CN110879968A - Anti-counterfeiting identification method and device for fruits and vegetables - Google Patents

Anti-counterfeiting identification method and device for fruits and vegetables Download PDF

Info

Publication number
CN110879968A
CN110879968A CN201910995400.3A CN201910995400A CN110879968A CN 110879968 A CN110879968 A CN 110879968A CN 201910995400 A CN201910995400 A CN 201910995400A CN 110879968 A CN110879968 A CN 110879968A
Authority
CN
China
Prior art keywords
fruit
counterfeiting
vegetable
image information
image
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201910995400.3A
Other languages
Chinese (zh)
Inventor
姜微波
杜镇蛟
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China Agricultural University
Original Assignee
China Agricultural University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by China Agricultural University filed Critical China Agricultural University
Priority to CN201910995400.3A priority Critical patent/CN110879968A/en
Publication of CN110879968A publication Critical patent/CN110879968A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/80Recognising image objects characterised by unique random patterns
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/22Matching criteria, e.g. proximity measures
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/018Certifying business or products
    • G06Q30/0185Product, service or business identity fraud
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/02Agriculture; Fishing; Forestry; Mining

Landscapes

  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Business, Economics & Management (AREA)
  • Strategic Management (AREA)
  • Marketing (AREA)
  • Economics (AREA)
  • Accounting & Taxation (AREA)
  • Artificial Intelligence (AREA)
  • Multimedia (AREA)
  • Evolutionary Computation (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Evolutionary Biology (AREA)
  • Development Economics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Finance (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • General Engineering & Computer Science (AREA)
  • Agronomy & Crop Science (AREA)
  • Animal Husbandry (AREA)
  • Marine Sciences & Fisheries (AREA)
  • Mining & Mineral Resources (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Human Resources & Organizations (AREA)
  • Primary Health Care (AREA)
  • Tourism & Hospitality (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The embodiment of the invention provides a fruit and vegetable anti-counterfeiting identification method and a device, wherein the method comprises the following steps: acquiring anti-counterfeiting image information of fruits and vegetables; analyzing the fruit and vegetable anti-counterfeiting image information to obtain an anti-counterfeiting identification image and fruit and vegetable grain image information around the anti-counterfeiting identification image; obtaining anti-counterfeiting number information according to the anti-counterfeiting identification image, and obtaining fruit and vegetable verification image information corresponding to the anti-counterfeiting number information from a preset database; and comparing and analyzing the fruit and vegetable anti-counterfeiting image information according to the fruit and vegetable verification image information to obtain an anti-counterfeiting identification result. The anti-counterfeiting identification method has the advantages that the anti-counterfeiting identification image information of the fruits and the vegetables is obtained through the anti-counterfeiting identification image, the fruit and vegetable natural texture image information with uniqueness generated by the fruit and vegetable shape information around the anti-counterfeiting identification image, the characteristics of the anti-counterfeiting identification image cannot be replaced, the anti-counterfeiting identification of a single fruit and vegetable product can be accurately achieved, and the anti-counterfeiting identification can be repeatedly carried out for many times.

