CN112288695A - Factory production area target identification system - Google Patents
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- CN112288695A CN112288695A CN202011121454.6A CN202011121454A CN112288695A CN 112288695 A CN112288695 A CN 112288695A CN 202011121454 A CN202011121454 A CN 202011121454A CN 112288695 A CN112288695 A CN 112288695A
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30248—Vehicle exterior or interior
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Abstract
The invention relates to a factory production area target identification system, which comprises: and the state identification device is used for taking the corresponding vehicle body target as a forward vehicle body target when the third analysis mechanism identifies the steering wheel imaging area, taking the corresponding vehicle body target as a forward vehicle body target when the third analysis mechanism identifies the steering wheel imaging area and the second reference mean value is larger than the first reference mean value and the numerical value exceeding the first reference mean value is larger than a preset depth threshold value, and taking the corresponding vehicle body target as a reverse vehicle body target when the third analysis mechanism identifies the steering wheel imaging area and the second reference mean value is smaller than or equal to the first reference mean value. The target identification system of the factory production area is compact in design and operation is saved. The compliance of the judged retrograde vehicle is judged only when the depth of the steering wheel scene is less than the depth of the whole vehicle field, so that the computation amount of real-time processing is reduced.
Description
Technical Field
The invention relates to the field of factory monitoring, in particular to a factory production area target identification system.
Background
Factories, also known as manufacturing plants, are a type of large industrial building used to produce goods. Most factories have production lines made up of large machines or equipment. Capital-oriented machinery mass production, i.e., a capital-oriented industrial site that uses mechanized labor instead of manual labor, is widely referred to in recent times of the world. In 18-19 th century, through industrial revolution, machines are widely applied in production, and a solid material technology foundation is laid for a capital-oriented production mode. Capital-oriented economy relies on mechanized mass production to finally overcome construction economy and small commodity economy, and establishes the dominance of the capital-oriented economy.
Before mass transportation became widespread, factories needed to be located in places where workers were dense and in industrial areas. Therefore, early factories were mostly located in cities, and even cities developed with factory construction. Plants also tend to build up-many times the finished goods or waste from one plant can become the feedstock for another plant.
Later, transportation networks such as canals and railways have been expanding with the flourishing of factories, and factories have begun to be built in the areas of low-cost energy, raw materials or markets nearby. The perfection of the transportation network is also one of the considerations for site selection of the factory: in the past, factories are built in the field where no people exist but the traffic connection is convenient, and as a result, the development is successful and the profit is obtained. Since factories typically produce pollution, many factories are built in specially planned suburbs, and workers commute between residential factories.
Disclosure of Invention
The invention has at least the following two important points:
(1) the complex operation mode for simultaneously detecting the license plate numbers of all vehicles is replaced, and the mode for judging the compliance of the judged retrograde vehicles only when the depth of the steering wheel scene is less than the depth of the whole vehicle field is adopted, so that the operation amount of real-time processing is reduced;
(2) a cloud computing network element is employed for pre-storing each license plate number that is allowed to go backwards on a road within a production area of a factory.
According to an aspect of the present invention, there is provided a factory production area target identification system, the system comprising:
and the state identification equipment is respectively connected with the second analysis mechanism and the third analysis mechanism and is used for taking the corresponding vehicle body target as the forward vehicle body target when the third analysis mechanism identifies the steering wheel imaging area.
More specifically, in the factory production area target identification system according to the present invention:
the state identification equipment is further used for taking the corresponding vehicle body target as the forward vehicle body target when the third analysis mechanism identifies the steering wheel imaging area and the second reference mean value is larger than the first reference mean value and the value exceeding the first reference mean value is larger than a preset depth of field threshold value.
