, thus obtaining the instrument U2 image. The sixth preset method includes, but is not limited to, inverse filtering, Wiener filtering, and Lucy-Richardson algorithm. The U22 corrected image is then transformed by spatial angle to correct the blur caused by camera jitter, thus obtaining the U23 image.
[0036] The instrument identification module includes an instrument center identification submodule, an instrument pointer identification submodule, and an instrument measurement identification submodule:
[0037] The instrument center recognition submodule is connected to the instrument alignment technology module and is used to identify the shape and center of the instrument panel in the instrument U2 image;
[0038] The instrument pointer recognition submodule is connected to the instrument center recognition submodule and is used to identify the pointer, pointer axis and pointer position of the instrument panel based on the shape and center of the instrument panel in the instrument U2 image, so as to obtain the pointer position information;
[0039] The instrument measurement recognition submodule is connected to the instrument pointer recognition submodule and is used to recognize the instrument pointer reading based on the pointer's position information to obtain the instrument data.
[0040] The instrument center identification submodule is specifically used for:
[0041] The shape and center of the instrument in the instrument U2 image are identified using a seventh preset method. The seventh preset method includes, but is not limited to, roundness calculation method, region growing method, Hough circle detection method, connected region dual descent method, and template matching expansion method.
[0042] The shape of the instrument panel includes one of the following: circular, oval, triangular, quadrilateral, or polygonal. The color of the pointer in the instrument panel includes one of the following: red, black, gray, or green, but is not limited to these shapes and colors.
[0043] According to one embodiment of the present invention, the transmission module is connected to the instrument identification module and is used to remotely transmit the instrument data identified in the instrument image;
[0044] The instrument data module is connected to the transmission module and remotely transmits the instrument data, instrument name, and data acquisition time identified in the instrument image to the management department's database through the selected data format and interaction protocol.
[0045] According to one embodiment of the present invention, the operation and maintenance unit connects the user end of the lightweight instrument and the operation and maintenance department of the lightweight instrument, and remotely accesses the instrument image field acquisition device, the front-end module, the instrument preprocessing module, the instrument alignment processing module, the instrument identification module, the transmission module, and the instrument data module via the network to remotely monitor, remotely set parameters, remotely reset the system, and remotely update the functions of the acquisition unit, the processing unit, and the transmission unit.
[0046] According to one embodiment of the present invention, the system further includes a system processor, which is a lightweight Raspberry Pi or other lightweight microprocessor. The acquisition unit, the processing unit, the transmission unit, and the operation and maintenance unit are all located in the system processor and implement the system algorithm.
[0047] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description
[0048] Figure 1 This is an overall block diagram of the lightweight instrument automatic identification system of the present invention;
[0049] Figure 2 This is a flowchart of the image reflection elimination method of the present invention;
[0050] Figure 3 This is a configuration diagram of the lightweight instrument automatic identification system of the present invention;
[0051] Figure 4 This is the architecture diagram of the lightweight instrument automatic identification system of the present invention. Detailed Implementation
[0052] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.
[0053] The following is a reference appendix. Figure 1-4 This invention describes a lightweight automatic instrument identification system according to an embodiment of the present invention.
[0054] Figure 1 This is an overall block diagram of the lightweight instrument automatic identification system of the present invention.
[0055] like Figure 1 As shown, the lightweight instrument automatic identification device 10 includes a data acquisition unit 11, a processing unit 12, a transmission unit 13, an operation and maintenance unit 14, and a system processor 15.
[0056] Specifically, such as system configuration Figure 3 As shown, the acquisition unit 11 includes an instrument image field acquisition device 110 for real-time acquisition of instrument images; the processing unit 12 includes a front-end module 121, an instrument preprocessing module 122, an instrument alignment processing module 123, and an instrument recognition module 124 for processing the instrument images to identify the instrument data in the images; the transmission unit 13 includes a transmission module 131 and an instrument data module 132 for transmitting the instrument data identified in the instrument images and storing the remotely transmitted instrument data in the management department's database; the operation and maintenance unit 14 is used to provide remote operation and maintenance services for the acquisition unit 11, processing unit 12, and transmission unit 13, and specific functions may include remote monitoring, remote parameter setting, remote system reset, and remote system update. It also includes a system processor 15 for executing the various functional modules of the lightweight instrument automatic recognition system 10. The system processor 15, using a lightweight Raspberry Pi or other lightweight processor, integrates the acquisition unit 11, processing unit 12, transmission unit 13, operation and maintenance unit 14, and all functions and algorithms of the instrument reading recognition system, and is used to execute the various functional modules of the lightweight instrument automatic recognition system 10.
