CN111368774A - Waste film rollback method, system, terminal and medium based on traffic violation image - Google Patents

Waste film rollback method, system, terminal and medium based on traffic violation image Download PDF

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Publication number
CN111368774A
CN111368774A CN202010172346.5A CN202010172346A CN111368774A CN 111368774 A CN111368774 A CN 111368774A CN 202010172346 A CN202010172346 A CN 202010172346A CN 111368774 A CN111368774 A CN 111368774A
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image
illegal
violation
images
vehicle
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刘�文
李凡平
石柱国
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Beijing Yisa Technology Co ltd
Qingdao Yisa Data Technology Co Ltd
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Beijing Yisa Technology Co ltd
Qingdao Yisa Data Technology Co Ltd
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/50Context or environment of the image
    • G06V20/52Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • G06V20/54Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/22Matching criteria, e.g. proximity measures
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/20Image preprocessing
    • G06V10/25Determination of region of interest [ROI] or a volume of interest [VOI]
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/20Image preprocessing
    • G06V10/26Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
    • G06V10/267Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion by performing operations on regions, e.g. growing, shrinking or watersheds
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/50Context or environment of the image
    • G06V20/56Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • G06V20/584Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of vehicle lights or traffic lights
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/50Context or environment of the image
    • G06V20/56Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/588Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/60Type of objects
    • G06V20/62Text, e.g. of license plates, overlay texts or captions on TV images
    • G06V20/625License plates

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  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Data Mining & Analysis (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Biology (AREA)
  • Evolutionary Computation (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • General Engineering & Computer Science (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention discloses a waste film rollback method based on traffic violation images, which comprises the steps of obtaining traffic violation instance images, and segmenting the violation instance images, wherein the instance images comprise a first violation image, a second violation image, a third violation image and a close-up image of a violation vehicle; randomly selecting one image from the three illegal images, analyzing lane information and traffic light information from the image, and correspondingly matching the traffic light information with the lane information; detecting the vehicles in the three illegal images by adopting a YOLO method and recording the position information of the vehicles in the images; finding out vehicles matched with the traffic violation records from the three violation images, and recording the positions of the vehicles in the three violation images; and judging whether the vehicles in the three illegal images are illegal or not according to the vehicle information, the lane information and the traffic light information. The method has the advantages that the manual intelligent technology is used for rolling back the waste films of the red light violation evidence images, the speed of checking the images is high, the accuracy is high, and manpower and material resources are saved.