More specifically, the target identification system for factory production areas according to the present invention further comprises:
the state identification device is also used for taking the corresponding vehicle body target as a retrograde vehicle body target when the third analysis mechanism identifies the steering wheel imaging area and the second reference mean value is less than or equal to the first reference mean value;
the state identification equipment is further used for taking the corresponding vehicle body target as a suspected retrograde vehicle body target when the third analysis mechanism identifies that the steering wheel imaging area and the second reference mean value are larger than the first reference mean value, and the numerical value exceeding the first reference mean value is smaller than or equal to the preset depth of field threshold value;
the cloud computing network element is used for pre-storing each license plate number which is allowed to run in the reverse direction on a road in a production area of a factory;
the signal detection mechanism is connected with the cloud computing network element through a network, is also connected with the state identification equipment, and is used for judging whether the license plate number corresponding to the retrograde vehicle body target exists in the license plate numbers stored in the cloud computing network element, when the license plate number corresponding to the retrograde vehicle body target does not serve as the illegal license plate number, and otherwise, the license plate number corresponding to the retrograde vehicle body target serves as the illegal license plate number;
the monitoring snapshot mechanism is arranged in a production area of a factory and used for executing snapshot operation on a road environment in the production area so as to obtain a corresponding environment snapshot image, and the monitoring snapshot mechanism is positioned above an entrance intersection of a road in the production area;
the combined filtering equipment is arranged in an explosion-proof box of a factory, is connected with the monitoring snapshot mechanism, and is used for executing combined filtering processing on the received environment snapshot image so as to obtain and output a corresponding combined filtering image;
the smoothing filtering device is connected with the combined filtering device and used for carrying out edge-preserving smoothing filtering processing on the received combined filtering image so as to obtain and output a corresponding smoothing filtering image;
the edge sharpening device is connected with the smooth filtering device and is used for carrying out edge sharpening processing on the received smooth filtering image so as to obtain and output a corresponding real-time sharpened image;
the first analysis mechanism is connected with the edge sharpening device and is used for identifying each vehicle body target in the real-time sharpened image and outputting an image area occupied by the vehicle body target as a vehicle body pattern;
the second analysis mechanism is respectively connected with the edge sharpening device and the first analysis mechanism and is used for executing the following actions on each car body pattern: identifying each depth value of each constituent pixel of the vehicle body pattern, and performing mean value calculation on each depth value of each constituent pixel of the vehicle body pattern to obtain a first reference mean value;
the third analysis mechanism is connected with the second analysis mechanism and is used for executing the following actions on each vehicle body pattern: and identifying a steering wheel imaging area in the vehicle body pattern based on the profile characteristics of the steering wheel, and performing mean value calculation on each depth value of each pixel of the steering wheel imaging area to obtain a second reference mean value.
The target identification system of the factory production area is compact in design and operation is saved. The compliance of the judged retrograde vehicle is judged only when the depth of the steering wheel scene is less than the depth of the whole vehicle field, so that the computation amount of real-time processing is reduced.
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Embodiments of the invention will now be described with reference to the accompanying drawings, in which:
fig. 1 is a diagram illustrating an internal structure of a factory production area target identification system according to an embodiment of the present invention.
Detailed Description
Embodiments of the factory production area target identification system of the present invention will be described in detail below with reference to the accompanying drawings.
Cloud computing is one of distributed computing, and means that a huge data computing processing program is decomposed into countless small programs through a network cloud, and then the small programs are processed and analyzed through a system consisting of a plurality of servers to obtain results and are returned to a user. In the early stage of cloud computing, simple distributed computing is adopted, task distribution is solved, and computing results are merged. Thus, cloud computing is also known as grid computing. By the technology, tens of thousands of data can be processed in a short time (several seconds), so that strong network service is achieved.
At present, the cloud service is not just distributed computing, but a result of hybrid evolution and leap of computer technologies such as distributed computing, utility computing, load balancing, parallel computing, network storage, hot backup redundancy, virtualization and the like.
