CN110826544A - Traffic sign detection and identification system and method - Google Patents
Traffic sign detection and identification system and method Download PDFInfo
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- G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
- G06V20/582—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of traffic signs
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Abstract
The embodiment of the invention provides a system and a method for detecting and identifying traffic signs, wherein the system comprises: the video acquisition module is used for acquiring video images of the surrounding environment of the motor vehicle and extracting image frames from the video images frame by frame; the detection module is connected with the video acquisition module and is used for detecting the image frames according to a pre-established traffic sign detection model, determining and acquiring the area where the traffic sign is located and correspondingly generating a traffic sign pattern to be identified; and the classification module is connected with the detection module and used for analyzing and judging the traffic sign pattern to be recognized according to the traffic sign classification model established in advance, determining the category information of the traffic sign contained in the traffic sign pattern to be recognized and outputting the category information as a recognition result. The embodiment determines the class information of the traffic signs contained in the traffic sign pattern through the detection module and the classification module, can accurately detect the traffic signs for the reference of a driver, and improves the driving safety of the motor vehicle.
Description
Technical Field
The embodiment of the invention relates to the technical field of auxiliary driving of motor vehicles, in particular to a system and a method for detecting and identifying a traffic sign.
Background
Generally, in a real road scene, traffic signs are often in a relatively complex environment, such as being blocked, being blurred due to aging, being reflected by strong light, and the like, and these factors may cause difficulty in detecting and identifying the traffic signs. At present, many detection systems exist in the industry, but many of the detection systems have no poor universality, and in addition, the detection and identification effects on the traffic signs of small targets are poor, and the traffic signs are easy to ignore or misjudge, so that the traffic sign detection and identification systems cannot accurately detect the traffic signs, and bring much inconvenience to motor vehicle drivers.
Disclosure of Invention
The embodiment of the invention aims to solve the technical problem that the embodiment of the invention provides a traffic sign detection and identification system so as to accurately detect a traffic sign for a driver to refer to.
The embodiment of the invention further aims to solve the technical problem that the embodiment of the invention provides a traffic sign detection and identification method so as to accurately detect a traffic sign for a driver to refer to.
In order to solve the above technical problem, an embodiment of the present invention provides the following technical solutions: a traffic sign detection and identification system, the system comprising:
the video acquisition module is used for acquiring video images of the surrounding environment of the motor vehicle and extracting image frames from the video images frame by frame;
the detection module is connected with the video acquisition module and is used for detecting the image frames according to a pre-established traffic sign detection model, determining and acquiring the area where the traffic sign is located and correspondingly generating a traffic sign pattern to be identified;
and the classification module is connected with the detection module and used for analyzing and judging the traffic sign pattern to be recognized according to a traffic sign classification model established in advance, determining the category information of the traffic sign contained in the traffic sign pattern to be recognized and outputting the category information as a recognition result.
Further, the video capture module specifically includes:
the vehicle speed unit is used for acquiring the current vehicle speed of the motor vehicle;
the acquisition unit is used for comparing the current speed of the motor vehicle with a preset speed threshold, acquiring video images of the surrounding environment of the motor vehicle when the current speed of the motor vehicle is greater than the speed threshold, and extracting image frames from the video images frame by frame.
Further, the detection module specifically includes:
the storage unit is used for storing a pre-trained traffic sign detection model;
the image processing unit is used for calling the traffic sign detection model to detect the image frame and determining the area where the traffic sign is located in the image frame;
and the target positioning unit is used for acquiring the area where the traffic sign is located and correspondingly generating a traffic sign pattern to be identified.
Further, the traffic sign detection model and the traffic sign classification model are convolutional neural network models based on deep learning.
Further, the traffic sign detecting and identifying system further comprises:
and the output module is connected with the classification module and used for displaying the identification result.
On the other hand, in order to solve the above technical problem, an embodiment of the present invention provides the following technical solutions: a traffic sign detection and identification method comprises the following steps:
collecting video images of the surrounding environment of the motor vehicle, and extracting image frames from the video images frame by frame to obtain image frames;
detecting the image frames according to a pre-established traffic sign detection model, determining and acquiring the area where the traffic sign is located and correspondingly generating a traffic sign pattern to be identified;
and analyzing and judging the traffic sign pattern to be recognized according to a pre-established traffic sign classification model, determining the category information of the traffic sign contained in the traffic sign pattern to be recognized and outputting the category information as a recognition result.
