CN114170583B - Vehicle detecting system based on convolutional neural network - Google Patents
Vehicle detecting system based on convolutional neural network Download PDFInfo
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- 238000001514 detection method Methods 0.000 claims abstract description 68
- 238000000605 extraction Methods 0.000 claims description 33
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- 230000005540 biological transmission Effects 0.000 claims description 17
- 238000013075 data extraction Methods 0.000 claims description 14
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- 238000004364 calculation method Methods 0.000 claims description 5
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- G—PHYSICS
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- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
- G08B25/10—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using wireless transmission systems
Abstract
The invention discloses a vehicle detection system based on a convolutional neural network, which comprises: the vehicle information storage system is used for classifying the vehicle information according to the vehicle characteristics to obtain first vehicle characteristic data and storing the first vehicle characteristic data; the data acquisition system is used for acquiring vehicle image data of the vehicle to be detected; and the comparison module is respectively connected with the vehicle information storage system and the data acquisition system, compares the received first vehicle characteristic data with the vehicle image data to obtain similarity, outputs a detection result which is qualified for the vehicle to be detected if the similarity is smaller than a set value, and otherwise, outputs a detection result which is unqualified for the vehicle to be detected. The invention can rapidly detect whether the vehicle is qualified or not.
Description
Technical Field
The invention relates to the technical field of vehicle detection, in particular to a vehicle detection system based on a convolutional neural network.
Background
In recent years, the convolutional neural network feature extraction method has been developed in the fields of speech recognition and image processing, and has been successful, the convolutional neural network has a multi-layer neural network, and shares a common weight structure, so that the complexity of a network model is greatly reduced.
At present, when a vehicle detection system based on a convolutional neural network is used for detecting a finished automobile, a camera is used for collecting a vehicle image, and then the similarity between the collected vehicle image and a vehicle qualified image stored in the system is compared through the vehicle detection system, so that whether the vehicle is qualified or not is detected, but the vehicle detection system does not store vehicle information in a classified mode, and when the collected vehicle image is processed, the collected vehicle image is required to be compared with the vehicle qualified image stored in the whole system, so that the comparison time is long, and whether the vehicle is qualified or not cannot be detected quickly.
Disclosure of Invention
The invention aims to provide a vehicle detection system based on a convolutional neural network, which is used for solving the problems that the existing vehicle detection system does not store vehicle information in a classified mode, and further, when an acquired vehicle image is processed, the acquired vehicle image is required to be compared with a qualified vehicle image stored in the whole system, so that the comparison time is long, and whether a vehicle is qualified or not cannot be detected rapidly.
In order to solve the problems, the invention is realized by the following technical scheme:
a convolutional neural network-based vehicle detection system, comprising: the vehicle information storage system 100 is configured to classify vehicle information according to vehicle characteristics to obtain first vehicle characteristic data and store the first vehicle characteristic data; the data acquisition system is used for acquiring vehicle image data of the vehicle to be detected; and the comparison module 112 is respectively connected with the vehicle information storage system 100 and the data acquisition system, compares the received first vehicle characteristic data with the vehicle image data to obtain similarity, outputs a detection result that the vehicle to be detected is qualified if the similarity is smaller than a set value, and otherwise, outputs a detection result that the vehicle to be detected is unqualified.
Preferably, the vehicle information storage system 100 includes: the information input module 101, the first analysis module 102, the classification module 103 and the vehicle information storage module 104 are sequentially connected; the first analysis module 102 is configured to analyze the vehicle information from the information input module 101 to obtain a vehicle feature of a corresponding vehicle; the classification module 103 is configured to classify the vehicle information according to the vehicle feature, to obtain first vehicle feature data; the vehicle information storage system 100 is configured to store first vehicle characteristic data.
Preferably, the data acquisition system comprises: the monitoring device 200, the camera control module 202, the main camera device 204 and the acquisition module 203 are connected in sequence, wherein the monitoring device 200 is used for monitoring whether a vehicle to be detected exists on the detection platform; the camera control module 202 is configured to generate a driving signal according to a monitoring result of the vehicle to be detected on the detection table fed back by the monitoring device 200; the main camera 204 is configured to capture the vehicle to be detected according to the received driving signal, so as to obtain vehicle image data; and the acquisition module 203 is used for collecting the vehicle image data.
