CN113947760A - Detection method and device for green channel vehicle - Google Patents
Detection method and device for green channel vehicle Download PDFInfo
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- CN113947760A CN113947760A CN202111559776.3A CN202111559776A CN113947760A CN 113947760 A CN113947760 A CN 113947760A CN 202111559776 A CN202111559776 A CN 202111559776A CN 113947760 A CN113947760 A CN 113947760A
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- G—PHYSICS
- G08—SIGNALLING
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
- G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
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Abstract
The invention provides a method and a device for detecting a green channel vehicle, wherein the method comprises the following steps: receiving a gray-scale image of a detected vehicle acquired by a ray light source and a ray imager; acquiring the real-time speed of the detected vehicle, and correcting the gray image of the detected vehicle according to the real-time speed; and acquiring a vehicle detection result according to the corrected gray level image. According to the invention, the gray-scale image and the real-time speed of the detected vehicle are obtained, the gray-scale image of the detected vehicle is corrected according to the real-time speed of the detected vehicle, and the vehicle detection result of the detected vehicle is obtained according to the corrected gray-scale image, so that the accuracy of green channel vehicle detection is effectively improved.
Description
Technical Field
The invention relates to the technical field of green channel detection, in particular to a method and a device for detecting a green channel vehicle.
Background
The green channel refers to a channel for road transportation of fresh agricultural products, and vehicles driving from the green channel are green channel vehicles. In 2011, the three-department commissions jointly issued "urgent notice on policy of further perfecting green channel for transporting fresh agricultural products" stipulates "all highways 'green vehicles' free passage". According to the latest 'green channel' policy issued by the department of transportation in 2021, fresh agricultural products loaded on a green channel vehicle account for more than 80% of the approved loading mass or carriage volume of the vehicle, and behaviors such as mixed loading with non-fresh agricultural products and the like do not exist. After the scheme is operated, the development of agriculture is greatly promoted, the production and living level of farmers is improved, the production and living environment in rural areas is improved, and the development of economic society is promoted.
However, in the process of policy implementation, illegal merchants fake green passage vehicles also appear, and a small amount of fresh agricultural products are placed on the surface layer or the outermost side of the vehicles, and other goods which do not belong to a 'green passage' list are mainly carried in the inner layer of the vehicles, so that road tolls are paid for less or not paid. If the detection is carried out one by one, the detection difficulty is greatly increased, the workload of detection personnel is increased, and the smoothness of the highway is influenced.
Currently, various green channel automatic vehicle detection systems have been developed in succession. The method for detecting the volume rate of fresh agricultural products in a carriage by utilizing the strong penetrating power of X rays, gamma rays and the like is a commonly used detection method for detecting whether counterfeit, mixed loading and the like exist. However, the accuracy of the detection result obtained by the detection method is not high, because the ray detector performs detection in a line scanning manner, in the process, the gray image of the detected vehicle is formed by splicing a row of pixels in a line scanning manner, and the precondition for accurate splicing is that the ray detector and the detected vehicle move relatively at a specified speed at a constant speed. In consideration of the problems of safety and investment cost, the ray detector is usually set to be fixed, and the detected vehicle moves forward at a constant speed. However, in practical processes, the vehicle speed often deviates from the set speed value, resulting in overall or local stretching and compression deformation of the finally spliced images to different degrees, which greatly affects the accuracy of the vehicle detection result.
Therefore, how to improve the accuracy of green channel vehicle detection in the prior art is an important issue to be urgently solved in the field of green channel vehicle detection.
Disclosure of Invention
The invention provides a method and a device for detecting a green channel vehicle, which are used for solving the defect that the accuracy of a detection result cannot be ensured in the green channel vehicle detection in the prior art so as to improve the accuracy of the green channel vehicle detection.
In one aspect, the present invention provides a method for detecting a green channel vehicle, including: receiving a gray-scale image of a detected vehicle acquired by a ray light source and a ray imager; acquiring the real-time speed of the detected vehicle, and correcting the gray image of the detected vehicle according to the real-time speed; and acquiring a vehicle detection result according to the corrected gray level image.
