CN117351697A - Traffic acquisition image processing method and system - Google Patents

Traffic acquisition image processing method and system Download PDF

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Publication number
CN117351697A
CN117351697A CN202311118501.5A CN202311118501A CN117351697A CN 117351697 A CN117351697 A CN 117351697A CN 202311118501 A CN202311118501 A CN 202311118501A CN 117351697 A CN117351697 A CN 117351697A
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vehicle
traffic
congestion
acquisition
speed
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闫军
王伟
冯澍
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Smart Intercommunication Technology Co ltd
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Smart Intercommunication Technology Co ltd
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Priority to CN202311118501.5A priority Critical patent/CN117351697A/en
Publication of CN117351697A publication Critical patent/CN117351697A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • G06V20/54—Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing
    • G08G1/0133—Traffic data processing for classifying traffic situation
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/065—Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/07—Target detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/08—Detecting or categorising vehicles

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  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention provides a traffic acquisition image processing method and system, which relate to the technical field of image processing and comprise the following steps: setting up a traffic management platform, carrying out continuous image acquisition through an image acquisition module, acquiring a vehicle image set, carrying out vehicle detection through a vehicle detection module, and acquiring a vehicle detection result, wherein the vehicle detection result comprises the number of vehicles and the vehicle speed in preset time, when the number of vehicles reaches a threshold value of the number of vehicles and/or the vehicle speed reaches a threshold value of the vehicle speed, judging that the kth acquisition point has traffic jam, and carrying out cooperative analysis by calling M acquisition points through a traffic analysis module to acquire a traffic jam road section, so as to carry out traffic management. The invention solves the technical problems that the traditional traffic acquisition image processing method only usually focuses on basic information such as the number and the speed of vehicles, and cannot accurately detect and manage the illegal behaviors and judge the congestion condition on the road, so that the road management and congestion processing effects are poor.

Description

Traffic acquisition image processing method and system
Technical Field
The invention relates to the technical field of image processing, in particular to a traffic acquisition image processing method and system.
Background
With the acceleration of the urban process and the continuous increase of the number of vehicles, the peak of traffic flow and frequent accidents become normal, higher requirements are provided for traffic supervision, the rapid development of an image processing technology provides a solution for collecting traffic images, and the vehicles can be detected and identified in real time, the traffic flow, the congestion situation and the illegal behaviors are analyzed by means of intelligent cameras, perception technology, machine learning and the like, and scientific basis is provided for traffic management and flow optimization.
The conventional traffic collection image processing method still has a certain disadvantage, and the conventional traffic collection image processing method usually only focuses on basic information such as the number and the speed of vehicles, and cannot accurately detect and manage illegal behaviors and judge the congestion condition on the road, so that the road management and congestion processing effects are poor. Therefore, a certain liftable space exists for traffic acquisition image processing.
Disclosure of Invention
The traffic collection image processing method and the traffic collection image processing system aim to solve the technical problems that the traditional traffic collection image processing method only usually focuses on basic information such as the number and the speed of vehicles, and cannot accurately detect and manage illegal behaviors and judge the congestion condition on roads, so that the road management and congestion processing effects are poor.
In view of the above problems, the present application provides a traffic collection image processing method and system.
In a first aspect of the disclosure, a traffic collection image processing method is provided, the method includes: building a traffic management platform, wherein the traffic management platform comprises an image acquisition module, a vehicle detection module and a traffic analysis module; the image acquisition module is used for continuously acquiring images of the vehicle at the kth acquisition point in a preset time to acquire a vehicle image set; the vehicle detection module is used for detecting the vehicle in the vehicle image set to obtain a vehicle detection result, wherein the vehicle detection result comprises the number of vehicles and the speed of the vehicles in a preset time; when the number of the vehicles reaches a threshold value of the number of the vehicles and/or the speed of the vehicles reaches a threshold value of the speed of the vehicles, judging that the kth acquisition point has traffic jam; the method comprises the steps that M acquisition points adjacent to the kth acquisition point in front of and behind the kth acquisition point are called through a traffic analysis module, and collaborative analysis is carried out to obtain a traffic jam road section; and connecting a traffic management system to manage traffic of the traffic congestion road section.
