CN112116015A - Material classification method and device based on image processing and computer equipment - Google Patents
Material classification method and device based on image processing and computer equipment Download PDFInfo
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Abstract
The invention provides a material classification method, a material classification device and computer equipment based on image processing. Second, a second material category list is determined for which the material image data matches based on the first material category list. The material image data is then sorted according to the second material category list. So, carry out classification to the material of waiting to classify who obtains through setting up first material category list and second material category list, like this when the category of a material has the multiple, need not to classify through the manual work, further can improve classification efficiency, can improve categorised accuracy simultaneously.
Description
Technical Field
The invention relates to the technical field of material classification, in particular to a material classification method and device based on image processing and computer equipment.
Background
Science and technology are key factors for promoting the development of human society, and the use of a large number of materials is involved in the research and development process of science and technology, and the classification of the materials is a crucial step in the research and development process of science and technology.
However, at present, classification is mainly performed manually by manually identifying the material category, and when there are a plurality of material categories, manual classification may result in low classification efficiency and inaccurate classification.
Disclosure of Invention
In order to improve the problems, the invention provides a material classification method and device based on image processing and a computer device.
The invention provides a material classification method based on image processing, which comprises the following steps:
inputting material image data corresponding to a target material in a sample material set; wherein the material image data comprises a set of material image data to be identified within a same monitoring range of the sample material set;
identifying the type of the material image data through record identification information in multiple thread running records of a material image data identification thread, and determining a first material category list matched with the material image data;
identifying a thread running record in multiple thread running records in threads through the material image data based on the first material category list, and determining a second material category list matched with the material image data;
and according to a second material category list matched with the material image data, identifying thread marking information of a thread through the material image data, and classifying the obtained material to be classified to obtain a classification result.
In an alternative embodiment, the determining a first material category list matching the material image data by performing type recognition on the material image data through record identification information in multiple thread running records of the material image data recognition thread specifically includes:
identifying first thread marking information in threads through the material image data, and determining multi-dimensional material size information corresponding to the material image data;
determining a target dimensional material corresponding to the multi-dimensional material size information through key information in the record identification information;
and responding to the target dimensional material, performing type recognition on the characteristic information of one dimensional material information in the multi-dimensional material size information through a plurality of information existing forms in the record identification information, and determining a first material category list matched with the material image data.
In an alternative embodiment, the determining, by the identifying first thread marking information in the thread by the material image data, multidimensional material size information corresponding to the material image data specifically includes:
filtering the material image data through the first thread marking information;
and performing material division processing on the filtered material image data according to the target marking information and the information expression form of the first thread marking information to obtain a division result corresponding to the material image data, performing category information fusion processing on the division result of the material image data, and determining multi-dimensional material size information corresponding to the material image data.
In an alternative embodiment, the classifying the acquired material to be classified according to the second material category list matched with the material image data and the thread marking information of the thread identified by the material image data includes:
determining an information marking position of second thread marking information of the material image data identification thread;
and based on a second material category list matched with the material image data, carrying out material size marking on the multi-dimensional material size information according to the second thread marking information of the corresponding information marking position to obtain a marking result, and carrying out classification processing on the obtained material to be classified according to the marking result to obtain a classification result.
The present invention also provides a material classification apparatus based on image processing, the apparatus comprising:
the material image data acquisition module is used for inputting material image data corresponding to a target material in the sample material set; wherein the material image data comprises a set of material image data to be identified within a same monitoring range of the sample material set;
the first material category list determining module is used for identifying the type of the material image data through record identification information in multiple thread running records of a material image data identification thread and determining a first material category list matched with the material image data;
the second material category list determining module is used for identifying thread running records in multiple thread running records in threads through the material image data based on the first material category list, and determining a second material category list matched with the material image data;
and the material classification module is used for identifying thread marking information of threads according to the second material category list matched with the material image data and classifying the obtained materials to be classified to obtain a classification result.