Further, the acquiring a video image of the surrounding environment of the motor vehicle and extracting frame by frame from the video image to obtain an image frame specifically includes:
acquiring the current speed of the motor vehicle;
comparing the current speed of the motor vehicle with a preset speed threshold, acquiring video images of the surrounding environment of the motor vehicle when the current speed of the motor vehicle is greater than the speed threshold, and extracting image frames from the video images frame by frame.
Further, the detecting the image frame according to the pre-established traffic sign detection model, determining and acquiring the area where the traffic sign is located and correspondingly generating the traffic sign pattern to be identified specifically includes:
storing a pre-trained traffic sign detection model;
calling the traffic sign detection model to detect the image frame and determining the area of the traffic sign in the image frame;
and acquiring the area where the traffic sign is located and correspondingly generating a traffic sign pattern to be identified.
Further, the traffic sign detection model and the traffic sign classification model are convolutional neural network models based on deep learning.
Further, the method comprises the following steps:
and displaying the identification result.
After the technical scheme is adopted, the embodiment of the invention at least has the following beneficial effects: the embodiment of the invention acquires the video images of the surrounding environment of the motor vehicle through the video acquisition module, extracts the image frames from the video images frame by frame, detects the image frames through the detection module by adopting a pre-established traffic sign detection model, determines and acquires the area where the traffic sign is located from the image frames and correspondingly generates a traffic sign pattern to be identified, and finally analyzes and judges the traffic sign pattern to be identified through the classification module by adopting a traffic sign classification model to determine the category information of the traffic sign contained in the traffic sign pattern to be identified and output the category information as an identification result, so that the traffic sign can be accurately detected for the reference of a driver, and the driving safety of the motor vehicle is improved.
Drawings
FIG. 1 is a schematic block diagram of an alternate embodiment of a traffic sign detection and identification system of the present invention.
Fig. 2 is a schematic block diagram of a video capture module of an alternate embodiment of the traffic sign detection and identification system of the present invention.
Fig. 3 is a schematic block diagram of a detection module of an alternate embodiment of the traffic sign detection and identification system of the present invention.
Fig. 4 is a schematic block diagram of yet another alternate embodiment of the traffic sign detection and identification system of the present invention.
Fig. 5 is a flow chart of steps of an alternative embodiment of a traffic sign detection and identification method of the present invention.
Fig. 6 is a detailed flowchart of step S1 of an alternative embodiment of the traffic sign detection and identification method according to the present invention.
Fig. 7 is a detailed flowchart of step S2 of an alternative embodiment of the traffic sign detection and identification method according to the present invention.
Fig. 8 is a flow chart of steps in yet another alternative embodiment of a traffic sign detection and identification method of the present invention.
Detailed Description
The present application will now be described in further detail with reference to the accompanying drawings and specific examples. It should be understood that the following illustrative embodiments and description are only intended to explain the present invention, and are not intended to limit the present invention, and features of the embodiments and examples in the present application may be combined with each other without conflict.
As shown in fig. 1, in an embodiment of the present invention, a traffic sign detection and identification system is provided, which includes:
the system comprises a video acquisition module 1, a video processing module and a video processing module, wherein the video acquisition module is used for acquiring video images of the surrounding environment of the motor vehicle and extracting image frames from the video images frame by frame;
the detection module 3 is connected with the video acquisition module 1 and is used for detecting the image frames according to a pre-established traffic sign detection model, determining and acquiring the area where the traffic sign is located and correspondingly generating a traffic sign pattern to be identified;
and the classification module 5 is connected with the detection module 3 and is used for analyzing and judging the traffic sign pattern to be recognized according to a traffic sign classification model established in advance, determining the category information of the traffic sign contained in the traffic sign pattern to be recognized and outputting the category information as a recognition result.
The embodiment of the invention acquires the video images of the surrounding environment of the motor vehicle through the video acquisition module 1, extracts the image frames from the video images frame by frame, detects the image frames through the detection module 3 by adopting a pre-established traffic sign detection model, determines and acquires the area of the traffic sign from the image frames and correspondingly generates a traffic sign pattern to be identified, and finally determines the traffic sign pattern to be identified and analyzes and judges the traffic sign pattern to be identified by adopting a traffic sign classification model through the classification module 5, determines the category information of the traffic sign contained in the traffic sign pattern to be identified and outputs the category information as an identification result, thereby accurately detecting the traffic sign for reference of a driver and improving the driving safety of the motor vehicle. In a specific implementation, the video capture module 1 may be a vehicle-mounted camera of a motor vehicle.
