Automobile overall dimension rapid screening system and method based on artificial intelligence

Abstract

The invention, which belongs to the technical field of automobile detection, discloses an artificial intelligence-based automobile overall dimension rapid screening system and method, the system comprises an image acquisition module, an artificial intelligence identification module, a dimension calculation module, a space generation module and a screening judgment module. The vehicle type is automatically recognized and the vehicle overall dimension is calculated through artificial intelligence, a deep learning model and an image processing algorithm are utilized, the vehicle type is more accurately recognized and the vehicle overall dimension is more accurately measured, measurement errors caused by human factors are reduced, meanwhile, the vehicle overall dimension can be screened according to a preset standard, and the detection accuracy is improved. The legality and effectiveness of the detection result are ensured, and the problems of low precision and low efficiency of the existing automobile overall dimension detection are effectively solved. The whole system can complete the screening of the overall dimension of the vehicle in a short time, and is suitable for scenes needing rapid detection, such as an automobile production line and a motor vehicle annual inspection station.

Description

Technical Field

[0001] The present invention belongs to the technical field of automobile detection, and in particular relates to a system and method for rapid screening of automobile external dimensions based on artificial intelligence. Background Art

[0002] In automobile production, sales, and annual inspections, measuring vehicle dimensions is a crucial step in ensuring compliance with relevant standards. Traditional vehicle dimension testing methods typically require manual measurement of the vehicle's length, width, and height using measuring tools. This method is not only inefficient but also susceptible to human error, resulting in inaccurate measurements and a time-consuming and labor-intensive process.

[0003] During annual vehicle inspections, vehicle dimensions are often measured dynamically (i.e., the vehicle drives through the measurement area at a specified speed, and radar or light curtain equipment scans the vehicle to obtain dimensional data). This significantly increases errors, and vehicles with unqualified data require continuous re-inspection to meet relevant national standards. This results in a significant waste of manpower and time. Summary of the Invention

[0004] The purpose of the present invention is to provide a system and method for rapid screening of automobile external dimensions based on artificial intelligence, so as to solve the problems of low accuracy and low efficiency in existing automobile external dimension detection.

[0005] The technical solution adopted in the present invention is as follows:

[0006] An artificial intelligence-based rapid screening system for automobile exterior dimensions, comprising an image acquisition module, an artificial intelligence recognition module, a dimension calculation module, a space generation module, and a screening and judgment module;

[0007] An image acquisition module, configured to capture an image of the vehicle under test and information about the relative position between the vehicle under test and the image acquisition module. The image acquisition module includes a high-definition camera and a laser ranging unit. The high-definition camera is configured to capture images of the vehicle's appearance from both a side and top view angles. The laser ranging unit is configured to measure the straight-line distance between the vehicle under test and the image acquisition module.

[0008] an artificial intelligence recognition module, communicatively connected to the image acquisition module, configured to receive the vehicle image and relative position information acquired by the image acquisition module, identify the vehicle type using a deep learning model based on the acquired vehicle image and relative position information, and obtain an allowable range of external dimensions of the corresponding vehicle type according to preset standards;

[0009] a size calculation module, communicatively connected to the image acquisition module, configured to receive the vehicle image and relative position information acquired by the image acquisition module, and calculate the actual outer dimensions of the vehicle based on the acquired vehicle image and relative position information;

[0010] a space generation module, in communication with the artificial intelligence recognition module, for generating a two-dimensional U-shaped space model according to an allowable range of the vehicle's outer dimensions, wherein the inner and outer interfaces of the two-dimensional U-shaped space model correspond to the lower and upper limits of the vehicle's outer dimensions, respectively;

[0011] The screening and judgment module is communicatively connected to the size calculation module and the space generation module, and is used to compare and analyze the actual outer dimensions of the vehicle output by the size calculation module with the two-dimensional U-shaped space model generated by the space generation module to determine whether the actual outer dimensions of the vehicle are within the allowable range of the outer dimensions.

[0012] Furthermore, the high-definition camera and the laser ranging unit of the image acquisition module adopt an integrated design, and the laser ranging unit is located in the same position as the lens component in the high-definition camera.