The cloud is a network in essence, and in a narrow sense, the cloud computing is a network for providing resources, a user can obtain the resources on the cloud at any time and use the resources according to the required quantity, the cloud computing can be regarded as infinitely expanded, the cloud can be used as a water supply plant only by paying according to the use quantity, and the cloud can receive water at any time and pay the water supply plant according to the water consumption of the user without limitation.
In a broad sense, cloud computing is a service related to information technology, software and the internet, the computing resource sharing pool is called cloud, the cloud computing integrates a plurality of computing resources, automatic management is realized through software, and the resources can be rapidly provided only by few people. That is, the computing power as a commodity can be circulated on the internet, like water, electricity, and gas, can be conveniently used, and is low in price.
In short, cloud computing is not a brand-new network technology, but a brand-new network application concept, and the core concept of cloud computing is to provide fast and safe cloud computing service and data storage on a website by taking the internet as a center, so that every person using the internet can use huge computing resources and data centers on the network.
At present, because the production areas of most factories are relatively important and relatively dangerous production environments, on one hand, vehicles with low authorization level are not expected to appear on the inner roads of the production areas, so that the normal production order is prevented from being interfered, and the production safety of factories is influenced, on the other hand, for some emergency states, important vehicles need to be authorized with higher level, for example, the vehicles are allowed to run backwards, so that the speed and the efficiency of solving the accident are improved, at the moment, if all vehicles are simultaneously detected to run backwards, the transport capacity is obviously large, a mechanism capable of primarily judging and screening the vehicles running backwards logically is needed, and only the screened vehicles running backwards are subjected to authority verification, so that the computation amount of real-time data processing is reduced.
In order to overcome the defects, the invention builds a factory production area target identification system, and can effectively solve the corresponding technical problem.
Fig. 1 is a diagram illustrating an internal structure of a factory production area target identification system according to an embodiment of the present invention, the system including:
the state identification equipment is respectively connected with the second analysis mechanism and the third analysis mechanism and is used for taking the corresponding vehicle body target as a forward vehicle body target when the third analysis mechanism identifies the steering wheel imaging area;
the state identification equipment is further used for taking the corresponding vehicle body target as a forward vehicle body target when the third analysis mechanism identifies that the steering wheel imaging area and the second reference mean value are larger than the first reference mean value and the value exceeding the first reference mean value is larger than a preset depth-of-field threshold value;
the state identification device is also used for taking the corresponding vehicle body target as a retrograde vehicle body target when the third analysis mechanism identifies the steering wheel imaging area and the second reference mean value is less than or equal to the first reference mean value;
the state identification equipment is further used for taking the corresponding vehicle body target as a suspected retrograde vehicle body target when the third analysis mechanism identifies that the steering wheel imaging area and the second reference mean value are larger than the first reference mean value, and the numerical value exceeding the first reference mean value is smaller than or equal to the preset depth of field threshold value;
the cloud computing network element is used for pre-storing each license plate number which is allowed to run in the reverse direction on a road in a production area of a factory;
the signal detection mechanism is connected with the cloud computing network element through a network, is also connected with the state identification equipment, and is used for judging whether the license plate number corresponding to the retrograde vehicle body target exists in the license plate numbers stored in the cloud computing network element, when the license plate number corresponding to the retrograde vehicle body target does not serve as the illegal license plate number, and otherwise, the license plate number corresponding to the retrograde vehicle body target serves as the illegal license plate number;
the monitoring snapshot mechanism is arranged in a production area of a factory and used for executing snapshot operation on a road environment in the production area so as to obtain a corresponding environment snapshot image, and the monitoring snapshot mechanism is positioned above an entrance intersection of a road in the production area;
the combined filtering equipment is arranged in an explosion-proof box of a factory, is connected with the monitoring snapshot mechanism, and is used for executing combined filtering processing on the received environment snapshot image so as to obtain and output a corresponding combined filtering image;
the smoothing filtering device is connected with the combined filtering device and used for carrying out edge-preserving smoothing filtering processing on the received combined filtering image so as to obtain and output a corresponding smoothing filtering image;
the edge sharpening device is connected with the smooth filtering device and is used for carrying out edge sharpening processing on the received smooth filtering image so as to obtain and output a corresponding real-time sharpened image;
the first analysis mechanism is connected with the edge sharpening device and is used for identifying each vehicle body target in the real-time sharpened image and outputting an image area occupied by the vehicle body target as a vehicle body pattern;
the second analysis mechanism is respectively connected with the edge sharpening device and the first analysis mechanism and is used for executing the following actions on each car body pattern: identifying each depth value of each constituent pixel of the vehicle body pattern, and performing mean value calculation on each depth value of each constituent pixel of the vehicle body pattern to obtain a first reference mean value;
the third analysis mechanism is connected with the second analysis mechanism and is used for executing the following actions on each vehicle body pattern: and identifying a steering wheel imaging area in the vehicle body pattern based on the profile characteristics of the steering wheel, and performing mean value calculation on each depth value of each pixel of the steering wheel imaging area to obtain a second reference mean value.