In an optional embodiment of the present invention, as shown in fig. 2, the video capture module 1 specifically includes:
the vehicle speed unit 10 is used for acquiring the current vehicle speed of the motor vehicle;
the acquisition unit 12 is configured to compare the current vehicle speed of the motor vehicle with a preset vehicle speed threshold, acquire a video image of the surrounding environment of the motor vehicle when the current vehicle speed is greater than the vehicle speed threshold, and extract image frames from the video image frame by frame.
In the embodiment, after the current speed of the motor vehicle is compared with the preset speed threshold value by the acquisition unit 12, the video image of the surrounding environment of the motor vehicle is correspondingly acquired when the current speed of the motor vehicle is greater than the speed threshold value, so that the acquisition is performed when the motor vehicle is in a preset speed; the detection and identification system can be effectively activated according to the current vehicle speed, the video image acquisition of the surrounding environment of the motor vehicle can be carried out, manual operation is not needed, and great convenience is realized.
In an optional embodiment of the present invention, as shown in fig. 3, the detection module 3 specifically includes:
a storage unit 30, configured to store a traffic sign detection model trained in advance;
the image processing unit 32 is configured to invoke the traffic sign detection model to detect the image frame, and determine an area where a traffic sign is located in the image frame;
and the target positioning unit 34 is used for acquiring the area where the traffic sign is located and correspondingly generating a traffic sign pattern to be identified.
In the embodiment, the storage unit 30 stores the traffic sign detection model in advance, and the image processing unit 32 can be directly called when the image frame needs to be detected, so that the detection efficiency is improved; and then the target location unit 34 correspondingly generates the traffic sign pattern to be identified in the area where the traffic sign is located, so that the classification processing is convenient.
In an optional embodiment of the invention, the traffic sign detection model and the traffic sign classification model are both convolutional neural network models based on deep learning. In the embodiment, the traffic sign detection model and the traffic sign classification model both adopt the convolutional neural network model based on deep learning, and a great amount of characteristics of the traffic sign such as shape, color and the like are deeply learned in advance through the convolutional neural network, so that the convolutional neural network model is generated, and the traffic sign can be efficiently detected and identified.
In an alternative embodiment of the present invention, as shown in fig. 4, the traffic sign detecting and identifying system further includes:
and the output module 7 is connected with the classification module 5 and used for displaying the identification result.
This embodiment is through setting up output module 7, demonstrates the recognition result that classification module 5 determined, makes things convenient for the driver to know and need not the driver and look up by oneself, has improved the security of driving. In specific implementation, the output module 7 may be an audio device that outputs in an audio broadcasting manner, a display device that outputs in a video display manner, or a multimedia device that outputs audio and video.
On the other hand, as shown in fig. 5, an embodiment of the present invention provides a traffic sign detection and identification method, including the following steps:
s1: collecting video images of the surrounding environment of the motor vehicle, and extracting image frames from the video images frame by frame to obtain image frames;
s2: detecting the image frames according to a pre-established traffic sign detection model, determining and acquiring the area where the traffic sign is located and correspondingly generating a traffic sign pattern to be identified;
s3: and analyzing and judging the traffic sign pattern to be recognized according to a pre-established traffic sign classification model, determining the category information of the traffic sign contained in the traffic sign pattern to be recognized and outputting the category information as a recognition result.
In an alternative embodiment of the present invention, as shown in fig. 6, the step S1 specifically includes:
s11: acquiring the current speed of the motor vehicle;
s12: comparing the current speed of the motor vehicle with a preset speed threshold, acquiring video images of the surrounding environment of the motor vehicle when the current speed of the motor vehicle is greater than the speed threshold, and extracting image frames from the video images frame by frame.
In the embodiment, after the current speed of the motor vehicle is compared with the preset speed threshold, the video image of the surrounding environment of the motor vehicle is correspondingly acquired when the current speed of the motor vehicle is greater than the speed threshold, so that the acquisition can be performed when the motor vehicle is in a preset speed; the detection and identification system can be effectively activated according to the current vehicle speed, the video image acquisition of the surrounding environment of the motor vehicle can be carried out, manual operation is not needed, and great convenience is realized.
In an alternative embodiment of the present invention, as shown in fig. 7, the step S2 specifically includes:
s21: storing a pre-trained traffic sign detection model;
s22: calling the traffic sign detection model to detect the image frame and determining the area of the traffic sign in the image frame;
s23: and acquiring the area where the traffic sign is located and correspondingly generating a traffic sign pattern to be identified.
In the embodiment, the traffic sign detection model is stored in advance, and can be directly called when the image frame needs to be detected, so that the detection efficiency is improved; and then, the traffic sign pattern to be identified is generated correspondingly in the area where the traffic sign is located, so that the classification processing is convenient.
