CN117057826A - Product traceability verification method based on blockchain technology - Google Patents
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Abstract
The application is applicable to the technical field of electric digital data processing, and particularly relates to a product traceability verification method based on a block chain technology, which comprises the following steps: acquiring product factory data, and storing the product factory data in a blockchain; acquiring product information to be traced, extracting part number data and whole machine number data from the product information, and tracing and inquiring based on the whole machine number data and the part number data to obtain an inquiry result; extracting feature information of the component based on the query result, and acquiring an image of the product to be traced to obtain a feature verification image; and extracting physical characteristics of the image to be verified, comparing the characteristics, calculating the coincidence rate, and when the coincidence rate is higher than a preset value, considering that verification is passed. According to the application, the traceability data are stored in the blockchain, so that the corresponding traceability data can be obtained during traceability verification, and the reliability of the component is further verified by comparing the color characteristics and the shape characteristics, so that the traceability reliability of the product is ensured.
Description
Technical Field
The application belongs to the technical field of electric digital data processing, and particularly relates to a product traceability verification method based on a block chain technology.
Background
The commodity product tracing is to combine the current advanced internet of things technology, automatic control technology, automatic identification technology and internet technology, and assign a unique one-dimensional code or two-dimensional code to a single product through professional machine equipment as an anti-counterfeiting identity card, so that one-object one-code is realized, and then data can be acquired and traced for each link of production, storage, distribution, logistics transportation, market inspection, sales terminal and the like of the product, thereby forming a full life cycle management tracing service of production, storage, sales, circulation and service of the product.
An industry blockchain is a system in which a plurality of preselected nodes are designated as billing agents within a group, the generation of each block is determined jointly by all preselected nodes (the preselected nodes participate in a consensus process), other access nodes can participate in transactions, but no other person in the billing process can do a qualified query through the open API of the blockchain.
In the prior art, the product tracing is generally realized through a two-dimensional code, but the two-dimensional code is used as a mark attached to the product, only single verification is performed, verification is not performed according to the characteristics of the product, and the reliability is not enough.
Disclosure of Invention
The embodiment of the application aims to provide a product tracing verification method based on a blockchain technology, and aims to solve the problems that product tracing is generally realized through two-dimensional codes in the prior art, but the two-dimensional codes are used as an identifier attached to a product, only single verification is performed, verification is not performed according to product characteristics, and reliability is insufficient.
The embodiment of the application is realized in such a way that the product traceability verification method based on the blockchain technology comprises the following steps:
acquiring product factory data, and storing the product factory data in a blockchain, wherein the product factory data at least comprises complete machine tracing information and component tracing information, and the component tracing information at least comprises component characteristic information;
acquiring product information to be traced, extracting part number data and whole machine number data from the product information, and tracing and inquiring based on the whole machine number data and the part number data to obtain an inquiry result;
extracting component characteristic information based on the query result, and carrying out image acquisition on a product to be traced to obtain a characteristic verification image, wherein the angle of image acquisition is the same as the angle recorded in the component characteristic information;
and extracting physical characteristics of the image to be verified, comparing the extracted physical characteristic information with the component characteristic information, calculating the coincidence rate, and when the coincidence rate is higher than a preset value, considering that verification is passed.
Preferably, the step of obtaining the information of the product to be traced, extracting the part number data and the whole machine number data from the information, tracing and inquiring based on the whole machine number data and the part number data to obtain an inquiry result specifically includes:
obtaining product information to be traced, wherein the product information to be traced at least comprises a complete machine number and a part number, and the complete machine number and the part number have uniqueness;
extracting part number data and whole machine number data, downloading corresponding data from a blockchain, and carrying out matching one by one to inquire corresponding whole machine tracing information and part tracing information;
judging whether the part tracing information obtained by query is matched with the whole machine tracing information or not according to the whole machine tracing information, and if not, judging that no query result exists.