In another aspect of the disclosure, there is provided a traffic collection image processing system for use in the above method, the system comprising: the system comprises a management platform building unit, a traffic management platform management unit and a traffic analysis unit, wherein the management platform building unit is used for building a traffic management platform, and the traffic management platform comprises an image acquisition module, a vehicle detection module and a traffic analysis module; the continuous image acquisition unit is used for continuously acquiring images of vehicles at a kth acquisition point in preset time through the image acquisition module to acquire a vehicle image set; the vehicle detection unit is used for detecting the vehicle on the vehicle image set through the vehicle detection module to obtain a vehicle detection result, wherein the vehicle detection result comprises the number of vehicles and the vehicle speed in a preset time; the traffic jam judging unit is used for judging that the k-th acquisition point has traffic jam when the number of vehicles reaches a vehicle number threshold value and/or the speed of the vehicles reaches a vehicle speed threshold value; the collaborative analysis unit is used for calling M adjacent acquisition points before and after the kth acquisition point through the traffic analysis module, and carrying out collaborative analysis to acquire a traffic congestion road section; and the traffic management unit is used for connecting a traffic management system and managing traffic of the traffic jam road section.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
setting up a traffic management platform, continuously acquiring images of vehicles at a kth acquisition point in a preset time through an image acquisition module, acquiring a vehicle image set, detecting the vehicles through a vehicle detection module to acquire a vehicle detection result, wherein the vehicle detection result comprises the number of vehicles and the vehicle speed in the preset time, when the number of vehicles reaches a threshold value of the number of vehicles and/or the vehicle speed reaches a threshold value of the vehicle speed, judging that the kth acquisition point is in traffic jam, acquiring M acquisition points adjacent to the kth acquisition point in front of and behind through a traffic analysis module, carrying out cooperative analysis, acquiring a traffic jam road section, connecting the traffic management system, and carrying out traffic management on the traffic jam road section. The method solves the technical problems that the traditional traffic collection image processing method usually only focuses on basic information such as the number and the speed of vehicles, cannot accurately detect and manage the offending behavior and judge the congestion situation on the road, so that the road management and congestion processing effect is poor, and achieves the technical effects of comprehensively collecting, analyzing and managing the vehicle data, providing accurate vehicle number and speed information, further judging and managing the traffic congestion road section and detecting and managing the traffic offending behavior, thereby improving the traffic management efficiency and the road safety.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
Fig. 1 is a schematic flow chart of a traffic collection image processing method according to an embodiment of the present application;
fig. 2 is a schematic diagram of a possible structure of a traffic collection image processing system according to an embodiment of the present application.
Reference numerals illustrate: the system comprises a management platform building unit 10, a continuous image acquisition unit 20, a vehicle detection unit 30, a traffic jam judging unit 40, a collaborative analysis unit 50 and a traffic management unit 60.
Detailed Description
The traffic collection image processing method solves the technical problems that the traditional traffic collection image processing method only focuses on basic information such as the number and the speed of vehicles, cannot accurately detect and manage illegal behaviors and judge congestion conditions on roads, so that road management and congestion processing effects are poor, and achieves the technical effects of improving traffic management efficiency and road safety by comprehensively collecting, analyzing and managing vehicle data, providing accurate vehicle number and speed information, judging and managing traffic congestion road sections and detecting and managing traffic illegal behaviors.
Having described the basic principles of the present application, various non-limiting embodiments of the present application will now be described in detail with reference to the accompanying drawings.
Example 1
As shown in fig. 1, an embodiment of the present application provides a traffic collection image processing method, where the method includes:
building a traffic management platform, wherein the traffic management platform comprises an image acquisition module, a vehicle detection module and a traffic analysis module;
the image acquisition module is used for continuously acquiring images of the vehicle, and can be realized through a camera or other visual sensors, wherein the position of the image acquisition module is arranged on a traffic intersection or a road to be monitored, and vehicle images in a certain time interval are continuously acquired to acquire vehicle conditions at a plurality of time points; the vehicle detection module is used for detecting vehicles in the vehicle image set, and comprises data such as the number of vehicles, the speed of the vehicles and the like in preset time, and a target detection algorithm in a computer vision technology, such as a fast convolution neural network, can be adopted to accurately detect and position the vehicles; the traffic analysis module is used for calling adjacent acquisition points and carrying out cooperative analysis so as to acquire traffic jam road sections. Through the traffic management platform, the collection of vehicle images, the detection of vehicles and the analysis of traffic jams can be realized, so that the traffic management is facilitated, the jam situation is effectively treated, and the traffic efficiency and the road safety are improved.