Next, the specific structure of the factory production area target identification system of the present invention will be further described.
In the factory production area target identification system:
the third analysis mechanism recognizing the steering wheel imaging area includes: and when the number of pixels occupied by the steering wheel imaging area identified by the third analysis mechanism is greater than a minimum number threshold, determining that the steering wheel imaging area is identified by the third analysis mechanism.
In the factory production area target identification system:
identifying a steering wheel imaging area in the vehicle body pattern based on the steering wheel profile features comprises: the identified steering wheel imaging region corresponds to an upper portion of the steering wheel object.
In the factory production area target identification system:
judging whether the license plate number corresponding to the retrograde vehicle body target exists in each license plate number stored by the cloud computing network element comprises the following steps: and performing OCR recognition on the vehicle body pattern corresponding to the retrograde vehicle body target to obtain a corresponding license plate number.
In the factory production area target identification system, the method further comprises:
and the voice playing chip is electrically connected with the signal detection mechanism and is used for receiving and playing the text information corresponding to the illegal license plate number in real time.
In the factory production area target identification system, the method further comprises:
ADSL communication equipment which is respectively connected with the state identification equipment and the signal detection mechanism and is used for receiving and reporting each fault code of the state identification equipment or the signal detection mechanism.
In the factory production area target identification system:
the state identification equipment is internally provided with a first fault self-checking unit used for carrying out self-checking on internal faults of the state identification equipment and sending fault codes.
In the factory production area target identification system:
a second fault self-checking unit is arranged in the signal detection mechanism and used for carrying out self-checking on internal faults of the signal detection mechanism and sending fault codes;
the first fault self-checking unit and the second fault self-checking unit are respectively realized by editable logic devices with different models;
the state identification equipment is also internally provided with a first electric quantity measuring unit which is used for measuring the current residual electric quantity of the state identification equipment;
the signal detection mechanism is also internally provided with a second electric quantity measurement unit which is used for measuring the current residual electric quantity of the signal detection mechanism;
the first electric quantity measuring unit and the second electric quantity measuring unit share the same quartz oscillation device.
In the factory production area target identification system, the method further comprises:
the load detection equipment is used for receiving the utilization rate of the current core of the state identification equipment, and the utilization rate is a percentage;
the data identification equipment is connected with the load detection equipment and is used for sending a load overfill signal when the utilization rate exceeds the limit;
wherein the data discrimination apparatus is further configured to signal a sufficient load when the received utilization is not exceeded.