[0013] A method for quickly screening automobile external dimensions based on artificial intelligence comprises the following steps:

[0014] Step S1, vehicle image and relative position information acquisition: The high-definition camera and laser ranging unit in the image acquisition module are used to acquire the appearance image of the vehicle under test from both side and top view angles, and simultaneously obtain the relative position information between the vehicle under test and the image acquisition module;

[0015] Step S2, vehicle type identification: using the deep learning model in the artificial intelligence recognition module to analyze the collected vehicle images, identify the vehicle type, and obtain the allowable range of the outer dimensions of the corresponding vehicle type according to the preset standards;

[0016] Step S3, vehicle outer dimensions calculation: The dimension calculation module uses the vehicle image captured by the high-definition camera and the distance data measured by the laser ranging unit to establish a mapping relationship between the image coordinate system and the world coordinate system, determine the ratio of the image pixel size to the actual physical size, and use an image processing algorithm to calculate the actual outer dimensions of the vehicle;

[0017] Step S4, generating a U-shaped limit space: Based on the allowable range of the vehicle's outer dimensions, a corresponding two-dimensional U-shaped space model is generated using a space generation module, wherein the inner and outer interfaces of the two-dimensional U-shaped space model correspond to the lower and upper limits of the vehicle's outer dimensions, respectively;

[0018] Step S5, eligibility screening: The calculated actual outer dimensions of the vehicle are compared with the generated U-shaped space model by the screening judgment module to determine whether the actual outer dimensions of the vehicle are completely located between the inner and outer interfaces of the U-shaped space. If the actual outer dimensions of the vehicle meet the conditions of not exceeding both the inner and outer interfaces, the screening is determined to have passed; if the actual outer dimensions of the vehicle exceed either the inner or outer interfaces, the screening is determined to have failed.

[0019] Step S6, data storage and feedback: the screening results and data are stored in the database for subsequent query and analysis.

[0020] Furthermore, the calculation process of the actual outer dimensions of the vehicle under test in step S3 is specifically as follows: the length and width two-dimensional dimensions of the imaging unit of the sensor device based on the high-definition camera are L p ×D p , the image resolution size is x L ×x D , the focal length of the camera is f, the straight-line distance measured by the laser ranging unit to the inspected vehicle is h, and the pixel size of the inspected vehicle in the image is n L ×n D , the actual size of the inspected vehicle is L×D×H;

[0021] In the top view, the actual length L of the inspected vehicle is:

[0022]

[0023] In the top view, the actual width D of the inspected vehicle is:

[0024]

[0025] In the side view, the actual height H of the inspected vehicle is:

[0026]

[0027] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0028] 1. In the present invention, artificial intelligence is used to automatically identify vehicle types and calculate vehicle dimensions, greatly reducing the workload and time of manual measurement and improving detection efficiency. In addition, by utilizing deep learning models and image processing algorithms, vehicle types can be identified and vehicle dimensions can be measured more accurately, reducing measurement errors caused by human factors. At the same time, vehicle dimensions can be screened according to preset standards to ensure the legitimacy and validity of the detection results. The entire system can complete the screening of vehicle dimensions in a short time and is suitable for scenarios requiring rapid detection, such as automobile production lines and motor vehicle annual inspection stations, effectively solving the problems of low accuracy and low efficiency in existing vehicle dimension detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be considered as limiting the scope. A person of ordinary skill in the art can also derive other relevant drawings based on these drawings without inventive effort, among which:

[0030] Figure 1 Schematic diagram of the system structure of the present invention;

[0031] Figure 2 is a flow chart of the method of the present invention;

[0032] Figure 3 This is a schematic diagram of the screening and judgment module of the present invention screening the outer dimensions based on the U-shaped space model;

[0033] Figure 4 This is a schematic diagram of the size calculation module of the present invention calculating the external dimensions of a car. DETAILED DESCRIPTION

[0034] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0035] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0036] It should be noted that reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not require further definition or explanation in subsequent drawings.

[0037] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer" and the like indicate positions or locations based on the positions shown in the accompanying drawings, or the positions or locations in which the inventive product is typically placed when in use. These terms are intended merely to simplify the description of the present invention and do not indicate or imply that the devices or components referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third," etc., are used solely to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0038] In addition, the terms "horizontal" and "vertical" do not mean that the components must be absolutely horizontal or overhanging, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", not that the structure must be completely horizontal, but can be slightly tilted.