The image acquisition module is used for continuously acquiring images of the vehicle at the kth acquisition point in a preset time to acquire a vehicle image set;
a preset time period is set to collect vehicle images, the time period can be 10 seconds, 1 minute, and the like, a proper image collecting device such as a high-definition camera or other type of vision sensor is installed at the position of a kth collecting point such as a traffic intersection or a road, continuous image collection is started, images of vehicles passing through the kth collecting point are taken, and a vehicle image set is obtained.
The vehicle detection module is used for detecting the vehicle in the vehicle image set to obtain a vehicle detection result, wherein the vehicle detection result comprises the number of vehicles and the speed of the vehicles in a preset time;
preferably, the vehicle detection module is configured to perform vehicle detection on the vehicle image set, and obtain a vehicle detection result, where the vehicle detection result includes the number of vehicles and the vehicle speed in a preset time, and the method includes:
the vehicle detection module comprises a vehicle identification channel and a speed detection channel; performing target detection on the first vehicle image through the vehicle identification channel, demarcating a boundary frame of the vehicle according to a target detection result, and counting the boundary frame to obtain the number of the vehicles; and tracking the displacement amount of the vehicle between the continuous frames in the vehicle image set through the speed detection channel, and calculating the vehicle speed according to the displacement amount.
Through the vehicle identification channel, an object detection algorithm, such as a convolutional neural network, is used, which locates possible vehicles in areas with different positions on the image, so as to identify vehicle objects in the first vehicle image, and a bounding box is defined for each detected vehicle object according to the object detection result, wherein the bounding box can accurately contain the whole vehicle object. Each bounding box is considered as an independent vehicle and the number of all delineated bounding boxes, i.e. the number of vehicles detected, is counted.
The method comprises the steps of obtaining continuous frames in a vehicle image set, shooting the continuous frames at certain time intervals, using a speed detection channel, using a target tracking algorithm such as an optical flow method, measuring the change of the vehicle position by using the center point coordinates or other characteristic points of the vehicle target, tracking the vehicle target in the continuous frames, obtaining the position change of the vehicle between different frames, obtaining the vehicle displacement, dividing the displacement by the time interval, and obtaining the average displacement, namely the speed, of the vehicle in unit time.
When the number of the vehicles reaches a threshold value of the number of the vehicles and/or the speed of the vehicles reaches a threshold value of the speed of the vehicles, judging that the kth acquisition point has traffic jam;
in the traffic management platform, a vehicle number threshold value and a vehicle speed threshold value are preset, the threshold values are based on consideration of the maximum allowed traffic flow and reasonable running speed of a specific road or road section, the vehicle number and the vehicle speed acquired by a vehicle detection module are compared with the preset threshold values, and if the vehicle number reaches the vehicle number threshold value or the vehicle speed reaches the vehicle speed threshold value, the condition that the traffic jam exists at the kth acquisition point can be judged.
The method comprises the steps that M acquisition points adjacent to the kth acquisition point in front of and behind the kth acquisition point are called through a traffic analysis module, and collaborative analysis is carried out to obtain a traffic jam road section;
further, the traffic analysis module is used for calling M adjacent acquisition points before and after the kth acquisition point to perform collaborative analysis to obtain a traffic congestion road section, and the method comprises the following steps:
the k+1th acquisition point which is adjacent to the k acquisition point backwards is called, and traffic jam judgment is carried out on the k+1th acquisition point; if the k+1 collecting point has traffic jam, continuously calling the k+2 collecting point which is backward adjacent to the k+1 collecting point, and judging the traffic jam of the k+2 collecting point; repeating the operation until no traffic jam exists at the k+n acquisition point, and taking the previous acquisition point of the k+n acquisition point as a congestion end point; likewise, the adjacent k-m acquisition points in front of the k acquisition point are acquired, and the later acquisition point of the k-m acquisition points is taken as a congestion starting point; and obtaining M acquisition points from the congestion starting point to the congestion ending point.