Description

Anti-counterfeiting identification method and device for fruits and vegetables
Technical Field
The invention relates to the technical field of agricultural information, in particular to a fruit and vegetable anti-counterfeiting identification method and device.
Background
Food counterfeiting brings great economic loss, consumer confidence is damaged, and meanwhile, the food safety risk is high, the annual output of fruit and vegetable products in China is up to billions of tons, the fruit and vegetable products are one of the products which are most prone to counterfeiting risk, the bar code system is still relied on, the whole box is used as an anti-counterfeiting unit, and the anti-counterfeiting of the fruit and vegetable products is not accurate to a single fruit and vegetable individual. Therefore, the manufacturing cost risks of stealing and replacing individual fruit and vegetable products and the like can be brought. In the prior art, an isotope traceability method or a DNA analysis method can realize accurate anti-counterfeiting identification on a single fruit and vegetable product, but the methods are high in cost and complex in operation, and have no potential for popularization.
Therefore, how to more efficiently realize the nondestructive fruit and vegetable anti-counterfeiting identification method becomes an urgent problem to be solved in the industry.
Disclosure of Invention
The embodiment of the invention provides an anti-counterfeiting identification method and device for fruits and vegetables, which are used for solving the technical problems in the background technology or at least partially solving the technical problems in the background technology.
In a first aspect, an embodiment of the present invention provides an anti-counterfeiting identification method for fruits and vegetables, including:
acquiring anti-counterfeiting image information of fruits and vegetables;
analyzing the fruit and vegetable anti-counterfeiting image information to obtain an anti-counterfeiting identification image and fruit and vegetable grain image information around the anti-counterfeiting identification image;
obtaining anti-counterfeiting number information according to the anti-counterfeiting identification image, and obtaining fruit and vegetable verification image information corresponding to the anti-counterfeiting number information from a preset database;
and comparing and analyzing the fruit and vegetable anti-counterfeiting image information according to the fruit and vegetable verification image information to obtain an anti-counterfeiting identification result.
More specifically, the fruit and vegetable verification image information includes: verifying the identification image and verifying texture image information of the fruits and vegetables around the verification identification image.
More specifically, the step of comparing and analyzing the fruit and vegetable anti-counterfeiting image information according to the fruit and vegetable verification image information to obtain an anti-counterfeiting identification result specifically includes:
carrying out size normalization processing on the fruit and vegetable anti-counterfeiting image information according to the pixel point information of the verification identification image to obtain normalized fruit and vegetable anti-counterfeiting image information;
analyzing the normalized fruit and vegetable anti-counterfeiting image information to obtain a normalized anti-counterfeiting mark image and normalized fruit and vegetable grain image information around the normalized anti-counterfeiting mark image;
and comparing and analyzing the normalized fruit and vegetable grain image information and the fruit and vegetable verification grain image information to obtain an anti-counterfeiting identification result.
More specifically, the step of comparing and analyzing the normalized fruit and vegetable grain image information and the fruit and vegetable verification grain image information to obtain an anti-counterfeiting identification result specifically comprises:
taking the verification mark image and the normalized anti-counterfeiting mark image as a common point, and calculating a similarity value according to fruit and vegetable verification texture image information around the verification mark image and normalized fruit and vegetable texture image information around the normalized anti-counterfeiting mark image to obtain a similarity calculation result;
and obtaining an anti-counterfeiting identification result according to the similarity calculation result.
More specifically, the step of calculating the similarity value according to the fruit and vegetable verification texture image information around the verification identification image and the normalized fruit and vegetable texture image information around the normalized anti-counterfeiting identification image specifically includes:
taking the verification mark image and the normalized anti-counterfeiting mark image as a common point, and translating or rotating the normalized fruit and vegetable grain image information around the normalized anti-counterfeiting mark image; obtaining the information of the adjusted and normalized fruit and vegetable grain images; and carrying out similarity value settlement according to the adjusted and normalized fruit and vegetable grain image information and the fruit and vegetable verification grain image information around the verification identification image. More specifically, before the step of obtaining the anti-counterfeiting number information according to the anti-counterfeiting identification image and obtaining the fruit and vegetable verification image information corresponding to the anti-counterfeiting number information in a preset database, the method further comprises the following steps:
acquiring fruit and vegetable verification image information;
and obtaining anti-counterfeiting number information according to the verification identification image of the fruit and vegetable verification image information, and storing the fruit and vegetable verification image information to a preset database according to the anti-counterfeiting number information.
In a second aspect, an embodiment of the present invention provides an anti-counterfeit device for identifying fruits and vegetables, including:
the acquisition module is used for acquiring anti-counterfeiting image information of the fruits and the vegetables;
the analysis module is used for analyzing the fruit and vegetable anti-counterfeiting image information to obtain an anti-counterfeiting mark image and fruit and vegetable grain image information around the anti-counterfeiting mark image;