Further, the correcting the gray-scale image of the detected vehicle according to the real-time speed comprises: determining the compression rate of the gray level image of the detected vehicle according to the real-time speed and the preset speed; determining the correction length and the correction width of the gray image according to the compression rate of the gray image to obtain the gray image corrected by the detected vehicle; and the compression rate is the ratio of the real-time speed to the preset speed.
Further, the acquiring a vehicle detection result according to the corrected grayscale image includes: and inputting the corrected gray level image into an automatic recognition algorithm model, processing the corrected gray level image by the automatic recognition algorithm model, and acquiring the vehicle detection result according to the judgment standard of the green channel vehicle.
Further, the obtaining a vehicle detection result according to the corrected gray-scale image further includes: making a corresponding decision according to the vehicle detection result; if the detected vehicle meets the standard of the green channel vehicle, the vehicle passes through freely; and if the detected vehicle does not meet the standard of the green channel vehicle, the vehicle charges for passing.
Further, the receiving of the grayscale image of the detected vehicle acquired by the radiation light source and the radiation imager previously includes: according to the attribute information of the detected vehicle, calling a vehicle appearance recognition algorithm, and driving a first optical camera to acquire the position information of the detected vehicle in real time; and when the position information of the detected vehicle shows that the cab of the detected vehicle passes through the irradiation area of the ray light source, starting the ray light source and the ray imager.
Further, the attribute information of the detected vehicle includes: the license plate number, the brand model and the overall dimension of the detected vehicle.
Further, the method for detecting a green channel vehicle provided by the invention further comprises the following steps: and acquiring and storing the attribute information of the detected vehicle according to the license plate number of the detected vehicle acquired by the second optical camera, the basic information of the detected vehicle uploaded by the mobile equipment terminal and the corresponding record information.
In a second aspect, the present invention further provides a detection apparatus for a green channel vehicle, including: the image receiving module is used for receiving the gray level image of the detected vehicle acquired by the ray light source and the ray imager; the image correction module is used for acquiring the real-time speed of the detected vehicle and correcting the gray image of the detected vehicle according to the real-time speed; and the result acquisition module is used for acquiring a vehicle detection result according to the corrected gray level image.
In a third aspect, the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method for detecting a green channel vehicle as described in any one of the above.
In a fourth aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method for detecting a green channel vehicle as described in any of the above.
According to the detection method of the green channel vehicle, the grayscale image of the detected vehicle is obtained through the ray light source and the ray imager, the real-time speed of the detected vehicle in the detection process is collected through the speedometer, the database system server corrects the received grayscale image of the detected vehicle according to the obtained real-time speed of the detected vehicle to obtain the corrected grayscale image, and the vehicle detection result of the detected vehicle is obtained according to the corrected grayscale image.
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In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a green channel vehicle detection method provided by the present invention;
FIG. 2 is a schematic diagram of a gray scale image correction process for a detected vehicle according to the present invention;
FIG. 3 is a schematic illustration of a vehicle under inspection according to the present invention;
FIG. 4 is a flow chart of vehicle detection provided by the present invention;
FIG. 5 is a schematic structural diagram of a monitoring device for a green channel vehicle according to the present invention;
FIG. 6 is a schematic diagram of a system of a green channel vehicle detection device provided by the present invention;
fig. 7 is a schematic structural diagram of an electronic device provided in the present invention.
Reference numerals: 02: a mobile device end; 03: a database system server; 04: a source of radiation; 05: a radiation imager; 06: a first optical camera; 07: a velocimeter; 08: and a second optical camera.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 shows a flow chart of a green channel vehicle detection method provided by the invention. As shown in fig. 1, the method includes:
and S11, receiving the gray-scale image of the detected vehicle acquired by the ray light source and the ray imager.