[0057] Among them, the aforementioned acquisition unit 11 is Figure 4 The camera device in the hardware layer shown; the aforementioned processing unit 12 is... Figure 4 The algorithm shown automatically identifies the data; the aforementioned transmission unit 13 is... Figure 4 The instrument data transmission of the application layer shown; the above-mentioned operation and maintenance unit 14 is... Figure 4The network operation and maintenance shown is illustrated. The aforementioned operation and maintenance unit 14 connects the user end of the lightweight instrument and the operation and maintenance department of the lightweight instrument via a network, enabling remote monitoring, remote parameter setting, remote system reset, and remote system update of the functions of the acquisition unit 11, processing unit 12, and transmission unit 13. The aforementioned system processor 15 is... Figure 4 The Raspberry Pi or other processor device in the hardware layer shown executes the functions of each module of the lightweight instrument automatic identification system 10 and the instrument reading identification algorithm.
[0058] Specifically, the aforementioned acquisition unit includes an instrument image field acquisition device 110, which is used to acquire images embedded in the front panel of the engineering operation console in real time to obtain the corresponding instrument images.
[0059] Furthermore, the instrument image acquisition device 110 is a lightweight camera device, fixed within a preset range around the lightweight instrument, used to acquire images of the instrument panel embedded in the front of the engineering vehicle's control panel in real time, and obtain the corresponding instrument image. The acquisition unit 11 transmits the acquired instrument panel image to the processing unit 12, and the processing unit 12 processes the received instrument panel image.
[0060] In this embodiment, the processing unit 12 specifically includes a front-end module 121, an instrument preprocessing module 122, an instrument alignment processing module 123, and an instrument identification module 124.
[0061] Specifically, the aforementioned front-end module 121 is connected to the instrument image field acquisition device 110, and is used to receive and store instrument images, as well as the user interface and system setting parameters of the lightweight instrument automatic recognition system 10; the aforementioned instrument preprocessing module 122 is connected to the front-end module 121, and is used to receive instrument images and preprocess them, including environmental recognition, instrument noise reduction, and light reflection preprocessing, to obtain the instrument U1 image; the aforementioned instrument alignment processing module 123 is connected to the instrument preprocessing module 122, and is used to perform instrument selection, positioning, alignment, and image stabilization processing based on the instrument U1 image to obtain the instrument U2 image; the aforementioned instrument recognition module 124 is connected to the instrument alignment processing module 123, and is used to perform instrument center recognition, pointer recognition, and reading recognition based on the instrument U2 image to obtain instrument data. The transmission unit 13 is connected to the instrument identification module 124 and is used to send instrument data to the database 132 of the management department; the above-mentioned operation and maintenance unit 14 is connected to the acquisition device 11, the processing unit 12, and the transmission unit 13 and is used to implement remote monitoring, remote parameter setting, remote system reset, and remote system update of the lightweight instrument automatic identification system.
[0062] It should be noted that the aforementioned processing unit 12 includes a front-end module 121 and an instrument preprocessing module 122. The front-end module 121 is used to receive instrument images and configure the environment, parameter settings, camera interface protocol, and instrument recognition software interface protocol for recognizing and processing the received instrument images. Therefore, the compilation language environment can be obtained through the front-end module 121.
[0063] Specifically, the instrument preprocessing module 122 includes an environment recognition submodule 1221, an instrument noise reduction submodule 1222, and a light reflection filtering submodule 1223.
[0064] Specifically, the aforementioned environmental recognition submodule 1221 is connected to the front-end module 121 and is used to process the environment of the image acquired by the instrument image field acquisition device 110, determine the target instrument from the instrument image, and obtain the instrument U11 image; the aforementioned instrument denoising submodule 1222 is connected to the environmental recognition submodule 1221 and is used to denoise the instrument U11 image to obtain the instrument U12 image; the aforementioned illumination reflection filtering submodule 1223 is connected to the instrument denoising submodule 1222 and is used to perform specular reflection filtering on the instrument U12 image to obtain the instrument U1 image. It should be noted that the execution order of the aforementioned instrument environmental recognition submodule 1221, instrument denoising submodule 1222, and illumination reflection filtering submodule 1223 can be adjusted.