the computing module is used for obtaining anti-counterfeiting number information according to the anti-counterfeiting identification image and obtaining fruit and vegetable verification image information corresponding to the anti-counterfeiting number information from a preset database;
and the identification module is used for comparing and analyzing the anti-counterfeiting image information of the fruits and the vegetables according to the fruit and vegetable verification image information to obtain an anti-counterfeiting identification result.
In a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program that is stored in the memory and can be run on the processor, where the processor executes the computer program to implement the steps of the anti-counterfeiting fruit and vegetable identification method according to the first aspect.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the fruit and vegetable anti-counterfeiting identification method according to the first aspect.
The embodiment of the invention provides a fruit and vegetable anti-counterfeiting identification method and a device, which are characterized in that the anti-counterfeiting identification image information of the fruit and vegetable is obtained through the anti-counterfeiting identification image, the fruit and vegetable line image information with uniqueness generated by the natural fruit and vegetable texture and the fruit and vegetable shape information at the periphery of the anti-counterfeiting identification image, and the fruit and vegetable verification image information corresponding to the anti-counterfeiting identification image stored in a preset database in advance is obtained through the universal anti-counterfeiting identification image, so that the fruit and vegetable anti-counterfeiting identification result is obtained by verifying the fruit and vegetable line image information with uniqueness and the pre-stored fruit and vegetable verification image information in a comparison way.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of an anti-counterfeiting identification method for fruits and vegetables according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating the distribution of the number of dissimilar regions between pears of different identities and the same identity in accordance with one embodiment of the present invention;
FIG. 3 is a diagram illustrating the distribution of the magnitude of dissimilar region between watermelons of different identities and the same identity according to another embodiment of the present invention;
FIG. 4 is a schematic structural diagram of an anti-counterfeit device for identifying fruits and vegetables according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. 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.
Fig. 1 is a schematic flow chart of an anti-counterfeiting identification method for fruits and vegetables according to an embodiment of the present invention, as shown in fig. 1, including:
step S1, acquiring anti-fake image information of the fruits and vegetables;
step S2, analyzing the fruit and vegetable anti-counterfeiting image information to obtain an anti-counterfeiting identification image and fruit and vegetable grain image information around the anti-counterfeiting identification image;
step S3, obtaining anti-counterfeiting number information according to the anti-counterfeiting identification image, and obtaining fruit and vegetable verification image information corresponding to the anti-counterfeiting number information from a preset database;
and step S4, comparing and analyzing the anti-counterfeiting image information of the fruits and vegetables according to the fruit and vegetable verification image information to obtain an anti-counterfeiting identification result.
The anti-counterfeiting mark image described in the embodiment of the invention refers to a stickable printing mark with a specific shape, pattern or character, the anti-counterfeiting mark image has a corresponding specific number in a preset database, and the stored data information can be found in the preset database through the specific number corresponding to the anti-counterfeiting mark image; the anti-counterfeiting mark image described in the embodiment of the invention can be a bar code image, a two-dimensional code image or a three-dimensional code image.
The fruit and vegetable grain image information around the anti-counterfeiting mark image described in the embodiment of the invention means that the anti-counterfeiting mark image has clear and identifiable natural vegetable and fruit grain characteristics, fruit surface shape characteristics, fruit surface spots or patch characteristics, and the natural grain characteristics comprise muskmelon fruit surface reticulate, muskmelon fruit surface stripes, fig fruit surface strips and the like; fruit surface shape characteristics such as the shape of the fruit of dragon fruit, durian, polo honey, custard apple, lychee, prickly pear, finger citron; blotches on fruit surfaces, features of plaques such as skin holes on fruit surfaces of apples, pears, mangoes, zucchini and wax gourd, and pigmented spots on fruit surfaces of nectarines, pomegranates, etc.
The fruit and vegetable texture image information described in the embodiment of the invention is the fruit and vegetable texture image in the specific area of the anti-counterfeiting mark image.
The anti-counterfeiting number information described in the embodiment of the present invention may be pre-stored in the anti-counterfeiting label image, for example, when the anti-counterfeiting label image is a barcode image, a two-dimensional code image or a three-dimensional code image, the anti-counterfeiting number information may be represented by a barcode, a two-dimensional code or a three-dimensional code.
The preset database described in the embodiment of the invention is used for shooting the fruit and vegetable verification image information according to a preset pixel value, wherein the fruit and vegetable verification image information comprises a verification identification image and fruit and vegetable verification texture image information around the verification identification image, then the anti-counterfeiting number information is obtained by identifying the verification identification image, and the fruit and vegetable verification image information is stored according to the anti-counterfeiting number information.