Preferably, the method further comprises: the first feedback module 113, the alarm control module 116 and the alarm device 400 are sequentially connected; the first feedback module 113 is further connected to the comparison module 112; the first feedback module 113 is configured to transmit the detection result output by the comparison module 112 to the alarm control module 116; the alarm control module 116 correspondingly generates a driving signal according to the detection result; the alarm device 400 sends out corresponding prompt information according to the corresponding driving signal.
Preferably, the data acquisition system further comprises: a second analysis module 110; a data extraction module 111; and an image extraction module 114 connected to the second analysis module 110 and the acquisition module 203, respectively; the image extraction module 114 is configured to perform feature extraction on the received vehicle image data by using a deep convolutional neural network to obtain second vehicle feature data, and the second analysis module 110 is further connected to the vehicle information storage module 104, and analyze the second vehicle feature data according to the first vehicle feature data to obtain an analysis result; the second analysis module 110 is further connected to the data extraction module 111, where the data extraction module 111 is configured to extract a feature class required in the first vehicle feature data extracted by the first vehicle feature data according to the second vehicle feature data in the image extraction module 114.
Preferably, the data acquisition system further comprises: an auxiliary image pickup device 201 connected to the image pickup control module 202 and the acquisition module 203, respectively; and a second feedback module 115 connected to the camera control module 202, the image extraction module 114, and the alarm control module 116, respectively; when the image extraction module 114 performs feature extraction on the received vehicle image data, if second vehicle feature data is not obtained, the main camera 204 is damaged; the image extraction module 114 generates information that the characteristic signal is not extracted and transmits the information to the second feedback module 115; the second feedback module 115 transmits the information that the characteristic signal is not extracted to the alarm control module 116; the alarm control module 116 is configured to drive the alarm device 400 to send out alarm information, so as to remind an operator to repair the main camera device 204 in time; the second feedback module 115 transmits the information of the feature signal not extracted to the camera control module 202; the camera control module 202 turns on the auxiliary camera 201 and turns off the main camera 204; the auxiliary image capturing device 201 is configured to capture the vehicle to be detected, and obtain the vehicle image data.
Preferably, the method further comprises: a recording system 300, a monitoring platform 500 and a mobile terminal 600 respectively connected with the recording system 300; the recording system 300 is further connected to the first feedback module 113 and the second feedback module 115; the recording system 300 is configured to store the comparison detection result output by the first feedback module 113 and the information, which is output by the second feedback module 115 and is not extracted from the feature signal, for storage; the monitoring platform 500 and the mobile terminal 600 are used for checking the detection result and the information of the feature signal which is not extracted.
Preferably, the recording system 300 includes: the recording module 304 is respectively connected with the first feedback module 113 and the second feedback module 115; the information recording module is used for recording the comparison detection result of the first vehicle characteristic data and the vehicle characteristic data to be detected, which are output by the first feedback module 113, and the information which is output by the second feedback module 115 and appears due to the damage of the camera and is not extracted from the characteristic signals, so as to obtain information record; an alarm information storage module 305, connected to the recording module 304, for storing the information record; the wireless transmission module 306 is respectively connected with the alarm information storage module 305, the mobile terminal 600 and the monitoring platform 500, and the mobile terminal 600 and the monitoring platform 500 directly check the detection result of the vehicle to be detected and the fault information of the main camera device in the information record through the wireless transmission module 306.
The setting storage module 301 is connected to the memory calculation module 302, and is configured to set a storage space of the alarm information storage module 305, and calculate an actual storage space of the alarm information storage module 305; the reminding module 303 and the memory calculating module 302 are respectively connected with the reminding module 303 and the alarm information storage module 305, and are used for calculating a storage space in the alarm information storage module 305, when the storage space is equal to the set value, the memory calculating module 302 controls the reminding module 303 to generate and transmit reminding information, and the reminding information is transmitted to the mobile terminal 600 and the monitoring platform 500 through the wireless transmission module 306, so as to remind an operator of timely cleaning data in the alarm information storage module 305.