In an optional embodiment of the invention, the traffic sign detection model and the traffic sign classification model are both convolutional neural network models based on deep learning. In the embodiment, the traffic sign detection model and the traffic sign classification model both adopt the convolutional neural network model based on deep learning, and a great amount of characteristics of the traffic sign such as shape, color and the like are deeply learned in advance through the convolutional neural network, so that the convolutional neural network model is generated, and the traffic sign can be efficiently detected and identified.
In an alternative embodiment of the present invention, as shown in fig. 8, the method further comprises the steps of:
s4: and displaying the identification result.
This embodiment demonstrates through the recognition result that will determine, makes things convenient for the driver to know and need not the driver and consult by oneself, has improved the security of driving. In specific implementation, the recognition result can be displayed to the driver by adopting various modes such as audio broadcasting, video display or audio and video output.
The functions described in the embodiments of the present invention may be stored in a storage medium readable by a computing device if they are implemented in the form of software functional modules or units and sold or used as independent products. Based on such understanding, part of the contribution of the embodiments of the present invention to the prior art or part of the technical solution may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computing device (which may be a personal computer, a server, a mobile computing device, a network device, or the like) to execute all or part of the steps of the method described in 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. The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A traffic sign detection and identification system, said system comprising:
the video acquisition module is used for acquiring video images of the surrounding environment of the motor vehicle and extracting image frames from the video images frame by frame;
the detection module is connected with the video acquisition module and is used for detecting the image frames according to a pre-established traffic sign detection model, determining and acquiring the area where the traffic sign is located and correspondingly generating a traffic sign pattern to be identified;
and the classification module is connected with the detection module and used for analyzing and judging the traffic sign pattern to be recognized according to a traffic sign classification model established in advance, determining the category information of the traffic sign contained in the traffic sign pattern to be recognized and outputting the category information as a recognition result.
2. The system for detecting and identifying traffic signs according to claim 1, wherein the video capture module specifically comprises:
the vehicle speed unit is used for acquiring the current vehicle speed of the motor vehicle;
the acquisition unit is used for comparing the current speed of the motor vehicle with a preset speed threshold, acquiring video images of the surrounding environment of the motor vehicle when the current speed of the motor vehicle is greater than the speed threshold, and extracting image frames from the video images frame by frame.
3. The system for detecting and identifying traffic signs according to claim 1, wherein the detection module specifically comprises:
the storage unit is used for storing a pre-trained traffic sign detection model;
the image processing unit is used for calling the traffic sign detection model to detect the image frame and determining the area where the traffic sign is located in the image frame;
and the target positioning unit is used for acquiring the area where the traffic sign is located and correspondingly generating a traffic sign pattern to be identified.
4. The system of claim 1, wherein the traffic sign detection model and the traffic sign classification model are deep learning based convolutional neural network models.
5. The traffic-sign detection and identification system according to claim 1, further comprising:
and the output module is connected with the classification module and used for displaying the identification result.
6. A traffic sign detection and identification method is characterized by comprising the following steps:
collecting video images of the surrounding environment of the motor vehicle, and extracting image frames from the video images frame by frame to obtain image frames;
detecting the image frames according to a pre-established traffic sign detection model, determining and acquiring the area where the traffic sign is located and correspondingly generating a traffic sign pattern to be identified;
and analyzing and judging the traffic sign pattern to be recognized according to a pre-established traffic sign classification model, determining the category information of the traffic sign contained in the traffic sign pattern to be recognized and outputting the category information as a recognition result.
7. The method for detecting and identifying traffic signs according to claim 6, wherein the step of capturing video images of the surroundings of the motor vehicle and extracting image frames from the video images frame by frame comprises:
acquiring the current speed of the motor vehicle;
comparing the current speed of the motor vehicle with a preset speed threshold, acquiring video images of the surrounding environment of the motor vehicle when the current speed of the motor vehicle is greater than the speed threshold, and extracting image frames from the video images frame by frame.
8. The method as claimed in claim 6, wherein the detecting the image frames according to the pre-established traffic sign detection model, determining and acquiring the area of the traffic sign and generating the traffic sign pattern to be identified correspondingly comprises:
storing a pre-trained traffic sign detection model;
calling the traffic sign detection model to detect the image frame and determining the area of the traffic sign in the image frame;
and acquiring the area where the traffic sign is located and correspondingly generating a traffic sign pattern to be identified.
9. The method as claimed in claim 6, wherein the traffic sign detection model and the traffic sign classification model are deep learning-based convolutional neural network models.
10. The method for detecting and identifying traffic signs according to claim 6, further comprising the steps of:
and displaying the identification result.
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