In this step, the radiographic imaging refers to a technology of projecting a beam of rays through the cargo bed of the detected vehicle onto the array of the radiographic imager, and reproducing an image of the internal structure of the cargo bed of the detected vehicle on a computer screen through an electronic reading and computer data acquisition and analysis system, and is widely applied to the technical field of transportation and security inspection at present. The ray beam can be X-ray, gamma ray or other particles.
Grayscale images, which refer to images having only one sample color per pixel, are typically displayed as a grayscale from the darkest black to the brightest white. It is clear that grayscale images are different from black and white images, which have only two colors, and grayscale images have many levels of color depth between black and white in the field of computer imaging.
It will be appreciated that when the vehicle under test travels to the test area, at the appropriate time, the radiation source begins to emit radiation at a frequency that is transmitted through the cargo bed of the vehicle under test. Because the ray light source and the ray imager are usually integrated, direct data interaction exists between the ray light source and the ray imager, after the ray light source emits rays, the ray imager starts to receive the rays emitted by the ray light source, gray level image data of a row of detected vehicles are formed according to the absorption condition of a large amount of rays obtained when the rays scan the detected vehicles, and all the gray level image data are spliced to obtain the final gray level image of the detected vehicles. And then, forwarding the obtained gray level image of the detected vehicle to a database system server, and receiving the gray level image of the detected vehicle by the database system server for subsequent steps. There is no specific limitation on the brand and model and the dimensions of the vehicle to be detected.
And S12, acquiring the real-time speed of the detected vehicle, and correcting the gray-scale image of the detected vehicle according to the real-time speed.
In this step, it can be understood that, while the radiation light source and the radiation imager acquire the grayscale image of the detected vehicle, the velocimeter may acquire the real-time speed of the detected vehicle according to a certain acquisition frequency, and forward the acquired real-time speed data to the database system server. And after the detected vehicle completely runs through the irradiation area of the ray light source, the database system server corrects the received gray level image of the detected vehicle according to the acquired real-time speed data of the detected vehicle to obtain the corrected gray level image of the detected vehicle. The velocimeter can be a radar velocimeter or a laser velocimeter. The image correction means that the gray image is stretched or compressed according to the stretching or compression deformation degree of the gray image, so that the accurate gray image of the detected vehicle is obtained.
The reason why the database system server corrects the received gray image data of the detected vehicle is that in the actual detection work, the ray light source and the ray imager are set to be fixed in consideration of the problems of safety and cost, and on the basis, the detected vehicle needs to move forwards at a constant speed to ensure the accuracy of splicing the gray image data of the last detected vehicle. However, during the process of irradiating the cargo bed of the detected vehicle by the radiation light source, the detected vehicle may travel forward at a constant speed, and the traveling speed of the detected vehicle may always deviate from the set speed, so that the gray scale image finally obtained by the radiation imager is deformed. For example, if the speed of the detected vehicle is too fast, the final image formed by stitching a row of rays is smaller than the actual length of the detected vehicle, and the resulting grayscale image may be compressed and deformed. On the contrary, tensile deformation occurs.
In order to avoid or reduce the situations, after the database system server acquires the gray-scale image of the detected vehicle from the ray imager, the database system server corrects the gray-scale image of the detected vehicle according to the acquired real-time speed of the detected vehicle. Preferably, in order to ensure the accuracy of the acquired real-time speed, the acquisition frequency of the velocimeter acquiring the real-time speed of the detected vehicle may be set to be greater than the emission frequency of the radiation light source, that is, the data acquisition time interval of the velocimeter is smaller than the emission radiation time interval of the radiation light source.
And S13, acquiring a vehicle detection result according to the corrected gray scale image.
And on the basis of correcting the gray image of the detected vehicle in the last step, acquiring a vehicle detection result according to the corrected gray image of the detected vehicle. The vehicle detection result can be that the detected vehicle accords with the newly issued 'green channel' vehicle policy and passes free; or the user can not meet the regulation of related policies and needs to pay for passing.
