CN112465517A - Anti-counterfeiting verification method and device and computer readable storage medium - Google Patents
Anti-counterfeiting verification method and device and computer readable storage medium Download PDFInfo
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- G06Q30/018—Certifying business or products
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Abstract
The invention discloses an anti-counterfeiting verification method, an anti-counterfeiting verification device and a computer readable storage medium. The anti-counterfeiting verification method comprises the following steps: when an anti-counterfeiting verification instruction sent by a user side is received, acquiring a commodity identification number (ID) of a commodity to be verified according to the anti-counterfeiting verification instruction; acquiring image acquisition position information corresponding to the commodity ID, and sending the image acquisition position information to the user side; receiving a first texture image returned by the user side based on the image acquisition position information, and performing feature extraction on the first texture image to obtain a first texture feature; and acquiring second texture features corresponding to the image acquisition position information and the commodity ID from a preset database, comparing the first texture features with the second texture features, and returning corresponding anti-counterfeiting verification results to the user side according to comparison results. The invention can solve the problem of poor reliability of the existing anti-counterfeiting verification method.
Description
Technical Field
The present invention relates to the field of anti-counterfeiting technologies, and in particular, to an anti-counterfeiting verification method, an anti-counterfeiting verification device, and a computer-readable storage medium.
Background
Currently, many merchandise are accompanied by a certificate of merchandise or a hang tag to prove that the merchandise is genuine. But because the certificate of the commodity and the commodity itself are separated physically, the certificate itself has the problem of anti-counterfeiting. For example, some commodities can be marked or printed with a unique coding mark on a real object, and a certificate is also printed with the same coding mark, so that the commodities and the certificate are bound, but a counterfeiter can forge the commodities and the fake serial number; in addition, there are many commodities on which unique coding marks are not easy to be engraved or printed, and at this time, the certificate is more easy to be stolen and used on fake commodities, so that the commodity certificate is meaningless. Therefore, how to improve the reliability of the anti-counterfeiting of the goods is a problem which needs to be solved urgently at present.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide an anti-counterfeiting verification method, an anti-counterfeiting verification device and a computer readable storage medium, and aims to solve the problem that the existing anti-counterfeiting verification method is poor in reliability.
In order to achieve the above object, the present invention provides an anti-counterfeiting authentication method, comprising the steps of:
when an anti-counterfeiting verification instruction sent by a user side is received, acquiring a commodity identification number (ID) of a commodity to be verified according to the anti-counterfeiting verification instruction;
acquiring image acquisition position information corresponding to the commodity ID, and sending the image acquisition position information to the user side;
receiving a first texture image returned by the user side based on the image acquisition position information, and performing feature extraction on the first texture image to obtain a first texture feature;
and acquiring second texture features corresponding to the image acquisition position information and the commodity ID from a preset database, comparing the first texture features with the second texture features, and returning corresponding anti-counterfeiting verification results to the user side according to comparison results.
Optionally, before the step of obtaining the product identification number ID of the product to be verified according to the anti-counterfeiting verification instruction when receiving the anti-counterfeiting verification instruction sent by the user side, the method further includes:
pre-obtaining a position division diagram of a surface area of the commodity corresponding to the commodity ID, wherein each division area in the position division diagram corresponds to an image acquisition position number;
acquiring a second texture image of the surface of the commodity corresponding to the image acquisition position number, and performing feature extraction on the second texture image to obtain a third texture feature;
and associating the commodity ID with the position division diagram, the image acquisition position number and the third texture characteristic, and storing the commodity ID in the preset database.
Optionally, the image capturing position information includes the position division map and a target image capturing position number, where the target image capturing position number is randomly selected from the image capturing position numbers.
Optionally, after the step of acquiring the image capturing position information corresponding to the commodity ID and sending the image capturing position information to the user side, the method further includes:
when an image acquisition position replacement instruction sent by the user side based on the image acquisition position information is received, a target image acquisition position number is selected again according to the image acquisition position replacement instruction;
obtaining updated image acquisition position information according to the reselected target image acquisition position number and the position division diagram, and sending the updated image acquisition position information to the user side;
the step of receiving a first texture image returned by the user side based on the image acquisition position information, and performing feature extraction on the first texture image to obtain a first texture feature comprises the following steps:
receiving a first texture image returned by the user side based on the updated image acquisition position information, and performing feature extraction on the first texture image to obtain a first texture feature;
the step of obtaining a second texture feature corresponding to the image acquisition position information and the commodity ID from a preset database, comparing the first texture feature with the second texture feature, and returning a corresponding anti-counterfeiting verification result to the user side according to the comparison result comprises the following steps:
and acquiring second texture features corresponding to the updated image acquisition position information and the commodity ID from a preset database, comparing the first texture features with the second texture features, and returning corresponding anti-counterfeiting verification results to the user side according to comparison results.
