CN112307115B - Distributed big data network service method - Google Patents
Distributed big data network service method Download PDFInfo
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- CN112307115B CN112307115B CN202010109844.5A CN202010109844A CN112307115B CN 112307115 B CN112307115 B CN 112307115B CN 202010109844 A CN202010109844 A CN 202010109844A CN 112307115 B CN112307115 B CN 112307115B
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- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000012795 verification Methods 0.000 claims abstract description 9
- 238000013523 data management Methods 0.000 claims abstract description 6
- 238000006243 chemical reaction Methods 0.000 claims description 39
- 238000013515 script Methods 0.000 claims description 16
- PXFBZOLANLWPMH-UHFFFAOYSA-N 16-Epiaffinine Natural products C1C(C2=CC=CC=C2N2)=C2C(=O)CC2C(=CC)CN(C)C1C2CO PXFBZOLANLWPMH-UHFFFAOYSA-N 0.000 claims description 4
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- 238000010586 diagram Methods 0.000 description 6
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/14—Error detection or correction of the data by redundancy in operation
- G06F11/1402—Saving, restoring, recovering or retrying
- G06F11/1446—Point-in-time backing up or restoration of persistent data
- G06F11/1448—Management of the data involved in backup or backup restore
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures
Abstract
The invention relates to a distributed big data network service method which comprises the step of providing a distributed big data network service platform used for carrying out field verification by adopting a targeted electronic authentication mechanism on the basis of big data management. The distributed big data network service method is reliable in data and convenient to use.
Description
Technical Field
The invention relates to the field of big data management, in particular to a distributed big data network service method.
Background
Big data includes structured, semi-structured, and unstructured data, with unstructured data becoming an increasingly dominant part of the data. Survey reports by IDC show: 80% of the data in a business is unstructured and the data grows exponentially by 60% each year.
The big data is a representation or a characteristic of the internet which is developed to the present stage, and does not need to be worried or worried about the big data, under the setback of a technical innovation large screen represented by cloud computing, the data which is originally hard to collect and use is easy to utilize, and the big data can gradually create more value for human beings through continuous innovation of various industries.
At present, a local verification mode capable of effectively detecting each real and false drawing book by applying a big data management mode is lacked, so that the existing drawing book verification mode has risks of data leakage and manual operation.
Disclosure of Invention
In order to solve the technical problems in the related field, the invention provides a distributed big data network service method, which can introduce a customized big data network service structure to finish the storage and backup of electronic files of real and false sketches, and finish the effective verification of the authenticity of local sketches based on the electronic files, thereby avoiding the electronic verification result from being manually controlled.
Therefore, the invention needs to have the following three key points:
(1) the arrangement of multiple nodes for data storage service and data processing service is realized by adopting a big data network service structure with distributed arrangement results, so that complex identification processing is transplanted to a network end for processing, and local personnel are prevented from controlling an electronic verification result;
(2) adopting an electronic identification mechanism, and determining that the local picture book is a fake when the content of the picture book to be identified is identified to be consistent with the content of the genuine picture book and is not consistent with the imitated picture book;
(3) two big data nodes are adopted to back up data stored mutually so as to reduce the probability that key data is lost or tampered.
According to an aspect of the present invention, a distributed big data network service method is provided, where the method includes providing a distributed big data network service platform for performing field verification on whether a local drawing is a counterfeit or not by using a targeted electronic identification mechanism on the basis of big data management, and the distributed big data network service platform includes:
the first big data node is used for storing the picture books of the real authors corresponding to the historical picture volumes respectively;
the second big data node is used for storing the picture books of the imitation authors corresponding to the historical picture volumes respectively;
the user input interface is arranged on a local portable terminal and used for receiving the name of the identification picture scroll input by the user as the name of the reference picture scroll according to the operation of the user;
the picture body capturing device is arranged on the right side of the user input interface and used for performing instant image capturing operation on the picture to be recognized below the picture body capturing device so as to obtain a corresponding picture body capturing image;
a first conversion device connected to the picture body capturing device, for performing affine transformation processing on the received picture volume captured image to obtain a first converted image;
a second conversion device connected to the first conversion device, for performing a tilt correction process on the received first converted image to obtain a second converted image;
a third big data node, connected to the second conversion device, the user input interface, the first big data node, and the second big data node through a network, for searching out, from the first big data node, each of the scripts corresponding to the reference scroll name based on the reference scroll name, as each of the first reference scripts, and for searching out, from the second big data node, each of the scripts corresponding to the reference scroll name based on the reference scroll name, as each of the second reference scripts;
the third big data node is also used for sending a first identification instruction when a first reference picture book with the matching degree exceeding the second conversion image exists and a second reference picture book with the matching degree exceeding the second conversion image does not exist, otherwise, sending a second identification instruction;
and the voice playing chip is arranged on a local portable terminal, is connected with the third big data node through a network and is used for playing a voice playing file related to the authentic work identification when the first identification instruction is received.