Preferably, the wireless transmission module 306 includes a 4G module 3061, a 5G module 3062, and a WIFI module 3063.
Preferably, the alarm device 400 includes a buzzer 401 and an indicator light 402; the alarm control module 116 generates a first driving signal when receiving the detection result and determining that the vehicle to be detected is qualified, and drives the indicator lamp 402 to light up through the first driving signal so as to remind an operator that the vehicle to be detected is the qualified vehicle; the alarm control module 116 generates a second driving signal when receiving the detection result and determining that the vehicle to be detected is not qualified, and drives the buzzer 401 to start through the second driving signal, so as to remind an operator that the vehicle to be detected is not qualified.
The invention has at least one of the following advantages:
according to the invention, through the matched arrangement of the information input module, the first analysis module, the classification module and the vehicle information storage module, the vehicle information input through the information input module can be stored in the vehicle information storage module in a classified manner according to the characteristics of the vehicle, and meanwhile, when the collected vehicle image is processed, the image extraction module, the second analysis module and the data extraction module are used for extracting and analyzing the characteristic points on the vehicle image, after analysis, the corresponding vehicle information is extracted through the data extraction module and transmitted to the comparison module, and at the moment, the comparison module only needs to compare the collected vehicle image with the extracted vehicle information, so that whether the vehicle is qualified or not can be detected, and the vehicle detection system can be used for rapidly detecting whether the vehicle is qualified or not.
According to the invention, when the image extraction module cannot extract characteristic information from the acquired vehicle image, the damage of the main camera device is indicated, at the moment, the image extraction module transmits a signal to the second feedback module, the second feedback module transmits the signal to the alarm control module, the alarm control module is used for opening the alarm device, then an operator is reminded of timely maintaining the main camera device through the alarm device, meanwhile, the second feedback module transmits the signal to the camera control module, then the auxiliary camera device is opened through the camera control module, the main camera device is closed, at the moment, the auxiliary camera device is used for shooting the vehicle, and the vehicle detection system can continue to detect the vehicle.
According to the invention, the detection result of the vehicle and the fault information of the main camera device are recorded through the recording system, and the wireless transmission module enables wireless transmission between the recording system and the mobile terminal and between the recording system and the monitoring platform, so that a user can inquire the detection result of the vehicle and the fault information of the main camera device through the mobile terminal and the monitoring platform.
Drawings
FIG. 1 is a block diagram of a vehicle detection system based on convolutional neural network according to an embodiment of the present invention;
FIG. 2 is a block diagram of a monitoring device in a vehicle detection system based on convolutional neural network according to an embodiment of the present invention;
FIG. 3 is a block diagram of an alarm device in a vehicle detection system based on convolutional neural network according to an embodiment of the present invention;
fig. 4 is a block diagram of a wireless transmission module in a vehicle detection system based on a convolutional neural network according to an embodiment of the present invention.
Detailed Description
The following describes a vehicle detection system based on convolutional neural network in further detail with reference to the drawings and detailed description. The advantages and features of the present invention will become more apparent from the following description. It should be noted that the drawings are in a very simplified form and are all to a non-precise scale, merely for the purpose of facilitating and clearly aiding in the description of embodiments of the invention. For a better understanding of the invention with objects, features and advantages, refer to the drawings. It should be understood that the structures, proportions, sizes, etc. shown in the drawings are for illustration purposes only and should not be construed as limiting the invention to the extent that any modifications, changes in the proportions, or adjustments of the sizes of structures, proportions, or otherwise, used in the practice of the invention, are included in the spirit and scope of the invention which is otherwise, without departing from the spirit or essential characteristics thereof.
As shown in fig. 1, the present embodiment provides a vehicle detection system based on a convolutional neural network, including: the vehicle information storage system 100 is configured to classify vehicle information according to vehicle characteristics to obtain first vehicle characteristic data and store the first vehicle characteristic data; the data acquisition system is used for acquiring vehicle image data of the vehicle to be detected; and the comparison module 112 is respectively connected with the vehicle information storage system 100 and the data acquisition system, compares the received first vehicle characteristic data with the vehicle image data to obtain similarity, outputs a detection result that the vehicle to be detected is qualified if the similarity is smaller than a set value, and otherwise, outputs a detection result that the vehicle to be detected is unqualified.