[0039] In the description of the present invention, it should also be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention in specific contexts.

[0040] In conjunction with the instructions Figure 1 ,

[0041] An artificial intelligence-based rapid screening system for automobile exterior dimensions comprises an image acquisition module 1, an artificial intelligence recognition module 2, a dimension calculation module 3, a space generation module 4, and a screening and judgment module 5.

[0042] Image acquisition module 1, consisting of a high-definition wide-angle camera and a laser ranging unit, adopts an integrated design and is deployed on one side and top of the vehicle inspection channel. The high-definition wide-angle camera can simultaneously capture the vehicle's exterior image from both a top-down and side-view perspective, ensuring that the inspected vehicle's outline information is fully captured. The laser ranging unit is located in the same position as the lens component within the high-definition wide-angle camera. The laser ranging unit achieves high-precision distance measurement based on the precise projection of the emitted laser beam onto the surface of the vehicle's outer shell and its effective reflection. The collected vehicle appearance image and ranging data are sent in real time to the artificial intelligence recognition module 2 and the size calculation module 3 via a data transmission line or wireless network, providing data support for subsequent vehicle type identification and exterior dimension calculation.

[0043] The artificial intelligence recognition module 2 uses a deep learning model, including but not limited to target detection algorithm models such as YOLO and Faster R-CNN, to identify the collected vehicle images. The model is trained using a large amount of image data of different models during the training phase, and can accurately identify various common models, including but not limited to common models such as flatbed trucks and vans. The recognition results include the vehicle type and the allowable range of the outer dimensions of the corresponding vehicle model (mainly including upper and lower limits), which are set in accordance with relevant regulations such as the national standard GB1589-2016. The recognition results are sent to the space generation module 4 in real time via a data transmission line or wireless network to provide data support for the subsequent determination of the eligibility of the vehicle's outer dimensions.

[0044] The size calculation module 3 receives the vehicle image and ranging data transmitted by the image acquisition module 1. This module first preprocesses the acquired image, including optimization operations such as denoising, correction, and enhancement to improve image quality. Subsequently, it uses image processing algorithms, including edge detection and feature point extraction, to analyze the vehicle image. Combined with the distance data provided by the laser ranging unit, it establishes a mapping relationship between the image coordinate system and the world coordinate system, determines the ratio of the image pixel size to the actual physical size, and accurately calculates the length, width, and height of the vehicle. After the calculation is completed, the actual vehicle external dimension data is sent to the screening and judgment module 5 via a data transmission line or wireless network, providing accurate measurement results for subsequent vehicle external dimension compliance determination.

[0045] The space generation module 4 generates a corresponding two-dimensional U-shaped space model based on the upper and lower limits of the vehicle's outer dimensions provided by the artificial intelligence recognition module 2. Among them, the inner interface of the U-shaped space corresponds to the lower limit of the vehicle's outer dimensions, and the outer interface corresponds to the upper limit of the vehicle's outer dimensions. This U-shaped space model serves as a benchmark for screening the compliance of the vehicle's outer dimensions. Through intuitive spatial boundary definition, it can quickly determine whether the actual outer dimensions of the vehicle comply with the provisions of the national standard GB1589-2016. The generated results are sent to the screening and judgment module 5 via a data transmission line or a wireless network, providing a clear basis for judgment for the screening and judgment module 5.

[0046] The screening and judgment module 5 compares and analyzes the actual outer dimensions of the vehicle provided by the size calculation module 3 with the U-shaped space provided by the space generation module 4. According to the relevant provisions of GB1589-2016, the vehicle type identified by the artificial intelligence recognition module 2 is processed to eliminate the size of the rearview mirror and other detachable parts, and based on the processed vehicle size data, it is determined whether it is completely located between the inner and outer interfaces of the U-shaped space. Figure 3 If the vehicle's dimensions do not exceed the inner and outer boundaries of the U-shaped space, the vehicle passes the screening; otherwise, it fails. The screening results can be displayed in real time on the display or transmitted to relevant systems via the network for subsequent processing and data recording.