Optionally, the receiving a first texture image returned by the user side based on the image acquisition position information, and performing feature extraction on the first texture image to obtain a first texture feature includes:
receiving a first texture image returned by the user side based on the image acquisition position information, and performing gray processing on the first texture image;
and performing feature extraction on the first texture image subjected to the gray processing to obtain a first texture feature.
Optionally, the step of obtaining a second texture feature corresponding to the image acquisition position information and the commodity ID from a preset database, comparing the first texture feature with the second texture feature, and returning a corresponding anti-counterfeiting verification result to the user side according to the comparison result includes:
acquiring second texture features corresponding to the image acquisition position information and the commodity ID from a preset database;
constructing a first texture feature vector according to the first texture feature, and constructing a second texture feature vector according to the second texture feature;
calculating a similarity value between the first texture feature vector and the second texture feature vector, and comparing the similarity value with a preset threshold value to obtain a comparison result;
and returning a corresponding anti-counterfeiting verification result to the user side according to the comparison result.
Optionally, before the step of acquiring the image capturing position information corresponding to the commodity ID and sending the image capturing position information to the user side, the method further includes:
detecting whether the commodity ID is in a preset genuine ID list or not;
if the commodity ID is in a preset genuine ID list, executing the following steps: acquiring image acquisition position information corresponding to the commodity ID, and sending the image acquisition position information to the user side;
and if the commodity ID is not in the preset genuine product ID list, generating an anti-counterfeiting verification result that the commodity to be verified is a fake commodity, and returning the anti-counterfeiting verification result to the user side.
Optionally, the anti-counterfeiting authentication method further comprises:
determining commodity information of the commodity to be verified according to the commodity ID;
and acquiring other anti-counterfeiting verification methods of the to-be-verified commodity according to the commodity information, and pushing the to-be-verified commodity to the user side so as to further perform anti-counterfeiting verification on the user.
In addition, to achieve the above object, the present invention also provides an anti-counterfeit authentication device, including: the anti-counterfeiting authentication method comprises a memory, a processor and an anti-counterfeiting authentication program which is stored on the memory and can run on the processor, wherein the anti-counterfeiting authentication program realizes the steps of the anti-counterfeiting authentication method when being executed by the processor.
In addition, to achieve the above object, the present invention further provides a computer readable storage medium, having an anti-counterfeiting authentication program stored thereon, where the anti-counterfeiting authentication program, when executed by a processor, implements the steps of the anti-counterfeiting authentication method as described above.
The invention provides an anti-counterfeiting verification method, an anti-counterfeiting verification device and a computer readable storage medium, wherein when an anti-counterfeiting verification instruction sent by a user end is received, the commodity ID of a commodity to be verified is obtained according to the anti-counterfeiting verification instruction; then acquiring image acquisition position information corresponding to the commodity ID, and sending the image acquisition position information to a user side so that the user side acquires a texture image of a position corresponding to the commodity to be verified; when a first texture image returned by a user side based on image acquisition position information is received, performing feature extraction on the first texture image to obtain a first texture feature; and then acquiring a second texture feature (namely the texture feature corresponding to the same position which is pre-recorded) corresponding to the image acquisition position information and the commodity ID from a preset database, comparing the first texture feature with the second texture feature, and returning a corresponding anti-counterfeiting verification result to the user side according to the comparison result. Through the mode, the authenticity of the commodity is verified based on the commodity ID and the textural features of the commodity, commodity counterfeiting through means of appropriating and forging certificates can be reduced, the anti-counterfeiting effect of the commodity is improved, and meanwhile, compared with the fact that authenticity verification is only performed based on the commodity ID in the prior art, the authenticity verification method based on the commodity ID can improve the reliability of an anti-counterfeiting verification result.
Drawings
Fig. 1 is a schematic terminal structure diagram of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a first embodiment of the anti-counterfeit authentication method according to the present invention;
FIG. 3 is a detailed flowchart of step S40 in the first embodiment of the present invention;
FIG. 4 is a schematic flow chart of a second embodiment of the anti-counterfeit verification method according to the present invention;
fig. 5 is a schematic flow chart of a third embodiment of the anti-counterfeiting authentication method according to the invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic terminal structure diagram of a hardware operating environment according to an embodiment of the present invention.
The terminal in the embodiment of the present invention may be a Personal Computer (PC), or may be a terminal device such as a smart phone, a tablet computer, a portable computer, or a server.
