CN112487034A - Double-queue asynchronous image processing method and device - Google Patents
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Abstract
The invention provides a double-queue asynchronous image processing method and device. The double-queue asynchronous image processing device includes: the camera image acquisition module is used for acquiring images, putting acquired image data into an image cache queue and then executing the next image acquisition step; the image cache queue is used for storing the image data acquired by the camera image acquisition module and simultaneously recording the time stamp of the image data when the image data is newly added; the image processing module is used for acquiring image data from the image cache queue in a polling mode, carrying out image processing on the image data, putting an image processing result into the image result queue, and then executing the next image processing step; and the image result queue is used for sequencing the image processing results according to the sequence of the time stamps and sending the image processing results outwards in sequence. The invention has reliable function and low cost, and can effectively avoid the problem that the production requirement can not be met because the image processing time is far longer than the image acquisition time in the prior art.
Description
Technical Field
The invention relates to the field of machine vision image processing, in particular to a double-queue asynchronous image processing method and device.
Background
At present, a typical machine vision processing flow adopted in the industry is to take an acquired image as a drawing step in an image processing process, perform image algorithm processing and other specific steps after drawing, wherein the acquired image and the image algorithm processing together form a complete image processing flow, the steps edited in the flow are sequentially executed in one flow execution process, and the next time is executed after all the steps are executed.
Therefore, under the condition that the image processing time is far longer than the image acquisition time, the image acquisition needs to wait for the next image acquisition after the image processing is finished, the beat of the image acquisition is reduced, and the condition that the production beat cannot be met can be generated.
Disclosure of Invention
In view of the above drawbacks of the prior art, an object of the present invention is to provide a method and an apparatus for processing a dual-queue asynchronous image, which are used to solve the problem in the prior art that the image processing time is much longer than the image acquisition time, which results in that the production requirement cannot be met.
To achieve the above and other related objects, the present invention provides a dual queue asynchronous image processing method, comprising: the camera image acquisition module acquires images, puts acquired image data into an image cache queue and then executes the next image acquisition step; when newly adding image data, the image buffer queue records the time stamp of the image data; the image processing module acquires image data from the image cache queue in a polling mode, performs image processing on the image data, puts an image processing result into an image result queue, and then executes the next image processing step; and the image result queue sorts the image processing results according to the sequence of the time stamps and sends the image processing results outwards in sequence.
In an embodiment of the present invention, the image processing module further includes: a thread pool management submodule; the thread pool management submodule comprises a plurality of pre-established reusable working threads; the method further comprises the following steps: and the thread pool management submodule loads an image processing algorithm by starting the working thread so that the image processing module can process images by using the image processing algorithm.
In an embodiment of the present invention, the image processing module further includes: an algorithm management submodule; the algorithm management submodule comprises a plurality of pre-established image processing algorithms suitable for different service scenes; the method further comprises the following steps: and when the thread pool management submodule starts a working thread to load the image processing algorithm, the corresponding image processing algorithm in the algorithm management submodule is loaded according to different service scenes.
In an embodiment of the present invention, the image result queue is configured to sort the image processing results by using a fast sorting algorithm by default.
In an embodiment of the present invention, the method further includes: and the alarm prompt module monitors the data growth condition of the image cache queue and sends corresponding prompt information.
To achieve the above and other related objects, the present invention provides a dual queue asynchronous image processing apparatus, comprising: the camera image acquisition module is used for acquiring images, putting acquired image data into an image cache queue and then executing the next image acquisition step; the image cache queue is used for storing the image data acquired by the camera image acquisition module and simultaneously recording the time stamp of the image data when the image data is newly added; the image processing module is used for acquiring image data from the image cache queue in a polling mode, carrying out image processing on the image data, putting an image processing result into an image result queue, and then executing the next image processing step; and the image result queue is used for sequencing the image processing results according to the sequence of the time stamps and sending the image processing results outwards in sequence.
In an embodiment of the present invention, the image processing module further includes: a thread pool management submodule; the thread pool management submodule comprises a plurality of pre-established reusable working threads; the thread pool management submodule is used for: and loading an image processing algorithm by starting the working thread so that the image processing module can process images by utilizing the image processing algorithm.
In an embodiment of the present invention, the image processing module further includes: an algorithm management submodule; the algorithm management submodule comprises a plurality of pre-established image processing algorithms suitable for different service scenes; the thread pool management submodule is further configured to: and when the working thread is started to load the image processing algorithm, loading the corresponding image processing algorithm in the algorithm management submodule according to different service scenes.
In an embodiment of the present invention, the image result queue is configured to sort the image processing results by using a fast sorting algorithm by default.