In addition, in the target identification system of the factory production area, ADSL is a technology for providing broadband data transmission service to homes and offices through the existing ordinary telephone line, and can provide very high data transmission bandwidth wide enough for telecommunication industry to be surreptitious. The ADSL solution does not require modification of the signal transmission line, and it only requires a pair of special MODEMs, one of which is connected to the user's computer and the other of which is installed in the telecommunications center of the telecommunications company, and the connections between them are still ordinary telephone lines. The speed of data transmission is indeed much improved after the ADSL scheme is adopted. The transmission speed of the ADSL scheme is about 50 times that of the ISDN scheme and 20 times that of the satellite scheme, and the ADSL does not need to change the line, so that the ADSL is a feasible network acceleration scheme. ADSL was designed for video on demand at the beginning of its development. With the rapid development of the internet, ADSL has changed over as a technology for accessing the internet at a high speed, so that users feel new and it becomes possible to provide multimedia services on the existing internet. Companies providing telecommunication services are worried that they can configure ASDL equipment according to the user amount very flexibly without investing astronomical digital funds for line replacement, and provide more online services for users.
It is to be understood that while the present invention has been described in conjunction with the preferred embodiments thereof, it is not intended to limit the invention to those embodiments. It will be apparent to those skilled in the art from this disclosure that many changes and modifications can be made, or equivalents modified, in the embodiments of the invention without departing from the scope of the invention. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the scope of the protection of the technical solution of the present invention, unless the contents of the technical solution of the present invention are departed.
Claims (9)
1. A factory production area target identification system, the system comprising:
and the state identification equipment is respectively connected with the second analysis mechanism and the third analysis mechanism and is used for taking the corresponding vehicle body target as the forward vehicle body target when the third analysis mechanism identifies the steering wheel imaging area.
2. The factory production area target identification system of claim 1, wherein:
the state identification equipment is further used for taking the corresponding vehicle body target as the forward vehicle body target when the third analysis mechanism identifies the steering wheel imaging area and the second reference mean value is larger than the first reference mean value and the value exceeding the first reference mean value is larger than a preset depth of field threshold value.
3. The factory production area target identification system of claim 2, wherein the system further comprises:
the state identification device is also used for taking the corresponding vehicle body target as a retrograde vehicle body target when the third analysis mechanism identifies the steering wheel imaging area and the second reference mean value is less than or equal to the first reference mean value;
the state identification equipment is further used for taking the corresponding vehicle body target as a suspected retrograde vehicle body target when the third analysis mechanism identifies that the steering wheel imaging area and the second reference mean value are larger than the first reference mean value, and the numerical value exceeding the first reference mean value is smaller than or equal to the preset depth of field threshold value;
the cloud computing network element is used for pre-storing each license plate number which is allowed to run in the reverse direction on a road in a production area of a factory;
the signal detection mechanism is connected with the cloud computing network element through a network, is also connected with the state identification equipment, and is used for judging whether the license plate number corresponding to the retrograde vehicle body target exists in the license plate numbers stored in the cloud computing network element, when the license plate number corresponding to the retrograde vehicle body target does not serve as the illegal license plate number, and otherwise, the license plate number corresponding to the retrograde vehicle body target serves as the illegal license plate number;
the monitoring snapshot mechanism is arranged in a production area of a factory and used for executing snapshot operation on a road environment in the production area so as to obtain a corresponding environment snapshot image, and the monitoring snapshot mechanism is positioned above an entrance intersection of a road in the production area;
the combined filtering equipment is arranged in an explosion-proof box of a factory, is connected with the monitoring snapshot mechanism, and is used for executing combined filtering processing on the received environment snapshot image so as to obtain and output a corresponding combined filtering image;
the smoothing filtering device is connected with the combined filtering device and used for carrying out edge-preserving smoothing filtering processing on the received combined filtering image so as to obtain and output a corresponding smoothing filtering image;
the edge sharpening device is connected with the smooth filtering device and is used for carrying out edge sharpening processing on the received smooth filtering image so as to obtain and output a corresponding real-time sharpened image;
the first analysis mechanism is connected with the edge sharpening device and is used for identifying each vehicle body target in the real-time sharpened image and outputting an image area occupied by the vehicle body target as a vehicle body pattern;
the second analysis mechanism is respectively connected with the edge sharpening device and the first analysis mechanism and is used for executing the following actions on each car body pattern: identifying each depth value of each constituent pixel of the vehicle body pattern, and performing mean value calculation on each depth value of each constituent pixel of the vehicle body pattern to obtain a first reference mean value;
the third analysis mechanism is connected with the second analysis mechanism and is used for executing the following actions on each vehicle body pattern: identifying a steering wheel imaging area in the vehicle body pattern based on the profile characteristics of the steering wheel, and performing mean value calculation on each depth of field value of each pixel of the steering wheel imaging area to obtain a second reference mean value;
wherein the third analysis mechanism identifying a steering wheel imaging region comprises: when the number of pixels occupied by the steering wheel imaging area identified by the third analysis mechanism is greater than a minimum number threshold, determining that the steering wheel imaging area is identified by the third analysis mechanism;
wherein identifying a steering wheel imaging region in the vehicle body pattern based on the steering wheel profile features comprises: the identified steering wheel imaging region corresponds to an upper portion of the steering wheel object.