In an alternative embodiment, the determining a first material category list matching the material image data by performing type recognition on the material image data through record identification information in multiple thread running records of the material image data recognition thread specifically includes:
identifying first thread marking information in threads through the material image data, and determining multi-dimensional material size information corresponding to the material image data;
determining a target dimensional material corresponding to the multi-dimensional material size information through key information in the record identification information;
and responding to the target dimensional material, performing type recognition on the characteristic information of one dimensional material information in the multi-dimensional material size information through a plurality of information existing forms in the record identification information, and determining a first material category list matched with the material image data.
In an alternative embodiment, the determining, by the identifying first thread marking information in the thread by the material image data, multidimensional material size information corresponding to the material image data specifically includes:
filtering the material image data through the first thread marking information;
and performing material division processing on the filtered material image data according to the target marking information and the information expression form of the first thread marking information to obtain a division result corresponding to the material image data, performing category information fusion processing on the division result of the material image data, and determining multi-dimensional material size information corresponding to the material image data.
In an alternative embodiment, the classifying the acquired material to be classified according to the second material category list matched with the material image data and the thread marking information of the thread identified by the material image data includes:
determining an information marking position of second thread marking information of the material image data identification thread;
and based on a second material category list matched with the material image data, carrying out material size marking on the multi-dimensional material size information according to the second thread marking information of the corresponding information marking position to obtain a marking result, and carrying out classification processing on the obtained material to be classified according to the marking result to obtain a classification result.
The present invention also provides a computer device comprising: a memory, a processor, and a network module; wherein the memory, the processor, and the network module are electrically connected directly or indirectly; the processor reads the computer program from the memory and runs the computer program to realize the method.
The present invention also provides a computer-readable storage medium, comprising a computer program; the computer program controls the electronic device where the readable storage medium is located to execute the method when running.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects.
The disclosure provides a material classification method, a material classification device and computer equipment based on image processing. Second, a second material category list is determined for which the material image data matches based on the first material category list. The material image data is then sorted according to the second material category list. So, carry out classification to the material of waiting to classify who obtains through setting up first material category list and second material category list, like this when the category of a material has the multiple, need not to classify through the manual work, further can improve classification efficiency, can improve categorised accuracy simultaneously.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flowchart of a material classification method based on image processing according to an embodiment of the present invention.
Fig. 2 is a functional block diagram of a material classifying device based on image processing according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a hardware structure of a computer device according to an embodiment of the present invention.
Detailed Description
In order to better understand the technical solutions of the present invention, the following detailed descriptions of the technical solutions of the present invention are provided with the accompanying drawings and the specific embodiments, and it should be understood that the specific features in the embodiments and the examples of the present invention are the detailed descriptions of the technical solutions of the present invention, and are not limitations of the technical solutions of the present invention, and the technical features in the embodiments and the examples of the present invention may be combined with each other without conflict.
Referring to fig. 1, a flowchart of a material classifying method based on image processing is shown, which includes the following steps S110 to S140.
Step S110, inputting material image data corresponding to a target material in a sample material set; wherein the material image data comprises a set of material image data to be identified within the same monitoring range of the sample material set.
Step S120, identifying the type of the material image data through the record identification information in the running records of various threads of the material image data identification thread, and determining a first material category list matched with the material image data.
Step S130, based on the first material category list, identifying a thread running record in multiple thread running records in the thread through the material image data, and determining a second material category list matched with the material image data.
And step S140, according to the second material category list matched with the material image data, identifying thread marking information of threads through the material image data, and classifying the obtained materials to be classified to obtain a classification result.
Executing the contents described in the above steps S110 to S140, first obtaining material image data, and further performing type identification on the material image data according to record identification information in multiple types of thread running records of the material image data identification thread. Second, a second material category list is determined for which the material image data matches based on the first material category list. The material image data is then sorted according to the second material category list. So, carry out classification to the material of waiting to classify who obtains through setting up first material category list and second material category list, like this when the category of a material has the multiple, need not to classify through the manual work, further can improve classification efficiency, can improve categorised accuracy simultaneously.