In the embodiment, the grayscale image of the detected vehicle is acquired through the ray light source and the ray imager, the real-time speed of the detected vehicle in the detection process is acquired through the speedometer, the database system server corrects the received grayscale image of the detected vehicle according to the acquired real-time speed of the detected vehicle to obtain the corrected grayscale image, and the vehicle detection result of the detected vehicle is acquired according to the corrected grayscale image.
Fig. 2 shows a schematic diagram of a gray scale image correction process of a detected vehicle provided by the invention.
On the basis of the above embodiment, further, modifying the grayscale image of the detected vehicle according to the real-time speed includes: determining the compression rate of the gray image of the detected vehicle according to the real-time speed and the preset speed; determining the correction length and the correction width of the gray image according to the compression rate of the gray image to obtain the gray image corrected by the detected vehicle; wherein, the compression ratio is the ratio of the real-time speed to the preset speed.
It can be understood that, in the process of the detected vehicle receiving detection, in order to ensure the accuracy of the gray image finally spliced by the radiation imager, a speed can be preset, so that the detected vehicle can run at the preset speed. However, in the actual detection process, the actual driving speed of the detected vehicle often deviates from the preset speed to a greater or lesser extent, so that the accuracy of the gray scale image obtained by the final radiation imager is deviated. In this case, the ratio of the actual running speed of the detected vehicle to the preset speed can be calculated, the ratio is the compression ratio of the gray scale image of the detected vehicle, the length and the width of the gray scale image are further calculated according to the compression ratio, the gray scale image of the detected vehicle is corrected according to the length and the width of the gray scale image, the corrected length and the corrected width of the gray scale image are obtained, and the corrected gray scale image of the detected vehicle is obtained.
For example, as shown in the lowermost drawing in FIG. 2,the detected vehicle is at a preset speed V0Through the ray region S0The time interval of the radiation source emitting the radiation is
At this time, a normal gray image of the detected vehicle can be obtained.
In a specific embodiment, as shown in the middle graph of fig. 2, the actual running speed V of the vehicle to be detected1Greater than a predetermined speed V0Then in the same ray emission time interval
Distance of passing through
，S1Greater than S0. That is, a part of the detected vehicle will not be captured by the rays, the image obtained by the final combination of a column of rays by the ray imager will be smaller than the actual length of the detected vehicle, the obtained gray image of the detected vehicle is compressed, and the compression rate of the gray image at this time is:
. Correspondingly, the correction length is as follows:
(ii) a The correction width is:
. Wherein L is1And W1Length and width, W being numerical and W, respectively, of the gray scale image originally acquired by the radiation imager1Are equal. And correcting the gray image of the detected vehicle according to the correction length and the correction width to obtain the corrected gray image of the detected vehicle.
In another specific embodiment, as shown in the uppermost graph in fig. 2, the actual running speed of the vehicle is detectedV2Less than a predetermined speed V0Then in the same ray emission time interval
Distance of passing through
，S2Less than S0. That is, a part of the images of the detected vehicle may overlap, the image obtained by the radiation imager through the last combination of the row and column of the radiation is longer than the actual length of the detected vehicle, the obtained gray image of the detected vehicle is stretched, and the compression rate of the gray image at this time is:
. Correspondingly, the correction length is as follows:
(ii) a The correction width is:
. Wherein L is2And W2Length and width, W being numerical and W, respectively, of the gray scale image originally acquired by the radiation imager2Are equal. And correcting the gray image of the detected vehicle according to the correction length and the correction width to obtain the corrected gray image of the detected vehicle.
It should be noted that, in order to ensure the accuracy of the velocimeter for acquiring the real-time speed of the detected vehicle, the time interval of the velocimeter for acquiring the real-time speed may be set to be smaller than the ray emission time interval. If at a time interval
In the method, if n real-time speed values of the detected vehicle are acquired, V is1And/or V2The n real-time velocity values may be averaged.
In the embodiment, the compression rate of the gray-scale image of the detected vehicle is calculated according to the actual running speed of the detected vehicle and the preset speed, and the due length and width of the gray-scale image are further determined, so that the gray-scale image after the detected vehicle is corrected is obtained, the defect that the accuracy of the vehicle detection result cannot be guaranteed in the green channel vehicle detection in the prior art is overcome, and the accuracy of the green channel vehicle detection is effectively improved.
