CN110555500A - map two-dimensional code generation method and system - Google Patents

map two-dimensional code generation method and system Download PDF

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CN110555500A
CN110555500A CN201910858280.2A CN201910858280A CN110555500A CN 110555500 A CN110555500 A CN 110555500A CN 201910858280 A CN201910858280 A CN 201910858280A CN 110555500 A CN110555500 A CN 110555500A
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image
information
map
matrix
pixel
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CN110555500B (en
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孙保林
陈彦民
闫建军
左俊健
李骁
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Beijing Tuchuang Times Technology Co Ltd
BEIJING QIANGHUA PRINTING FACTORY
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Beijing Tuchuang Times Technology Co Ltd
BEIJING QIANGHUA PRINTING FACTORY
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/602—Providing cryptographic facilities or services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K19/00—Record carriers for use with machines and with at least a part designed to carry digital markings
    • G06K19/06—Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code
    • G06K19/06009—Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code with optically detectable marking
    • G06K19/06037—Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code with optically detectable marking multi-dimensional coding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/70—Denoising; Smoothing
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B29/00—Maps; Plans; Charts; Diagrams, e.g. route diagram
    • G09B29/003—Maps
    • G09B29/005—Map projections or methods associated specifically therewith
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20024—Filtering details
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20172—Image enhancement details
    • G06T2207/20192—Edge enhancement; Edge preservation

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  • General Engineering & Computer Science (AREA)
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Abstract

the invention provides a map two-dimensional code generation method and a map two-dimensional code generation system, wherein the map two-dimensional code generation method comprises the following steps: acquiring image information of a map; extracting feature information of the image information; acquiring current time information; and generating the two-dimensional code information of the map according to the feature information and the current time information, thereby realizing the generation of the two-dimensional code information of the image of the map.

Description

map two-dimensional code generation method and system
Technical Field
the invention relates to the technical field of two-dimensional codes, in particular to a map two-dimensional code generation method and system.
Background
The two-dimensional code is also called as a two-dimensional bar code, data symbol information is recorded by black and white figures distributed on a plane (two-dimensional direction) according to a certain rule by using a certain specific geometric figure, and compared with the traditional bar code, the two-dimensional bar code can store and represent more data types, so that the two-dimensional bar code is widely applied to the aspects of life, consumption and the like of people.
however, piracy of publications such as maps is rampant at present, and users can not distinguish whether the maps are legal or not when purchasing the maps, so that normal use of the maps by the users is influenced, and meanwhile, publishers suffer economic loss.
therefore, a map two-dimensional code generation method and system are urgently needed.
disclosure of Invention
in order to solve the technical problem, the invention provides a map two-dimensional code generation method and a map two-dimensional code generation system, which are used for generating two-dimensional code information of a map.
the embodiment of the invention provides a map two-dimensional code generation method, which comprises the following steps:
Acquiring image information of a map;
extracting feature information of the image information;
Acquiring current time information;
and generating two-dimensional code information of the map according to the feature information and the current time information.
in one embodiment, the steps of: extracting feature information of the image information; the method also comprises the following steps:
uniformly dividing the image information into a plurality of area images;
Respectively carrying out motion detection on the plurality of area images to acquire motion information of the plurality of area images;
comparing the motion information with preset motion threshold information, and judging that the noise reduction processing is not required to be carried out on the image of the area when the motion information exceeds or equals to the motion threshold information;
when the motion information is lower than the motion threshold information, judging that the regional image needs to be subjected to noise reduction processing;
the noise reduction processing comprises the following specific steps: acquiring local parameter information of the area image;
acquiring a parameter matrix of a noise reduction algorithm of the regional image according to the local parameter information of the regional image;
Acquiring a plurality of vector characteristic graphs of the regional image, and synthesizing the vector characteristic graphs by adopting a parameter matrix of the noise reduction algorithm to acquire the regional image after noise reduction;
and synthesizing the area image subjected to the noise reduction processing and the image not subjected to the noise reduction processing to generate preprocessed image information.