In an alternative embodiment, the determining a first material category list matching the material image data by performing type recognition on the material image data through record identification information in multiple thread running records of the material image data recognition thread specifically includes:
identifying first thread marking information in threads through the material image data, and determining multi-dimensional material size information corresponding to the material image data;
determining a target dimensional material corresponding to the multi-dimensional material size information through key information in the record identification information;
and responding to the target dimensional material, performing type recognition on the characteristic information of one dimensional material information in the multi-dimensional material size information through a plurality of information existing forms in the record identification information, and determining a first material category list matched with the material image data.
In an alternative embodiment, the determining, by the identifying first thread marking information in the thread by the material image data, multidimensional material size information corresponding to the material image data specifically includes:
filtering the material image data through the first thread marking information;
and performing material division processing on the filtered material image data according to the target marking information and the information expression form of the first thread marking information to obtain a division result corresponding to the material image data, performing category information fusion processing on the division result of the material image data, and determining multi-dimensional material size information corresponding to the material image data.
In an alternative embodiment, the classifying the acquired material to be classified according to the second material category list matched with the material image data and the thread marking information of the thread identified by the material image data includes:
determining an information marking position of second thread marking information of the material image data identification thread;
and based on a second material category list matched with the material image data, carrying out material size marking on the multi-dimensional material size information according to the second thread marking information of the corresponding information marking position to obtain a marking result, and carrying out classification processing on the obtained material to be classified according to the marking result to obtain a classification result.
Referring to fig. 2, a functional block diagram of an image processing-based material classifying apparatus 200 is shown, the apparatus including:
a material image data obtaining module 210, configured to input material image data corresponding to a target material in a sample material set; wherein the material image data comprises a set of material image data to be identified within a same monitoring range of the sample material set;
a first material category list determining module 220, configured to perform type identification on the material image data through record identification information in multiple thread running records of a material image data identification thread, and determine a first material category list matched with the material image data;
a second material category list determining module 230, configured to identify, based on the first material category list, a thread run record in multiple thread run records in the thread through the material image data, and determine a second material category list matching the material image data;
and the material classification module 240 is configured to, according to the second material category list matched with the material image data, identify thread marking information of a thread through the material image data, and perform classification processing on the obtained material to be classified to obtain a classification result.
In an alternative embodiment, the determining a first material category list matching the material image data by performing type recognition on the material image data through record identification information in multiple thread running records of the material image data recognition thread specifically includes:
identifying first thread marking information in threads through the material image data, and determining multi-dimensional material size information corresponding to the material image data;
determining a target dimensional material corresponding to the multi-dimensional material size information through key information in the record identification information;
and responding to the target dimensional material, performing type recognition on the characteristic information of one dimensional material information in the multi-dimensional material size information through a plurality of information existing forms in the record identification information, and determining a first material category list matched with the material image data.
In an alternative embodiment, the determining, by the identifying first thread marking information in the thread by the material image data, multidimensional material size information corresponding to the material image data specifically includes:
filtering the material image data through the first thread marking information;
and performing material division processing on the filtered material image data according to the target marking information and the information expression form of the first thread marking information to obtain a division result corresponding to the material image data, performing category information fusion processing on the division result of the material image data, and determining multi-dimensional material size information corresponding to the material image data.
In an alternative embodiment, the classifying the acquired material to be classified according to the second material category list matched with the material image data and the thread marking information of the thread identified by the material image data includes:
determining an information marking position of second thread marking information of the material image data identification thread;
and based on a second material category list matched with the material image data, carrying out material size marking on the multi-dimensional material size information according to the second thread marking information of the corresponding information marking position to obtain a marking result, and carrying out classification processing on the obtained material to be classified according to the marking result to obtain a classification result.
Referring to fig. 3, a hardware structure diagram of a computer device 100 is provided.
Fig. 3 shows a block diagram of a computer device 100 according to an embodiment of the present invention. A computer device 100 in the embodiment of the present invention may be a server with data storage, transmission, and processing functions, as shown in fig. 3, the computer device 100 includes: memory 111, processor 112, network module 113, and image processing-based material classification device 200.