The starting acquisition point, i.e. the kth acquisition point, at which the operation is performed is determined, on the basis of which the next adjacent acquisition point, i.e. the k+1th acquisition point, is determined, depending on the preset sampling interval. And acquiring traffic data related to the (k+1) th acquisition point, and performing traffic jam judgment, wherein the traffic jam judgment comprises analyzing the number, the speed or other related indexes of the vehicles, for example, judging whether the traffic jam exists according to whether the number or the speed of the vehicles exceeds a threshold value.
If the k+1 acquisition point has traffic jam, determining the next adjacent acquisition point, namely the k+2 acquisition point, on the basis of the k+1 acquisition point, carrying out traffic jam judgment again, determining whether the subsequent acquisition point is required to be continuously called and congestion judged according to the traffic jam judgment result of the k+2 acquisition point, and if congestion exists, repeating the operation until the k+n acquisition point does not have traffic jam, and considering that the congestion end point is positioned at the k+n-1 acquisition point, thereby judging the position of the congestion end point.
And adopting the same method to search the kth acquisition point forwards until the kth-m acquisition point without traffic jam is acquired, taking the next acquisition point of the kth-m acquisition point as a congestion starting point, and judging the position of the congestion starting point.
And executing query operation on the acquisition points between the starting index and the ending index to acquire M acquisition points in the range.
And connecting a traffic management system to manage traffic of the traffic congestion road section.
And ensuring that effective connection and communication are established between the traffic analysis module and the traffic management system, and transmitting the traffic congestion road section information acquired by the traffic analysis module to the traffic management system, wherein the information comprises data such as the position, duration, number and speed of the congestion road section. The traffic management system uses the transmitted traffic congestion road section information to further analyze and decide, and according to the congestion condition, adopts corresponding measures to relieve or manage the traffic congestion, such as optimizing the timing of signal lamps, guiding traffic to other roads, providing real-time traffic information to drivers, etc. Thereby improving traffic fluency, reducing congestion and optimizing road use efficiency.
Further, the method further comprises the following steps:
the vehicle detection module further comprises an illegal detection submodule, wherein the illegal detection submodule comprises a vehicle body detection channel, a line pressing detection channel and an overspeed detection channel; extracting features of the vehicle through the vehicle body detection channel, and identifying illegal behaviors according to the extracted features to obtain the illegal behaviors of the vehicle body; geometrically judging the vehicle position and the marking position through the line pressing detection channel to obtain line pressing illegal behaviors; comparing the vehicle speed with a limiting speed through the overspeed detection channel to obtain overspeed illegal behaviors; and carrying out illegal vehicle management according to the vehicle body illegal behaviors, the line pressing illegal behaviors and the overspeed illegal behaviors.
The vehicle detection module further comprises an violation detection sub-module, wherein the sub-module comprises a vehicle body detection channel, a line pressing detection channel and an overspeed detection channel, and the channels are used for detecting different violations of the vehicle.
Through the vehicle body detection channel, a target detection algorithm in a computer vision technology is utilized to extract characteristics of the vehicle, characteristic analysis is carried out according to the extracted characteristics of the vehicle, such as the outline, the size, the shape and the like of the vehicle, and the illegal behaviors of the vehicle body are identified according to predefined rules and models, for example, whether the illegal behaviors, such as ultra-wide, ultra-high, ultra-long and the like, exist can be judged by comparing whether the size and the shape of the vehicle meet the standards of traffic regulations. According to the recognition result of the illegal act, the illegal vehicle is classified as the illegal act of the vehicle body, and relevant information such as the vehicle recognition number, time, position and the like is recorded.