[0065] It should be noted that the aforementioned environmental recognition submodule 1221 uses a first preset method to determine the target instrument from the image acquired by the instrument image field acquisition device 110, obtaining the instrument U11 image. The first preset method is the SIFT feature point matching method and / or information filtering method, but is not limited to these methods. The instrument denoising submodule 1222 includes a noise filtering submodule and a specular reflection filtering submodule. The noise filtering submodule uses a second preset method to denoise the instrument U11 image, obtaining the instrument U12 image. The second preset method is a Gaussian filtering algorithm, a median filtering algorithm, an NLM algorithm, a bilateral filtering algorithm, a nonlocal mean filter, a WLS filter, and a Sobel edge-preserving filtering algorithm, but is not limited to these methods. The illumination reflection filtering submodule 1223 uses a third preset method to perform light reflection filtering processing on the instrument U12 image, obtaining the instrument U1 image. The third preset method is a polarizing filter CPL algorithm, a layered filtering method, an adaptive histogram equalization algorithm, and an improved dark channel algorithm (see [link to relevant documentation]). Figure 2 However, it is not limited to these methods. Dark channel algorithms include: dark channel processing, white balance processing, global illumination processing, image erosion and dilation processing, dark channel smoothing correction, and image reflection elimination.
[0066] Specifically, since instrument panels are typically embedded in the front of the control panel, they are surrounded by multiple instrument and non-instrument components. To identify specific information on the instrument panel (e.g., instrument gauges, pointers, scales), it is first necessary to distinguish between the instrument and non-instrument components. Therefore, the instrument preprocessing module 122 can identify the area containing the instrument image from the received instrument image, and the environment recognition submodule 1221 can filter out the non-instrument environmental components from the instrument image, resulting in an U11 image containing only the instrument components.
[0067] Furthermore, since both the instrument image acquisition device 110 and the instrument panel are typically located inside the engineering vehicle, and the engineering vehicle often causes significant interference to the normal operation of the instrument image acquisition device 110 during operation (e.g., dust generated by the engineering vehicle), the instrument noise reduction submodule 1222 can be used to process the instrument U11 image to obtain the instrument U12 image. When the instrument image acquisition device 110 acquires instrument images, the effects of light reflection or mirroring may cause blurring or ghosting in the acquired instrument images. Therefore, the light reflection filtering submodule 1223 can be used to process the instrument U12 image to obtain the instrument U1 image.
[0068] Therefore, the instrument preprocessing module 122 can process the received instrument image to obtain an instrument U1 image that contains only the instrument part and is free from interference and reflection.
[0069] Furthermore, the aforementioned instrument alignment processing module 123 specifically includes an instrument positioning submodule 1231, an instrument alignment submodule 1232, and an instrument anti-shake submodule 1233.
[0070] Specifically, the instrument positioning submodule 1231 is connected to the instrument preprocessing module 122, and is used to select one from multiple instrument U1 images and determine the position of the target instrument panel in the selected instrument U1 image to obtain the instrument U21 image. The instrument alignment submodule 1232 is connected to the instrument positioning submodule 1231, and is used to rotate, translate, and adjust the instrument U21 image to obtain the corrected instrument U22 image. The instrument anti-shake submodule 1233 is connected to the instrument alignment submodule 1232, and is used to perform spatial angle transformation on the corrected instrument U22 image to correct the image blur caused by the shaking of the instrument image acquisition device, and obtain the instrument U2 image. The execution order of the instrument positioning submodule 1231, instrument alignment submodule 1232, and instrument anti-shake submodule 1233 can be adjusted.
[0071] It should be noted that the instrument positioning submodule 1231 above: uses the fourth preset method to determine the position of the instrument panel in the selected instrument U1 image to obtain the instrument U21 image. The fourth preset method is a circle detection algorithm, Hough gradient method, Hough ellipse detection algorithm, and contour detection algorithm, but is not limited to these methods; the instrument alignment submodule 1232 above: uses the fifth preset method to rotate, translate, and adjust the instrument U21 image to obtain the instrument U22 corrected image. The fifth preset method is a coordinate transformation method, a checkerboard calibration method, an ORB feature extraction algorithm, and a feature... The method of matching points is not limited to these methods; the above-mentioned instrument anti-shake submodule 1233: uses the sixth preset method to eliminate the shaking of the instrument image of instrument U22, improve the robustness of the recognition algorithm, and performs spatial angle transformation on the image captured by the camera with a certain degree of shaking to obtain the instrument U2 image. The sixth preset method is the inverse filtering method, Wiener filtering method, Lucy-Richardson algorithm, but is not limited to these methods. The spatial angle transformation is performed on the U22 corrected image to correct the blurring of the image caused by the camera shaking to obtain the U23 image.