The memory 111, the processor 112, and the network module 113 are electrically connected directly or indirectly to enable transmission or interaction of data. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 111 stores therein the image processing-based material classifying device 200, the image processing-based material classifying device 200 includes at least one software function module which can be stored in the memory 111 in the form of software or firmware (firmware), and the processor 112 executes various functional applications and data processing by running a software program and a module stored in the memory 111, such as the image processing-based material classifying device 200 in the embodiment of the present invention, so as to implement the multidimensional analysis-based material screening method in the embodiment of the present invention.
The Memory 111 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 111 is used for storing a program, and the processor 112 executes the program after receiving the execution instruction.
The processor 112 may be an integrated circuit chip having data processing capabilities. The Processor 112 may be a general-purpose Processor including a Central Processing Unit (CPU), a Network Processor (NP), and the like. The various methods, steps and logic blocks disclosed in embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The network module 113 is used for establishing a communication connection between the computer device 100 and other communication terminal devices through a network, so as to implement transceiving operations of network signals and data. The network signal may include a wireless signal or a wired signal.
It will be appreciated that the configuration shown in FIG. 3 is merely illustrative and that a computing device 100 may include more or fewer components than shown in FIG. 3 or have a different configuration than shown in FIG. 3. The components shown in fig. 3 may be implemented in hardware, software, or a combination thereof.
An embodiment of the present invention also provides a computer-readable storage medium, which includes a computer program. The computer program controls, when executed, a computer device 100 on which the readable storage medium resides to perform the following image processing-based material classification method.
In summary, by applying the method, the apparatus and the computer device, the material image data is first obtained, and the type of the material image data is further identified according to the record identification information in the multiple thread running records of the material image data identification thread. Second, a second material category list is determined for which the material image data matches based on the first material category list. The material image data is then sorted according to the second material category list. So, carry out classification to the material of waiting to classify who obtains through setting up first material category list and second material category list, like this when the category of a material has the multiple, need not to classify through the manual work, further can improve classification efficiency, can improve categorised accuracy simultaneously.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus and method embodiments described above are illustrative only, as the flowcharts 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 of the present invention. 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 of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention or a part thereof, which essentially contributes to the prior art, can be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, an electronic device 10, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It should be noted that, in this document, 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 an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method for image processing based material classification, the method comprising:
inputting material image data corresponding to a target material in a sample material set; wherein the material image data comprises a set of material image data to be identified within a same monitoring range of the sample material set;
identifying the type of the material image data through record identification information in multiple thread running records of a material image data identification thread, and determining a first material category list matched with the material image data;
identifying a thread running record in multiple thread running records in threads through the material image data based on the first material category list, and determining a second material category list matched with the material image data;
and according to a second material category list matched with the material image data, identifying thread marking information of a thread through the material image data, and classifying the obtained material to be classified to obtain a classification result.
2. The method according to claim 1, wherein the determining a first material category list matching the material image data by performing type recognition on the material image data through record identification information in a plurality of types of thread run records of the material image data recognition thread comprises:
identifying first thread marking information in threads through the material image data, and determining multi-dimensional material size information corresponding to the material image data;
determining a target dimensional material corresponding to the multi-dimensional material size information through key information in the record identification information;
and responding to the target dimensional material, performing type recognition on the characteristic information of one dimensional material information in the multi-dimensional material size information through a plurality of information existing forms in the record identification information, and determining a first material category list matched with the material image data.
3. The method according to claim 2, wherein the determining multidimensional material size information corresponding to the material image data by identifying first thread marking information in a thread by the material image data specifically comprises:
filtering the material image data through the first thread marking information;
and performing material division processing on the filtered material image data according to the target marking information and the information expression form of the first thread marking information to obtain a division result corresponding to the material image data, performing category information fusion processing on the division result of the material image data, and determining multi-dimensional material size information corresponding to the material image data.