4. The factory production area target identification system of claim 3, wherein:
judging whether the license plate number corresponding to the retrograde vehicle body target exists in each license plate number stored by the cloud computing network element comprises the following steps: and performing OCR recognition on the vehicle body pattern corresponding to the retrograde vehicle body target to obtain a corresponding license plate number.
5. The factory production area target identification system of claim 4, wherein the system further comprises:
and the voice playing chip is electrically connected with the signal detection mechanism and is used for receiving and playing the text information corresponding to the illegal license plate number in real time.
6. The factory production area target identification system of claim 5, wherein the system further comprises:
ADSL communication equipment which is respectively connected with the state identification equipment and the signal detection mechanism and is used for receiving and reporting each fault code of the state identification equipment or the signal detection mechanism.
7. The factory production area target identification system of claim 6, wherein:
the state identification equipment is internally provided with a first fault self-checking unit used for carrying out self-checking on internal faults of the state identification equipment and sending fault codes.
8. The factory production area target identification system of claim 7, wherein:
a second fault self-checking unit is arranged in the signal detection mechanism and used for carrying out self-checking on internal faults of the signal detection mechanism and sending fault codes;
the first fault self-checking unit and the second fault self-checking unit are respectively realized by editable logic devices with different models;
the state identification equipment is also internally provided with a first electric quantity measuring unit which is used for measuring the current residual electric quantity of the state identification equipment;
the signal detection mechanism is also internally provided with a second electric quantity measurement unit which is used for measuring the current residual electric quantity of the signal detection mechanism;
the first electric quantity measuring unit and the second electric quantity measuring unit share the same quartz oscillation device.
9. The factory production area target identification system of claim 8, wherein the system further comprises:
the load detection equipment is used for receiving the utilization rate of the current core of the state identification equipment, and the utilization rate is a percentage;
the data identification equipment is connected with the load detection equipment and is used for sending a load overfill signal when the utilization rate exceeds the limit;
wherein the data discrimination apparatus is further configured to signal a sufficient load when the received utilization is not exceeded.
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| CN114549457A (en) * | 2022-02-19 | 2022-05-27 | 江阴瑞兴塑料玻璃制品有限公司 | Transportation target state analysis platform |
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| CN111340003A (en) * | 2020-03-26 | 2020-06-26 | 公安部交通管理科学研究所 | Evidence obtaining method and system for illegal lane change behavior in electronic police blind area |
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| CN113850170A (en) * | 2021-09-17 | 2021-12-28 | 泰州市雷信农机电制造有限公司 | Reverse-running identification system based on block chain storage |
| CN114549457A (en) * | 2022-02-19 | 2022-05-27 | 江阴瑞兴塑料玻璃制品有限公司 | Transportation target state analysis platform |
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