Through the line pressing detection channel, edge detection, image segmentation and other methods in computer vision technology are used for extracting the position information of the vehicle and the marked line on the road from the image, and based on the obtained position of the vehicle and the marked line position, geometric judgment is performed to judge whether line pressing illegal behaviors exist, for example, the relative position relation between the vehicle and the marked line on the road is analyzed, so as to judge whether the vehicle completely or partially passes the marked line, whether the distance exceeding the marked line exceeds the allowable range and the like. Whether the line pressing violation exists is identified according to the result of the geometric judgment, and when the vehicle is judged to pass through the marked line or exceed the limit, the vehicle can be classified as the line pressing violation.
Obtaining the speed limit information of the position on the road, comparing the vehicle speed with the speed limit, if the moving speed of the vehicle exceeds the speed limit on the road, determining that overspeed violations exist, and recording the detected overspeed violations, wherein the detected overspeed violations comprise relevant vehicle information, time, position and the like.
When the illegal behavior is found, an alarm can be triggered and sent to related departments or personnel, the related departments can take appropriate measures in time, such as dispatching management personnel, changing signal lights or sending warning information to other drivers, and the like, and further, corresponding punishment and punishment stopping measures, such as fine, deduction, stopping or limiting running, are carried out on the illegal vehicle. Therefore, the road safety is improved, the traffic order is maintained, and the driving environment is improved.
Further, the method further includes, before comparing the vehicle speed with the limit speed:
carrying out background recognition on the vehicle image set to acquire road information; and calling the limiting speed of the road according to the road information.
A background model is built using successive frames in a set of vehicle images, the background model being capable of capturing static elements on roads, such as roads, buildings, vegetation, and the like. After the road area is extracted, the geometric structure, the marks and the like of the road area are analyzed, and related information of the road, such as the length of a road section, the number of lanes, the lane marks, the intersections and the like, is further extracted from the road area, so that the road information is obtained.
The system comprises a database connected to a traffic management system, wherein the database contains related information of roads, speed limiting information corresponding to the roads is queried or obtained from the database, and speed limiting values suitable for the roads are obtained according to the identification, classification, position and other attributes of the roads and used for subsequent traffic management and analysis, so that drivers are ensured to observe the speed limiting specified by the roads.
Further, when the number of vehicles reaches the threshold of the number of vehicles and/or the speed of the vehicles reaches the threshold of the speed of the vehicles, determining that the k-th acquisition point has traffic jam, before the step of determining that the k-th acquisition point has traffic jam, the method further comprises:
calling images of the congestion routes in the past time period, and acquiring a historical congestion image set; inputting the historical congestion image set into the vehicle identification channel to obtain a congestion vehicle number set; and descending order arrangement is carried out on the congestion vehicle quantity collection, and the minimum value of the congestion vehicle quantity is obtained and is used as the vehicle quantity threshold value.
The method comprises the steps of defining a time period for acquiring a historical congestion image set, connecting to a database storing traffic image data for the last 5 years, executing query operation in an image storage system, screening according to the time period and the current node to retrieve image data meeting the conditions, and acquiring the historical congestion image set from the image storage system according to the query result, wherein the images reflect the condition of a congestion route in the selected time period.
And processing the preprocessed historical congestion image set by using a target detection and recognition algorithm in the vehicle recognition channel, positioning and recognizing a vehicle target in the image, providing a vehicle position and a boundary frame, calculating the number of vehicles in each image in the congestion image based on the target detection and recognition result, and forming a congestion vehicle number set by the number of vehicles acquired from each image.
Sorting the congestion vehicle number sets from large to small according to the number, and selecting the last value, namely the smallest value, from the congestion vehicle number sets after descending sorting as the threshold value of the congestion vehicle number, wherein the smallest value represents the smallest value of the vehicle number under the condition of congestion in the historical congestion image set.
Further, when the number of vehicles reaches the threshold of the number of vehicles and/or the speed of the vehicles reaches the threshold of the speed of the vehicles, determining that the k-th acquisition point has traffic jam, before the step of determining that the k-th acquisition point has traffic jam, the method further comprises:
inputting the historical congestion image set into a speed detection channel to obtain a congestion vehicle speed set; and descending order arrangement is carried out on the congestion vehicle speed sets, and the maximum value of the congestion vehicle speed is obtained and is used as the vehicle speed threshold value.