As shown in fig. 1, the terminal may include: a processor 1001, such as a CPU (Central Processing Unit), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wi-Fi interface, Wireless-Fidelity, Wi-Fi interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Optionally, the terminal may further include a camera, a Radio Frequency (RF) circuit, a sensor, an audio circuit, a Wi-Fi module, and the like. Such as light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor that adjusts brightness of the display screen according to brightness of ambient light, and a proximity sensor that turns off the display screen and/or backlight when the terminal moves to the ear. As one of the motion sensors, the gravity acceleration sensor can detect the magnitude of acceleration in each direction (generally, three axes), detect the magnitude and direction of gravity when the mobile terminal is stationary, and can be used for applications (such as horizontal and vertical screen switching, related games, magnetometer attitude calibration), vibration recognition related functions (such as pedometer and tapping) and the like for recognizing the attitude of the mobile terminal; of course, the terminal may also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which are not described herein again.
Those skilled in the art will appreciate that the terminal structure shown in fig. 1 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and an anti-counterfeit authentication program.
In the terminal shown in fig. 1, the network interface 1004 is mainly used for connecting to a backend server and performing data communication with the backend server; the user interface 1003 is mainly used for connecting a client and performing data communication with the client; and the processor 1001 may be configured to call the anti-counterfeiting authentication program stored in the memory 1005, and perform the following operations:
when an anti-counterfeiting verification instruction sent by a user side is received, acquiring a commodity identification number (ID) of a commodity to be verified according to the anti-counterfeiting verification instruction;
acquiring image acquisition position information corresponding to the commodity ID, and sending the image acquisition position information to the user side;
receiving a first texture image returned by the user side based on the image acquisition position information, and performing feature extraction on the first texture image to obtain a first texture feature;
and acquiring second texture features corresponding to the image acquisition position information and the commodity ID from a preset database, comparing the first texture features with the second texture features, and returning corresponding anti-counterfeiting verification results to the user side according to comparison results.
Further, the processor 1001 may call the anti-counterfeiting authentication program stored in the memory 1005, and further perform the following operations:
pre-obtaining a position division diagram of a surface area of the commodity corresponding to the commodity ID, wherein each division area in the position division diagram corresponds to an image acquisition position number;
acquiring a second texture image of the surface of the commodity corresponding to the image acquisition position number, and performing feature extraction on the second texture image to obtain a third texture feature;
and associating the commodity ID with the position division diagram, the image acquisition position number and the third texture characteristic, and storing the commodity ID in the preset database.
Further, the image capturing position information includes the position division map and a target image capturing position number, wherein the target image capturing position number is randomly selected from the image capturing position numbers.
Further, the processor 1001 may call the anti-counterfeiting authentication program stored in the memory 1005, and further perform the following operations:
when an image acquisition position replacement instruction sent by the user side based on the image acquisition position information is received, a target image acquisition position number is selected again according to the image acquisition position replacement instruction;
obtaining updated image acquisition position information according to the reselected target image acquisition position number and the position division diagram, and sending the updated image acquisition position information to the user side;
receiving a first texture image returned by the user side based on the updated image acquisition position information, and performing feature extraction on the first texture image to obtain a first texture feature;
and acquiring second texture features corresponding to the updated image acquisition position information and the commodity ID from a preset database, comparing the first texture features with the second texture features, and returning corresponding anti-counterfeiting verification results to the user side according to comparison results.
Further, the processor 1001 may call the anti-counterfeiting authentication program stored in the memory 1005, and further perform the following operations:
receiving a first texture image returned by the user side based on the image acquisition position information, and performing gray processing on the first texture image;
and performing feature extraction on the first texture image subjected to the gray processing to obtain a first texture feature.
Further, the processor 1001 may call the anti-counterfeiting authentication program stored in the memory 1005, and further perform the following operations:
acquiring second texture features corresponding to the image acquisition position information and the commodity ID from a preset database;
constructing a first texture feature vector according to the first texture feature, and constructing a second texture feature vector according to the second texture feature;
calculating a similarity value between the first texture feature vector and the second texture feature vector, and comparing the similarity value with a preset threshold value to obtain a comparison result;
and returning a corresponding anti-counterfeiting verification result to the user side according to the comparison result.
Further, the processor 1001 may call the anti-counterfeiting authentication program stored in the memory 1005, and further perform the following operations:
detecting whether the commodity ID is in a preset genuine ID list or not;
if the commodity ID is in a preset genuine ID list, executing the following steps: acquiring image acquisition position information corresponding to the commodity ID, and sending the image acquisition position information to the user side;
and if the commodity ID is not in the preset genuine product ID list, generating an anti-counterfeiting verification result that the commodity to be verified is a fake commodity, and returning the anti-counterfeiting verification result to the user side.