With continued reference to fig. 1, the vehicle information storage system 100 includes: the information input module 101, the first analysis module 102, the classification module 103 and the vehicle information storage module 104 are sequentially connected; the first analysis module 102 is configured to analyze the vehicle information from the information input module 101 to obtain a vehicle feature of a corresponding vehicle; the classification module 103 is configured to classify the vehicle information according to the vehicle feature, to obtain first vehicle feature data; the vehicle information storage module 104 is configured to store first vehicle characteristic data.
With continued reference to fig. 1, the data acquisition system includes: the monitoring device 200, the camera control module 202, the main camera device 204 and the acquisition module 203 are connected in sequence, wherein the monitoring device 200 is used for monitoring whether a vehicle to be detected exists on the detection platform; the camera control module 202 is configured to generate a driving signal according to a monitoring result of the vehicle to be detected on the detection table fed back by the monitoring device 200; the main camera 204 is configured to capture the vehicle to be detected according to the received driving signal, so as to obtain vehicle image data; and the acquisition module 203 is used for collecting the vehicle image data.
With continued reference to fig. 1, the method further includes: the first feedback module 113, the alarm control module 116 and the alarm device 400 are sequentially connected; the first feedback module 113 is further connected to the comparison module 112; the first feedback module 113 is configured to transmit the detection result output by the comparison module 112 to the alarm control module 116; the alarm control module 116 correspondingly generates a driving signal according to the detection result; the alarm device 400 sends out corresponding prompt information according to the corresponding driving signal.
With continued reference to fig. 1, the data acquisition system further includes: a second analysis module 110; a data extraction module 111; and an image extraction module 114 connected to the second analysis module 110 and the acquisition module 203, respectively; the image extraction module 114 is configured to perform feature extraction on the received vehicle image data by using a deep convolutional neural network to obtain second vehicle feature data, and the second analysis module 110 is further connected to the vehicle information storage module 104, and analyze the second vehicle feature data according to the first vehicle feature data to obtain an analysis result; the second analysis module 110 is further connected to the data extraction module 111, where the data extraction module 111 is configured to extract a feature class required by the first vehicle feature data, where the first vehicle feature data is extracted according to the second vehicle feature data in the image extraction module 114. The obtained first feature data and the vehicle data feature to be detected obtained by the image extraction module 114 are compared in the comparison module 112, so as to obtain the similarity. The first feedback module 113 outputs the detection result to the alarm control module 116 and the recording module 304.
With continued reference to fig. 1, the data acquisition system further includes: an auxiliary image pickup device 201 connected to the image pickup control module 202 and the acquisition module 203, respectively; and a second feedback module 115 connected to the camera control module 202, the image extraction module 114, and the alarm control module 116, respectively. When the image extraction module 114 performs feature extraction on the received vehicle image data, if second vehicle feature data is not obtained, the main camera 204 is damaged; the image extraction module 114 generates information that the characteristic signal is not extracted and transmits the information to the second feedback module 115; the second feedback module 115 transmits the information that the characteristic signal is not extracted to the alarm control module 116; the alarm control module 116 is configured to drive the alarm device 400 to send out alarm information, so as to remind an operator to repair the main camera device 204 in time; the second feedback module 115 transmits the information of the feature signal not extracted to the camera control module 202; the image capturing control module 202 controls the auxiliary image capturing device 201 to be turned on and the main image capturing device 204 to be turned off; the auxiliary image capturing device 201 is configured to capture the vehicle to be detected, and obtain the vehicle image data, so that the vehicle detection system can continue to detect the vehicle.
With continued reference to fig. 1, the method further includes: a recording system 300, a monitoring platform 500 and a mobile terminal 600 respectively connected with the recording system 300; the recording system 300 is further connected to the first feedback module 113 and the second feedback module 115; the recording system 300 is configured to store the comparison detection result output by the first feedback module 113 and the fault information of the main camera device output by the second feedback module 115; the monitoring platform 500 and the mobile terminal 600 are used for checking the detection result and fault information of the main camera device.