[0072] Specifically, in actual use, the instrument image acquisition device 110 is often not directly aligned with the instrument panel, resulting in the received instrument image not being aligned correctly. Furthermore, multiple instrument panels may appear in the acquired image, leading to multiple instrument panel images within the same image. Therefore, the instrument alignment processing module 123 can be used to select and process these images.
[0073] In this embodiment, the instrument positioning submodule 1231 can select the desired instrument panel image from images containing multiple instrument panels and determine its specific position. Then, the instrument alignment submodule 1232 can perform operations such as rotation, translation, and adjustment on the selected instrument panel image to align it. Furthermore, since the instrument image acquisition device 110 may experience some degree of shaking during actual use, causing a certain degree of spatial angular displacement in the acquired image, the instrument anti-shake submodule 1233 can correct this.
[0074] Therefore, the instrument U1 image can be processed by the instrument alignment processing module 123 to locate the required instrument panel image, perform image correction operation on it, and repair the spatial angle offset of the image caused by the jitter of the instrument image field acquisition device 110, thereby obtaining the instrument U2 image that can be recognized by the instrument recognition module 124.
[0075] Furthermore, the aforementioned instrument identification module 124 specifically includes an instrument center identification submodule 1241, an instrument pointer identification submodule 1242, and an instrument measurement identification submodule 1243.
[0076] Specifically, the aforementioned instrument center recognition submodule 1241 is connected to the instrument alignment processing module 123, and is used to recognize the shape and center of the instrument panel in the instrument U2 image to obtain the instrument U31 image; the aforementioned instrument pointer recognition submodule 1242 is connected to the instrument center recognition submodule 1241, and is used to recognize the pointer, pointer axis, and pointer position information of the instrument panel based on the shape and center of the instrument panel in the instrument U31 image to obtain the instrument U32 image; the aforementioned instrument measurement recognition submodule 1243 is connected to the instrument pointer recognition submodule 1242, and is used to recognize the instrument pointer reading based on the pointer position information to obtain instrument data. The execution order of the aforementioned instrument center recognition submodule 1241, instrument pointer recognition submodule 1242, and instrument measurement recognition submodule 1243 can be adjusted.
[0077] It should be noted that the aforementioned instrument center recognition submodule 1241 is specifically used to: identify the shape and center of the instrument in the instrument U2 image using a seventh preset method. The seventh preset method includes, but is not limited to, roundness calculation, region growing, Hough circle detection, connected component dual descent, and template matching expansion methods. The shape of the aforementioned instrument panel is one of a circle, ellipse, triangle, quadrilateral, or polygon, and the color of the pointer in the aforementioned instrument panel is one of red, black, gray, or green, but is not limited to these shapes and colors. The aforementioned instrument pointer recognition submodule 1242 can binarize or multi-value the instrument image to display the instrument pointer and instrument readability, and eliminate the influence of pointer color, thereby obtaining the pointer's position information using pointer recognition technology. The aforementioned instrument measurement recognition module 1243 can use instrument scale measurement recognition technology, such as recognition through image pixel ratio relationships or recognition using the instrument pointer rotation angle, but is not limited to these methods, to obtain instrument data.
[0078] Therefore, specific instrument data on the instrument panel can be obtained through the instrument recognition module 124.
[0079] Furthermore, the instrument identification module 124 transmits the identified data to the transmission unit 13, and the transmission unit 13 transmits the identified instrument data from the instrument panel to the management department's database.
[0080] In one embodiment of the present invention, the transmission module 131 is connected to the instrument identification module 124 for remotely transmitting the instrument data identified in the instrument image; the instrument data module 132 is connected to the transmission module 131 for remotely transmitting the instrument data, instrument name, and data acquisition time identified in the instrument image to the database of the management department through the selected data format and interaction protocol.