In one embodiment, the steps of: synthesizing the area image subjected to noise reduction processing and the image not subjected to noise reduction processing to generate preprocessed image information; then, the method further comprises the following steps:
carrying out self-adaptive filtering processing on the preprocessed image information;
detecting the signal-to-noise ratio of the image information after the self-adaptive filtering processing to obtain the signal-to-noise ratio of the image information;
when the signal-to-noise ratio of the image information after the self-adaptive filtering processing exceeds the preset signal-to-noise ratio threshold, taking the image information after the self-adaptive filtering processing as the image information after the filtering processing;
and when the signal-to-noise ratio of the image information after the self-adaptive filtering processing does not exceed the preset signal-to-noise ratio threshold, performing wavelet filtering processing on the image information to obtain the image information after the filtering processing.
in one embodiment, the steps of: acquiring image information after filtering processing; then, the method further comprises the following steps:
Extracting image edge information in the image information;
Acquiring contrast image information of the image information;
Subtracting the image edge information from the image information to obtain a difference image; and adding the difference image and the contrast image information to obtain the image information after enhancement processing.
in one embodiment, the steps of: generating two-dimensional code information of the map according to the feature information and the current time information, and then further comprising:
generating a unique identification code of the map according to the two-dimensional code information of the map;
Encrypting the unique identification code by using a public key and adopting an RSA asymmetric encryption algorithm to generate an encrypted unique identification code;
When the encrypted unique identification code is scanned, the encrypted unique identification code is decrypted by using a private key and adopting an RSA asymmetric secret algorithm, so that the unique identification code is acquired.
In one embodiment, the steps of: extracting feature information of the image information; the method also comprises the following steps:
Performing difference enhancement on boundary information of the image information; the following steps are carried out:
firstly, converting the image information of the map into an image pixel matrix M of N P pixel points, wherein N P indicates that the image of the map has N P pixel points, N is the height when the image of the map is represented by the pixel, P is the length when the image of the map is represented by the pixel, the map pixel matrix M contains N rows and P columns, the value of each position of the map pixel matrix M represents the value of the pixel point corresponding to the position, the value of the pixel point is a set containing R, G, B three-channel values, and the optimization coefficients of R, G, B three channels are obtained by using a formula (1);
P＝{PR＝ρG,B,PG＝ρR,B,PB＝ρG,R}
Wherein，ρi,jfor the exchangeability between the ith and jth channels of a map pixel image matrix M, Mi,sthe value of the ith channel which is the s-th position of the map pixel image matrix M, s belongs to the value of the s of the M and is all the positions of the map pixel image matrix M,is the mean value of the ith channel of a map pixel image matrix M, Mj,sis the value of the jth channel at the s-th position of the map pixel image matrix M,is the mean of the jth channel of the map pixel image matrix M, P is the formed replacement set, PG,B、ρR,B、ρG,RAre respectively rhoi,jWherein i is G, R, G, j is B, B, R, PR、PG、PBseparately mapping the information importance, γ, of the R, G, B channels in the pixel-image matrix Mifor the optimization coefficient of the ith channel in the map pixel image matrix M, sum () is summation, min () is minimum value, max () is maximum value, and i, j can take R, G, B three channels;
then, converting the R, G, B three-channel value of each position in the map pixel image matrix M into a comprehensive value by using a formula (2), thereby obtaining a comprehensive map pixel matrix Z;
Wherein Z issis the integrated value of the s-th position of the integrated map pixel matrix Z;
secondly, the pixel matrix Z of the comprehensive map is segmented into K square matrixes with equal size, the row number and the column number of each square matrix are both n, and when the row number or the column number of a certain square matrix is less than n during segmentation, 0 is used for completing the segmentation;
Finally, carrying out difference enhancement on the boundary information by utilizing the pixel comprehensive value in the formula (3) comprehensive map pixel matrix Z;
wherein Q issValue of s-th position, Z, of map image after differential enhancement for line boundary informationmthe method comprises the steps that the value of the mth position of a map pixel matrix Z is synthesized, all positions contained in a square matrix to which the mth position belongs after the map pixel matrix Z is segmented are taken, wherein m belongs to zs, and eta is a preset adjustment coefficient and is generally near 1;
the image corresponding to the matrix Q is the image information of the map after the enhancement of the image information, that is, the image information corresponding to the extraction of the feature information of the image information.
the method has the beneficial effects that: according to the image information of the map, the extraction of the characteristic information of the image information is realized; according to the feature information and the current time information, the generation of the two-dimensional code information of the map is realized; when a user purchases a map, the time information and the characteristic information of the image information of the map can be obtained by scanning the two-dimensional code information on the map, so that whether the map is legal or not is judged, the problem that whether the map is legal or not cannot be judged by the user in the traditional technology is solved, the normal use of the map by the user is further ensured, and the defect that economic losses are caused by pirates is also avoided.