With continued reference to fig. 1, the recording system 300 includes: the recording module 304 is respectively connected with the first feedback module 113 and the second feedback module 115; the information recording module is used for recording the comparison detection result of the first vehicle characteristic data and the vehicle characteristic data to be detected, which are output by the first feedback module 113, and the information which is output by the second feedback module 115 and appears due to the damage of the camera and is not extracted from the characteristic signals, so as to obtain information record; an alarm information storage module 305, connected to the recording module 304, for storing the information record; the wireless transmission module 306 is respectively connected with the alarm information storage module 305, the mobile terminal 600 and the monitoring platform 500, and the mobile terminal 600 and the monitoring platform 500 directly check the detection result of the vehicle to be detected and the fault information of the main camera device in the information record through the wireless transmission module 306.
The setting storage module 301 is connected to the memory calculation module 302, and is configured to set a storage space of the alarm information storage module 305, and calculate an actual storage space of the alarm information storage module 305; the reminding module 303 and the memory calculating module 302 are respectively connected with the reminding module 303 and the alarm information storage module 305, and are used for calculating a storage space in the alarm information storage module 305, when the storage space is equal to the set value, the memory calculating module 302 controls the reminding module 303 to generate and transmit reminding information, and the reminding information is transmitted to the mobile terminal 600 and the monitoring platform 500 through the wireless transmission module 306, so as to remind an operator of timely cleaning data in the alarm information storage module 305.
As shown in fig. 4, the wireless transmission module 306 includes a 4G module 3061, a 5G module 3062, and a WIFI module 3063.
As shown in fig. 3, the alarm device 400 includes a buzzer 401 and an indicator light 402; the alarm control module 116 generates a first driving signal when receiving the detection result and determining that the vehicle to be detected is qualified, and drives the indicator lamp 402 to light up through the first driving signal so as to remind an operator that the vehicle to be detected is the qualified vehicle; the alarm control module 116 generates a second driving signal when receiving the detection result and determining that the vehicle to be detected is not qualified, and drives the buzzer 401 to start through the second driving signal, so as to remind an operator that the vehicle to be detected is not qualified.
As shown in fig. 2, the monitoring device 200 is an infrared rangefinder 210.
According to the embodiment, through the cooperation setting of the information input module, the first analysis module, the classification module and the vehicle information storage module, the vehicle information input through the information input module can be stored in the vehicle information storage module according to the classification of the vehicle characteristics, meanwhile, when the collected vehicle images are processed, the image extraction module, the second analysis module and the data extraction module are used for extracting and analyzing the characteristic points on the vehicle images, after analysis, the corresponding vehicle information is extracted through the data extraction module and transmitted to the comparison module, at the moment, the comparison module only needs to compare the collected vehicle images with the extracted vehicle information, whether the vehicle is qualified or not can be detected, and therefore the vehicle detection system can be used for rapidly detecting whether the vehicle is qualified or not.
According to the embodiment, when the image extraction module cannot extract the characteristic information from the acquired vehicle image, the damage of the main camera device is illustrated, at the moment, the image extraction module transmits signals to the second feedback module, the second feedback module transmits signals to the alarm control module, the alarm control module is used for opening the alarm device, then, an operator is reminded of timely maintaining the main camera device through the alarm device, meanwhile, the second feedback module transmits the signals to the camera control module, then, the auxiliary camera device is opened through the camera control module, the main camera device is closed, at the moment, the auxiliary camera device is used for shooting a vehicle, and the vehicle detection system can continue to detect the vehicle.
According to the embodiment, the detection result of the vehicle and the fault information of the main camera device are recorded through the recording system, and through the wireless transmission module, wireless transmission can be achieved between the recording system and the mobile terminal and between the recording system and the monitoring platform, and further a user can inquire the detection result of the vehicle and the fault information of the main camera device through the mobile terminal and the monitoring platform.