Further, the processor 1001 may call the anti-counterfeiting authentication program stored in the memory 1005, and further perform the following operations:
determining commodity information of the commodity to be verified according to the commodity ID;
and acquiring other anti-counterfeiting verification methods of the to-be-verified commodity according to the commodity information, and pushing the to-be-verified commodity to the user side so as to further perform anti-counterfeiting verification on the user.
Based on the hardware structure, the invention provides various embodiments of the anti-counterfeiting verification method.
The invention provides an anti-counterfeiting verification method.
Referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of the anti-counterfeiting authentication method of the invention.
In this embodiment, the anti-counterfeit verification method includes:
step S10, when receiving an anti-counterfeiting verification instruction sent by a user terminal, obtaining a commodity identification number ID of a commodity to be verified according to the anti-counterfeiting verification instruction;
in this embodiment, before the step S10, the method further includes:
step A, a position division diagram of a surface area of a commodity corresponding to the commodity ID is obtained in advance, and each division area in the position division diagram corresponds to an image acquisition position number;
b, acquiring a second texture image of the surface of the commodity corresponding to the image acquisition position number, and performing feature extraction on the second texture image to obtain a third texture feature;
and step C, associating the commodity ID with the position division diagram, the image acquisition position number and the third texture characteristic, and storing the commodity ID in the preset database.
In the embodiment, the anti-counterfeiting verification method is based on the random non-replicability of the texture, the commodity object (namely the texture feature of the commodity) is associated with the commodity certificate (namely the commodity ID), and then the authenticity of the commodity is verified based on the commodity ID and the texture feature of the commodity, so that the counterfeiting of the commodity by using and forging the certificate can be reduced, the anti-counterfeiting effect of the commodity is improved, and meanwhile, compared with the prior art in which the authenticity is verified only based on the commodity ID, the reliability of the anti-counterfeiting verification result can be improved. The terminal according to the embodiment of the present invention may be a PC, a server, or the like, and for convenience of description, the server is taken as an example for description.
In this embodiment, a position division map of a surface area of a commodity corresponding to a commodity ID is obtained in advance, wherein each division area in the position division map corresponds to one image capture position number, and then a second texture image of the surface of the commodity corresponding to the image capture position number is obtained. The position division diagram and the image acquisition position number therein can be preset by a worker through a working end (such as a smart phone, a tablet personal computer and the like) and sent to the server, and the second texture image can also be obtained by shooting the worker through the working end, can also be obtained by respectively shooting through cameras at different fixed positions and then sent to the server. It is understood that the division areas in the position division map may cover only a few local positions of the surface of the commodity, or may cover all the position areas of the surface of the commodity.
And after the server acquires the second texture image, performing feature extraction on the second texture image to acquire a third texture feature. The texture feature extraction method may include, but is not limited to: gray-level co-occurrence matrix (GLCM), Markov Random Field (MRF) model, Gibbs Random Field (Gibbs) model. Correspondingly, the third texture feature may include one or more, preferably, a plurality of third texture features, so as to improve the accuracy of the alignment result. For example, when the texture features are extracted by using the gray level co-occurrence matrix, the corresponding third texture features may include energy, entropy, correlation, and contrast, and may further include color features.
In order to facilitate subsequent searching and obtaining, the commodity ID can be associated with the position division diagram, the image acquisition position number and the third texture characteristic and stored in a preset database. Of course, it is understood that, in an embodiment, the image may be acquired only at a specific position in the position partition map, so as to obtain a texture image, and further extract texture features of the texture image to be associated with other information. When only the texture feature of a specific location is obtained, the specific location may be worn or damaged, and an accurate verification result may not be obtained. In addition, when the association storage is performed, the image acquisition position numbers and the third texture features are in one-to-one correspondence. When the association storage is performed, a new number, such as ID-n, can be generated according to the product ID and the image capture position number (denoted as n), and then the new number and the corresponding third texture feature are associated and stored.
It should be noted that, in the acquisition process, texture images at the same position may be acquired for multiple times to obtain multiple texture images, and then texture features of each acquired texture image are extracted respectively, and then a final third texture feature is obtained by taking an average value and the like, so that an error can be reduced to a certain extent, and the accuracy of a subsequent verification result is improved.
In this embodiment, when a user wants to perform anti-counterfeit verification on a commodity, a corresponding anti-counterfeit verification instruction can be triggered by scanning a two-dimensional code on a commodity surface, a commodity certificate, or a commodity tag through corresponding software or an Application (App) on a user side (such as a smart phone), where the two-dimensional code is generated according to a commodity ID (i.e., a commodity certificate number), and the content of the two-dimensional code has a unique ID, which is also the unique ID of the commodity. When the user terminal scans the two-dimensional code, the user terminal can directly identify the commodity ID corresponding to the two-dimensional code, and further trigger the anti-counterfeiting verification instruction, and at the moment, when the server receives the anti-counterfeiting verification instruction sent by the user terminal, the server can directly obtain the commodity ID (identification number) of the commodity to be verified carried in the anti-counterfeiting verification instruction. Certainly, in a specific embodiment, the user terminal may also shoot the two-dimensional code, and then upload the two-dimensional code image through corresponding software or App, and trigger the anti-counterfeiting verification instruction, at this time, when receiving the anti-counterfeiting verification instruction sent by the user terminal, the server acquires the two-dimensional code image carried in the anti-counterfeiting verification instruction, and further identifies the product ID corresponding to the two-dimensional code image. That is, the product ID may be identified at the user side or at the server.