In an embodiment of the present invention, the apparatus further includes: and the alarm prompt module is used for monitoring the data growth condition of the image cache queue and sending out corresponding prompt information.
As described above, the method and the device for processing the double-queue asynchronous image have the advantages of reliable function and low cost, and can effectively solve the problem that the production requirement cannot be met due to the fact that the image processing time is far longer than the image acquisition time in the prior art.
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FIG. 1 is a block diagram of a dual-queue asynchronous image processing apparatus according to an embodiment of the present invention.
Fig. 2 is a flowchart illustrating a method for processing a dual-queue asynchronous image according to an embodiment of the present invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the drawings only show the components related to the present invention rather than the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
In view of the problems in the prior art, the method and the device for processing the image are based on a reasonable data structure queue, a multithreading parallel mode and a reasonable design mode are combined, a simple and practical double-queue asynchronous parallel image processing scheme is designed, and the problem that the production requirement cannot be met due to the fact that the image processing time is far longer than the image acquisition time is solved, and detailed description is provided below.
As shown in fig. 1, the present application provides a dual-queue asynchronous image processing apparatus, which mainly includes the following components: the system comprises a camera image collecting module 1, an image buffer queue 2, an image processing module 3 and an image result queue 4. In an embodiment, preferably, the image processing module 3 further includes a thread pool management submodule 301 and an algorithm management submodule 302. The functions of the respective modules will be described in detail below.
The camera image collecting module 1 is used for collecting images, putting collected image data into the image buffer queue 2, and then executing the next image collecting step.
It should be noted that, a conventional common machine vision processing flow is composed of image acquisition and an image processing algorithm, the image processing algorithm is directly executed after the image acquisition is performed by the camera, the image acquisition is not performed by the camera during the image processing period until the image processing algorithm returns an image processing result, and then the acquisition of the next image is started, so that the efficiency is very low. However, in the present application, the camera image capturing module 1 puts the currently acquired image data into the image buffer queue 2, and then continues the image capturing operation, so that the image capturing frequency can be increased. For example, the camera image capturing module 1 acquires the image data 1 for the first time, stores the image data into the image buffer queue 2, continues to acquire the image data for the second time, acquires the image data 2 for the second time, stores the image data into the image buffer queue 2, and so on. Therefore, even if the image capturing frequency of the camera is greater than the image processing frequency, the image capturing module 1 does not need to wait for blocking, continues to capture images and transmits image data to the subsequent working module through the middle layer of the image buffer queue 2.
It should be noted that, because the implementation details of the camera SDK image capturing of different manufacturers are different, but a series of operations such as connecting the camera, disconnecting the camera, capturing an image have commonality, when developing the camera image capturing module 1, those skilled in the art can abstract these operations into abstract classes, and implement them by using a template method mode and a rewritable method for cameras of different manufacturers, which is not limited in the present invention.
And the image buffer queue 2 is used for storing the image data acquired by the camera image acquisition module 1 and recording the time stamp of the image data when the image data is newly added.
It should be noted that the purpose of the buffer queue is to decouple image capture from image processing as an intermediate layer, Java/C # and other thread security queues supported by language level can be used, and the image buffer queue 2 is a packaged module to interact with other modules, specifically:
1) the image buffer queue 2 receives the image data of the camera image acquisition module 1 and adds the image data to the queue, and the queue records a timestamp while adding the image data so as to facilitate the processing of a subsequent image result queue;
2) the image buffer queue 2 controls queue data first-in first-out to be consumed by the image processing module 2, and manages data concurrency.
The image processing module 3 is configured to acquire image data from the image buffer queue in a polling manner, perform image processing on the image data, place an image processing result in the image result queue 4, and then execute a next image processing step.
In an embodiment, the image processing module 3 further comprises: a thread pool management submodule 301 and an algorithm management submodule 302.
The thread pool management submodule 301 includes a plurality of pre-created reusable working threads, and the thread pool management submodule 301 loads the image processing algorithm by enabling the working threads, so that the image processing module 3 performs image processing by using the image processing algorithm.
It should be noted that creating a thread is an expensive operation, creating a thread for each transient asynchronous operation would generate significant overhead, and to solve this problem, the present application uses a thread pool, allocates a certain resource in advance, puts the resource into the pool, needs a new resource each time, acquires from the pool instead of creating again, and returns to the pool when the resource is no longer used. The advantages of using a thread pool are:
1) the resource expenditure of an operating system is reduced, each working thread can be repeatedly used, and the threads do not need to be frequently established and destroyed;
2) the response speed of the program is improved, and the phenomenon that the program operation is blocked due to the creation of a new thread is avoided;
3) existing mature libraries such as an Executor framework and a Task Parallel Library (TPL for short) can be used, so that threads are managed better, development efficiency is improved, and a program has better maintainability; Java/C # has an execution frame to encapsulate the thread pool, and technicians in the field can choose to adopt the Java/C # when developing the thread pool sub-module 301, so that the development efficiency is effectively improved, a uniform interface is provided, and a clearer and more standard program structure is maintained;
4) thread pool parameters are reasonably set according to conditions such as actual hardware resource production beats, and specific production conditions are effectively attached.