The embodiment of the invention describes that the fruit and vegetable anti-counterfeiting image information is compared and analyzed according to the fruit and vegetable verification image information, specifically, pixel point information of a verification identification image in the fruit and vegetable verification image information is obtained, then pixel normalization processing is carried out on the anti-counterfeiting identification image in the fruit and vegetable anti-counterfeiting image information according to the pixel point information of the verification identification image, meanwhile, the same pixel normalization processing is also carried out on fruit and vegetable grain image information around the anti-counterfeiting identification image, normalized fruit and vegetable anti-counterfeiting image information is obtained, the anti-counterfeiting identification image and the verification identification image are ensured to be consistent in size, and subsequent verification is facilitated.
Comparing the normalized fruit and vegetable anti-counterfeiting image information with the fruit and vegetable verification image information, wherein the sizes of the anti-counterfeiting mark image and the verification mark image are consistent, the anti-counterfeiting mark image and the verification mark image are used as a common point, the fruit and vegetable verification image information and the fruit and vegetable texture image information around the common point are compared to obtain a similarity calculation result, if the similarity calculation result meets a preset condition, the anti-counterfeiting identification result is passed, and if the similarity calculation result does not meet the preset condition, the anti-counterfeiting identification result is not passed.
The embodiment of the invention obtains the anti-counterfeiting image information of the fruits and vegetables through the anti-counterfeiting mark image and the unique fruit and vegetable grain image information generated by the natural fruit and vegetable grains and the fruit and vegetable shape information around the anti-counterfeiting mark image, and obtains the fruit and vegetable verification image information corresponding to the anti-counterfeiting mark image prestored in the preset database through the universal anti-counterfeiting mark image, so that the anti-counterfeiting identification result of the fruits and vegetables is obtained by verifying the unique fruit and vegetable grain image information and the prestored fruit and vegetable verification image information in a comparison way.
On the basis of the above embodiment, the fruit and vegetable verification image information includes: verifying the identification image and verifying texture image information of the fruits and vegetables around the verification identification image.
The fruit and vegetable verification texture image information around the verification identification image described in the embodiment of the invention is the verification identification image as a reference system, the collected image information of the area with the specific size around the verification identification image contains the fruit and vegetable textures, and the size of the fruit and vegetable verification texture image information can be obtained by subtracting the size of the verification identification image from the size of the fruit and vegetable verification image information.
The fruit and vegetable verification texture image information around the verification identification image described in the embodiment of the invention utilizes the unique fruit and vegetable texture information of each fruit and vegetable, the characteristics of the fruit and vegetable verification texture image information cannot be replaced, the anti-counterfeiting identification of a single fruit and vegetable product can be accurately achieved, and the monitoring accuracy and efficiency are improved.
On the basis of the above embodiment, the step of comparing and analyzing the fruit and vegetable anti-counterfeiting image information according to the fruit and vegetable verification image information to obtain an anti-counterfeiting identification result specifically includes:
carrying out size normalization processing on the fruit and vegetable anti-counterfeiting image information according to the pixel point information of the verification identification image to obtain normalized fruit and vegetable anti-counterfeiting image information;
analyzing the normalized fruit and vegetable anti-counterfeiting image information to obtain a normalized anti-counterfeiting mark image and normalized fruit and vegetable grain image information around the normalized anti-counterfeiting mark image;
and comparing and analyzing the normalized fruit and vegetable grain image information and the fruit and vegetable verification grain image information to obtain an anti-counterfeiting identification result.
The pixel point information of the verification identification image described in the embodiment of the invention is preset, and the size normalization processing is performed on the fruit and vegetable anti-counterfeiting image information, namely the pixel normalization processing is performed on the size of the anti-counterfeiting identification image in the fruit and vegetable anti-counterfeiting image information according to the pixel point information of the verification identification image, and the same pixel normalization processing is performed on the fruit and vegetable grain image information around the anti-counterfeiting identification image to obtain the normalized fruit and vegetable anti-counterfeiting image information.
In the embodiment of the invention, the normalized fruit and vegetable grain image information and the fruit and vegetable verification grain image information are compared and analyzed, which can mean that the similarity value of the normalized fruit and vegetable grain image information and the fruit and vegetable verification grain image information is directly calculated; or after the normalization fruit and vegetable grain image information and the fruit and vegetable verification grain image information are subjected to binarization processing, similarity value calculation can be performed.
According to the embodiment of the invention, the pixel point information of the verification identification image is subjected to size normalization processing according to the fruit and vegetable anti-counterfeiting image information, the size of the fruit and vegetable anti-counterfeiting image information is adjusted to be the same as that of the fruit and vegetable verification image information, so that the normalized fruit and vegetable grain image information and the fruit and vegetable verification grain image information are conveniently compared and analyzed, and the operation amount is reduced.