Preferably, the step of extracting feature information of the component based on the query result, and performing image acquisition on the product to be traced to obtain a feature verification image specifically includes:
extracting component characteristic information based on the query result, and classifying the component characteristic information to obtain appearance color characteristics and appearance shape characteristics;
determining an image acquisition angle according to the feature information of the component, and controlling an image acquisition device to record video of the product to be traced according to the image acquisition angle;
at least one frame of picture is selected as a feature verification image based on the recorded video.
Preferably, the step of extracting the physical characteristics of the image to be verified, comparing the extracted physical characteristic information with the component characteristic information, calculating the coincidence rate, and when the coincidence rate is higher than a preset value, regarding the step as that the verification is passed, specifically includes:
extracting shape characteristics and color characteristics of the image to be verified to obtain physical characteristic information;
verifying the component characteristic information based on the physical characteristic information, and calculating color similarity and shape similarity;
and calculating the coincidence rate based on the color similarity and the shape similarity, and when the coincidence rate is higher than a preset value, considering that the verification is passed.
Preferably, when verifying the coincidence rate, the preset value is adjusted according to the delivery time of the product, and the longer the delivery time is, the smaller the preset value is.
Preferably, when the shape similarity is calculated, binarization processing and Hough transformation are carried out on the image to be verified, and the image to be verified is converted into a line drawing.
Preferably, the line drawing of the product framework structure is recorded in the whole machine tracing information.
Preferably, the information of the product to be traced is extracted by scanning a two-dimensional code or by text recognition.
Preferably, when verification fails, the product is regarded as a source tracing failure.
Another object of an embodiment of the present application is to provide a product traceability verification system based on a blockchain technology, the system including:
the block chain storage module is used for acquiring product factory data and storing the product factory data in the block chain, wherein the product factory data at least comprises complete machine tracing information and component tracing information, and the component tracing information at least comprises component characteristic information;
the serial number tracing module is used for acquiring product information to be traced, extracting part serial number data and whole machine serial number data from the product information to be traced, and tracing and inquiring based on the whole machine serial number data and the part serial number data to obtain an inquiring result;
the image processing module is used for extracting component characteristic information based on the query result, and carrying out image acquisition on the product to be traced to obtain a characteristic verification image, wherein the angle of image acquisition is the same as the angle recorded in the component characteristic information;
the feature verification module is used for extracting the physical features of the image to be verified, comparing the extracted physical feature information with the component feature information, calculating the coincidence rate, and considering that verification is passed when the coincidence rate is higher than a preset value.
Preferably, the numbering tracing module includes:
the product information acquisition unit is used for acquiring product information to be traced, wherein the product information to be traced at least comprises a complete machine number and a part number, and the complete machine number and the part number are unique;
the product matching unit is used for extracting the component number data and the whole machine number data, downloading corresponding data from the block chain, performing one-by-one matching, and inquiring corresponding whole machine tracing information and component tracing information;
and the numbering inquiry unit is used for judging whether the part tracing information obtained by inquiry is matched with the whole machine tracing information or not according to the whole machine tracing information, and if the part tracing information is not matched with the part tracing information, the part tracing information is regarded as a non-inquiry result.
Preferably, the image processing module includes:
the appearance characteristic extraction unit is used for extracting component characteristic information based on the query result, classifying the component characteristic information and obtaining appearance color characteristics and appearance shape characteristics;
the video recording unit is used for determining an image acquisition angle according to the component characteristic information and controlling the image acquisition equipment to record the video of the product to be traced according to the image acquisition angle;
and the image extraction unit is used for selecting at least one frame of picture as a characteristic verification image based on the recorded video.
Preferably, the feature verification module includes:
the physical characteristic extraction unit is used for extracting shape characteristics and color characteristics of the image to be verified to obtain physical characteristic information;
the similarity calculation unit is used for verifying the component characteristic information based on the physical characteristic information and calculating color similarity and shape similarity;
and the coincidence checking unit is used for calculating the coincidence rate based on the color similarity and the shape similarity, and when the coincidence rate is higher than a preset value, the coincidence rate is considered to pass the verification.