A map two-dimensional code generation system includes: the device comprises an image acquisition module, an image processing module, a time acquisition module and a two-dimensional code generation module; wherein,
The image acquisition module is used for acquiring the image information of the map and transmitting the image information to the image processing module; the image processing module is used for extracting the characteristic information of the image information and transmitting the characteristic information to the two-dimensional code generating module; the time acquisition module is used for acquiring current time information and transmitting the current time information to the two-dimensional code generation module;
The two-dimension code generating module is used for generating the two-dimension code information of the map according to the feature information transmitted by the image processing module and the current time information transmitted by the clock acquiring module.
in one embodiment, the image processing module comprises an image preprocessing unit;
the image preprocessing unit is used for uniformly dividing the image information into a plurality of area images, respectively carrying out motion detection on the area images and acquiring the motion information of the area images; comparing the motion information with preset motion threshold information, and judging that the noise reduction processing is not required to be carried out on the image of the area when the motion information exceeds or equals to the motion threshold information; when the motion information is lower than the motion threshold information, judging that the regional image needs to be subjected to noise reduction processing; the noise reduction treatment comprises the following specific steps: acquiring local parameter information of the regional image, and acquiring a parameter matrix of a noise reduction algorithm of the regional image according to the local parameter information of the regional image; acquiring a plurality of vector characteristic graphs of the regional image, and synthesizing the vector characteristic graphs by adopting a parameter matrix of the noise reduction algorithm to acquire the regional image after noise reduction; the image preprocessing unit is further configured to synthesize the area image subjected to noise reduction processing and the area image not subjected to noise reduction processing, and generate preprocessed image information.
In one embodiment, the image processing module further comprises an image filtering unit;
the image filtering unit comprises a control subunit, a first filtering subunit, a wavelet filtering subunit and a signal-to-noise ratio detection subunit; the control subunit is configured to transmit the received preprocessed image information acquired by the image preprocessing unit to the first filtering subunit; the first filtering subunit is configured to perform adaptive filtering processing on the preprocessed image information transmitted by the control subunit, and transmit the image information after the adaptive filtering processing to the signal-to-noise ratio detection subunit; the signal-to-noise ratio detection subunit is configured to detect a signal-to-noise ratio of the processed image information, acquire the signal-to-noise ratio of the image information, and transmit the image information to the control subunit when the signal-to-noise ratio of the image information after the adaptive filtering processing exceeds a preset signal-to-noise ratio threshold; when the signal-to-noise ratio of the image information after the self-adaptive filtering processing does not exceed the preset signal-to-noise ratio threshold, transmitting the image information to the wavelet filtering subunit; the wavelet filtering subunit is configured to perform wavelet filtering processing on the image information transmitted by the signal-to-noise ratio detection subunit, and transmit the processed image information to the control subunit; and the control subunit is configured to, when receiving the image information transmitted by the signal-to-noise ratio detection subunit or the wavelet filtering subunit, obtain the image information after filtering processing.
In one embodiment, the image processing module further comprises an image feature enhancement unit;
The image characteristic enhancement unit comprises an image edge information extraction subunit, a contrast conversion subunit and an image enhancement subunit; the image edge information extracting subunit is configured to extract image edge information in the image information according to the image information obtained by the image filtering unit, and transmit the image edge information to the image enhancement subunit; the contrast conversion subunit is configured to perform contrast conversion processing on the image information obtained by the image filtering unit, obtain contrast image information, and transmit the contrast image information to the image enhancement subunit; the image enhancement unit is configured to subtract the image edge information acquired by the image edge information extraction subunit from the image information transmitted by the image filtering unit to obtain a difference image, and add the difference image and the contrast image information to acquire the image information after enhancement processing.