On the basis of the above embodiment, further, acquiring a vehicle detection result according to the corrected grayscale image includes: and inputting the corrected gray level image into an automatic identification algorithm model, processing the corrected gray level image by the automatic identification algorithm model, and acquiring a vehicle detection result according to the judgment standard of the green channel vehicle.
It should be noted that the judgment criteria of the green channel vehicle mainly includes three aspects: firstly, the fresh agricultural products loaded by the detected vehicle must belong to the variety range recorded in the fresh agricultural product variety catalog, and specifically comprise 128 specific varieties or categories of fresh vegetables, fresh fruits, fresh aquatic products, fresh meat, eggs and milk. Secondly, the loading of the inspected vehicle must meet the loading requirements of the whole vehicle, i.e. the vehicle enjoys the policy of 'green passage', the loaded fresh agricultural products should account for more than 80% of the approved mass or the carriage volume of the vehicle, and the fresh agricultural products are not loaded in a mixed way with the non-fresh agricultural products. Finally, the detected vehicle should legally load and transport the fresh agricultural products, that is, the vehicle cannot enjoy the policy of 'green passage' for counterfeit and illegal overload transportation of the fresh agricultural products.
It is understood that after the corrected grayscale image is obtained, the vehicle detection result of the detected vehicle is obtained according to the corrected grayscale image. Specifically, after the gray level image corrected by the detected vehicle is input into the automatic identification algorithm model, the automatic identification algorithm model processes the corrected gray level image to obtain a processing result, and the quantity of articles loaded in the cargo bucket of the detected vehicle can be known through the result. Meanwhile, the automatic identification algorithm model can obtain the mass of the agricultural products actually loaded by the detected vehicle and the volume of the compartment occupied by the loaded agricultural products according to the corrected gray level image. The variety, the quantity, the quality and the occupied carriage volume of agricultural products actually loaded by the detected vehicle are compared with relevant standards in a 'green channel' policy one by one to judge whether the detected vehicle meets the requirements of the relevant policy, so that corresponding decisions are made to obtain corresponding vehicle detection results.
In the embodiment, the gray-scale image corrected by the detected vehicle is input into the automatic identification algorithm model, the corrected gray-scale image is processed by the automatic identification algorithm model, and a corresponding vehicle detection result is obtained according to the judgment standard of the green channel vehicle, so that the accuracy of green channel vehicle detection is effectively improved.
On the basis of the above embodiment, further, a vehicle detection result is obtained according to the corrected grayscale image, and then the method further includes: making a corresponding decision according to the vehicle detection result; if the detected vehicle meets the standard of the green channel vehicle, the vehicle passes through freely; and if the detected vehicle does not meet the standard of the green channel vehicle, the vehicle charges for passing.
It can be understood that the vehicle detection result of the detected vehicle is obtained according to the modified gray-scale image, and after the corresponding vehicle detection result is obtained, a further decision can be made according to the vehicle detection result. Specifically, if the vehicle detection result shows that the detected vehicle meets the judgment standard of the green channel vehicle, a decision for letting the detected vehicle pass through freely is made; and if the vehicle detection result shows that the detected vehicle does not accord with the judgment standard of the green channel vehicle, making a decision that the detected vehicle cannot pass through for free, wherein the vehicle can pass through after the vehicle needs to be charged.
In the embodiment, the corresponding decision is made according to the vehicle detection result of the detected vehicle, so that the vehicles meeting the green channel vehicle standard can pass freely, and powerful guarantee is provided for promoting the circulation of fresh agricultural products.
FIG. 3 shows a schematic diagram of the detection of a detected vehicle provided by the present invention.
