CN113761242A - Big data image recognition system and method based on artificial intelligence - Google Patents
Big data image recognition system and method based on artificial intelligence Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/51—Indexing; Data structures therefor; Storage structures
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/951—Indexing; Web crawling techniques
Abstract
The invention relates to the technical field of image recognition and discloses a big data image recognition system based on artificial intelligence, which comprises a data acquisition module, a data analysis module, an image arrangement module, an image storage module and an image query module, wherein the data acquisition module is connected with the data analysis module, the data analysis module is connected with the image arrangement module, the image arrangement module is connected with the image storage module, and the image storage module is connected with the image query module through a data network. The big data image recognition system and method based on artificial intelligence are convenient for processing speed when a user side retrieves pictures, low in requirement on network bandwidth, easy to transmit in a local area network, capable of better distinguishing different picture types by binary codes, free of manual auxiliary processing in the processing process, easy to process a large number of pictures, and effective in improving efficiency and market fitness of the image recognition system.
Description
Technical Field
The invention relates to the technical field of image recognition, in particular to a big data image recognition system and method based on artificial intelligence.
Background
Image recognition, which is a technology for processing, analyzing and understanding images by using a computer to recognize various targets and objects in different modes, is a practical application of a deep learning algorithm, and the image recognition technology at the present stage is generally divided into face recognition and commodity recognition, wherein the face recognition is mainly applied to security inspection, identity verification and mobile payment, and the commodity recognition is mainly applied to the commodity circulation process.
The image recognition system can store and classify pictures, and when a user needs to check or search the pictures, the pictures can be pushed according to used keywords so as to meet the requirements of the user.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a big data image recognition system and method based on artificial intelligence, which have the advantages of accurate big data processing and recognition and the like, and solve the problems that the extraction of the image recognition system is completed in a manual preprocessing mode by constructing local feature extractors of different types, and pictures irrelevant to keywords can be pushed in the image retrieval process.
(II) technical scheme
In order to achieve the purpose of accurate big data processing and identification, the invention provides the following technical scheme:
the big data image recognition system based on artificial intelligence comprises a data acquisition module, a data analysis module, an image arrangement module, an image storage module and an image query module, wherein the data acquisition module is connected with the data analysis module, the data analysis module is connected with the image arrangement module, the image arrangement module is connected with the image storage module, and the image storage module is connected with the image query module through a data network.
Preferably, crawler software is arranged in the data acquisition module, and is used for crawling the picture information on the internet one by one and updating the picture information in real time.
Preferably, the image analysis module includes a data binary conversion unit and a data decoding unit, and the data decoding unit serves the data binary conversion unit.
Preferably, the data arranging unit adopts binary coding to produce the linked list of the database area by the data and codes the data, the image storage module stores and arranges the data according to the codes and processes the pushbuttons in multiple batches to form the picture information into the remote management terminal.
Preferably, the image query module is a remote user side, the user side is established through JAVA language codes, and the user side is connected with the management side through a data network.
A big data image recognition method based on artificial intelligence comprises the following steps:
1) collecting pictures: the method comprises the steps that a crawler program is utilized to collect picture information of the internet, the picture information comprises pictures in various different fields, large-batch crawling is carried out, the picture information is periodically updated and perfected, and the picture information is periodically supplemented;
2) picture analysis: dragging the pictures collected in the step one to a binary transcoding program, wherein the program can check the pictures one by one, convert the picture information into binary digital information, and correspondingly store the pictures and the binary digital information thereof;
3) image arrangement: classifying and arranging the binary digital information in the second step, reading the binary digital information of the picture, dividing the data with the same four bits before binary coding of the picture into one item, then performing coding classification on the data with the same four bits after binary coding of the picture, and classifying the same data and storing different data into a plurality of categories;
4) establishing a data table: extracting the classified data in the third step, storing a data table corresponding to the database according to data classification, and providing data support for a management end;
5) data application: the method comprises the steps that coding of a management end and a user end is completed through programming, the management end manages a database and pushes picture information to the user end, the management end is provided with the functions of adding pictures for updating, deleting redundant picture information, changing data arrangement categories and pushing remote data, the user end can conduct retrieval according to keywords of data, the management end produces picture retrieval requirements through a data network, then the management end searches for pictures with binary codes in the same field as the keywords through a database system to push, and the requirements of users on the pictures are met.