The distributed big data network service method is reliable in data and convenient to use. Because the key data and key operation for executing true and false drawing identification are placed at the big data network server side of the customized structure, the probability that the electronic identification result is manually controlled is reduced.
Drawings
Embodiments of the invention will now be described with reference to the accompanying drawings, in which:
fig. 1 is a component configuration diagram of a distributed big data network service platform of the present invention.
Fig. 2 is a block diagram illustrating a distributed big data network service platform according to a first embodiment of the present invention.
Fig. 3 is a block diagram illustrating a distributed big data network service platform according to a second embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
Currently, true and false authentication of sketches has begun to shift from manual authentication mode to electronic authentication mode. Although the electronic authentication mode has the advantages of high speed, high efficiency and no need of excessive manual participation, the electronic authentication mode has the disadvantage that the authentication result is easy to be manually controlled and tampered due to the mechanism of the electronic authentication mode, and therefore, the data storage and authentication operation of the electronic authentication mode need to be localized as much as possible so as to reduce the probability of manual control and tampering.
In order to overcome the defects, the invention builds a distributed big data network service method, which comprises the step of providing a distributed big data network service platform used for carrying out on-site verification on whether a local picture book is a counterfeit or not by adopting a targeted electronic identification mechanism on the basis of big data management, wherein the distributed big data network service platform can effectively solve the corresponding technical problem.
Fig. 1 is a block diagram showing a distributed big data network service platform according to the present invention, and as shown in fig. 1, there are at least three big data nodes and one conversion device.
In the following, several embodiments of the invention are given to give a careful explanation and description of the invention.
< first embodiment >
Fig. 2 is a block diagram illustrating a distributed big data network service platform according to a first embodiment of the present invention, where the platform includes:
the first big data node is used for storing the picture books of the real authors corresponding to the historical picture volumes respectively;
the second big data node is used for storing the picture books of the imitation authors corresponding to the historical picture volumes respectively;
the user input interface is arranged on a local portable terminal and used for receiving the name of the identification picture scroll input by the user as the name of the reference picture scroll according to the operation of the user;
the picture body capturing device is arranged on the right side of the user input interface and used for performing instant image capturing operation on the picture to be recognized below the picture body capturing device so as to obtain a corresponding picture body capturing image;
a first conversion device connected to the picture body capturing device, for performing affine transformation processing on the received picture volume captured image to obtain a first converted image;
a second conversion device connected to the first conversion device, for performing a tilt correction process on the received first converted image to obtain a second converted image;
a third big data node, connected to the second conversion device, the user input interface, the first big data node, and the second big data node through a network, for searching out, from the first big data node, each of the scripts corresponding to the reference scroll name based on the reference scroll name, as each of the first reference scripts, and for searching out, from the second big data node, each of the scripts corresponding to the reference scroll name based on the reference scroll name, as each of the second reference scripts;
the third big data node is also used for sending a first identification instruction when a first reference picture book with the matching degree exceeding the second conversion image exists and a second reference picture book with the matching degree exceeding the second conversion image does not exist, otherwise, sending a second identification instruction;
and the voice playing chip is arranged on a local portable terminal, is connected with the third big data node through a network and is used for playing a voice playing file related to the authentic work identification when the first identification instruction is received.
< second embodiment >
Fig. 3 is a block diagram illustrating a distributed big data network service platform according to a second embodiment of the present invention, where the platform includes:
the temperature sensing equipment is respectively connected with the first conversion equipment and the second conversion equipment and is used for respectively detecting the shell temperatures of the first conversion equipment and the second conversion equipment;
the flash lamp controller is positioned on one side of the picture body capturing device and used for controlling the on-off of the flash lamp based on the real-time environment brightness;
the first big data node is used for storing the picture books of the real authors corresponding to the historical picture volumes respectively;
the second big data node is used for storing the picture books of the imitation authors corresponding to the historical picture volumes respectively;
the user input interface is arranged on a local portable terminal and used for receiving the name of the identification picture scroll input by the user as the name of the reference picture scroll according to the operation of the user;
the picture body capturing device is arranged on the right side of the user input interface and used for performing instant image capturing operation on the picture to be recognized below the picture body capturing device so as to obtain a corresponding picture body capturing image;
a first conversion device connected to the picture body capturing device, for performing affine transformation processing on the received picture volume captured image to obtain a first converted image;
a second conversion device connected to the first conversion device, for performing a tilt correction process on the received first converted image to obtain a second converted image;
a third big data node, connected to the second conversion device, the user input interface, the first big data node, and the second big data node through a network, for searching out, from the first big data node, each of the scripts corresponding to the reference scroll name based on the reference scroll name, as each of the first reference scripts, and for searching out, from the second big data node, each of the scripts corresponding to the reference scroll name based on the reference scroll name, as each of the second reference scripts;
the third big data node is also used for sending a first identification instruction when a first reference picture book with the matching degree exceeding the second conversion image exists and a second reference picture book with the matching degree exceeding the second conversion image does not exist, otherwise, sending a second identification instruction;
and the voice playing chip is arranged on a local portable terminal, is connected with the third big data node through a network and is used for playing a voice playing file related to the authentic work identification when the first identification instruction is received.