According to the product traceability verification method based on the blockchain technology, the traceability data are stored in the blockchain, the corresponding traceability data can be obtained when the traceability verification is carried out, and the reliability of the component is further verified through comparison of the color characteristics and the shape characteristics, so that the traceability reliability of the product is guaranteed.
Drawings
FIG. 1 is a flowchart of a product traceability verification method based on a blockchain technique according to an embodiment of the present application;
fig. 2 is a flowchart of a step of obtaining product information to be traced, extracting part number data and whole machine number data from the product information, and tracing and inquiring based on the whole machine number data and the part number data to obtain an inquiry result, provided by the embodiment of the application;
FIG. 3 is a flowchart of a step of extracting feature information of a component based on a query result, performing image acquisition on a product to be traced, and obtaining a feature verification image according to an embodiment of the present application;
fig. 4 is a flowchart of a step of extracting physical characteristics of an image to be verified, comparing the extracted physical characteristic information with component characteristic information, calculating a coincidence rate, and considering that verification is passed when the coincidence rate is higher than a preset value;
FIG. 5 is a block chain technology-based architecture diagram of a product traceability verification system according to an embodiment of the present application;
fig. 6 is a architecture diagram of a numbering tracing module according to an embodiment of the present application;
fig. 7 is a schematic diagram of an image processing module according to an embodiment of the present application;
fig. 8 is a schematic diagram of a feature verification module according to an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
As shown in fig. 1, a flowchart of a product traceability verification method based on a blockchain technology according to an embodiment of the present application is shown, where the method includes:
s100, product factory data are obtained and stored in a block chain, wherein the product factory data at least comprise complete machine traceability information and component traceability information, and the component traceability information at least comprises component characteristic information.
In this step, product factory data is obtained, when the product is shipped, the product complete machine number and the line drawing of the complete machine are recorded, the line drawing is a line structure obtained by performing binarization processing and Hough transformation after image acquisition, the line drawing is stored in a vector diagram mode, so that the line drawing can be used as complete machine traceability information, traceability information is also set for each component forming the complete machine, specifically, the factory color, the shape (namely component characteristic information) and the component number of the component are included, the uniqueness is achieved, the data are packaged and issued in a block chain, and the safety of the traceability data can be ensured because the block chain has the characteristic of non-tampering.
S200, obtaining product information to be traced, extracting part number data and whole machine number data from the product information, and tracing and inquiring based on the whole machine number data and the part number data to obtain an inquiring result.
In this step, the product information to be traced is obtained, the product information to be traced is all from the real object of the product to be traced, the two-dimensional code and the text pasted or imprinted on the product information to be traced are extracted, the component number data and the whole machine number data are obtained through extraction, if the product information is the two-dimensional code, the product information is obtained through code scanning, if the product information is the text information, the product information can be input through manual input, the product information can also be input through text recognition, tracing inquiry is performed based on the whole machine number data and the component number data, an inquiry result is obtained, and the inquiry result is the corresponding whole machine tracing information and the corresponding component tracing information.
And S300, extracting component characteristic information based on the query result, and carrying out image acquisition on the product to be traced to obtain a characteristic verification image, wherein the image acquisition angle is the same as the angle recorded in the component characteristic information.
In this step, component feature information is extracted based on the query result, and the shape feature and the color feature of the product are recorded in the component feature information, then for comparison, image acquisition is performed on the product to be traced to obtain a feature verification image for comparison, and a line drawing of the whole machine is recorded in the tracing information of the whole machine, so that image acquisition is required to be performed according to the shooting angle recorded by the line drawing to obtain the feature verification image, further, the recorded video can be compared with the line drawing by recording the video, and if the line drawing can be overlapped with the product in the video, the picture at the moment is taken as the feature verification image.
S400, extracting physical characteristics of the image to be verified, comparing the extracted physical characteristic information with the component characteristic information, calculating the coincidence rate, and considering that verification is passed when the coincidence rate is higher than a preset value.