Inputting the historical congestion image set into a speed detection channel, tracking a vehicle target in the historical congestion image set by using image processing and computer vision technology, calculating the displacement of each congestion vehicle between continuous frames according to a target tracking result, calculating the average speed of the congestion vehicles according to the displacement and time intervals, recording the speed of each congestion vehicle based on the speed calculation result, and forming a congestion vehicle speed set.
The congestion vehicle speed sets are ranked from high to low according to the speed, and the first congestion vehicle speed set after descending ranking, namely the maximum value is selected as the threshold value of the congestion vehicle speed, and the maximum value represents the maximum value of the vehicle speed under the condition of congestion in the historical congestion image set.
In summary, the traffic collection image processing method and system provided by the embodiment of the application have the following technical effects:
setting up a traffic management platform, continuously acquiring images of vehicles at a kth acquisition point in a preset time through an image acquisition module, acquiring a vehicle image set, detecting the vehicles through a vehicle detection module to acquire a vehicle detection result, wherein the vehicle detection result comprises the number of vehicles and the vehicle speed in the preset time, when the number of vehicles reaches a threshold value of the number of vehicles and/or the vehicle speed reaches a threshold value of the vehicle speed, judging that the kth acquisition point is in traffic jam, acquiring M acquisition points adjacent to the kth acquisition point in front of and behind through a traffic analysis module, carrying out cooperative analysis, acquiring a traffic jam road section, connecting the traffic management system, and carrying out traffic management on the traffic jam road section.
The method solves the technical problems that the traditional traffic collection image processing method usually only focuses on basic information such as the number and the speed of vehicles, cannot accurately detect and manage the offending behavior and judge the congestion situation on the road, so that the road management and congestion processing effect is poor, and achieves the technical effects of comprehensively collecting, analyzing and managing the vehicle data, providing accurate vehicle number and speed information, further judging and managing the traffic congestion road section and detecting and managing the traffic offending behavior, thereby improving the traffic management efficiency and the road safety.
Example two
Based on the same inventive concept as one of the traffic collection image processing methods in the foregoing embodiments, as shown in fig. 2, the present application provides a traffic collection image processing system, which includes:
the management platform construction unit 10 is used for constructing a traffic management platform, wherein the traffic management platform comprises an image acquisition module, a vehicle detection module and a traffic analysis module;
the continuous image acquisition unit 20 is used for continuously acquiring images of the vehicle at the kth acquisition point in a preset time through the image acquisition module to acquire a vehicle image set;
the vehicle detection unit 30 is configured to perform vehicle detection on the vehicle image set through a vehicle detection module, and obtain a vehicle detection result, where the vehicle detection result includes the number of vehicles and the vehicle speed in a preset time;
a traffic congestion determination unit 40, where the traffic congestion determination unit 40 is configured to determine that a kth acquisition point is congested when the number of vehicles reaches a vehicle number threshold and/or the speed of the vehicles reaches a vehicle speed threshold;
the collaborative analysis unit 50 is configured to call M adjacent collection points before and after a kth collection point through a traffic analysis module, perform collaborative analysis, and obtain a traffic congestion road section;
and the traffic management unit 60 is used for connecting a traffic management system and managing traffic of the traffic jam road section.
Further, the system further comprises:
the vehicle detection module description unit is used for the vehicle detection module and further comprises an violation detection submodule, wherein the violation detection submodule comprises a vehicle body detection channel, a line pressing detection channel and an overspeed detection channel;
the feature extraction unit is used for extracting features of the vehicle through the vehicle body detection channel, and identifying illegal behaviors according to the extracted features to obtain vehicle body illegal behaviors;
the geometric judgment unit is used for carrying out geometric judgment on the vehicle position and the marking position through the line pressing detection channel to obtain line pressing illegal behaviors;
the comparison unit is used for comparing the vehicle speed with the limiting speed through the overspeed detection channel to obtain overspeed illegal behaviors;
and the illegal vehicle management unit is used for managing the illegal vehicle according to the vehicle body illegal behaviors, the line pressing illegal behaviors and the overspeed illegal behaviors.
Further, the system further comprises:
the background recognition unit is used for carrying out background recognition on the vehicle image set to acquire road information;
and the limiting speed calling unit is used for calling the limiting speed of the road according to the road information.