Next, a detailed description of the specific structure of each embodiment of the distributed big data network service platform according to the present invention will be further described.
In the distributed big data network service platform: and the voice playing chip is also used for playing a voice playing file related to the counterfeit recognition when the second recognition instruction is received.
In the distributed big data network service platform: the first big data node is also used for backing up the picture books of the imitation authors corresponding to the historical picture volumes stored in the second big data node; the second big data node is further used for backing up the picture book of each real author corresponding to each historical picture volume stored in the first big data node.
In the distributed big data network service platform: controlling the flash to turn on and off based on the real-time ambient brightness includes: when real-time environment brightness is less than or equal to a preset brightness threshold value, the flash lamp is opened, wherein the flash lamp controller controls the flash lamp to be opened and closed based on the real-time environment brightness and comprises the following steps: and when the real-time environment brightness is greater than the preset brightness threshold value, the flash lamp is turned off.
In the distributed big data network service platform: the flash controller controlling the flash to be turned on and off based on the real-time ambient brightness includes: and when the real-time environment brightness is less than or equal to the preset brightness threshold, turning on the flash lamp and adjusting the flash brightness of the flash lamp according to the real-time environment brightness, wherein the lower the real-time environment brightness is, the higher the flash brightness of the flash lamp is.
In the distributed big data network service platform, the platform further comprises: and the GPS positioning device is arranged on one side of the first conversion device and is used for providing the current GPS position of the first conversion device.
And in the distributed big data network service platform: alternatively, the GPS positioning device is replaced by a beidou satellite navigation device or a galileo navigation device, wherein the user input interface is a touch screen integrated on the display unit or a keyboard array consisting of a plurality of keys.
In addition, the first conversion equipment or the second conversion equipment is respectively realized by adopting DSP chips with different models.
The DSP chip adopts a Harvard structure with separated programs and data, is provided with a special hardware multiplier, widely adopts pipeline operation, provides special DSP instructions, and can be used for quickly realizing various digital signal processing algorithms. According to the requirements of digital signal processing, a DSP chip generally has some main features as follows: (1) one multiply and one add may be done in one instruction cycle. (2) The program and data spaces are separate and instructions and data may be accessed simultaneously. (3) On-chip with fast RAM, it is usually accessible in two blocks simultaneously via separate data buses. (4) Hardware support with low or no overhead loops and jumps. (5) Fast interrupt handling and hardware I/O support. (6) There are multiple hardware address generators operating in a single cycle. (7) Multiple operations may be performed in parallel. (8) And pipeline operation is supported, so that the operations of fetching, decoding, executing and the like can be executed in an overlapping way.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature.
Although the present invention has been described with reference to the above embodiments, it should be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention. Therefore, the protection scope of the present invention should be subject to the scope defined by the claims of the present application.