In the step, the physical characteristic extraction is carried out on the image to be verified, in the image to be verified, the position of the product to be traced is determined, then the position of each component is also determined, each component can be positioned accordingly, the color information and the shape information of each component are determined, the physical characteristic information is extracted, the physical characteristic information is compared with the component characteristic information obtained by inquiry, the coincidence rate is calculated, when the coincidence rate is higher than a preset value, the current product to be traced is proved to pass tracing verification, the identity of the current product to be traced can be determined, otherwise, the correlation between the tracing data obtained by current inquiry and the product to be traced is low, and the identity of the current product to be traced cannot be determined.
As shown in fig. 2, as a preferred embodiment of the present application, the steps of obtaining the information of the product to be traced, extracting the part number data and the whole machine number data from the information, and tracing and inquiring based on the whole machine number data and the part number data to obtain an inquiry result specifically include:
s201, obtaining to-be-traced product information, wherein the to-be-traced product information at least comprises a complete machine number and a part number, and the complete machine number and the part number are unique.
In the step, the information of the product to be traced is obtained, the information is obtained by scanning a two-dimensional code or extracting the information through image recognition, and finally, all the obtained information is text data, and the whole machine or the part obtained by inquiry is unique because the whole machine number and the part number are unique.
S202, extracting part number data and whole machine number data, downloading corresponding data from a block chain, performing matching one by one, and inquiring corresponding whole machine tracing information and part tracing information.
In this step, the component number data and the complete machine number data are extracted, the block in which the data are stored can be determined based on the component number and the complete machine number, and downloaded, and the corresponding complete machine tracing information and the component tracing information are further searched in a searching manner.
And S203, judging whether the part traceability information obtained by query is matched with the whole machine traceability information according to the whole machine traceability information, and if not, judging that no query result exists.
In this step, whether the component tracing information obtained by query is matched with the component tracing information is determined according to the complete machine tracing information, if the complete machine A is assembled by the components A1, A2, A3, A4 and A5, the number of the complete machine and the number of the five components have a corresponding relationship, if the retrieved complete machine tracing information is not matched with the component tracing information, no query result is considered, namely tracing failure is considered.
As shown in fig. 3, as a preferred embodiment of the present application, the step of extracting feature information of a component based on a query result, and performing image acquisition on a product to be traced to obtain a feature verification image specifically includes:
s301, extracting component characteristic information based on the query result, and classifying the component characteristic information to obtain appearance color characteristics and appearance shape characteristics.
In this step, component feature information is extracted based on the query result, the component feature information records the shape structure and color condition of the product, that is, the appearance color feature and the appearance shape feature, and the appearance color feature is recorded by RGB colors.
S302, determining an image acquisition angle according to the component characteristic information, and controlling the image acquisition equipment to record the video of the product to be traced according to the image acquisition angle.
In this step, the image acquisition angle is determined according to the feature information of the component, and different angles are adopted for shooting, so that the integrally corresponding images are different, and in order to ensure that the finally obtained feature verification image and the complete machine tracing information have the same angle, the image acquisition angle can be determined by recording a video.
S303, selecting at least one frame of picture as a feature verification image based on the recorded video.
In the step, video recording is carried out, the recorded video is subjected to linearization processing, the linearization video is compared with a proper amount of line drawings recorded in the whole machine tracing information, and if the line drawings can be overlapped, the current picture is selected as a characteristic verification image.
As shown in fig. 4, as a preferred embodiment of the present application, the step of extracting the physical characteristics of the image to be verified, comparing the extracted physical characteristic information with the component characteristic information, and calculating the coincidence rate, when the coincidence rate is higher than a preset value, the step of identifying that the verification is passed specifically includes:
s401, extracting shape features and color features of the image to be verified to obtain physical feature information.
In the step, shape feature extraction and color feature extraction are carried out on the image to be checked, specifically, the positions of all the components in the image are determined, the outline shape of the components is further determined, and the pixel color information of the corresponding pixels is identified according to the positions of the components, so that the physical feature information is obtained.
S402, verifying the component characteristic information based on the physical characteristic information, and calculating the color similarity and the shape similarity.
In the step, the component characteristic information is verified based on the physical characteristic information, specifically, the extracted shape is compared with the shape recorded in the component traceability information, the shape similarity is calculated, and the color similarity is calculated in the same way.