(III) advantageous effects
Compared with the prior art, the invention provides a big data image recognition system and method based on artificial intelligence, which has the following beneficial effects:
1. the big data image recognition system and method based on artificial intelligence convert picture information into binary codes, the binary codes are directly recognized by a computer in the data storage process, compared with the traditional pictures formed by compiling dot matrix binary codes, the binary codes are more easily recognized by the computer and can be directly read in the recognition process, the processing speed is convenient when a user side retrieves the pictures, the requirement on network bandwidth is lower, meanwhile, the transmission is easier in a local area network, meanwhile, the binary codes can better distinguish different picture types, auxiliary processing is not needed manually in the processing process, a large number of pictures are more easily processed, and the efficiency and market adaptability of the image recognition system are effectively improved.
2. The big data image identification system and method based on artificial intelligence crawl through big data pictures, crawl big data in the internet in data processing, store data, can finish picture pushing rapidly when a user needs to search pictures, and can identify images rapidly according to binary codes, push promotion of irrelevant pictures is reduced in the process of pushing, so that a user side can better search for needed pictures, unnecessary pictures are prevented from being pushed to the user, search experience of the user is improved, and more users are attracted.
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FIG. 1 is a general framework of the present invention;
fig. 2 is a schematic view of the working process of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention and the accompanying drawings, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
A big data image recognition system based on artificial intelligence comprises a data acquisition module, a data analysis module, an image arrangement module, an image storage module and an image query module, wherein the data acquisition module is connected with the data analysis module, crawler software is arranged in the data acquisition module to crawl image information on the Internet one by one and update the image information in real time, the data analysis module is connected with the image arrangement module, the image analysis module comprises a data binary system conversion unit and a data decoding unit, the data decoding unit serves the data binary system conversion unit, the image arrangement module is connected with the image storage module, the image information is converted into binary codes, the binary codes are directly recognized by a computer in the data storage process, and compared with a picture formed by compiling traditional dot matrix binary codes, the binary codes are more easily recognized by the computer, the image recognition system can be directly read in the recognition process, is convenient for the processing speed when a user side retrieves images, has lower requirement on network bandwidth, is easier to transmit in a local area network, simultaneously binary codes can better distinguish different image types, does not need manual auxiliary processing in the processing process, is easier to process a large number of images, effectively improves the efficiency and market fitness of the image recognition system, adopts the binary codes to process a data production database region linked list and encode the data production by a data arrangement unit, stores and sorts the data according to the codes by an image storage module, processes the pushing batch to form image information into a remote management end, connects the image storage module and an image query module through a data network, is a remote user side, and establishes the user side through JAVA code, the user side, the user side passes through data network with the management end and is connected, crawl through big data picture, crawl the big data in the internet in data processing, save data, when the user needs to search for the picture, can accomplish the picture propelling movement fast, and can be according to the quick discernment image of binary code, the promotion of irrelevant picture is reduced to the in-process of propelling movement, make the user side can be better search for required picture, avoid to the unnecessary picture of user's propelling movement, thereby improve customer's search experience, thereby attract more users.
A big data image recognition method based on artificial intelligence comprises the following steps:
1) collecting pictures: the method comprises the steps that a crawler program is utilized to collect picture information of the internet, the picture information comprises pictures in various different fields, large-batch crawling is carried out, the picture information is periodically updated and perfected, and the picture information is periodically supplemented;
2) picture analysis: dragging the pictures collected in the step one to a binary transcoding program, wherein the program can check the pictures one by one, convert the picture information into binary digital information, and correspondingly store the pictures and the binary digital information thereof;
3) image arrangement: classifying and arranging the binary digital information in the second step, reading the binary digital information of the picture, dividing the data with the same four bits before binary coding of the picture into one item, then performing coding classification on the data with the same four bits after binary coding of the picture, and classifying the same data and storing different data into a plurality of categories;
4) establishing a data table: extracting the classified data in the third step, storing a data table corresponding to the database according to data classification, and providing data support for a management end;
5) data application: the method comprises the steps that coding of a management end and a user end is completed through programming, the management end manages a database and pushes picture information to the user end, the management end is provided with the functions of adding pictures for updating, deleting redundant picture information, changing data arrangement categories and pushing remote data, the user end can conduct retrieval according to keywords of data, the management end produces picture retrieval requirements through a data network, then the management end searches for pictures with binary codes in the same field as the keywords through a database system to push, and the requirements of users on the pictures are met.
The invention has the beneficial effects that: the big data image recognition system and method based on artificial intelligence convert picture information into binary codes, the binary codes are directly recognized by a computer in the data storage process, compared with the traditional pictures formed by compiling dot matrix binary codes, the binary codes are more easily recognized by the computer and can be directly read in the recognition process, the processing speed is convenient when a user side retrieves the pictures, the requirement on network bandwidth is lower, meanwhile, the transmission is easier in a local area network, meanwhile, the binary codes can better distinguish different picture types, auxiliary processing is not needed manually in the processing process, a large number of pictures are more easily processed, and the efficiency and market adaptability of the image recognition system are effectively improved.