Step S20, acquiring image acquisition position information corresponding to the commodity ID, and sending the image acquisition position information to the user side;
after the commodity ID is acquired, the server may acquire image capturing position information corresponding to the commodity ID from a preset database, where the image capturing position information includes a position division map corresponding to the commodity ID and a target image capturing position number, and the target image capturing position number is randomly selected from the image capturing position numbers. It is understood that the target image collection position number may include one or more than one, and the user may select a mode for collecting one or more than one image for verification, and in addition, in a specific embodiment, the position partition map may be sent to the user side first, so that the user side selects the target image collection position number from the position partition map in combination with an actual situation, and shoots the first texture image corresponding to the selected target image collection position number, and then sends the selected target image collection position number and the corresponding first texture image to the server through the user side, and the server then executes a next processing procedure.
Step S30, receiving a first texture image returned by the user side based on the image acquisition position information, and performing feature extraction on the first texture image to obtain a first texture feature;
the user side can display the image acquisition position information in a terminal screen after receiving the image acquisition position information, so that a user can determine a target image acquisition position according to a position division diagram and a target image acquisition position number in the image acquisition position information, further shoot to obtain a corresponding first texture image, and send the first texture image to the server through the user side. The method for extracting the texture features may include, but is not limited to: gray level co-occurrence matrix, Markov random field model method, Gibbs random field model method. Correspondingly, the first texture feature may include one or more, preferably, the first texture feature includes a plurality of, so as to improve the accuracy of the alignment result. For example, when the texture features are extracted using the gray level co-occurrence matrix, the corresponding first texture features may include energy, entropy, correlation, and contrast, and may further include color features. Of course, it may be understood that, in a specific embodiment, after the user side acquires the first texture image, the user side may directly perform feature extraction on the first texture image, and then send the extracted first texture feature to the server. That is, the server may perform texture feature extraction, and the client may perform texture feature extraction.
Further, when the first texture features do not include color features, the accuracy of the feature extraction result is improved, the accuracy of the anti-counterfeiting verification result is further improved, and the gray processing can be performed on the first texture image after the first texture image returned by the user side based on the image acquisition position information is received. At this time, step S30 may include:
a1, receiving a first texture image returned by the user side based on the image acquisition position information, and performing gray processing on the first texture image;
specifically, after receiving a first texture image returned by a user terminal based on image acquisition position information, gray processing is performed on the first texture image. The process of performing gray scale processing on the first texture image is as follows: reading the first texture image through an imread function in MATLAB (matrix laboratory, commercial mathematical software produced by MathWorks company in America) software to obtain an array formed by image pixel values, wherein the array is used for expressing the read first texture image, then converting the first texture image into a gray image through an rgb2gray function in the MATLAB software, and performing gray processing to more clearly express the texture of a commodity to be verified so as to be beneficial to subsequent texture feature extraction.
Step a2, performing feature extraction on the first texture image subjected to the gray processing to obtain a first texture feature.
And then, performing feature extraction on the first texture image subjected to the gray processing to obtain a first texture feature.
Step S40, obtaining a second texture feature corresponding to the image acquisition position information and the commodity ID from a preset database, comparing the first texture feature with the second texture feature, and returning a corresponding anti-counterfeiting verification result to the user side according to the comparison result.
After the first texture feature is obtained, a second texture feature (namely, a second texture feature corresponding to the target image acquisition position number and the commodity ID) corresponding to the image acquisition position information and the commodity ID is obtained from a preset database, then the first texture feature and the second texture feature are compared, and a corresponding anti-counterfeiting verification result is returned to the user side according to the comparison result.
Specifically, referring to fig. 3, step S40 may include:
step S41, obtaining a second texture feature corresponding to the image acquisition position information and the commodity ID from a preset database;
first, second texture features corresponding to the image acquisition position information and the commodity ID, namely the target image acquisition position number and the second texture features corresponding to the commodity ID, are obtained from a preset database.