[0081] In one embodiment of the present invention, the operation and maintenance unit 14 connects the user end of the lightweight instrument and the operation and maintenance department of the lightweight instrument. It remotely accesses the instrument image field acquisition device 110, the front-end module 121, the instrument preprocessing module 122, the instrument alignment processing module 123, the instrument recognition module 124, the transmission module 131, and the instrument data module 132 via the network, and performs remote monitoring, remote parameter setting, remote system reset, and remote system update of the functions of the acquisition unit 11, the processing unit 12, and the transmission unit 13.
[0082] The operation and maintenance unit 14 is used to provide remote operation and maintenance services for the acquisition unit 11, processing unit 12 and transmission unit 13. Its specific functions include remote monitoring, remote parameter setting, remote system reset and remote system update.
[0083] The system processor 15, using a lightweight Raspberry Pi or other lightweight microprocessor, integrates the acquisition unit 11, processing unit 12, transmission unit 13, operation and maintenance unit 14, and all functions and algorithms of the instrument reading recognition system. It is used to execute the functional modules of the lightweight instrument automatic recognition system 10, and to acquire instrument images and process and implement the instrument system reading recognition algorithm.
[0084] In summary, the lightweight instrument automatic identification system of this invention can collect and automatically identify the data displayed on the instrument panel in real time, thereby realizing the real-time acquisition, identification, transmission, and remote operation and maintenance of the data displayed on the instrument panel, providing data support and information services for modern enterprise management.
[0085] It should be noted that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.
[0086] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.
[0087] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.
[0088] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.
[0089] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.
[0090] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.
[0091] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.
Claims
1. A lightweight instrument automatic identification system, characterized in that, include: The acquisition unit includes an instrument image field acquisition device, which is used to acquire instrument images in real time. The processing unit includes a front-end module, an instrument preprocessing module, an instrument alignment processing module, and an instrument recognition module, which are used to process the instrument image to identify the instrument data in the instrument image. The transmission unit includes a transmission module and an instrument data module, used to remotely transmit the instrument data identified in the instrument image to the database of the management department; An operation and maintenance unit is used to provide remote operation and maintenance services for the acquisition unit, the processing unit and the transmission unit. The front-end module is connected to the instrument image field acquisition device and is used to receive and store the instrument image. The instrument preprocessing module is connected to the front-end module and is used to perform environmental recognition, instrument noise reduction, and light reflection preprocessing on the instrument image to obtain the instrument U1 image. The instrument preprocessing module includes an environment recognition submodule, an instrument noise reduction submodule, and a light reflection filtering submodule; The environmental recognition submodule is connected to the front-end module and is used to process the environment of the image acquired by the instrument image field acquisition device, determine the target instrument, and obtain the instrument U11 image. The instrument denoising submodule is connected to the environment recognition submodule and is used to denoise the instrument U11 image to obtain the instrument U12 image. The light reflection filtering submodule is connected to the instrument denoising submodule and is used to perform specular reflection filtering on the instrument U12 image to obtain the instrument U1 image. The light reflection filtering submodule is specifically used for: The image of instrument U12 is subjected to specular reflection filtering using an improved dark channel algorithm; The improved dark channel algorithm includes: performing dark channel processing on the instrument U12 image, performing RGB statistics based on the dark channel processing result, performing white balance processing, image swelling and decay processing, and global illumination processing based on the RGB statistics result, performing dark channel smoothing correction on the image swelling and decay processing result, and performing image reflection elimination based on the dark channel smoothing correction result, global illumination processing result, and white balance processing result to obtain the instrument U1 image.
2. The lightweight instrument automatic identification system as described in claim 1, characterized in that, The instrument image field acquisition device is a lightweight camera device, fixed within a preset range around the lightweight instrument, used to acquire images of the instrument panel embedded in the front of the engineering vehicle's control panel in real time, and obtain the corresponding instrument image.
3. The lightweight instrument automatic identification system according to claim 1, characterized in that, The front-end module includes the user interface and system setting parameters of the instrument automatic identification system; The instrument alignment processing module is connected to the instrument preprocessing module and is used to perform instrument selection, positioning, and image stabilization processing based on the instrument U1 image obtained by the instrument preprocessing module to obtain the instrument U2 image. The instrument recognition module is connected to the instrument alignment processing module and is used to identify the instrument pointer reading based on the instrument U2 image obtained by the instrument alignment processing module to obtain the instrument data.