In one embodiment, the system further comprises a unique identification code generation module and an identification code encryption module;
The unique identification code generating module is used for generating a unique identification code of the map according to the two-dimensional code information of the map;
the identification code encryption module is used for processing the unique identification code by adopting an RAS asymmetric encryption algorithm and a public key, so that the encryption processing of the unique identification code is realized;
when the user uses the electronic equipment to scan the unique identification code, the encrypted unique identification code is decrypted through the RSA asymmetric encryption algorithm and the private key, and the unique identification code is acquired.
in one embodiment, the system includes an image enhancement module; the image enhancement module is used for carrying out difference enhancement on the boundary information of the image information;
The image enhancement module is used for converting the image information of the map into an image pixel image matrix M of N P pixel points, wherein N P indicates that the image of the map has N P pixel points, N is the height when the image of the map is represented by pixels, P is the length when the image of the map is represented by pixels, the image pixel image matrix M contains N rows and P columns, the value of each position of the image pixel matrix M represents the value of the pixel point corresponding to the position, the value of the pixel point is a set containing R, G, B values of three channels, and the optimization coefficients of R, G, B three channels are obtained by using a formula (1);
P＝{PR＝ρG,B,PG＝ρR,B,PB＝ρG,R}
where ρ isi,jFor the exchangeability between the ith and jth channels of a map pixel image matrix M, Mi,sThe value of the ith channel which is the s-th position of the map pixel image matrix M, s belongs to the value of the s of the M and is all the positions of the map pixel image matrix M,is the mean value of the ith channel of a map pixel image matrix M, Mj,sis the value of the jth channel at the s-th position of the map pixel image matrix M,is the mean of the jth channel of the map pixel image matrix M, P is the formed replacement set, PG,B、ρR,B、ρG,RAre respectively rhoi,jWherein i is G, R, G, j is B, B, R, PR、PG、PBSeparately mapping the information importance, γ, of the R, G, B channels in the pixel-image matrix MiFor the optimization coefficient of the ith channel in the map pixel image matrix M, sum () is summation, min () is minimum value, max () is maximum value, and i, j can take R, G, B three channels;
Then, converting the R, G, B three-channel value of each position in the map pixel image matrix M into a comprehensive value by using a formula (2), thereby obtaining a comprehensive map pixel matrix Z;
wherein Z issis the integrated value of the s-th position of the integrated map pixel matrix Z;
secondly, the pixel matrix Z of the comprehensive map is segmented into K square matrixes with equal size, the row number and the column number of each square matrix are both n, and when the row number or the column number of a certain square matrix is less than n during segmentation, 0 is used for completing the segmentation;
finally, carrying out difference enhancement on the boundary information by utilizing the pixel comprehensive value in the formula (3) comprehensive map pixel matrix Z;
Wherein Q issvalue of s-th position, Z, of map image after differential enhancement for line boundary informationmTo a comprehensive map pixel matrix ZThe method comprises the following steps that values of m positions are obtained, wherein m belongs to all positions contained in a square matrix to which an s-th position belongs after a map pixel matrix Z is segmented, wherein zs is m, eta is a preset adjustment coefficient and is generally near 1;
The image corresponding to the matrix Q is the image information of the map after the enhancement of the image information, that is, the image information corresponding to the extraction of the feature information of the image information.
The beneficial effect of above-mentioned system lies in: the image information of the map is acquired through the image acquisition module; the extraction of the characteristic information of the image information is realized through the image processing module; the two-dimension code information of the map is generated according to the characteristic information acquired by the image processing module and the current time information acquired by the clock acquisition module through the two-dimension code generation module; when a user purchases a map, the time information and the characteristic information of the image information of the map can be obtained by scanning the two-dimensional code information on the map, so that whether the map is legal or not is judged, the problem that whether the map is legal or not cannot be judged by the user in the traditional technology is solved, the normal use of the map by the user is further ensured, and the defect that economic losses are caused by pirates is also avoided.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
fig. 1 is a schematic diagram of a map two-dimensional code generation method provided by the present invention;
Fig. 2 is a schematic structural diagram of a map two-dimensional code generation system provided by the present invention.