On the basis of the embodiment, the step of comparing and analyzing the normalized fruit and vegetable grain image information and the fruit and vegetable verification grain image information to obtain the anti-counterfeiting identification result specifically comprises the following steps:
taking the verification mark image and the normalized anti-counterfeiting mark image as a common point, and calculating a similarity value according to fruit and vegetable verification texture image information around the verification mark image and normalized fruit and vegetable texture image information around the normalized anti-counterfeiting mark image to obtain a similarity calculation result;
and obtaining an anti-counterfeiting identification result according to the similarity calculation result.
The similarity calculation described in the embodiment of the invention means that the number of pixel points of the overlapping region of the fruit and vegetable verification texture image information around the verification identification image and the normalized fruit and vegetable texture image information around the normalized anti-counterfeiting identification image, the number of the overlapping region and the area of the overlapping region are counted, and the calculated similarity is optimized to a certain extent according to different feature types. Preferably, when the superposed region is adjacent to the misaligned region in the matching process of the pear, the misaligned region of the adjacent superposed region is also regarded as the statistical difference of the superposed regions and the number of the regions is used as a similarity value, but in the calculation of the similarity value watermelon, the misaligned region adjacent to the superposed region does not need to be used as the basis for similarity calculation.
According to the embodiment of the invention, the similarity value calculation is carried out on the fruit and vegetable verification texture image information around the verification identification image and the normalized fruit and vegetable texture image information around the normalized anti-counterfeiting identification image, so that the anti-counterfeiting identification of the fruit and vegetable can be more accurately realized.
On the basis of the above embodiment, the step of calculating the similarity value according to the fruit and vegetable verification texture image information around the verification identification image and the normalized fruit and vegetable texture image information around the normalized anti-counterfeiting identification image specifically includes:
taking the verification mark image and the normalized anti-counterfeiting mark image as a common point, and translating or rotating the normalized fruit and vegetable grain image information around the normalized anti-counterfeiting mark image; obtaining the information of the adjusted and normalized fruit and vegetable grain images;
and carrying out similarity value settlement according to the adjusted and normalized fruit and vegetable grain image information and the fruit and vegetable verification grain image information around the verification identification image.
Specifically, the translation and rotation described in the embodiment of the present invention refer to that a common point between the verification identifier image and the normalized anti-counterfeit identifier image is used as a reference point, the normalized fruit and vegetable grain image information around the normalized anti-counterfeit identifier image is translated or rotated, and a similarity value matching every translation or rotation is recorded, wherein 1% -20% of pixel points of the total pixel size of the image are translated every time, all pixel points are traversed, and the rotation is performed by 0.1-5.0 degrees every time, and the translation and the rotation are performed again for matching.
The translation or rotation described in the embodiment of the invention can further improve the result of similarity value calculation, thereby improving the accuracy of anti-counterfeiting identification of fruits and vegetables.
On the basis of the above embodiment, before the step of obtaining the anti-counterfeiting number information according to the anti-counterfeiting identification image and obtaining the fruit and vegetable verification image information corresponding to the anti-counterfeiting number information in a preset database, the method further includes:
acquiring fruit and vegetable verification image information;
and obtaining anti-counterfeiting number information according to the verification identification image of the fruit and vegetable verification image information, and storing the fruit and vegetable verification image information to a preset database according to the anti-counterfeiting number information.
The fruit and vegetable verification image information obtained in the embodiment of the invention is obtained according to the preset pixel value, the fruit and vegetable verification image information comprises a verification identification image and fruit and vegetable verification texture image information around the verification identification image, and the verification identification image cannot be covered by the fruit and vegetable.
According to the embodiment of the invention, the unique fruit and vegetable verification image information with the biological characteristics of the fruit and vegetable is stored in advance, so that the biological characteristics have uniqueness, and the accuracy of anti-counterfeiting identification of the fruit and vegetable can be effectively ensured.
On the basis of the above embodiment, the dissimilarity calculation result corresponding to the similarity calculation result can be obtained from the similarity calculation result.
In another embodiment, fig. 2 is a schematic diagram illustrating a distribution of numbers of dissimilar areas between pears with Different identities and the Same identity according to an embodiment of the present invention, as shown in fig. 2, where Dissimilarity (Same peak's image similarity Values; SPIDV) of pears with the Same identity can obviously see that peak positions between two curves are Different, and can be distinguished by selecting a certain threshold, so as to implement identity identification, for example, 68 is used as the threshold, and the correct identification rate is 100%, and it can be ensured that a person without error is identified as correct, and a person without error is not identified as error.