4. The lightweight instrument automatic identification system as described in claim 3, characterized in that, The environment recognition submodule is specifically used for: The target instrument is determined from the image acquired by the instrument image field acquisition device using a first preset method to obtain the instrument U11 image. The first preset method includes SIFT feature point matching method and information filtering method. The instrument noise reduction submodule is specifically used for: The image of instrument U11 is denoised using a second preset method, wherein the second preset method includes Gaussian filtering algorithm, median filtering algorithm, NLM algorithm, bilateral filtering algorithm, nonlocal mean filter, WLS filter, and Sobel edge-preserving filtering algorithm. The light reflection filtering submodule is also used for: The instrument U12 image is subjected to specular reflection filtering using algorithms other than the dark channel algorithm in the third preset method. The other algorithms in the third preset method include polarizing filter CPL algorithm, layered filtering method, and adaptive histogram equalization algorithm. The instrument alignment processing module also includes an instrument positioning submodule, an instrument alignment submodule, and an instrument anti-shake submodule: The instrument positioning submodule is connected to the instrument preprocessing module and is used to select one from multiple instrument U1 images and determine the position of the target instrument panel in the selected instrument U1 image to obtain the instrument U21 image; The instrument alignment submodule is connected to the instrument positioning submodule and is used to rotate, translate, and adjust the instrument U21 image to obtain the instrument U22 corrected image. The instrument anti-shake submodule is connected to the instrument alignment submodule and is used to perform spatial angle transformation on the instrument U22 correction image to obtain the instrument U2 image; The instrument positioning submodule is specifically used for: The position of the instrument panel in the selected instrument U1 image is determined by the fourth preset method to obtain the instrument U21 image. The fourth preset method includes a circle detection algorithm, Hough gradient method, Hough ellipse detection algorithm, and contour detection algorithm. The instrument alignment submodule is specifically used for: The instrument U21 image is rotated, translated, and adjusted using the fifth preset method to obtain the instrument U22 rectified image. The fifth preset method includes a coordinate transformation method, a checkerboard calibration method, an ORB feature extraction algorithm, and a feature point matching method. The instrument anti-shake submodule is specifically used for: The U22 corrected image is transformed by spatial angle using a sixth preset method to obtain the instrument U2 image. The sixth preset method includes an inverse filtering method, a Wiener filtering method, and a Lucy-Richardson algorithm. The instrument identification module includes an instrument center identification submodule, an instrument pointer identification submodule, and an instrument measurement identification submodule: The instrument center recognition submodule is connected to the instrument anti-shake submodule and is used to identify the shape and center of the instrument panel in the instrument U2 image; The instrument pointer recognition submodule is connected to the instrument center recognition submodule and is used to identify the pointer, pointer axis and pointer position of the instrument panel based on the shape and center of the instrument panel in the instrument U2 image, so as to obtain the pointer position information; The instrument measurement recognition submodule is connected to the instrument pointer recognition submodule and is used to recognize the instrument pointer reading based on the pointer's position information to obtain the instrument data. The instrument center identification submodule is specifically used for: The shape and center of the instrument in the instrument U2 image are identified using a seventh preset method, wherein the seventh preset method includes a roundness calculation method, a region growing method, a Hough circle detection method, a connected region dual descent method, and a template matching expansion method; The shape of the instrument panel includes one of the following: circular, oval, triangular, quadrilateral, and polygonal. The color of the pointer in the instrument panel includes one of the following: red, black, gray, and green.
5. The lightweight instrument automatic identification system as described in claim 1, characterized in that, The transmission module is connected to the instrument recognition module and is used to remotely transmit the instrument data recognized in the instrument image; The instrument data module is connected to the transmission module and remotely transmits the instrument data, instrument name, and data acquisition time identified in the instrument image to the management department's database through the selected data format and interaction protocol.
6. The lightweight instrument automatic identification system as described in claim 1, characterized in that, The operation and maintenance unit connects the user end of the lightweight instrument and the operation and maintenance department of the lightweight instrument. It remotely accesses the instrument image field acquisition device, the front-end module, the instrument preprocessing module, the instrument alignment processing module, the instrument identification module, the transmission module, and the instrument data module via the network to remotely monitor, remotely set parameters, remotely reset the system, and remotely update the functions of the acquisition unit, the processing unit, and the transmission unit.
7. The lightweight instrument automatic identification system according to claim 1, characterized in that, The system also includes a system processor, which is a lightweight Raspberry Pi or other lightweight microprocessor. The acquisition unit, the processing unit, the transmission unit, and the operation and maintenance unit are all located in the system processor, implementing the system's algorithm.