Detailed Description
the preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
The embodiment of the invention provides a map two-dimensional code generation method, as shown in fig. 1, comprising the following steps:
Acquiring image information of a map;
extracting characteristic information of the image information;
acquiring current time information;
And generating two-dimensional code information of the map according to the characteristic information and the current time information.
the working principle of the method is as follows: extracting characteristic information of the image information according to the acquired image information of the map; and according to the characteristic information and the acquired current time information, acquiring the two-dimensional code information of the map.
the method has the beneficial effects that: according to the image information of the map, the extraction of the characteristic information of the image information is realized; according to the feature information and the current time information, the generation of the two-dimensional code information of the map is realized; when a user purchases a map, the time information and the characteristic information of the image information of the map can be obtained by scanning the two-dimensional code information on the map, so that whether the map is legal or not is judged, the problem that whether the map is legal or not cannot be judged by the user in the traditional technology is solved, the normal use of the map by the user is further ensured, and the defect that economic losses are caused by pirates is also avoided.
In one embodiment, the steps of: extracting characteristic information of the image information; the method also comprises the following steps:
uniformly dividing image information into a plurality of area images;
respectively carrying out motion detection on the plurality of area images to acquire motion information of the plurality of area images;
Comparing the motion information with preset motion threshold information, and judging that the noise reduction processing is not required to be carried out on the region image when the motion information exceeds or equals to the motion threshold information;
when the motion information is lower than the motion threshold information, judging that the regional image needs to be subjected to noise reduction processing;
the noise reduction processing comprises the following specific steps: acquiring local parameter information of the area image;
Acquiring a parameter matrix of a noise reduction algorithm of the regional image according to the local parameter information of the regional image;
acquiring a plurality of vector characteristic graphs of the regional image, synthesizing the plurality of vector characteristic graphs by adopting a parameter matrix of a noise reduction algorithm, and acquiring the regional image after noise reduction;
and synthesizing the area image subjected to the noise reduction processing and the image not subjected to the noise reduction processing to generate preprocessed image information. According to the technical scheme, the image information is uniformly divided into a plurality of area images, the divided area images are respectively subjected to motion detection, the obtained motion information is compared with preset motion threshold information, whether the area images need to be subjected to noise reduction processing or not is judged, and when the motion information is lower than the motion threshold information, the area images are subjected to noise reduction processing to obtain the area images subjected to the noise reduction processing; and the area image after the noise reduction processing is synthesized with the area image without the noise reduction processing to generate the preprocessed image information, so that the preprocessing before the characteristic information of the image information is extracted is realized through the technical scheme, and the processing of the image information in the subsequent steps is facilitated.
in one embodiment, the steps of: synthesizing the area image subjected to noise reduction processing and the image not subjected to noise reduction processing to generate preprocessed image information; then, the method further comprises the following steps:
carrying out self-adaptive filtering processing on the preprocessed image information;
Detecting the signal-to-noise ratio of the image information after the self-adaptive filtering processing to obtain the signal-to-noise ratio of the image information;
When the signal-to-noise ratio of the image information after the self-adaptive filtering processing exceeds a preset signal-to-noise ratio threshold value, taking the image information after the self-adaptive filtering processing as the image information after the filtering processing;
and when the signal-to-noise ratio of the image information after the self-adaptive filtering processing does not exceed a preset signal-to-noise ratio threshold, performing wavelet filtering processing on the image information to obtain the image information after the filtering processing. In the technical scheme, the image information after the pre-processing is subjected to the self-adaptive filtering processing, the image information after the self-adaptive filtering processing is subjected to signal-to-noise ratio detection, the acquired signal-to-noise ratio is compared with a preset signal-to-noise ratio threshold value, and when the signal-to-noise ratio of the image information after the self-adaptive filtering processing exceeds the preset signal-to-noise ratio threshold value, the image information after the self-adaptive filtering processing is taken as the image information after the filtering processing; when the signal-to-noise ratio of the image information after the adaptive filtering processing does not exceed a preset signal-to-noise ratio threshold, performing wavelet filtering processing on the image information, and taking the image information after the wavelet filtering processing as the image information after the filtering processing; therefore, the filtering processing of the preprocessed image information is realized, and the efficiency of the subsequent steps for processing the image information is further improved.