FIG. 3 is a diagram illustrating a distribution of Values of Dissimilarity between watermelons of Different identities and watermelons of the Same identity according to another embodiment of the present invention, as shown in FIG. 3, wherein Dissimilarity (difference Water identity's image Dissimilarity Values; DWIDV) between watermelons of Different identities can clearly see that the peak positions of two curves are Different, and can be distinguished by selecting a certain threshold, so as to realize identity identification, for example, 7000 is used as the threshold, the correct identification rate is 100%, and it can be ensured that an incorrect identification is not correctly identified as an error, and that an incorrect identification is correctly identified as an error can also be controlled within 2%.
Fig. 4 is a schematic structural diagram of an anti-counterfeiting identification device for fruits and vegetables according to an embodiment of the present invention, as shown in fig. 4, including: an acquisition module 410, an analysis module 420, a calculation module 430, and an authentication module 440; the obtaining module 410 is used for obtaining anti-counterfeiting image information of the fruits and vegetables; the analysis module 420 is configured to analyze the fruit and vegetable anti-counterfeiting image information to obtain an anti-counterfeiting mark image and fruit and vegetable texture image information around the anti-counterfeiting mark image; the computing module 430 is configured to obtain anti-counterfeiting number information according to the anti-counterfeiting identification image, and obtain fruit and vegetable verification image information corresponding to the anti-counterfeiting number information from a preset database; the identification module 440 is configured to compare and analyze the fruit and vegetable anti-counterfeiting image information according to the fruit and vegetable verification image information to obtain an anti-counterfeiting identification result.
The apparatus provided in the embodiment of the present invention is used for executing the above method embodiments, and for details of the process and the details, reference is made to the above embodiments, which are not described herein again.
The embodiment of the invention obtains the anti-counterfeiting image information of the fruits and vegetables through the anti-counterfeiting mark image and the unique fruit and vegetable grain image information generated by the natural fruit and vegetable grains and the fruit and vegetable shape information around the anti-counterfeiting mark image, and obtains the fruit and vegetable verification image information corresponding to the anti-counterfeiting mark image prestored in the preset database through the universal anti-counterfeiting mark image, so that the anti-counterfeiting identification result of the fruits and vegetables is obtained by verifying the unique fruit and vegetable grain image information and the prestored fruit and vegetable verification image information in a comparison way.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 5, the electronic device may include: a processor (processor)510, a communication Interface (Communications Interface)520, a memory (memory)530 and a communication bus 540, wherein the processor 510, the communication Interface 520 and the memory 530 communicate with each other via the communication bus 540. Processor 510 may call logic instructions in memory 530 to perform the following method: acquiring anti-counterfeiting image information of fruits and vegetables; analyzing the fruit and vegetable anti-counterfeiting image information to obtain an anti-counterfeiting identification image and fruit and vegetable grain image information around the anti-counterfeiting identification image; obtaining anti-counterfeiting number information according to the anti-counterfeiting identification image, and obtaining fruit and vegetable verification image information corresponding to the anti-counterfeiting number information from a preset database; and comparing and analyzing the fruit and vegetable anti-counterfeiting image information according to the fruit and vegetable verification image information to obtain an anti-counterfeiting identification result.
Furthermore, the logic instructions in the memory 530 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
An embodiment of the present invention discloses a computer program product, which includes a computer program stored on a non-transitory computer readable storage medium, the computer program including program instructions, when the program instructions are executed by a computer, the computer can execute the methods provided by the above method embodiments, for example, the method includes: acquiring anti-counterfeiting image information of fruits and vegetables; analyzing the fruit and vegetable anti-counterfeiting image information to obtain an anti-counterfeiting identification image and fruit and vegetable grain image information around the anti-counterfeiting identification image; obtaining anti-counterfeiting number information according to the anti-counterfeiting identification image, and obtaining fruit and vegetable verification image information corresponding to the anti-counterfeiting number information from a preset database; and comparing and analyzing the fruit and vegetable anti-counterfeiting image information according to the fruit and vegetable verification image information to obtain an anti-counterfeiting identification result.
Embodiments of the present invention provide a non-transitory computer-readable storage medium storing server instructions, where the server instructions cause a computer to execute the method provided in the foregoing embodiments, for example, the method includes: acquiring anti-counterfeiting image information of fruits and vegetables; analyzing the fruit and vegetable anti-counterfeiting image information to obtain an anti-counterfeiting identification image and fruit and vegetable grain image information around the anti-counterfeiting identification image; obtaining anti-counterfeiting number information according to the anti-counterfeiting identification image, and obtaining fruit and vegetable verification image information corresponding to the anti-counterfeiting number information from a preset database; and comparing and analyzing the fruit and vegetable anti-counterfeiting image information according to the fruit and vegetable verification image information to obtain an anti-counterfeiting identification result.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (9)