S403, calculating the coincidence rate based on the color similarity and the shape similarity, and when the coincidence rate is higher than a preset value, considering that the verification is passed.
In this step, the coincidence rate is calculated based on the color similarity and the shape similarity, specifically, the coincidence rate is calculated according to a preset weighted value, the coincidence rate=color coefficient×color similarity+shape coefficient×shape similarity, and the preset value is adjusted according to the product delivery time, and the longer the delivery time, the smaller the preset value is, because the color will naturally change in the long-term use process, specifically, according to the material characteristic setting, when the coincidence rate is higher than the preset value, the verification is considered to pass.
As shown in fig. 5, a product traceability verification system based on a blockchain technology according to an embodiment of the present application includes:
the block chain storage module 100 is configured to obtain product factory data, and store the product factory data in a block chain, where the product factory data includes at least complete machine tracing information and component tracing information, and the component tracing information includes at least component feature information.
In the system, the blockchain storage module 100 acquires product delivery data, records the whole machine number of the product and a line drawing of the whole machine when the product delivers the product, wherein the line drawing is a line structure obtained by performing binarization processing and Hough transformation after image acquisition, and stores the line drawing in a vector diagram mode, namely, the line drawing can be used as whole machine traceability information, traceability information is also set for each part forming the whole machine, and the traceability information specifically comprises delivery color, shape (namely, part characteristic information) of the part and the number of the part, has uniqueness no matter the number of the whole machine or the number of the part, packages the data and distributes the data in a blockchain, and can ensure the safety of the traceability data due to the fact that the blockchain has the non-tamperable characteristic.
The serial number tracing module 200 is configured to obtain information of a product to be traced, extract part serial number data and complete machine serial number data from the information, and perform tracing inquiry based on the complete machine serial number data and the part serial number data to obtain an inquiry result.
In the system, the serial number tracing module 200 acquires information of a product to be traced, the information of the product to be traced is all from a real object of the product to be traced, two-dimensional codes and characters pasted or imprinted on the information of the product to be traced are extracted, part serial number data and whole machine serial number data are firstly extracted, if the information is the two-dimensional codes, the information is acquired in a code scanning mode, if the information is the characters, the information can be input in a manual input mode, and also can be input in a character recognition mode, tracing inquiry is carried out based on the whole machine serial number data and the part serial number data, an inquiry result is obtained, and the inquiry result is the corresponding whole machine tracing information and the corresponding part tracing information.
The image processing module 300 is configured to extract feature information of a component based on a query result, perform image acquisition on a product to be traced, and obtain a feature verification image, where an angle of image acquisition is the same as an angle recorded in the feature information of the component.
In the system, the image processing module 300 extracts feature information of the components based on the query result, the shape features and color features of the products are recorded in the feature information, then for comparison, image acquisition is performed on the product to be traced to obtain a feature verification image for comparison, and line drawings of the whole machine are recorded in the tracing information of the whole machine, so that image acquisition is required according to the shooting angle recorded by the line drawings to obtain the feature verification image, further, the recorded video can be compared with the line drawings by recording the video, and if the line drawings can be overlapped with the products in the video, the picture at the moment is taken as the feature verification image.
The feature verification module 400 is configured to perform physical feature extraction on the image to be verified, compare the extracted physical feature information with the component feature information, and calculate a coincidence rate, and when the coincidence rate is higher than a preset value, the verification is considered to pass.
In the system, the feature verification module 400 performs physical feature extraction on the image to be verified, in the image to be verified, the position of the product to be traced is determined, then the position of each component is also determined, each component can be positioned accordingly, color information and shape information of each component are determined, physical feature information is extracted and obtained, the physical feature information is compared with the component feature information obtained by inquiry, the coincidence rate is calculated, when the coincidence rate is higher than a preset value, the current product to be traced is indicated to be traced and verified, the identity of the current product to be traced can be determined, otherwise, the correlation between the tracing data obtained by current inquiry and the product to be traced is indicated to be low, and the identity of the current product to be traced cannot be determined.