On the basis of the above embodiment, further, receiving a grayscale image of the detected vehicle acquired by the radiation light source and the radiation imager, before further comprising: according to the attribute information of the detected vehicle, calling a vehicle appearance recognition algorithm, and driving a first optical camera to acquire the position information of the detected vehicle in real time; and when the position information of the detected vehicle shows that the cab of the detected vehicle has completely passed through the irradiation area of the ray light source, starting the ray light source and the ray imager.
Before the radiation light source and the radiation imager are started, the database system server drives the first optical camera to acquire the position information of the detected vehicle in real time according to the pre-stored attribute information of the detected vehicle, the first optical camera can accurately track the cab of the detected vehicle in real time according to a vehicle appearance recognition algorithm called by the database system server, when the cab of the detected vehicle completely runs through the irradiation area of the radiation light source, the first optical camera forwards the information to the database system server, the database system server receives the information and then sends a signal to start the radiation light source and the radiation imager according to the information, and the radiation light source and the radiation imager can start to work only after receiving the starting signal. The attribute information of the detected vehicle comprises the license plate number, the brand model and the overall dimension of the detected vehicle.
In addition, the radiation source and the radiation imager are activated when the cab of the vehicle under test has completely passed the irradiation area of the radiation source. As shown in fig. 3, if the cab of the detected vehicle does not or does not completely pass through the radiation area of the radiation light source, the radiation light source starts to emit radiation to irradiate the detected vehicle, which inevitably causes the radiation to irradiate the driver and other related personnel, but the radiation of the X-ray, the gamma-ray or other radiation in the figure can cause harm to the body of the driver and other related personnel due to the radioactivity.
Considering that, this embodiment is followed tracks the real-time position of being detected the vehicle through first optical camera, discerns the driver's cabin of being detected the vehicle through vehicle outward appearance recognition algorithm, and when the driver's cabin of being detected the vehicle was completely driven through the ray region of ray light source, the side sends the signal and starts ray light source and ray imager, has avoided X ray radioactivity to relevant personnel's physical injury in the vehicle testing process, has improved the security of green passageway vehicle testing process.
On the basis of the above embodiment, further, the method for detecting a green channel vehicle provided by the present invention further includes: and acquiring and storing attribute information of the detected vehicle according to the license plate number of the detected vehicle acquired by the second optical camera, the basic information of the detected vehicle uploaded by the mobile equipment terminal and the corresponding record information.
It can be understood that the driver holds the mobile device, and before reaching the detection area of the green channel vehicle, the driver submits the basic vehicle information to the database system server through the mobile device, and the database system server receives and stores the basic vehicle information.
Meanwhile, the second optical camera acquires the image of the green channel vehicle detection area in real time, and when the detected vehicle runs to the detection area, the license plate number of the detected vehicle is recognized through an OCR recognition algorithm loaded by the second optical camera, so that the license plate number of the detected vehicle is acquired. Among them, the ocr (optical Character recognition) recognition algorithm, i.e., optical Character recognition, is a process of determining a shape by detecting a dark or light pattern, so that a Character recognition method translates the shape into a computer word. If the license plate number of the detected vehicle is partially shielded and cannot be identified, manual operation is needed for detection, or the subsequent steps are executed after the license plate number of the detected vehicle is determined.
In addition, the relevant departments performing vehicle detection usually have recorded information. The database system server obtains attribute information of the detected vehicle, such as the license plate number, the external dimension and the brand model of the detected vehicle, according to the license plate number of the detected vehicle, the basic vehicle information submitted by the driver through the mobile equipment terminal and the corresponding filing information stored by the vehicle detection department, which are obtained by the second optical camera, and stores the attribute information of the detected vehicle, so that when the detected vehicle runs to the detection area, the database system server calls the attribute information of the detected vehicle.
In the embodiment, the attribute information of the detected vehicle is acquired through the acquired license plate number of the detected vehicle, the basic information of the detected vehicle and the corresponding filing information, and is stored so as to be convenient for calling and using, thereby effectively improving the detection efficiency of the green channel vehicle.