In summary, the invention relates to the technical field of vehicle detection, and discloses a vehicle detection system based on a convolutional neural network, which comprises a monitoring device, a camera control module, a main camera device, an auxiliary camera device, an acquisition module, an image extraction module, a second feedback module, a comparison module, a data extraction module, a second analysis module, a first feedback module, an alarm control module, an alarm device and a vehicle information storage system. According to the vehicle information classifying and storing device, the vehicle information can be classified and stored through the vehicle information storing system, then, the characteristic points on the vehicle image are extracted and analyzed through the image extracting module, the second analyzing module and the data extracting module, and the corresponding vehicle information is extracted through the data extracting module, so that the comparison module only needs to compare the collected vehicle image with the extracted vehicle information, and whether the vehicle is qualified or not can be detected.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
It should be noted that the apparatus and methods disclosed in the embodiments herein may be implemented in other ways. The apparatus embodiments described above are merely illustrative, for example, flow diagrams and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments herein. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments herein may be integrated together to form a single part, or the modules may exist alone, or two or more modules may be integrated to form a single part.
While the present invention has been described in detail through the foregoing description of the preferred embodiment, it should be understood that the foregoing description is not to be considered as limiting the invention. Many modifications and substitutions of the present invention will become apparent to those of ordinary skill in the art upon reading the foregoing. Accordingly, the scope of the invention should be limited only by the attached claims.
Claims (6)
1. A vehicle detection system based on a convolutional neural network, comprising:
a vehicle information storage system (100) for classifying vehicle information according to vehicle characteristics to obtain first vehicle characteristic data and storing the first vehicle characteristic data;
the vehicle information storage system (100) includes:
the system comprises an information input module (101), a first analysis module (102), a classification module (103) and a vehicle information storage module (104) which are connected in sequence;
the first analysis module (102) is used for analyzing the vehicle information from the information input module (101) to obtain the vehicle characteristics of the corresponding vehicle;
the classification module (103) is used for classifying the vehicle information according to the vehicle characteristics to obtain first vehicle characteristic data;
the vehicle information storage system (100) is configured to store first vehicle characteristic data;
the data acquisition system is used for acquiring vehicle image data of the vehicle to be detected;
the data acquisition system comprises:
a monitoring device (200), a camera control module (202), a main camera device (204) and an acquisition module (203) which are connected in sequence,
the monitoring device (200) is used for monitoring whether a vehicle to be detected exists on the detection table;
the camera control module (202) is used for generating a driving signal according to the monitoring result of the vehicle to be detected on the detection table fed back by the monitoring device (200);
the main camera device (204) is used for shooting the vehicle to be detected according to the received driving signal to obtain vehicle image data;
-an acquisition module (203) for collecting the vehicle image data;
further comprises: the first feedback module (113), the alarm control module (116) and the alarm device (400) are sequentially connected;
the first feedback module (113) is also connected with the contrast module (112);
the first feedback module (113) is used for transmitting the detection result output by the comparison module (112) to the alarm control module (116);
the alarm control module (116) correspondingly generates a driving signal according to the detection result;
the alarm device (400) sends out corresponding prompt information according to the corresponding driving signal;
the data acquisition system further comprises:
a second analysis module (110);
a data extraction module (111);
and an image extraction module (114) connected to the second analysis module (110) and the acquisition module (203), respectively;
the image extraction module (114) is used for carrying out feature extraction on the vehicle image data received by the acquisition module (203) by adopting a deep convolutional neural network to obtain second vehicle feature data,
the second analysis module (110) is further connected with the vehicle information storage module (104) and is used for analyzing the second vehicle characteristic data according to the first vehicle characteristic data to obtain an analysis result; the second analysis module (110) is further connected to the data extraction module (111), and the data extraction module (111) is configured to extract a feature class of the first vehicle feature data according to the second vehicle feature data in the image extraction module (114); an auxiliary imaging device (201) connected to the imaging control module (202) and the acquisition module (203), respectively;
and a second feedback module (115) respectively connected to the imaging control module (202), the image extraction module (114) and the alarm control module (116);
when the image extraction module (114) performs feature extraction on the received vehicle image data, if second vehicle feature data is not obtained, the main camera device (204) is damaged;
the image extraction module (114) generates information of the characteristic signal which is not extracted when the second analysis module (110) does not extract the characteristic signal and transmits the information to the second feedback module (115);
the second feedback module (115) transmits the information of the unextracted characteristic signals to the alarm control module (116);
the alarm control module (116) is used for driving the alarm device (400) to send out alarm information so as to remind operators of timely maintaining the main camera device (204);
the second feedback module (115) transmits the information of the unextracted characteristic signals to the camera control module (202);
the image pickup control module (202) controls the auxiliary image pickup device (201) to be turned on and the main image pickup device (204) to be turned off;
the auxiliary image pickup device (201) is used for shooting the vehicle to be detected to obtain the vehicle image data;
and the comparison module (112) is respectively connected with the vehicle information storage system (100) and the data acquisition system, compares the received first vehicle characteristic data with the vehicle image data to obtain similarity, outputs a detection result which is qualified for the vehicle to be detected if the similarity is smaller than a set value, and otherwise, outputs a detection result which is unqualified for the vehicle to be detected.