And, through big data picture crawl, crawl the big data in the internet in data processing, save data, when the user needs to search for the picture, can accomplish the picture propelling movement fast, and can discern the image fast according to the binary code, the promotion of irrelevant picture is reduced in the in-process of propelling movement, make the user side can better search for required picture, avoid to the unnecessary picture of user's propelling movement, thereby improve customer's search experience, thereby attract more users, the extraction of having solved image recognition system is accomplished with the mode of artifical preliminary treatment through the local feature extractor that the construction different grade type was given, can push the problem with the irrelevant picture of keyword in the in-process of image retrieval.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. The big data image recognition system based on artificial intelligence comprises a data acquisition module, a data analysis module, an image arrangement module, an image storage module and an image query module, and is characterized in that the data acquisition module is connected with the data analysis module, the data analysis module is connected with the image arrangement module, the image arrangement module is connected with the image storage module, and the image storage module is connected with the image query module through a data network.
2. The big data image recognition system based on artificial intelligence as claimed in claim 1, wherein crawler software is built in the data collection module, and crawls picture information on the internet one by one and updates the information in real time.
3. The big data image recognition system based on artificial intelligence, as claimed in claim 1, wherein said image analysis module comprises a data binary conversion unit and a data decoding unit, the data decoding unit serves the data binary conversion unit.
4. The artificial intelligence based big data image recognition system as claimed in claim 1, wherein the data arrangement unit uses binary coding to produce the data database region linked list and to code the data production, the image storage module stores and sorts the data according to the coding and performs multi-batch processing to push the data, and the picture information forms the remote management terminal.
5. The big data image recognition system of claim 4, wherein the image query module is a remote client, the client is created by JAVA language coding, and the client is connected to the management terminal through a data network.
6. A big data image recognition method based on artificial intelligence is characterized by comprising the following steps:
1) collecting pictures: the method comprises the steps that a crawler program is utilized to collect picture information of the internet, the picture information comprises pictures in various different fields, large-batch crawling is carried out, the picture information is periodically updated and perfected, and the picture information is periodically supplemented;
2) picture analysis: dragging the pictures collected in the step one to a binary transcoding program, wherein the program can check the pictures one by one, convert the picture information into binary digital information, and correspondingly store the pictures and the binary digital information thereof;
3) image arrangement: classifying and arranging the binary digital information in the second step, reading the binary digital information of the picture, dividing the data with the same four bits before binary coding of the picture into one item, then performing coding classification on the data with the same four bits after binary coding of the picture, and classifying the same data and storing different data into a plurality of categories;
4) establishing a data table: extracting the classified data in the third step, storing a data table corresponding to the database according to data classification, and providing data support for a management end;
5) data application: the method comprises the steps that coding of a management end and a user end is completed through programming, the management end manages a database and pushes picture information to the user end, the management end is provided with the functions of adding pictures for updating, deleting redundant picture information, changing data arrangement categories and pushing remote data, the user end can conduct retrieval according to keywords of data, the management end produces picture retrieval requirements through a data network, then the management end searches for pictures with binary codes in the same field as the keywords through a database system to push, and the requirements of users on the pictures are met.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114565820A (en) * | 2022-03-01 | 2022-05-31 | 中科海慧（北京）科技有限公司 | Mineral sample identification system based on space-time big data analysis |
| CN114615207A (en) * | 2022-03-10 | 2022-06-10 | 四川三思德科技有限公司 | Method and device for oriented processing of data before plug flow |
| CN115203462A (en) * | 2022-07-12 | 2022-10-18 | 中国建筑西南设计研究院有限公司 | Building structure edge member identification method and device based on multi-dimensional coding |
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2021
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114565820A (en) * | 2022-03-01 | 2022-05-31 | 中科海慧（北京）科技有限公司 | Mineral sample identification system based on space-time big data analysis |
| CN114615207A (en) * | 2022-03-10 | 2022-06-10 | 四川三思德科技有限公司 | Method and device for oriented processing of data before plug flow |
| CN114615207B (en) * | 2022-03-10 | 2022-11-25 | 四川三思德科技有限公司 | Method and device for oriented processing of data before plug flow |
| CN115203462A (en) * | 2022-07-12 | 2022-10-18 | 中国建筑西南设计研究院有限公司 | Building structure edge member identification method and device based on multi-dimensional coding |
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Application publication date: 20211207 |