Further, the system further comprises:
the detection module description unit is used for the vehicle detection module to comprise a vehicle identification channel and a speed detection channel;
the target detection unit is used for carrying out target detection on the first vehicle image through the vehicle identification channel, demarcating a boundary frame of the vehicle according to a target detection result, counting the boundary frame and obtaining the number of the vehicles;
and the vehicle speed calculation unit is used for tracking the displacement amount of the vehicle between the continuous frames in the vehicle image set through the speed detection channel and calculating the vehicle speed according to the displacement amount.
Further, the system further comprises:
the historical congestion image acquisition unit is used for acquiring images of the congestion routes in the past time period and acquiring a historical congestion image set;
the congestion vehicle number acquisition unit is used for inputting the historical congestion image set into the vehicle identification channel to acquire a congestion vehicle number set;
and the vehicle number threshold value acquisition unit is used for descending order of the congestion vehicle number set and acquiring the minimum value of the congestion vehicle number as the vehicle number threshold value.
Further, the system further comprises:
the congestion vehicle speed acquisition unit is used for inputting the historical congestion image set into a speed detection channel to acquire a congestion vehicle speed set;
and the vehicle speed threshold acquisition unit is used for descending order of the congestion vehicle speed sets and acquiring the maximum value of the congestion vehicle speed as the vehicle speed threshold.
Further, the system further comprises:
the first traffic jam judging unit is used for calling a k+1th acquisition point which is backwards adjacent to the k acquisition point, and judging the traffic jam of the k+1th acquisition point;
the second traffic jam judging unit is used for continuously calling the k+2 collecting point which is adjacent to the k+1 collecting point backwards if the k+1 collecting point has traffic jam, and judging the traffic jam of the k+2 collecting point;
a congestion end point obtaining unit, configured to repeat operations until no traffic congestion exists at the kth+n collection point, and take the previous collection point of the kth+n collection point as a congestion end point;
the congestion starting point acquisition unit is used for also acquiring the k-m acquisition points adjacent to the k acquisition points and taking the next acquisition point of the k-m acquisition points as a congestion starting point;
and the acquisition point acquisition unit is used for acquiring M acquisition points from the congestion starting point to the congestion ending point.
The foregoing detailed description of a traffic collection image processing method and system in this embodiment will be apparent to those skilled in the art, and the device disclosed in the embodiments corresponds to the method disclosed in the embodiments, so that the description is relatively simple, and the relevant places refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (8)

1. A method for processing traffic collection images, the method comprising:
building a traffic management platform, wherein the traffic management platform comprises an image acquisition module, a vehicle detection module and a traffic analysis module;
the image acquisition module is used for continuously acquiring images of the vehicle at the kth acquisition point in a preset time to acquire a vehicle image set;
the vehicle detection module is used for detecting the vehicle in the vehicle image set to obtain a vehicle detection result, wherein the vehicle detection result comprises the number of vehicles and the speed of the vehicles in a preset time;
when the number of the vehicles reaches a threshold value of the number of the vehicles and/or the speed of the vehicles reaches a threshold value of the speed of the vehicles, judging that the kth acquisition point has traffic jam;
the method comprises the steps that M acquisition points adjacent to the kth acquisition point in front of and behind the kth acquisition point are called through a traffic analysis module, and collaborative analysis is carried out to obtain a traffic jam road section;
and connecting a traffic management system to manage traffic of the traffic congestion road section.
2. The method as recited in claim 1, further comprising:
the vehicle detection module further comprises an illegal detection submodule, wherein the illegal detection submodule comprises a vehicle body detection channel, a line pressing detection channel and an overspeed detection channel;
extracting features of the vehicle through the vehicle body detection channel, and identifying illegal behaviors according to the extracted features to obtain the illegal behaviors of the vehicle body;
geometrically judging the vehicle position and the marking position through the line pressing detection channel to obtain line pressing illegal behaviors;
comparing the vehicle speed with a limiting speed through the overspeed detection channel to obtain overspeed illegal behaviors;
and carrying out illegal vehicle management according to the vehicle body illegal behaviors, the line pressing illegal behaviors and the overspeed illegal behaviors.