The algorithm management submodule 302 includes a plurality of pre-created image processing algorithms suitable for different service scenes. When the working thread is enabled to load the image processing algorithm, the thread pool management submodule 301 loads the corresponding image processing algorithm in the algorithm management submodule 302 according to different service scenes.
It should be noted that the algorithm management sub-module 302 is responsible for the specific algorithm logic of image processing, and processes the input image data into result data. Because the image processing algorithms required by different service scenes are different, a strategy mode is adopted, so that the program has better expansibility.
And the image result queue 4 is used for sequencing the image processing results according to the sequence of the time stamps and sending the image processing results outwards in sequence.
It should be noted that, because the image processing algorithm of the image processing module 3 is an asynchronous multi-thread parallel processing mode, the image result queue 4 needs to use the time stamp generated when the image data is previously added into the image buffer queue 2 to perform result sorting, so as to maintain the corresponding relationship between the image data and the image processing result.
In detail, the image result queue 4 receives and records all image processing results, sorts the image processing results in sequence from small to large according to the time stamps, and sends the image processing results according to the sorting results, so that the image data and the image processing results are corresponding to each other according to the original sequence. For example, the image processing module 3 sequentially sends the processing result "image result 3" of the image data 3, the processing result "image result 1" of the image data 1, and the processing result "image result 2" of the image data 2 to the image result queue 4, and the image result queue 4 sorts the image results 1 to 3 according to the time stamps of the image data 1 to 3, and sends the image result 1, the image result 2, and the image result 3 to the outside first. In addition, the image results and the image data can be sent to a cloud server so that the cloud server can perform machine learning data processing such as classification, clustering and feature extraction or big data storage and processing, and therefore intelligent manufacturing can be better served.
Preferably, the sorting method of the image result queue 4 is a quick sorting algorithm by default. The average time complexity of the quick sequencing algorithm is O (nlog2n), the space complexity is O (nlog2n), and sequencing can be efficiently completed. In addition, the sorting algorithm can also adopt a strategy mode, and other sorting algorithms such as direct insertion sorting and the like are built in the sorting algorithm, so that the image result queue 4 can realize the switching among the algorithms according to specific service scenes.
In an embodiment, the dual-queue asynchronous image processing apparatus of the present application further includes: and the alarm prompting module (not shown) is used for monitoring the data growth condition of the image cache queue 2 and sending corresponding prompting information. For example, the data growth condition of the image cache queue 2 is displayed to the user by means of automatic mail, enterprise WeChat, nailing or hardware alarm, or a person skilled in the art can set a reminding condition of the alarm prompting module, and the information prompt is performed only when the data growth of the image cache queue 2 reaches a certain threshold value.
To summarize the above, the dual queue asynchronous image processing apparatus of the present application has the following advantages:
1) the method is realized from a software level without purchasing and changing related hardware facilities, and the conventional hardware equipment can achieve the purpose of improving the production beat by adopting the double-queue asynchronous image processing device without changing the hardware equipment, so the method has the advantages of reliable function, simple structure, low cost and the like.
2) The method has a simple and easily-expanded good interface design to support the realization of productization. The asynchronous visual image processing flow can summarize and abstract the execution steps of each module, and the whole process sequentially executes image acquisition, image cache queue, multithreading parallel image algorithm processing and image result processing by adopting a template method mode. In an actual service scene, only a method for rewriting specific camera brand image collection and an image processing algorithm need to be inherited, and common industrial camera brand image collection subclasses can be built in to realize the method, and a user can specify an existing realized brand through configuration options, so that only the image processing algorithm needs to be rewritten every time.
3) On the basis that a double-queue and thread parallel processing mechanism in a thread pool form the core of the device, the system is supported to perform an expansion function, for example, an image cache queue can support a camera to adopt an image to perform image data enqueue, an image processing flow to consume image data to perform dequeue, an image processing module to perform data enqueue and the like in the double-queue asynchronous image processing device of the application, double-queue data can also support systems such as an MES (manufacturing execution system) and the like to perform data reading and viewing, and an image result queue can also support dequeue operation expansion realization of consumption data and the like.