As shown in fig. 6, as a preferred embodiment of the present application, the numbering trace module 200 includes:
the product information obtaining unit 201 is configured to obtain product information to be traced, where the product information to be traced at least includes a complete machine number and a component number, and the complete machine number and the component number have uniqueness.
In this module, the product information obtaining unit 201 obtains the product information to be traced, where the information is obtained by scanning a two-dimensional code or extracting through image recognition, and the obtained text data is finally obtained, and since the complete machine number and the component number have uniqueness, the complete machine or the component obtained by querying is also unique.
The product matching unit 202 is configured to extract the part number data and the complete machine number data, download corresponding data from the blockchain, and perform matching one by one, so as to query corresponding complete machine tracing information and part tracing information.
In this module, the product matching unit 202 extracts the part number data and the whole machine number data, and can determine the block in which the data is stored based on the part number and the whole machine number, download the block, and further search the corresponding whole machine tracing information and the part tracing information in a searching manner.
And the number query unit 203 is configured to determine whether the component tracing information obtained by the query matches the component tracing information according to the complete machine tracing information, and if not, consider that there is no query result.
In this module, the number query unit 203 determines, according to the complete machine tracing information, whether the queried component tracing information is matched with the complete machine tracing information, where the complete machine and the components have a matching relationship, if the complete machine a is assembled by the components A1, A2, A3, A4 and A5, then the number of the complete machine and the numbers of the five components have a corresponding relationship, and if the retrieved complete machine tracing information is not matched with the component tracing information, the complete machine is considered as no query result, that is, tracing failure.
As shown in fig. 7, as a preferred embodiment of the present application, the image processing module 300 includes:
the appearance feature extracting unit 301 is configured to extract component feature information based on the query result, and classify the component feature information to obtain appearance color features and appearance shape features.
In this module, the appearance feature extraction unit 301 extracts component feature information based on the query result, the component feature information records the shape structure and color condition of the product, that is, appearance color features and appearance shape features, and the appearance color features are recorded by RGB colors.
The video recording unit 302 is configured to determine an image acquisition angle according to the feature information of the component, and control the image acquisition device to record video of the product to be traced according to the image acquisition angle.
In this module, the video recording unit 302 determines the image acquisition angle according to the feature information of the component, and shoots with different angles, so that the corresponding overall images are different, and in order to ensure that the finally obtained feature verification image has the same angle as the whole machine tracing information, the video recording unit can determine the feature verification image by recording the video.
An image extraction unit 303 is configured to select at least one frame of picture as a feature verification image based on the recorded video.
In this module, the image extraction unit 303 records a video, performs a linearization process on the recorded video, compares the streaked video with a proper line drawing recorded in the entire machine tracing information, and if the line drawing is coincident, selects the current picture as a feature verification image.
As shown in fig. 8, as a preferred embodiment of the present application, the feature verification module 400 includes:
the physical feature extraction unit 401 is configured to perform shape feature extraction and color feature extraction on the image to be verified, so as to obtain physical feature information.
In this module, the physical feature extraction unit 401 performs shape feature extraction and color feature extraction on the image to be checked, specifically, determines the position of each component in the image, further determines the shape of the outline thereof, and identifies the pixel color information of each corresponding pixel according to the position of the component, thereby obtaining physical feature information.
And a similarity calculating unit 402 for verifying the feature information of the component based on the feature information of the object, and calculating the color similarity and the shape similarity.
In this module, the similarity calculation unit 402 verifies feature information of the component based on the feature information of the real object, specifically, compares the extracted shape with the shape recorded in the traceability information of the component, calculates the shape similarity, and similarly calculates the color similarity.
And a coincidence checking unit 403 for calculating a coincidence rate based on the color similarity and the shape similarity, and when the coincidence rate is higher than a preset value, it is regarded as passing the verification.