Description

Waste film rollback method, system, terminal and medium based on traffic violation image
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a method, a system, a terminal and a medium for rolling back waste traffic violation images.
Background
At present, for the illegal act of making a dash across red light of the illegal act of transportation, although adopt electronic camera to gather the image, because first off-site intelligent law enforcement system may have the error, need the manual work to further check, the speed of manual check is not only slow, can consume a large amount of manpower and materials moreover.
Disclosure of Invention
Aiming at the defects in the prior art, the embodiment of the invention provides a waste film rollback method, a waste film rollback system, a waste film rollback terminal and a waste film rollback medium based on a traffic violation image.
On the first aspect, the waste film rollback method based on the traffic violation images, provided by the embodiment of the invention, comprises the steps of obtaining traffic violation instance images, and segmenting the violation instance images, wherein the instance images comprise a first violation image, a second violation image, a third violation image and a close-up image of a violation vehicle;
randomly selecting one image from the three illegal images, analyzing lane information and traffic light information from the selected image, and correspondingly matching the traffic light information with the lane information;
detecting the vehicles in the three illegal images by adopting a YOLO detection method and recording the position information of the vehicles in the images;
finding out vehicles matched with the traffic violation records from the three violation images, and recording the positions of the vehicles in the three violation images;
and judging whether the vehicles in the three illegal images are illegal according to the vehicle information, the lane information and the traffic light information.
In a second aspect, the waste sheet rollback system based on the traffic violation image provided by the embodiment of the present invention includes an image acquisition module, an analysis module, a detection module, a violation matching module, and a violation determination module,
the image acquisition module acquires an example image of the traffic violation, and segments the example image, wherein the example image comprises a first illegal image, a second illegal image, a third illegal image and a close-up image of an illegal vehicle;
the analysis module randomly selects one image from the three illegal images, analyzes the lane information and the traffic light information from the selected image, and correspondingly matches the traffic light information with the lane information;
the detection module detects the vehicles in the three illegal images by adopting a YOLO detection method and records the position information of the vehicles in the images;
the illegal matching module finds a vehicle matched with the traffic violation record from the three illegal images and records the positions of the vehicles in the three illegal images;
the violation judging module is used for judging whether the vehicles in the three violation images are illegal according to the vehicle information, the lane information and the traffic light information.
In a third aspect, an intelligent terminal provided in an embodiment of the present invention includes a processor, an input device, an output device, and a memory, where the processor, the input device, the output device, and the memory are connected to each other, the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method steps described in the foregoing embodiment.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, in which a computer program is stored, the computer program comprising program instructions, which, when executed by a processor, cause the processor to perform the method steps described in the above embodiments.
The invention has the beneficial effects that:
according to the waste film rollback method, the waste film rollback system, the waste film rollback terminal and the waste film rollback medium based on the traffic violation images, the waste film rollback is performed on the red light violation evidence images through an artificial intelligence technology, the picture checking speed is high, the accuracy is high, and manpower and material resources are saved.
Drawings
In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below. Throughout the drawings, like elements or portions are generally identified by like reference numerals. In the drawings, elements or portions are not necessarily drawn to scale.
Fig. 1 is a flowchart illustrating a waste sheet rollback method based on a traffic violation image according to a first embodiment of the present invention;
fig. 2 is a schematic structural diagram illustrating a waste sheet rollback system based on a traffic violation image according to another embodiment of the present invention;
fig. 3 shows a schematic structural diagram of an intelligent terminal according to another embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, 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.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.
As shown in fig. 1, a flowchart of a waste-sheet rollback method based on traffic violation images according to a first embodiment of the present invention is shown, and the method includes the following steps:
s1: the method comprises the steps of obtaining an image of an instance of the traffic law violation, and segmenting the image of the violation instance, wherein the image of the instance comprises a first image of the violation, a second image of the violation, a third image of the violation and a close-up image of the violation vehicle.
Specifically, the example images comprise three panoramic images before, during and after the violation and one illegal vehicle sketch.
S2: and (3) randomly selecting one image from the three illegal images, analyzing the lane information and the traffic light information from the selected image, and correspondingly matching the traffic light information and the lane information.
Specifically, the lane information and the traffic light information are analyzed by analyzing the selected images. The lane information comprises lane areas and types, the traffic light information comprises the traffic light areas and types, the lane types are corresponding to the traffic light types, the types of the general traffic lights comprise left-turning arrows, straight-going arrows, right-turning arrows and round lights, the types of the lanes are generally divided into left-turning, left-turning straight-going, right-turning straight-going and right-turning, the number of the traffic lights and the number of the lanes are not corresponding under most conditions, the number of the lanes is generally greater than the number of the traffic lights, and the method adopts a method for constructing a lane corresponding to multiple signal lights by taking the lanes as a reference, so that the corresponding problem of the signal lights and the lanes is solved.
S3: and detecting the vehicles in the three illegal images by adopting a YOLO detection method and recording the position information of the vehicles in the images.
Specifically, in this embodiment, a YOLO detection method is used to detect vehicles, fine tuning and correction are performed on vehicle detection by automatically labeling real scene data, and cache record is performed on position information of each vehicle in a picture, because each vehicle may be a vehicle running a red light.
S4: and finding the vehicle matched with the traffic violation record from the three illegal images, and recording the positions of the vehicles in the three illegal images.
And (3) carrying out license plate recognition on each vehicle in the three illegal images, wherein the condition that the number of license plate recognition digits is wrong or one digit cannot be recognized possibly exists in the license plate recognition, so that the recognized license plate is fuzzy matched with the illegal license plate in the traffic illegal record. The illegal vehicles in the general first illegal image are close in distance, the license plate recognition method has a good effect, the recognition result is clear and accurate, and the illegal vehicles in the first illegal image can be found. Because the second illegal image and the third illegal image are far away from each other, the vehicle is not easily identified due to image blurring. Therefore, when the positions of illegal vehicles cannot be identified by vehicle identification of the second illegal image and the third illegal image by using the fuzzy matching method, similarity calculation is used, and the identified first illegal vehicle image is compared with the vehicles in the second illegal image and the third illegal image in similarity, and the vehicle image with the maximum similarity is the same vehicle image. And finding the image of the same vehicle from the three illegal images, and recording the position information of the vehicle in the three images.