1. An anti-counterfeiting identification method for fruits and vegetables is characterized by comprising the following steps:
acquiring anti-counterfeiting image information of fruits and vegetables;
analyzing the fruit and vegetable anti-counterfeiting image information to obtain an anti-counterfeiting identification image and fruit and vegetable grain image information around the anti-counterfeiting identification image;
obtaining anti-counterfeiting number information according to the anti-counterfeiting identification image, and obtaining fruit and vegetable verification image information corresponding to the anti-counterfeiting number information from a preset database;
and comparing and analyzing the fruit and vegetable anti-counterfeiting image information according to the fruit and vegetable verification image information to obtain an anti-counterfeiting identification result.
2. The fruit and vegetable anti-counterfeiting identification method according to claim 1, wherein the fruit and vegetable verification image information comprises: verifying the identification image and verifying texture image information of the fruits and vegetables around the verification identification image.
3. The fruit and vegetable anti-counterfeiting identification method according to claim 2, wherein the step of comparing and analyzing the fruit and vegetable anti-counterfeiting image information according to the fruit and vegetable verification image information to obtain an anti-counterfeiting identification result specifically comprises the following steps:
carrying out size normalization processing on the fruit and vegetable anti-counterfeiting image information according to the pixel point information of the verification identification image to obtain normalized fruit and vegetable anti-counterfeiting image information;
analyzing the normalized fruit and vegetable anti-counterfeiting image information to obtain a normalized anti-counterfeiting mark image and normalized fruit and vegetable grain image information around the normalized anti-counterfeiting mark image;
and comparing and analyzing the normalized fruit and vegetable grain image information and the fruit and vegetable verification grain image information to obtain an anti-counterfeiting identification result.
4. The fruit and vegetable anti-counterfeiting identification method according to claim 3, wherein the step of comparing and analyzing the normalized fruit and vegetable grain image information and the fruit and vegetable verification grain image information to obtain an anti-counterfeiting identification result specifically comprises the following steps:
taking the verification mark image and the normalized anti-counterfeiting mark image as a common point, and calculating a similarity value according to fruit and vegetable verification texture image information around the verification mark image and normalized fruit and vegetable texture image information around the normalized anti-counterfeiting mark image to obtain a similarity calculation result;
and obtaining an anti-counterfeiting identification result according to the similarity calculation result.
5. The fruit and vegetable anti-counterfeiting identification method according to claim 4, wherein the step of calculating the similarity value according to the fruit and vegetable verification texture image information around the verification identification image and the normalized fruit and vegetable texture image information around the normalized anti-counterfeiting identification image specifically comprises the following steps:
taking the verification mark image and the normalized anti-counterfeiting mark image as a common point, and translating or rotating the normalized fruit and vegetable grain image information around the normalized anti-counterfeiting mark image; obtaining the information of the adjusted and normalized fruit and vegetable grain images; and calculating the similarity value according to the adjusted normalized fruit and vegetable grain image information and the fruit and vegetable verification grain image information around the verification identification image.
6. The fruit and vegetable anti-counterfeiting identification method according to claim 2, wherein before the steps of obtaining anti-counterfeiting number information according to the anti-counterfeiting identification image and obtaining fruit and vegetable verification image information corresponding to the anti-counterfeiting number information in a preset database, the method further comprises the following steps:
acquiring fruit and vegetable verification image information;
and obtaining anti-counterfeiting number information according to the verification identification image of the fruit and vegetable verification image information, and storing the fruit and vegetable verification image information to a preset database according to the anti-counterfeiting number information.
7. An anti-counterfeiting identification device for fruits and vegetables is characterized by comprising:
the acquisition module is used for acquiring anti-counterfeiting image information of the fruits and the vegetables;
the analysis module is used for analyzing the fruit and vegetable anti-counterfeiting image information to obtain an anti-counterfeiting mark image and fruit and vegetable grain image information around the anti-counterfeiting mark image;
the computing module is used for obtaining anti-counterfeiting number information according to the anti-counterfeiting identification image and obtaining fruit and vegetable verification image information corresponding to the anti-counterfeiting number information from a preset database;
and the identification module is used for comparing and analyzing the anti-counterfeiting image information of the fruits and the vegetables according to the fruit and vegetable verification image information to obtain an anti-counterfeiting identification result.
8. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the anti-counterfeiting fruit and vegetable identification method according to any one of claims 1 to 6 when executing the program.
9. A non-transitory computer readable storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the steps of the fruit and vegetable anti-counterfeiting identification method according to any one of claims 1 to 6.
CN201910995400.3A 2019-10-18 2019-10-18 Anti-counterfeiting identification method and device for fruits and vegetables Pending CN110879968A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910995400.3A CN110879968A (en) 2019-10-18 2019-10-18 Anti-counterfeiting identification method and device for fruits and vegetables