Step S42, constructing a first texture feature vector according to the first texture feature and constructing a second texture feature vector according to the second texture feature;
then, a first texture feature vector is constructed according to the first texture feature, and a second texture feature vector is constructed according to the second texture feature, and the specific construction method can be constructed according to a preset texture feature sequence, for example, the first texture feature comprises a1, b1, c1 and d1, the second texture feature comprises a2, b2, c2 and d2, and the construction can be carried out according to the sequence from a feature to d feature, so that a first texture feature vector { a1, b1, c1, d1} and a second texture feature vector { a2, b2, c2 and d2} are obtained.
Step S43, calculating a similarity value between the first texture feature vector and the second texture feature vector, and comparing the similarity value with a preset threshold value to obtain a comparison result;
after the first texture feature vector and the second texture feature vector are obtained, a similarity value between the first texture feature vector and the second texture feature vector is calculated, and the similarity value is compared with a preset threshold value to obtain a comparison result. The calculation method of the similarity value may include, but is not limited to: the Euclidean distance, the Manhattan distance, the Chebyshev distance, the cosine of the included angle and the like, and the preset threshold value can be specifically set according to the adopted comparison method.
And step S44, returning a corresponding anti-counterfeiting verification result to the user side according to the comparison result.
Then, returning a corresponding anti-counterfeiting verification result to the user side according to the comparison result, wherein the anti-counterfeiting verification result is determined according to the comparison result and the adopted comparison method, generally speaking, when the similarity value is represented by the method of calculating the distance, if the similarity value is smaller than a preset threshold value, the similarity between the two is very large, the commodity to be verified is a genuine commodity, and at the moment, returning the anti-counterfeiting verification result that the commodity to be verified is the genuine commodity to the user side; if the similarity value is larger than or equal to the preset threshold value, the similarity between the two is small, the commodity to be verified is a counterfeit commodity, and at the moment, the anti-counterfeiting verification result that the commodity to be verified is the counterfeit commodity is returned to the user side.
The embodiment of the invention provides an anti-counterfeiting verification method, which comprises the steps of obtaining a commodity ID of a commodity to be verified according to an anti-counterfeiting verification instruction when the anti-counterfeiting verification instruction sent by a user side is received; then acquiring image acquisition position information corresponding to the commodity ID, and sending the image acquisition position information to a user side so that the user side acquires a texture image of a position corresponding to the commodity to be verified; when a first texture image returned by a user side based on image acquisition position information is received, performing feature extraction on the first texture image to obtain a first texture feature; and then acquiring a second texture feature (namely the texture feature corresponding to the same position which is pre-recorded) corresponding to the image acquisition position information and the commodity ID from a preset database, comparing the first texture feature with the second texture feature, and returning a corresponding anti-counterfeiting verification result to the user side according to the comparison result. Through the mode, the authenticity of the commodity is verified based on the commodity ID and the textural features of the commodity, commodity counterfeiting through means of appropriating and forging certificates can be reduced, the anti-counterfeiting effect of the commodity is improved, and meanwhile, compared with the fact that authenticity verification is conducted only based on the commodity ID in the prior art, the authenticity verification method based on the commodity ID can improve the reliability of an anti-counterfeiting verification result.
Further, referring to fig. 4, fig. 4 is a schematic flow chart of a second embodiment of the anti-counterfeiting authentication method according to the present invention.
Based on the first embodiment shown in fig. 2, after step S20, the method for verifying anti-counterfeiting further includes:
step S50, when receiving an image acquisition position replacement instruction sent by the user side based on the image acquisition position information, reselecting a target image acquisition position number according to the image acquisition position replacement instruction;
in this embodiment, after the image capturing position information is sent to the user side, if the user determines the target image capturing position according to the position division map and the target image capturing position number in the image capturing position information, it is found that the target image capturing position of the commodity to be verified is damaged or worn, and the anti-counterfeiting verification result may be affected.
Step S60, obtaining updated image acquisition position information according to the reselected target image acquisition position number and the position division diagram, and sending the updated image acquisition position information to the user side;
and then, obtaining updated image acquisition position information according to the reselected target image acquisition position number and the position division diagram, and sending the updated image acquisition position information to the user side.
At this time, step S30 includes:
step S31, receiving a first texture image returned by the user side based on the updated image acquisition position information, and performing feature extraction on the first texture image to obtain a first texture feature;
step S40 includes:
step S41, obtaining a second texture feature corresponding to the updated image capturing position information and the commodity ID from a preset database, comparing the first texture feature with the second texture feature, and returning a corresponding anti-counterfeiting verification result to the user side according to the comparison result.