2. The convolutional neural network-based vehicle detection system of claim 1, wherein the vehicle information storage system (100) comprises:
the system comprises an information input module (101), a first analysis module (102), a classification module (103) and a vehicle information storage module (104) which are connected in sequence;
the first analysis module (102) is used for analyzing the vehicle information from the information input module (101) to obtain the vehicle characteristics of the corresponding vehicle;
the classification module (103) is used for classifying the vehicle information according to the vehicle characteristics to obtain first vehicle characteristic data;
the vehicle information storage system (100) is configured to store first vehicle characteristic data.
3. The convolutional neural network-based vehicle detection system of claim 2, further comprising: a recording system (300), a monitoring platform (500) and a mobile terminal (600) respectively connected with the recording system (300);
the recording system (300) is further connected with the first feedback module (113) and the second feedback module (115);
the recording system (300) is used for storing a comparison result of the first vehicle characteristic data and the vehicle characteristic data to be detected, which are output by the first feedback module (113), and information of non-extracted characteristic signals, which are output by the second feedback module (115) and occur due to damage of a camera;
the monitoring platform (500) and the mobile terminal (600) are used for checking the comparison result and fault information of the main camera device.
4. A convolutional neural network-based vehicle detection system as recited in claim 3, wherein said recording system (300) comprises:
the recording module (304) is respectively connected with the first feedback module (113) and the second feedback module (115); the device is used for recording the comparison result of the required first vehicle characteristic data and the vehicle characteristic data to be detected, which are output by the first feedback module (113), and the information of the non-extracted characteristic signals, which are output by the second feedback module (115) and occur due to the damage of the camera, so as to obtain information records;
an alarm information storage module (305) connected with the recording module (304) and used for storing the information record;
the wireless transmission module (306) is respectively connected with the alarm information storage module (305), the mobile terminal (600) and the monitoring platform (500), and the mobile terminal (600) and the monitoring platform (500) directly check the detection result of the vehicle to be detected and the fault information of the main camera device in the information record through the wireless transmission module (306);
the setting storage module (301) is connected with the memory calculation module (302) and is used for setting the storage space of the alarm information storage module (305) and calculating the actual storage space of the alarm information storage module (305);
a reminder module (303),
the memory calculation module (302) is respectively connected with the reminding module (303) and the alarm information storage module (305) and is used for calculating the storage space in the alarm information storage module (305), when the storage space is equal to the set value, the memory calculation module (302) controls the reminding module (303) to generate and transmit reminding information,
the reminding information is transmitted to the mobile terminal (600) and the monitoring platform (500) through the wireless transmission module (306) so as to remind operators of timely cleaning the data in the alarm information storage module (305).
5. The convolutional neural network-based vehicle detection system of claim 4, wherein the wireless transmission module (306) comprises a 4G module (3061), a 5G module (3062), and a WIFI module (3063).
6. The convolutional neural network-based vehicle detection system of claim 5, wherein the alarm device (400) comprises a buzzer (401) and an indicator light (402);
the alarm control module (116) generates a first driving signal when receiving the detection result and judging that the vehicle to be detected is qualified, and drives the indicator lamp (402) to light up through the first driving signal so as to remind an operator that the vehicle to be detected is the qualified vehicle;
and the alarm control module (116) generates a second driving signal when receiving the detection result and judging that the vehicle to be detected is unqualified, and drives the buzzer (401) to start through the second driving signal so as to remind an operator that the vehicle to be detected is the unqualified vehicle.
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