S5: and judging whether the vehicles in the three illegal images are illegal according to the vehicle information, the lane information and the traffic light information.
The embodiment of the invention provides a waste film rollback method based on a traffic violation image, which performs waste film rollback on a red light violation evidence image through an artificial intelligence technology, has high picture checking speed and high accuracy, and saves manpower and material resources.
In the first embodiment, the application provides a waste sheet rollback method based on a traffic violation image, and correspondingly, the application also provides a waste sheet rollback system based on a traffic violation image. Please refer to fig. 2, which is a schematic diagram of a waste-sheet rolling system based on traffic violation images according to a second embodiment of the present invention. Since the apparatus embodiments are substantially similar to the method embodiments, they are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for relevant points.
As shown in fig. 2, the system for rolling back waste films based on traffic violation images according to another embodiment of the present invention includes an image obtaining module, an analyzing module, a detecting module, an violation matching module, and a violation judging module.
The image acquisition module acquires traffic violation instance images and segments the violation instance images, wherein the instance images comprise a first violation image, a second violation image, a third violation image and a close-up image of a violation vehicle.
The lane information and the traffic light information are analyzed by analyzing the selected images. The lane information comprises lane areas and types, the traffic light information comprises the traffic light areas and types, the lane types are corresponding to the traffic light types, the types of the general traffic lights comprise left-turning arrows, straight-going arrows, right-turning arrows and round lights, the types of the lanes are generally divided into left-turning, left-turning straight-going, right-turning straight-going and right-turning, the number of the traffic lights and the number of the lanes are not corresponding under most conditions, the number of the lanes is generally greater than the number of the traffic lights, and the method adopts a method for constructing a lane corresponding to multiple signal lights by taking the lanes as a reference, so that the corresponding problem of the signal lights and the lanes is solved.
The analysis module randomly selects one image from the three illegal images, analyzes the lane information and the traffic light information from the selected image, and correspondingly matches the traffic light information with the lane information.
In this embodiment, a YOLO detection method is used to detect vehicles, fine tuning and correction are performed on vehicle detection by automatically labeling real scene data, and cache record is performed on position information of each vehicle in a picture, because each vehicle may be a vehicle running a red light.
The detection module detects the vehicles in the three illegal images by adopting a YOLO detection method and records the position information of the vehicles in the images.
And the illegal matching module finds the vehicle matched with the traffic violation record from the three illegal images and records the positions of the vehicles in the three illegal images.
And (3) carrying out license plate recognition on each vehicle in the three illegal images, wherein the condition that the number of license plate recognition digits is wrong or one digit cannot be recognized possibly exists in the license plate recognition, so that the recognized license plate is fuzzy matched with the illegal license plate in the traffic illegal record. The illegal vehicles in the general first illegal image are close in distance, the license plate recognition method has a good effect, the recognition result is clear and accurate, and the illegal vehicles in the first illegal image can be found. Because the second illegal image and the third illegal image are far away from each other, the vehicle is not easily identified due to image blurring. Therefore, when the positions of illegal vehicles cannot be identified by vehicle identification of the second illegal image and the third illegal image by using the fuzzy matching method, similarity calculation is used, and the identified first illegal vehicle image is compared with the vehicles in the second illegal image and the third illegal image in similarity, and the vehicle image with the maximum similarity is the same vehicle image. And finding the image of the same vehicle from the three illegal images, and recording the position information of the vehicle in the three images.
And the violation judging module is used for judging whether the vehicles in the three violation images are illegal according to the vehicle information, the lane information and the traffic light information.
According to the waste film rollback system based on the traffic violation images, the waste film rollback is performed on the red light violation evidence images through the artificial intelligence technology, the picture checking speed is high, the accuracy is high, and manpower and material resources are saved.
As shown in fig. 3, a schematic diagram of an intelligent terminal according to a third embodiment of the present invention is provided, where the terminal includes a processor, an input device, an output device, and a memory, where the processor, the input device, the output device, and the memory are connected to each other, the memory is used for storing a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method described in the first embodiment.
It should be understood that in the embodiments of the present invention, the Processor may be a Central Processing Unit (CPU), and the Processor may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The input device may include a touch pad, a fingerprint sensor (for collecting fingerprint information of a user and direction information of the fingerprint), a microphone, etc., and the output device may include a display (LCD, etc.), a speaker, etc.
The memory may include both read-only memory and random access memory, and provides instructions and data to the processor. The portion of memory may also include non-volatile random access memory. For example, the memory may also store device type information.
In a specific implementation, the processor, the input device, and the output device described in the embodiments of the present invention may execute the implementation described in the method embodiments provided in the embodiments of the present invention, and may also execute the implementation described in the system embodiments in the embodiments of the present invention, which is not described herein again.
The invention also provides an embodiment of a computer-readable storage medium, in which a computer program is stored, which computer program comprises program instructions that, when executed by a processor, cause the processor to carry out the method described in the above embodiment.
The computer readable storage medium may be an internal storage unit of the terminal described in the foregoing embodiment, for example, a hard disk or a memory of the terminal. The computer readable storage medium may also be an external storage device of the terminal, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the terminal. Further, the computer-readable storage medium may also include both an internal storage unit and an external storage device of the terminal. The computer-readable storage medium is used for storing the computer program and other programs and data required by the terminal. The computer readable storage medium may also be used to temporarily store data that has been output or is to be output.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the terminal and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed terminal and method can be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electric, mechanical or other form of connection.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.