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910995400.3A CN110879968A (en) 2019-10-18 2019-10-18 Anti-counterfeiting identification method and device for fruits and vegetables

Publications (1)

Publication Number Publication Date
CN110879968A true CN110879968A (en) 2020-03-13

Family

ID=69727933

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910995400.3A Pending CN110879968A (en) 2019-10-18 2019-10-18 Anti-counterfeiting identification method and device for fruits and vegetables

Country Status (1)

Country Link
CN (1) CN110879968A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112598008A (en) * 2020-12-25 2021-04-02 上海大学 Thin film pattern database establishing and classification identification method for non-duplicable anti-counterfeit label
CN113379720A (en) * 2021-06-29 2021-09-10 云南昆船设计研究院有限公司 Tea cake anti-counterfeiting method based on tea cake image feature code

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN204883768U (en) * 2015-08-31 2015-12-16 杨骏 False proof mark , product packaging and false proof mark's manufacturing system
CN105224976A (en) * 2015-08-31 2016-01-06 杨骏 A kind of making of anti-counterfeiting mark and recognition methods, Apparatus and system
CN110222602A (en) * 2019-05-23 2019-09-10 艾科芯(深圳)智能科技有限公司 Antiforge recognizing method, system, device end and computer readable storage medium
CN110276709A (en) * 2019-06-18 2019-09-24 周晓明 It is a kind of for the generation of protectiveness document, discrimination method and information management system

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN204883768U (en) * 2015-08-31 2015-12-16 杨骏 False proof mark , product packaging and false proof mark's manufacturing system
CN105224976A (en) * 2015-08-31 2016-01-06 杨骏 A kind of making of anti-counterfeiting mark and recognition methods, Apparatus and system
CN110222602A (en) * 2019-05-23 2019-09-10 艾科芯(深圳)智能科技有限公司 Antiforge recognizing method, system, device end and computer readable storage medium
CN110276709A (en) * 2019-06-18 2019-09-24 周晓明 It is a kind of for the generation of protectiveness document, discrimination method and information management system

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
欧冬秀: "《交通信息技术》", 31 May 2007, 同济大学出版社 *
蒋先刚: "《数字图像模式识别工程项目研究》", 31 March 2014, 西南交通大学出版社 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112598008A (en) * 2020-12-25 2021-04-02 上海大学 Thin film pattern database establishing and classification identification method for non-duplicable anti-counterfeit label
CN113379720A (en) * 2021-06-29 2021-09-10 云南昆船设计研究院有限公司 Tea cake anti-counterfeiting method based on tea cake image feature code
CN113379720B (en) * 2021-06-29 2022-08-09 云南昆船设计研究院有限公司 Tea cake anti-counterfeiting method based on tea cake image feature code

Similar Documents

Publication Publication Date Title
Makandar et al. Malware analysis and classification using artificial neural network
Hall et al. Evaluation of features for leaf classification in challenging conditions
CN111726248A (en) Alarm root cause positioning method and device
AU2009246750A1 (en) Fingerprint representation using gradient histograms
CN111461164B (en) Sample data set capacity expansion method and model training method
CN110879968A (en) Anti-counterfeiting identification method and device for fruits and vegetables
Pradana et al. Blockchain modeling for traceability information system in supply chain of coffee agroindustry
KR20210126485A (en) Matching method, apparatus, electronic device, computer readable storage medium, and computer program
Ayyub et al. Fruit disease classification and identification using image processing
CN115302963B (en) Bar code printing control method, system and medium based on machine vision
CN118266424B (en) Method, device and equipment for separating flea larvae of macrobrachium rosenbergii
CN111814862A (en) Fruit and vegetable identification method and device
Schraml et al. Towards the applicability of biometric wood log traceability using digital log end images
CN114998274A (en) Object positioning method and device, electronic equipment and readable storage medium
CN116740473B (en) Automatic sorting method and system for fish catch based on machine vision
CN112200789B (en) Image recognition method and device, electronic equipment and storage medium
CN116610821B (en) Knowledge graph-based enterprise risk analysis method, system and storage medium
CN109740335A (en) The classification method and device of identifying code operation trace
CN116168275B (en) Lightweight dual-attention mechanism identification method based on feature grouping and channel replacement
CN112668412A (en) Two-dimensional code generation method and device, electronic equipment and storage medium
CN110428409B (en) Furniture quality inspection method and system
CN108021570A (en) A kind of farm produce sale tracking system analysis method
CN116861225A (en) Data screening method and device, electronic equipment and storage medium
CN112183540A (en) Label parameter extraction method and device, storage medium and electronic device
CN107844735B (en) Authentication method and device for biological characteristics

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20200313