3. The method of claim 2, wherein comparing the vehicle speed to a limit speed, prior to further comprising:
carrying out background recognition on the vehicle image set to acquire road information;
and calling the limiting speed of the road according to the road information.
4. The method of claim 1, wherein the vehicle detection is performed on the set of vehicle images by a vehicle detection module to obtain a vehicle detection result, the vehicle detection result including a number of vehicles and a vehicle speed within a preset time, comprising:
the vehicle detection module comprises a vehicle identification channel and a speed detection channel;
performing target detection on the first vehicle image through the vehicle identification channel, demarcating a boundary frame of the vehicle according to a target detection result, and counting the boundary frame to obtain the number of the vehicles;
and tracking the displacement amount of the vehicle between the continuous frames in the vehicle image set through the speed detection channel, and calculating the vehicle speed according to the displacement amount.
5. The method of claim 4, wherein determining that traffic congestion exists at the first collection point when the number of vehicles reaches a vehicle number threshold and/or the vehicle speed reaches a vehicle speed threshold, further comprises:
calling images of the congestion routes in the past time period, and acquiring a historical congestion image set;
inputting the historical congestion image set into the vehicle identification channel to obtain a congestion vehicle number set;
and descending order arrangement is carried out on the congestion vehicle quantity collection, and the minimum value of the congestion vehicle quantity is obtained and is used as the vehicle quantity threshold value.
6. The method of claim 5, wherein determining that traffic congestion exists at the first collection point when the number of vehicles reaches a vehicle number threshold and/or the vehicle speed reaches a vehicle speed threshold, further comprises:
inputting the historical congestion image set into a speed detection channel to obtain a congestion vehicle speed set;
and descending order arrangement is carried out on the congestion vehicle speed sets, and the maximum value of the congestion vehicle speed is obtained and is used as the vehicle speed threshold value.
7. The method of claim 1, wherein the step of retrieving, by the traffic analysis module, M collection points adjacent to and behind the kth collection point to perform collaborative analysis to obtain a traffic congestion road segment includes:
the k+1th acquisition point which is adjacent to the k acquisition point backwards is called, and traffic jam judgment is carried out on the k+1th acquisition point;
if the k+1 collecting point has traffic jam, continuously calling the k+2 collecting point which is backward adjacent to the k+1 collecting point, and judging the traffic jam of the k+2 collecting point;
repeating the operation until no traffic jam exists at the k+n acquisition point, and taking the previous acquisition point of the k+n acquisition point as a congestion end point;
likewise, the adjacent k-m acquisition points in front of the k acquisition point are acquired, and the later acquisition point of the k-m acquisition points is taken as a congestion starting point;
and obtaining M acquisition points from the congestion starting point to the congestion ending point.
8. A traffic acquisition image processing system for implementing a traffic acquisition image processing method according to any one of claims 1 to 7, comprising:
the system comprises a management platform building unit, a traffic management platform management unit and a traffic analysis unit, wherein the management platform building unit is used for building a traffic management platform, and the traffic management platform comprises an image acquisition module, a vehicle detection module and a traffic analysis module;
the continuous image acquisition unit is used for continuously acquiring images of vehicles at a kth acquisition point in preset time through the image acquisition module to acquire a vehicle image set;
the vehicle detection unit is used for detecting the vehicle on the vehicle image set through the vehicle detection module to obtain a vehicle detection result, wherein the vehicle detection result comprises the number of vehicles and the vehicle speed in a preset time;
the traffic jam judging unit is used for judging that the k-th acquisition point has traffic jam when the number of vehicles reaches a vehicle number threshold value and/or the speed of the vehicles reaches a vehicle speed threshold value;
the collaborative analysis unit is used for calling M adjacent acquisition points before and after the kth acquisition point through the traffic analysis module, and carrying out collaborative analysis to acquire a traffic congestion road section;
and the traffic management unit is used for connecting a traffic management system and managing traffic of the traffic jam road section.
CN202311118501.5A 2023-09-01 2023-09-01 Traffic acquisition image processing method and system Pending CN117351697A (en)

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