in one embodiment, the steps of: acquiring image information after filtering processing; then, the method further comprises the following steps:
Extracting image edge information in the image information;
acquiring contrast image information of the image information;
Subtracting the image edge information from the image information to obtain a difference image; and adding the difference image and the contrast image information to obtain the image information after enhancement processing. According to the technical scheme, the enhancement processing of the image information is realized by processing the acquired image information, the image edge information and the contrast image information; therefore, the efficiency of extracting the characteristic information of the image information is effectively improved.
in one embodiment, the steps of: generating two-dimensional code information of the map according to the feature information and the current time information, and then:
generating a unique identification code of the map according to the two-dimensional code information of the map;
encrypting the unique identification code by using a public key and adopting an RSA asymmetric encryption algorithm to generate an encrypted unique identification code;
When the encrypted unique identification code is scanned, the encrypted unique identification code is decrypted by using a private key and adopting an RSA asymmetric secret algorithm, so that the unique identification code is acquired. According to the technical scheme, the unique identification code of the map is acquired according to the two-dimension code information of the map, so that the two-dimension code information and the unique identification code are bound; the unique identification code is encrypted through an RSA asymmetric encryption algorithm to generate an encrypted and protected unique identification code, so that the safety of map information is ensured; when a user scans the unique identification code, the encrypted unique identification code is decrypted by the private key and the RSA asymmetric secret algorithm, so that the unique identification code can be acquired, and the safety of map information is effectively guaranteed.
in one embodiment, the steps of: extracting characteristic information of the image information; the method also comprises the following steps:
performing difference enhancement on boundary information of the image information;
In one embodiment, the boundary information of the image information is differentially enhanced into; for example, the boundary between the two places can be clearly distinguished by enhancing the information of the boundary between the Hunan and the Hubei, so that the boundary between the two places can be better distinguished, and the extraction of the characteristic information is facilitated.
The following steps are carried out:
firstly, converting image information of a map into an image pixel image matrix M of N P pixel points, wherein N P indicates that an image of the map has N P pixel points, N is the height when the image of the map is represented by the pixel, P is the length when the image of the map is represented by the pixel, the map pixel image matrix M contains N rows and P columns, the value of each position of the map pixel image matrix M represents the value of the pixel point corresponding to the position, the value of the pixel point is a set containing R, G, B values, and the optimization coefficients of R, G, B three channels are obtained by using a formula (1);
P＝{PR＝ρG,B,PG＝ρR,B,PB＝ρG,R}
Where ρ isi,jfor the exchangeability between the ith and jth channels of a map pixel image matrix M, Mi,sthe value of the ith channel which is the s-th position of the map pixel image matrix M, s belongs to the value of the s of the M and is all the positions of the map pixel image matrix M,is the mean value of the ith channel of a map pixel image matrix M, Mj,sIs the value of the jth channel at the s-th position of the map pixel image matrix M,is the mean of the jth channel of the map pixel image matrix M, P is the formed replacement set, PG,B、ρR,B、ρG,RAre respectively rhoi,jWherein i is G, R, G, j is B, B, R, PR、PG、PBseparately mapping the information importance, γ, of the R, G, B channels in the pixel-image matrix MiFor the optimization coefficient of the ith channel in the map pixel image matrix M, sum () is summation, min () is minimum value, max () is maximum value, and i, j can take R, G, B three channels;
the information importance of R, G, B channels in the map pixel image matrix M can be obtained by using the formula (1), so that the optimization coefficient of each channel can be obtained according to the information importance, and R, G, B channels can be converted into a comprehensive channel.
then, converting the R, G, B three-channel value of each position in the map pixel image matrix M into a comprehensive value by using a formula (2), thereby obtaining a comprehensive map pixel matrix Z;
Wherein Z issis the integrated value of the s-th position of the integrated map pixel matrix Z;
The pixel of the image of the map is converted from a three-dimensional channel into a corresponding channel by using the formula (2), so that the calculation workload is reduced, but in the process of synthesizing the channels, the channels with more information content in the channels are given higher weight by integrating the formula (1) and the formula (2), so that the lost information is less, and the structural characteristics can be stored more completely;
Meanwhile, the same comprehensive coefficient is adopted for all pixels of the image of the whole map in the process, so that the information of the global structure of the image of the whole map can be better preserved.