FIG. 4 illustrates a flow chart for vehicle detection provided by the present invention. As shown in fig. 4, before entering the green channel vehicle detection area, the driver of the detected vehicle submits basic vehicle information including, but not limited to, the license plate number, the driving license number, the type and quality of the fresh agricultural products loaded, etc. of the detected vehicle through the mobile device, and stores the basic vehicle information in the database system server.
When the detected vehicle runs into the detection area of the green channel vehicle, the second optical camera identifies and acquires the license plate number of the detected vehicle through an OCR (optical character recognition) algorithm loaded by the second optical camera, and transmits the license plate number to the database system server, and the database system server inquires whether the information related to the vehicle is stored in a database of the detected vehicle through the license plate number information, namely, inquires whether a driver of the detected vehicle uploads the basic information of the vehicle in advance. If the database system server stores the basic information of the vehicle, all the information is integrated to obtain the attribute information of the detected vehicle. And calling a corresponding vehicle appearance recognition algorithm according to the attribute information of the detected vehicle, sending a signal to start a first optical camera to track the cab of the detected vehicle in real time, sending the signal to a database system server by the first optical camera when the cab of the detected vehicle completely passes through the irradiation area of the ray light source, and sending the signal to start the ray light source, the ray imager and the velocimeter by the database system server.
The ray light source module and the ray imager form a gray image of the detected vehicle by scanning the detected vehicle and transmit the gray image to the database system server; meanwhile, the velocimeter collects the running speed of the detected vehicle in real time and transmits the collected real-time speed data to the database system server, wherein the real-time speed collection frequency is greater than the emission frequency of the ray light source. After the detected vehicle completely passes through the ray light source and the ray imager, the database system server corrects the gray image data of the detected vehicle according to the real-time speed data of the detected vehicle and obtains a vehicle detection result according to the corrected gray image. And finishing the vehicle detection process.
Fig. 5 shows a schematic structural diagram of a monitoring device for a green channel vehicle provided by the invention. As shown in fig. 5, the detecting device includes: an image receiving module 51, configured to receive a grayscale image of the detected vehicle acquired by the radiation light source and the radiation imager; the image correction module 52 is used for acquiring the real-time speed of the detected vehicle and correcting the gray image of the detected vehicle according to the real-time speed; and a result obtaining module 53, configured to obtain a vehicle detection result according to the corrected grayscale image.
The monitoring device for the green channel vehicle provided by the invention and the detection method for the green channel vehicle described above are referred to correspondingly, and are not repeated herein.
Fig. 6 is a schematic system diagram of a detection apparatus for a green-channel vehicle according to the present invention. As shown in fig. 6, the detection apparatus for a green channel vehicle includes a mobile device terminal 02, a database system server 03, a radiation light source 04, a radiation imager 05, a velocimeter 07, a first optical camera 06, and a second optical camera 08. The mobile device 02, the ray light source 04, the ray imager 05, the velocimeter 07, the first optical camera 06 and the second optical camera 08 can perform data interaction with the database system server 03 through the wireless data transmission device. Before the detected vehicle 01 passes through the green channel detection device, the mobile equipment terminal 02 firstly transmits basic information of the detected vehicle 01 to the database system server 03; when the detected vehicle 01 passes through the detection area, the second optical camera 08 firstly collects the number plate number data of the detected vehicle, the number plate number data is transmitted to the database system server 03 and is judged, then the first optical camera 06 is started to automatically identify the cab of the detected vehicle 01, after the cab of the detected vehicle 01 completely passes through the ray area, the database system server 03 sends a signal to start the ray light source 04, and simultaneously the velocimeter 07 is started, the ray imager 05 receives the ray penetrating through the detected vehicle 01 and generates a gray level image of the detected vehicle 01, and transmits the gray level image to the database system server 03, and simultaneously the velocimeter 07 also transmits the obtained real-time speed data to the database system server 03. All signals are processed and analyzed in the database system server 03 and relevant command signals are sent to the various components. All modules except the database system server 03, except the ray light source 04 and the ray imager are integrated, direct data interaction exists between the modules, and no direct data interaction exists between the rest modules.