Claims (7)
1. A distributed big data network service method comprises the steps of providing a distributed big data network service platform, and using a targeted electronic identification mechanism to carry out on-site verification on whether a local drawing is a counterfeit or not on the basis of big data management, wherein the distributed big data network service platform comprises:
the first big data node is used for storing the picture books of the real authors corresponding to the historical picture volumes respectively;
the second big data node is used for storing the picture books of the imitation authors corresponding to the historical picture volumes respectively;
the user input interface is arranged on a local portable terminal and used for receiving the name of the identification picture scroll input by the user as the name of the reference picture scroll according to the operation of the user;
the picture body capturing device is arranged on the right side of the user input interface and used for performing instant image capturing operation on the picture to be recognized below the picture body capturing device so as to obtain a corresponding picture body capturing image;
a first conversion device connected to the picture body capturing device, for performing affine transformation processing on the received picture volume captured image to obtain a first converted image;
a second conversion device connected to the first conversion device, for performing a tilt correction process on the received first converted image to obtain a second converted image;
a third big data node, connected to the second conversion device, the user input interface, the first big data node, and the second big data node through a network, for searching out, from the first big data node, each of the scripts corresponding to the reference scroll name based on the reference scroll name, as each of the first reference scripts, and for searching out, from the second big data node, each of the scripts corresponding to the reference scroll name based on the reference scroll name, as each of the second reference scripts;
the third big data node is also used for sending a first identification instruction when a first reference picture book with the matching degree exceeding the second conversion image exists and a second reference picture book with the matching degree exceeding the second conversion image does not exist, otherwise, sending a second identification instruction;
the voice playing chip is arranged on a local portable terminal, is connected with the third big data node through a network and is used for playing a voice playing file related to the authentic work identification when receiving the first identification instruction;
the voice playing chip is further used for playing a voice playing file related to the counterfeit recognition when the second recognition instruction is received;
the first big data node is also used for backing up the picture books of the imitation authors corresponding to the historical picture volumes stored in the second big data node;
the second big data node is further used for backing up the picture book of each real author corresponding to each historical picture volume stored in the first big data node.
2. The method of claim 1, wherein the platform further comprises:
and the temperature sensing equipment is respectively connected with the first conversion equipment and the second conversion equipment and is used for respectively detecting the shell temperatures of the first conversion equipment and the second conversion equipment.
3. The method of claim 2, wherein the platform further comprises:
and the flash lamp controller is positioned on one side of the picture body capturing device and is used for controlling the on-off of the flash lamp based on the real-time environment brightness.
4. The method of claim 3, wherein:
controlling the flash to turn on and off based on the real-time ambient brightness includes: when the real-time environment brightness is smaller than or equal to a preset brightness threshold value, a flash lamp is turned on;
wherein, flash controller includes based on the switching of real-time environment luminance control flash: and when the real-time environment brightness is greater than the preset brightness threshold value, the flash lamp is turned off.
5. The method of claim 4, wherein:
the flash controller controlling the flash to be turned on and off based on the real-time ambient brightness includes: and when the real-time environment brightness is less than or equal to the preset brightness threshold, turning on the flash lamp and adjusting the flash brightness of the flash lamp according to the real-time environment brightness, wherein the lower the real-time environment brightness is, the higher the flash brightness of the flash lamp is.
6. The method of claim 5, wherein the platform further comprises:
and the GPS positioning device is arranged on one side of the first conversion device and is used for providing the current GPS position of the first conversion device.
7. The method of claim 6, wherein:
alternatively, a Beidou satellite navigation device or a Galileo navigation device is adopted to replace the GPS positioning device;
the user input interface is a touch screen integrated on the display part or a keyboard array composed of a plurality of keys.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202010109844.5A CN112307115B (en) | 2020-02-23 | 2020-02-23 | Distributed big data network service method |
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| CN202010109844.5A CN112307115B (en) | 2020-02-23 | 2020-02-23 | Distributed big data network service method |
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| CN112307115B true CN112307115B (en) | 2021-06-25 |
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Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1529270A (en) * | 2003-09-29 | 2004-09-15 | 朱先成 | Calligraphy and painting real-false appraising method |
| US20070179978A1 (en) * | 2005-11-14 | 2007-08-02 | Lee Kin K | Systems and methods for anti-counterfeit authentication |
| CN107679872A (en) * | 2017-09-28 | 2018-02-09 | 中链科技有限公司 | Art work discrimination method and device, electronic equipment based on block chain |
| CN108520196B (en) * | 2018-02-01 | 2021-08-31 | 平安科技（深圳）有限公司 | Luxury discrimination method, electronic device, and storage medium |
| CN108846330A (en) * | 2018-05-30 | 2018-11-20 | 中科智文（北京）科技有限公司 | A kind of paper calligraphy and painting micro-image intelligent identifying system and recognition methods |
| CN110427742B (en) * | 2019-08-06 | 2021-05-25 | 北京如优教育科技有限公司 | Authentication service platform content saving system, method and storage medium |
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Effective date of registration: 20210607 Address after: 100016 room 836, 8 / F, Xinhua science and technology building, 8 tuofangying Road, Jiangtai Township, Chaoyang District, Beijing Applicant after: Beijing leading future smart technology Co.,Ltd. Address before: 215000 no.282 Shanggong Road, Xukou Town, Wuzhong District, Suzhou City, Jiangsu Province Applicant before: Deng Tao |
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