[0047] like Figure 2 As shown, a method for rapid screening of automobile external dimensions based on artificial intelligence includes the following steps:

[0048] Step S1, vehicle image and relative position information acquisition: The high-definition camera and laser ranging unit in the image acquisition module are used to acquire the appearance image of the vehicle under test from both side and top view angles, and simultaneously obtain the relative position information between the vehicle under test and the image acquisition module;

[0049] Step S2, vehicle type identification: using the pre-trained deep learning model in the artificial intelligence recognition module to analyze the collected vehicle images, identify the vehicle type, and obtain the allowable range of the outer dimensions of the corresponding vehicle type according to the national standard GB1589-2016;

[0050] Step S3, vehicle outer dimensions calculation: The dimension calculation module uses the vehicle image captured by the high-definition camera and the distance data measured by the laser ranging unit to establish a mapping relationship between the image coordinate system and the world coordinate system, determine the ratio of the image pixel size to the actual physical size, and use an image processing algorithm to calculate the actual outer dimensions of the vehicle;

[0051] Step S4, generating a U-shaped limit space: Based on the allowable range of the vehicle's outer dimensions, a corresponding two-dimensional U-shaped space model is generated using a space generation module, wherein the inner and outer interfaces of the two-dimensional U-shaped space model correspond to the lower and upper limits of the vehicle's outer dimensions, respectively;

[0052] Step S5, eligibility screening: The calculated actual outer dimensions of the vehicle are compared with the generated U-shaped space model through the screening and judgment module. After the vehicle rearview mirrors and other detachable parts are sized and eliminated according to the relevant provisions of GB1589-2016, it is determined whether the actual outer dimensions of the vehicle are completely located between the inner and outer interfaces of the U-shaped space. If the actual outer dimensions of the vehicle meet the conditions of not exceeding both the inner and outer interfaces, the screening is determined to be passed; if the actual outer dimensions of the vehicle exceed either the inner or outer interfaces, the screening is determined to be failed.

[0053] Step S6, data storage and feedback: the screening results and data are stored in the database for subsequent query and analysis. At the same time, the system can be optimized and adjusted according to the screening results to improve the accuracy and efficiency of screening.

[0054] The calculation process of the actual outer dimensions of the vehicle under test in step S3 is as follows: the dimensions of the length and width of the two-dimensional plane of the imaging unit of the sensor device based on the high-definition camera are L p ×D p , the image resolution size is x L ×x D , the focal length of the camera is f, the straight-line distance measured by the laser ranging unit to the inspected vehicle is h, and the pixel size of the inspected vehicle in the image is n L ×n D , the actual size of the inspected vehicle is L×D×H;

[0055] In the top view, the actual length L of the inspected vehicle is:

[0056]

[0057] In the top view, the actual width D of the inspected vehicle is:

[0058]

[0059] In the side view, the actual height H of the inspected vehicle is:

[0060]

[0061] like Figure 4As shown, the image information of vehicle 11 in the world coordinate system is transmitted by light 12 through the lens component 13 of the high-definition camera, and a two-dimensional image is generated in the imaging unit of the high-definition camera, namely vehicle 14 in the image coordinate system. The focal length of the camera is f, and the straight-line distance to the inspected vehicle measured by the laser ranging unit is h. For this high-definition camera, the size of its sensor device in the two-dimensional plane of the length and width of the imaging unit is L p ×D p , the image resolution size is x L ×x D , the pixel size of the inspected vehicle in the image is n L ×n D The actual size of the inspected vehicle is L×D×H.

[0062] The above are the embodiments of the present invention. The foregoing are the preferred embodiments of the present invention. If the preferred implementation methods in each preferred embodiment are not obviously self-contradictory or based on a certain preferred implementation method, each preferred implementation method can be arbitrarily superimposed and used in combination. The embodiments and the specific parameters in the embodiments are only for the purpose of clearly describing the verification process of the invention, and are not intended to limit the scope of patent protection of the present invention. The scope of patent protection of the present invention is still subject to its claims. Any equivalent structural changes made by using the contents of the description and drawings of the present invention should also be included in the scope of protection of the present invention.