As shown in fig. 2, the present application further provides a method for processing a dual-queue asynchronous image, and since the specific implementation of the method is the same as that of the foregoing device embodiment, the same technical details are not repeated herein.
The double-queue asynchronous image processing method comprises the following steps:
s1: the camera image acquisition module acquires images, puts acquired image data into an image cache queue and then executes the next image acquisition step; and when newly adding image data, the image buffer queue records the time stamp of the image data.
S2: and the image processing module acquires image data from the image cache queue in a polling mode, performs image processing on the image data, puts an image processing result into an image result queue, and then executes the next image processing step.
In one embodiment, the image processing module further comprises: a thread pool management submodule; the thread pool management submodule comprises a plurality of pre-established reusable working threads; and the thread pool management submodule loads an image processing algorithm by starting the working thread so that the image processing module can process images by using the image processing algorithm.
In one embodiment, the image processing module further comprises: an algorithm management submodule; the algorithm management submodule comprises a plurality of pre-established image processing algorithms suitable for different service scenes; and when the thread pool management submodule starts a working thread to load the image processing algorithm, the corresponding image processing algorithm in the algorithm management submodule is loaded according to different service scenes.
S3: and the image result queue sorts the image processing results according to the sequence of the time stamps and sends the image processing results outwards in sequence.
Preferably, the image result queue ranks the image processing results by default using a fast ranking algorithm.
In an embodiment, the dual-queue asynchronous image processing method of the present application further includes: and the alarm prompt module monitors the data growth condition of the image cache queue and sends corresponding prompt information.
In summary, the dual-queue asynchronous image processing method and apparatus of the present invention effectively overcome various disadvantages in the prior art, and have high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (10)
1. A double-queue asynchronous image processing method is characterized by comprising the following steps:
the camera image acquisition module acquires images, puts acquired image data into an image cache queue and then executes the next image acquisition step; when newly adding image data, the image buffer queue records the time stamp of the image data;
the image processing module acquires image data from the image cache queue in a polling mode, performs image processing on the image data, puts an image processing result into an image result queue, and then executes the next image processing step;
and the image result queue sorts the image processing results according to the sequence of the time stamps and sends the image processing results outwards in sequence.
2. The method of claim 1, wherein the image processing module further comprises: a thread pool management submodule; the thread pool management submodule comprises a plurality of pre-established reusable working threads; the method further comprises the following steps:
and the thread pool management submodule loads an image processing algorithm by starting the working thread so that the image processing module can process images by using the image processing algorithm.
3. The method of claim 2, wherein the image processing module further comprises: an algorithm management submodule; the algorithm management submodule comprises a plurality of pre-established image processing algorithms suitable for different service scenes; the method further comprises the following steps:
and when the thread pool management submodule starts a working thread to load the image processing algorithm, the corresponding image processing algorithm in the algorithm management submodule is loaded according to different service scenes.
4. The method of claim 1, wherein the image result queue orders each of the image processing results by default using a quick ordering algorithm.
5. The method of claim 1, further comprising: and the alarm prompt module monitors the data growth condition of the image cache queue and sends corresponding prompt information.
6. A dual queue asynchronous image processing apparatus, comprising:
the camera image acquisition module is used for acquiring images, putting acquired image data into an image cache queue and then executing the next image acquisition step;
the image cache queue is used for storing the image data acquired by the camera image acquisition module and simultaneously recording the time stamp of the image data when the image data is newly added;
the image processing module is used for acquiring image data from the image cache queue in a polling mode, carrying out image processing on the image data, putting an image processing result into an image result queue, and then executing the next image processing step;
and the image result queue is used for sequencing the image processing results according to the sequence of the time stamps and sending the image processing results outwards in sequence.
7. The apparatus of claim 6, wherein the image processing module further comprises: a thread pool management submodule; the thread pool management submodule comprises a plurality of pre-established reusable working threads; the thread pool management submodule is used for: and loading an image processing algorithm by starting the working thread so that the image processing module can process images by utilizing the image processing algorithm.
8. The apparatus of claim 7, wherein the image processing module further comprises: an algorithm management submodule; the algorithm management submodule comprises a plurality of pre-established image processing algorithms suitable for different service scenes; the thread pool management submodule is further configured to: and when the working thread is started to load the image processing algorithm, loading the corresponding image processing algorithm in the algorithm management submodule according to different service scenes.
9. The apparatus of claim 6, wherein the image result queue orders each of the image processing results by default using a fast ordering algorithm.
10. The apparatus of claim 6, further comprising: and the alarm prompt module is used for monitoring the data growth condition of the image cache queue and sending out corresponding prompt information.
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