Fig. 7 is a schematic physical structure diagram of an electronic device, which may include, as shown in fig. 7: a processor (processor) 710, a communication Interface (communications Interface) 720, a memory (memory) 730, and a communication bus 740, wherein the processor 710, the communication Interface 720, and the memory 730 communicate with each other via the communication bus 740. Processor 710 may invoke logic instructions in memory 730 to perform a green channel vehicle detection method provided by the present invention, the method comprising: receiving a gray-scale image of a detected vehicle acquired by a ray light source and a ray imager; acquiring the real-time speed of the detected vehicle, and correcting the gray image of the detected vehicle according to the real-time speed; and acquiring a vehicle detection result according to the corrected gray level image.
In addition, the logic instructions in the memory 730 can be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method for detecting a green channel vehicle provided by the above methods, the method including: receiving a gray-scale image of a detected vehicle acquired by a ray light source and a ray imager; acquiring the real-time speed of the detected vehicle, and correcting the gray image of the detected vehicle according to the real-time speed; and acquiring a vehicle detection result according to the corrected gray level image.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for detecting a green channel vehicle, comprising:
receiving a gray-scale image of a detected vehicle acquired by a ray light source and a ray imager;
acquiring the real-time speed of the detected vehicle, and correcting the gray image of the detected vehicle according to the real-time speed;
and acquiring a vehicle detection result according to the corrected gray level image.
2. The method for detecting a green channel vehicle according to claim 1, wherein the modifying the gray-scale image of the detected vehicle according to the real-time speed comprises:
determining the compression rate of the gray level image of the detected vehicle according to the real-time speed and the preset speed;
determining the correction length and the correction width of the gray image according to the compression rate of the gray image to obtain the gray image corrected by the detected vehicle;
and the compression rate is the ratio of the real-time speed to the preset speed.
3. The method for detecting the vehicle on the green channel according to claim 1, wherein the obtaining of the vehicle detection result according to the corrected gray-scale image comprises:
and inputting the corrected gray level image into an automatic recognition algorithm model, processing the corrected gray level image by the automatic recognition algorithm model, and acquiring the vehicle detection result according to the judgment standard of the green channel vehicle.
4. The method for detecting a green channel vehicle according to claim 3, wherein the step of obtaining a vehicle detection result according to the corrected gray-scale image further comprises:
making a corresponding decision according to the vehicle detection result;
if the detected vehicle meets the standard of the green channel vehicle, the vehicle passes through freely;
and if the detected vehicle does not meet the standard of the green channel vehicle, the vehicle charges for passing.
5. The method for detecting vehicles according to claim 1, wherein said receiving the gray scale image of the detected vehicle obtained by the radiation source and the radiation imager further comprises:
according to the attribute information of the detected vehicle, calling a vehicle appearance recognition algorithm, and driving a first optical camera to acquire the position information of the detected vehicle in real time;
and when the position information of the detected vehicle shows that the cab of the detected vehicle passes through the irradiation area of the ray light source, starting the ray light source and the ray imager.
6. The method according to claim 5, wherein the attribute information of the detected vehicle includes: the license plate number, the brand model and the overall dimension of the detected vehicle.
7. The method of detecting a green channel vehicle of claim 6, further comprising:
and acquiring and storing the attribute information of the detected vehicle according to the license plate number of the detected vehicle acquired by the second optical camera, the basic information of the detected vehicle uploaded by the mobile equipment terminal and the corresponding record information.
8. A green channel vehicle detection device, comprising:
the image receiving module is used for receiving the gray level image of the detected vehicle acquired by the ray light source and the ray imager;
the image correction module is used for acquiring the real-time speed of the detected vehicle and correcting the gray image of the detected vehicle according to the real-time speed;
and the result acquisition module is used for acquiring a vehicle detection result according to the corrected gray level image.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the method for green channel vehicle detection according to any of claims 1 to 7.
10. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for detecting a green channel vehicle according to any one of claims 1 to 7.
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