The user side receives the updated image acquisition position information and then displays the updated image acquisition position information on a terminal screen, so that a user can shoot a corresponding first texture image according to the updated image acquisition position information and further send the first texture image to the server, and at the moment, the server performs feature extraction on the first texture image after receiving the first texture image returned by the user side based on the updated image acquisition position information to obtain a first texture feature; then, second texture features corresponding to the updated image acquisition position information and the commodity ID are obtained from a preset database (namely, the corresponding second texture features are determined according to the target image acquisition position number and the commodity ID in the updated image acquisition position information at the same time), the first texture features and the second texture features are compared, and corresponding anti-counterfeiting verification results are returned to the user side according to comparison results. The specific feature extraction process and the specific feature comparison process may refer to the first embodiment, which is not described herein again.
Further, referring to fig. 5, fig. 5 is a schematic flow chart of a third embodiment of the anti-counterfeiting authentication method according to the present invention.
Based on the first embodiment and the second embodiment, before step S20, the anti-counterfeiting authentication method further includes:
step S70, detecting whether the commodity ID is in a preset genuine product ID list;
in this embodiment, after the commodity ID of the commodity to be verified is obtained, it may be preliminarily detected whether the commodity ID is in the preset genuine product ID list.
If the product ID is in the preset genuine product ID list, execute step S20: acquiring image acquisition position information corresponding to the commodity ID, and sending the image acquisition position information to the user side;
if the product ID is not in the preset genuine product ID list, execute step S80: and generating an anti-counterfeiting verification result that the commodity to be verified is a counterfeit commodity, and returning the anti-counterfeiting verification result to the user side.
If the commodity ID is in the preset genuine product ID list, it is preliminarily verified that the commodity to be verified may be a genuine product, at this time, texture detection is further performed on the commodity to be verified, specifically, image acquisition position information corresponding to the commodity ID is obtained, and the image acquisition position information is sent to the user side, and then subsequent steps are performed.
If the commodity ID is not in the preset genuine product ID list, the commodity to be verified is definitely a counterfeit commodity, and at the moment, the anti-counterfeiting verification result that the commodity to be verified is the counterfeit commodity can be directly generated without continuously carrying out texture detection and returned to the user side.
Further, based on the above embodiments, the anti-counterfeit verification method further includes:
determining commodity information of the commodity to be verified according to the commodity ID;
and acquiring other anti-counterfeiting verification methods of the to-be-verified commodity according to the commodity information, and pushing the to-be-verified commodity to the user side so as to further perform anti-counterfeiting verification on the user.
In this embodiment, besides performing the anti-counterfeiting verification on the commodity in the above manner, some other anti-counterfeiting verification methods can be pushed to the user for the user to perform secondary anti-counterfeiting verification, or when the surface of the commodity is worn or damaged, the verification can be performed in other anti-counterfeiting verification methods, so as to ensure that the commodity is genuine, and the user does not need to search for the anti-counterfeiting verification method of the commodity by himself, thereby improving the user experience. Specifically, the server may determine the commodity information of the commodity to be verified according to the commodity ID, where the commodity information includes, but is not limited to, a commodity brand, a commodity model, a commodity type, and the like. And then, acquiring other anti-counterfeiting verification methods of the commodity to be verified according to the commodity information, and pushing the acquired other anti-counterfeiting verification methods to the user side so as to further perform anti-counterfeiting verification on the user. Other anti-counterfeiting verification methods are collected in advance and can include, but are not limited to, a trademark anti-counterfeiting verification method, a commodity number anti-counterfeiting verification method, a commodity self-characteristic anti-counterfeiting verification method (such as a verification method of characteristics of smell, texture, color and the like) and the like.
The invention also provides an anti-counterfeiting verification device, which comprises a memory, a processor and an anti-counterfeiting verification program which is stored on the memory and can run on the processor, wherein the anti-counterfeiting verification program realizes the steps of the anti-counterfeiting verification method according to any one of the above embodiments when being executed by the processor.
The specific embodiment of the anti-counterfeiting verification device of the invention is basically the same as the embodiments of the anti-counterfeiting verification method, and is not repeated herein.
The present invention also provides a computer readable storage medium having stored thereon an anti-counterfeiting validation program, which when executed by a processor implements the steps of the anti-counterfeiting validation method according to any one of the above embodiments.
The specific embodiment of the computer-readable storage medium of the present invention is substantially the same as the embodiments of the above-mentioned anti-counterfeit verification method, and will not be described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. 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 (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. An anti-counterfeiting verification method is characterized by comprising the following steps:
when an anti-counterfeiting verification instruction sent by a user side is received, acquiring a commodity identification number (ID) of a commodity to be verified according to the anti-counterfeiting verification instruction;
acquiring image acquisition position information corresponding to the commodity ID, and sending the image acquisition position information to the user side;
receiving a first texture image returned by the user side based on the image acquisition position information, and performing feature extraction on the first texture image to obtain a first texture feature;
and acquiring second texture features corresponding to the image acquisition position information and the commodity ID from a preset database, comparing the first texture features with the second texture features, and returning corresponding anti-counterfeiting verification results to the user side according to comparison results.