In this module, the coincidence checking unit 403 calculates the coincidence rate based on the color similarity and the shape similarity, specifically, calculates the coincidence rate according to a preset weighted value, where the coincidence rate=color coefficient×color similarity+shape coefficient×shape similarity, and the preset value is adjusted according to the product delivery time, and the longer the delivery time, the smaller the preset value is, because the color will naturally change during long-term use, specifically, according to the material feature setting, when the coincidence rate is higher than the preset value, it is regarded as passing the verification.
It should be understood that, although the steps in the flowcharts of the embodiments of the present application are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in various embodiments may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
The foregoing description of the preferred embodiments of the application is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the application.
Claims (9)
1. The product traceability verification method based on the blockchain technology is characterized by comprising the following steps of:
acquiring product factory data, and storing the product factory data in a blockchain, wherein the product factory data at least comprises complete machine tracing information and component tracing information, and the component tracing information at least comprises component characteristic information;
acquiring product information to be traced, extracting part number data and whole machine number data from the product information, and tracing and inquiring based on the whole machine number data and the part number data to obtain an inquiry result;
extracting component characteristic information based on the query result, and carrying out image acquisition on a product to be traced to obtain a characteristic verification image, wherein the angle of image acquisition is the same as the angle recorded in the component characteristic information;
and extracting physical characteristics of the image to be verified, comparing the extracted physical characteristic information with the component characteristic information, calculating the coincidence rate, and when the coincidence rate is higher than a preset value, considering that verification is passed.
2. The blockchain technology-based product traceability verification method according to claim 1, wherein the step of obtaining the product information to be traced, extracting the part number data and the whole machine number data from the obtained product information, and tracing and inquiring based on the whole machine number data and the part number data to obtain an inquiry result specifically comprises the following steps:
obtaining product information to be traced, wherein the product information to be traced at least comprises a complete machine number and a part number, and the complete machine number and the part number have uniqueness;
extracting part number data and whole machine number data, downloading corresponding data from a blockchain, and carrying out matching one by one to inquire corresponding whole machine tracing information and part tracing information;
judging whether the part tracing information obtained by query is matched with the whole machine tracing information or not according to the whole machine tracing information, and if not, judging that no query result exists.
3. The blockchain technology-based product traceability verification method according to claim 1, wherein the step of extracting feature information of a component based on a query result, and performing image acquisition on a product to be traced to obtain a feature verification image specifically comprises the steps of:
extracting component characteristic information based on the query result, and classifying the component characteristic information to obtain appearance color characteristics and appearance shape characteristics;
determining an image acquisition angle according to the feature information of the component, and controlling an image acquisition device to record video of the product to be traced according to the image acquisition angle;
at least one frame of picture is selected as a feature verification image based on the recorded video.
4. The blockchain technology-based product traceability verification method according to claim 1, wherein the step of extracting the physical characteristics of the image to be verified, comparing the extracted physical characteristic information with the component characteristic information, and calculating the coincidence rate, wherein when the coincidence rate is higher than a preset value, the step is regarded as verification passing, and specifically comprises the following steps:
extracting shape characteristics and color characteristics of the image to be verified to obtain physical characteristic information;
verifying the component characteristic information based on the physical characteristic information, and calculating color similarity and shape similarity;
and calculating the coincidence rate based on the color similarity and the shape similarity, and when the coincidence rate is higher than a preset value, considering that the verification is passed.
5. The blockchain technology-based product traceability verification method according to claim 1, wherein the preset value is adjusted according to the product delivery time when verifying the coincidence rate, and the preset value is smaller as the delivery time is longer.
6. The blockchain technology-based product traceability verification method according to claim 4, wherein when the shape similarity is calculated, binarization processing and Hough transformation are performed on the image to be verified, and the image is converted into a line drawing.
7. The blockchain technology-based product traceability verification method according to claim 1, wherein the whole machine traceability information is recorded with a product frame structure line drawing.
8. The blockchain technology-based product traceability verification method according to claim 1, wherein the product information to be traced is extracted by scanning a two-dimensional code or by text recognition.
9. The blockchain technology-based product traceability verification method according to claim 1, wherein when verification fails, the product traceability is considered as failed.
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