Claims

1. A rapid screening system for automobile dimensions based on artificial intelligence, characterized in that: It includes image acquisition module, artificial intelligence recognition module, size calculation module, space generation module and screening judgment module; An image acquisition module, configured to capture an image of the vehicle under test and information about the relative position between the vehicle under test and the image acquisition module. The image acquisition module includes a high-definition camera and a laser ranging unit. The high-definition camera is configured to capture images of the vehicle's appearance from both a side and top view angles. The laser ranging unit is configured to measure the straight-line distance between the vehicle under test and the image acquisition module. an artificial intelligence recognition module, communicatively connected to the image acquisition module, configured to receive the vehicle image and relative position information acquired by the image acquisition module, identify the vehicle type using a deep learning model based on the acquired vehicle image and relative position information, and obtain an allowable range of external dimensions of the corresponding vehicle type according to preset standards; a size calculation module, communicatively connected to the image acquisition module, configured to receive the vehicle image and relative position information acquired by the image acquisition module, and calculate the actual outer dimensions of the vehicle based on the acquired vehicle image and relative position information; a space generation module, in communication with the artificial intelligence recognition module, for generating a two-dimensional U-shaped space model according to an allowable range of the vehicle's outer dimensions, wherein the inner and outer interfaces of the two-dimensional U-shaped space model correspond to the lower and upper limits of the vehicle's outer dimensions, respectively; The screening and judgment module is communicatively connected to the size calculation module and the space generation module, and is used to compare and analyze the actual outer dimensions of the vehicle output by the size calculation module with the two-dimensional U-shaped space model generated by the space generation module to determine whether the actual outer dimensions of the vehicle are within the allowable range of the outer dimensions.

2. The artificial intelligence-based rapid screening system for automobile dimensions according to claim 1, characterized in that: The high-definition camera and the laser distance measuring unit of the image acquisition module adopt an integrated design, and the laser distance measuring unit is located in the same position as the lens component in the high-definition camera.

3. A rapid screening method for automobile external dimensions based on artificial intelligence, characterized in that: The following steps are involved: Step S1, vehicle image and relative position information acquisition: The high-definition camera and laser ranging unit in the image acquisition module are used to acquire the appearance image of the vehicle under test from both side and top view angles, and simultaneously obtain the relative position information between the vehicle under test and the image acquisition module; Step S2, vehicle type identification: using the deep learning model in the artificial intelligence recognition module to analyze the collected vehicle images, identify the vehicle type, and obtain the allowable range of the outer dimensions of the corresponding vehicle type according to the preset standards; Step S3, vehicle outer dimensions calculation: The dimension calculation module uses the vehicle image captured by the high-definition camera and the distance data measured by the laser ranging unit to establish a mapping relationship between the image coordinate system and the world coordinate system, determine the ratio of the image pixel size to the actual physical size, and use an image processing algorithm to calculate the actual outer dimensions of the vehicle; Step S4, U-shaped limit space production: Based on the allowable range of vehicle outer dimensions, use the space generation module to generate right The inner and outer interfaces of the two-dimensional U-shaped space model correspond to the vehicle The lower and upper limits of the outer dimensions; Step S5, eligibility screening: The calculated actual outer dimensions of the vehicle are compared with the generated U-shaped space model by the screening judgment module to determine whether the actual outer dimensions of the vehicle are completely located between the inner and outer interfaces of the U-shaped space. If the actual outer dimensions of the vehicle meet the conditions of not exceeding both the inner and outer interfaces, the screening is determined to have passed; if the actual outer dimensions of the vehicle exceed either the inner or outer interfaces, the screening is determined to have failed. Step S6, data storage and feedback: the screening results and data are stored in the database for subsequent query and analysis.

4. The method for rapid screening of automobile dimensions based on artificial intelligence according to claim 3, characterized in that: The calculation process of the actual outer dimensions of the vehicle under test in step S3 is as follows: the length and width of the two-dimensional plane of the imaging unit of the sensor device based on the high-definition camera is L p ×D p , the image resolution size is x L ×x D , the focal length of the camera is f, the straight-line distance measured by the laser ranging unit to the inspected vehicle is h, and the pixel size of the inspected vehicle in the image is n L ×n D , the actual size of the inspected vehicle is L×D×H; In the top view, the actual length L of the inspected vehicle is: In the top view, the actual width D of the inspected vehicle is: In the side view, the actual height H of the inspected vehicle is:

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