Claims (10)

1. A waste piece rollback method based on traffic violation images is characterized by comprising the following steps:
acquiring an example image of the traffic violation, and segmenting the illegal example image, wherein the example image comprises a first illegal image, a second illegal image, a third illegal image and an illegal vehicle close-up image;
randomly selecting one image from the three illegal images, analyzing lane information and traffic light information from the selected image, and correspondingly matching the traffic light information with the lane information;
detecting the vehicles in the three illegal images by adopting a YOLO detection method and recording the position information of the vehicles in the images;
finding out vehicles matched with the traffic violation records from the three violation images, and recording the positions of the vehicles in the three violation images;
and judging whether the vehicles in the three illegal images are illegal according to the vehicle information, the lane information and the traffic light information.
2. The method for rolling back the waste films based on the traffic violation images as claimed in claim 1, wherein the specific method for finding the vehicle matching the traffic violation record from the three violation images comprises:
and carrying out license plate recognition on the vehicles in the first illegal image, and carrying out fuzzy matching on the recognized license plates and illegal license plates in the traffic illegal record.
3. The method for rolling back waste films based on traffic violation images as claimed in claim 2, wherein the specific method for finding the vehicle matching the traffic violation record from the three violation images further comprises:
and when the vehicle identification is carried out on the second illegal image and the third illegal image by adopting a fuzzy matching method, and the illegal vehicle is not identified, the vehicle image in the first illegal image is adopted to carry out similarity contrast on the vehicles in the second illegal image and the third illegal image, and the same vehicle image is obtained when the similarity is maximum.
4. The method of claim 1, wherein the lane information comprises a lane area and a type, and the traffic light information comprises a traffic light area and a type.
5. A waste piece rollback system based on traffic violation images is characterized by comprising an image acquisition module, an analysis module, a detection module, a violation matching module and a violation judgment module,
the image acquisition module acquires an example image of the traffic violation, and segments the example image, wherein the example image comprises a first illegal image, a second illegal image, a third illegal image and a close-up image of an illegal vehicle;
the analysis module randomly selects one image from the three illegal images, analyzes the lane information and the traffic light information from the selected image, and correspondingly matches the traffic light information with the lane information;
the detection module detects the vehicles in the three illegal images by adopting a YOLO detection method and records the position information of the vehicles in the images;
the illegal matching module finds a vehicle matched with the traffic violation record from the three illegal images and records the positions of the vehicles in the three illegal images;
the violation judging module is used for judging whether the vehicles in the three violation images are illegal according to the vehicle information, the lane information and the traffic light information.
6. The system of claim 5, wherein the violation matching module comprises a fuzzy matching unit configured to perform license plate recognition on the vehicle in the first violation image and perform fuzzy matching between the recognized license plate and the illegal license plate in the traffic violation record.
7. The system for waste film rollback based on traffic violation images as claimed in claim 6, wherein the violation matching module further comprises a similarity comparison unit, wherein the similarity comparison unit is configured to compare the similarity of the vehicle image in the first violation image with the similarity of the vehicle in the second violation image and the vehicle in the third violation image when the vehicle identification of the second violation image and the third violation image is performed by the fuzzy matching method and the illegal vehicle is not identified, and the vehicle image with the maximum similarity is the same vehicle image.
8. The scrap roll system based on traffic violation images as set forth in claim 5 wherein said lane information comprises a lane area and a type and wherein said traffic light information comprises a traffic light area and a type.
9. An intelligent terminal comprising a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory being interconnected, the memory being adapted to store a computer program, the computer program comprising program instructions, characterized in that the processor is configured to invoke the program instructions to perform the method steps according to any of claims 1 to 4.
10. A computer-readable storage medium, characterized in that the computer storage medium stores a computer program comprising program instructions which, when executed by a processor, cause the processor to carry out the method steps according to any one of claims 1 to 4.
CN202010172346.5A 2020-03-12 2020-03-12 Waste film rollback method, system, terminal and medium based on traffic violation image Pending CN111368774A (en)

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