2. The anti-counterfeiting authentication method according to claim 1, wherein before the step of obtaining the product identification number ID of the product to be authenticated according to the anti-counterfeiting authentication instruction when receiving the anti-counterfeiting authentication instruction sent by the user side, the method further comprises:
pre-obtaining a position division diagram of a surface area of the commodity corresponding to the commodity ID, wherein each division area in the position division diagram corresponds to an image acquisition position number;
acquiring a second texture image of the surface of the commodity corresponding to the image acquisition position number, and performing feature extraction on the second texture image to obtain a third texture feature;
and associating the commodity ID with the position division diagram, the image acquisition position number and the third texture characteristic, and storing the commodity ID in the preset database.
3. The anti-counterfeit authentication method according to claim 2, wherein the image capturing position information includes the position division map and a target image capturing position number, wherein the target image capturing position number is randomly selected from the image capturing position numbers.
4. The anti-counterfeit authentication method according to claim 3, wherein after the step of obtaining the image capturing position information corresponding to the commodity ID and sending the image capturing position information to the user side, the method further comprises:
when an image acquisition position replacement instruction sent by the user side based on the image acquisition position information is received, a target image acquisition position number is selected again according to the image acquisition position replacement instruction;
obtaining updated image acquisition position information according to the reselected target image acquisition position number and the position division diagram, and sending the updated image acquisition position information to the user side;
the step of receiving a first texture image returned by the user side based on the image acquisition position information, and performing feature extraction on the first texture image to obtain a first texture feature comprises the following steps:
receiving a first texture image returned by the user side based on the updated image acquisition position information, and performing feature extraction on the first texture image to obtain a first texture feature;
the step of obtaining a second texture feature corresponding to the image acquisition position information and the commodity ID from a preset database, comparing the first texture feature with the second texture feature, and returning a corresponding anti-counterfeiting verification result to the user side according to the comparison result comprises the following steps:
and acquiring second texture features corresponding to the updated image acquisition position information and the commodity ID from a preset database, comparing the first texture features with the second texture features, and returning corresponding anti-counterfeiting verification results to the user side according to comparison results.
5. The anti-counterfeit verification method according to claim 1, wherein the step of receiving the first texture image returned by the user side based on the image acquisition location information and performing feature extraction on the first texture image to obtain the first texture feature comprises:
receiving a first texture image returned by the user side based on the image acquisition position information, and performing gray processing on the first texture image;
and performing feature extraction on the first texture image subjected to the gray processing to obtain a first texture feature.
6. The anti-counterfeit verification method according to any one of claims 1 to 5, wherein the step of obtaining a second texture feature corresponding to the image acquisition location information and the product ID from a preset database, comparing the first texture feature with the second texture feature, and returning a corresponding anti-counterfeit verification result to the user side according to the comparison result comprises:
acquiring second texture features corresponding to the image acquisition position information and the commodity ID from a preset database;
constructing a first texture feature vector according to the first texture feature, and constructing a second texture feature vector according to the second texture feature;
calculating a similarity value between the first texture feature vector and the second texture feature vector, and comparing the similarity value with a preset threshold value to obtain a comparison result;
and returning a corresponding anti-counterfeiting verification result to the user side according to the comparison result.
7. The anti-counterfeit authentication method according to any one of claims 1 to 5, wherein before the step of obtaining the image capturing position information corresponding to the commodity ID and sending the image capturing position information to the user side, the method further comprises:
detecting whether the commodity ID is in a preset genuine ID list or not;
if the commodity ID is in a preset genuine ID list, executing the following steps: acquiring image acquisition position information corresponding to the commodity ID, and sending the image acquisition position information to the user side;
and if the commodity ID is not in the preset genuine product ID list, generating an anti-counterfeiting verification result that the commodity to be verified is a fake commodity, and returning the anti-counterfeiting verification result to the user side.
8. The anti-counterfeiting authentication method according to any one of claims 1 to 5, further comprising:
determining commodity information of the commodity to be verified according to the commodity ID;
and acquiring other anti-counterfeiting verification methods of the to-be-verified commodity according to the commodity information, and pushing the to-be-verified commodity to the user side so as to further perform anti-counterfeiting verification on the user.
9. A counterfeit-proof authentication device, comprising: a memory, a processor and an anti-counterfeiting validation program stored on the memory and executable on the processor, the anti-counterfeiting validation program when executed by the processor implementing the steps of the anti-counterfeiting validation method according to any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon an anti-counterfeiting validation program, which when executed by a processor implements the steps of the anti-counterfeiting validation method according to any one of claims 1 to 8.
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