4. The method according to claim 1, wherein the classifying the acquired material to be classified by identifying thread marking information of a thread according to the second material category list matched with the material image data by the material image data specifically comprises:
determining an information marking position of second thread marking information of the material image data identification thread;
and based on a second material category list matched with the material image data, carrying out material size marking on the multi-dimensional material size information according to the second thread marking information of the corresponding information marking position to obtain a marking result, and carrying out classification processing on the obtained material to be classified according to the marking result to obtain a classification result.
5. An apparatus for classifying material based on image processing, the apparatus comprising:
the material image data acquisition module is used for inputting material image data corresponding to a target material in the sample material set; wherein the material image data comprises a set of material image data to be identified within a same monitoring range of the sample material set;
the first material category list determining module is used for identifying the type of the material image data through record identification information in multiple thread running records of a material image data identification thread and determining a first material category list matched with the material image data;
the second material category list determining module is used for identifying thread running records in multiple thread running records in threads through the material image data based on the first material category list, and determining a second material category list matched with the material image data;
and the material classification module is used for identifying thread marking information of threads according to the second material category list matched with the material image data and classifying the obtained materials to be classified to obtain a classification result.
6. The apparatus according to claim 5, wherein the determining a first material category list matching the material image data by performing type recognition on the material image data through record identification information in a plurality of types of thread run records of the material image data recognition thread comprises:
identifying first thread marking information in threads through the material image data, and determining multi-dimensional material size information corresponding to the material image data;
determining a target dimensional material corresponding to the multi-dimensional material size information through key information in the record identification information;
and responding to the target dimensional material, performing type recognition on the characteristic information of one dimensional material information in the multi-dimensional material size information through a plurality of information existing forms in the record identification information, and determining a first material category list matched with the material image data.
7. The apparatus according to claim 5, wherein the determining multidimensional material size information corresponding to the material image data by identifying first thread marking information in a thread by the material image data specifically comprises:
filtering the material image data through the first thread marking information;
and performing material division processing on the filtered material image data according to the target marking information and the information expression form of the first thread marking information to obtain a division result corresponding to the material image data, performing category information fusion processing on the division result of the material image data, and determining multi-dimensional material size information corresponding to the material image data.
8. The apparatus according to claim 5, wherein the classifying the acquired material to be classified by identifying thread marking information of a thread according to the second material category list matched with the material image data by the material image data specifically includes:
determining an information marking position of second thread marking information of the material image data identification thread;
and based on a second material category list matched with the material image data, carrying out material size marking on the multi-dimensional material size information according to the second thread marking information of the corresponding information marking position to obtain a marking result, and carrying out classification processing on the obtained material to be classified according to the marking result to obtain a classification result.
9. A computer device, comprising: a memory, a processor, and a network module; wherein the memory, the processor, and the network module are electrically connected directly or indirectly; the processor implements the method of any one of claims 1-4 by reading the computer program from the memory and running it.
10. A computer-readable storage medium, characterized in that the readable storage medium comprises a computer program; the computer program controls the electronic device in which the readable storage medium is executed to perform the method of any one of claims 1-4 when executed.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011020437.3A CN112116015A (en) | 2020-09-25 | 2020-09-25 | Material classification method and device based on image processing and computer equipment |
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| CN202011020437.3A CN112116015A (en) | 2020-09-25 | 2020-09-25 | Material classification method and device based on image processing and computer equipment |
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| CN112116015A true CN112116015A (en) | 2020-12-22 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116119284A (en) * | 2022-12-16 | 2023-05-16 | 工业富联(杭州)数据科技有限公司 | Material assembling method, device, equipment and medium based on artificial intelligence |
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2020
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116119284A (en) * | 2022-12-16 | 2023-05-16 | 工业富联(杭州)数据科技有限公司 | Material assembling method, device, equipment and medium based on artificial intelligence |
| CN116119284B (en) * | 2022-12-16 | 2023-11-24 | 工业富联(杭州)数据科技有限公司 | Material assembling method, device, equipment and medium based on artificial intelligence |
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