secondly, dividing the comprehensive map pixel matrix Z into K square matrixes with equal size, wherein the row number and the column number of each square matrix are both n, and when the row number or the column number of a certain square matrix is less than n during division, the row number or the column number of the certain square matrix is supplemented by 0;
Finally, carrying out difference enhancement on the boundary information by utilizing the pixel comprehensive value in the formula (3) comprehensive map pixel matrix Z;
wherein Q issValue of s-th position, Z, of map image after differential enhancement for line boundary informationmthe method comprises the steps that the value of the mth position of a map pixel matrix Z is synthesized, all positions contained in a square matrix to which the mth position belongs after the map pixel matrix Z is segmented are taken, wherein m belongs to zs, and eta is a preset adjustment coefficient and is generally near 1;
the image corresponding to the matrix Q is the image information of the map after the enhancement of the image information, that is, the image information corresponding to the extraction of the feature information of the image information.
Has the advantages that:
The boundary information of the image information can be subjected to difference enhancement by the technology.
in the process, different places in the map image can be better distinguished by enhancing the boundary information, so that the feature information can be better extracted.
In the process, three channels of the map are converted into a comprehensive channel by using the formula (1) and the formula (2), so that the calculated amount can be reduced.
In the process of channel synthesis, the channels with more information content in the channels are given higher weight, so that the lost information is less, and the structural characteristics can be stored more completely.
The same comprehensive coefficient is adopted for all pixels of the image of the whole map in the process of synthesizing the channel, so that the information of the global structure of the image of the whole map can be better preserved.
before the formula (3) is operated, the map is firstly segmented into a plurality of square matrixes, so that a whole image is converted into a plurality of local images, and when image information is enhanced, each local image is operated, so that each local image can be better matched.
A map two-dimensional code generation system, as shown in fig. 2, includes: the device comprises an image acquisition module 11, an image processing module 12, a time acquisition module 13 and a two-dimensional code generation module 14; wherein,
the image acquisition module 11 is used for acquiring the image information of the map and transmitting 12 the image information to the image processing module; the image processing module 12 is configured to extract feature information of the image information and transmit the feature information to the two-dimensional code generation module 14; the time acquisition module 13 is configured to acquire current time information and transmit the current time information to the two-dimensional code generation module 14;
and a two-dimensional code generating module 14, configured to generate two-dimensional code information of the map according to the feature information transmitted by the image processing module 12 and the current time information transmitted by the clock obtaining module 13.
the working principle of the system is as follows: the image acquisition module 11 transmits the image information of the map to the image processing module; the image processing module 12 extracts feature information of the image information and transmits the feature information to the two-dimensional code generation module 14; the time obtaining module 13 transmits the current time information to the two-dimensional code generating module 14; the two-dimensional code generation module 14 generates two-dimensional code information of the map according to the feature information transmitted by the image processing module 12 and the current time information transmitted by the clock acquisition module 13.
the beneficial effect of above-mentioned system lies in: the image information of the map is acquired through the image acquisition module; the extraction of the characteristic information of the image information is realized through the image processing module; the two-dimension code information of the map is generated according to the characteristic information acquired by the image processing module and the current time information acquired by the clock acquisition module through the two-dimension code generation module; when a user purchases a map, the time information and the characteristic information of the image information of the map can be obtained by scanning the two-dimensional code information on the map, so that whether the map is legal or not is judged, the problem that whether the map is legal or not cannot be judged by the user in the traditional technology is solved, the normal use of the map by the user is further ensured, and the defect that economic losses are caused by pirates is also avoided.
in one embodiment, an image processing module includes an image pre-processing unit;
the image preprocessing unit is used for uniformly dividing the image information into a plurality of area images, respectively carrying out motion detection on the area images and acquiring the motion information of the area images; comparing the motion information with preset motion threshold information, and judging that the noise reduction processing is not required to be carried out on the region image when the motion information exceeds or equals to the motion threshold information; when the motion information is lower than the motion threshold information, judging that the regional image needs to be subjected to noise reduction processing; the noise reduction treatment comprises the following specific steps: acquiring local parameter information of the regional image, and acquiring a parameter matrix of a noise reduction algorithm of the regional image according to the local parameter information of the regional image; acquiring a plurality of vector characteristic graphs of the regional image, synthesizing the plurality of vector characteristic graphs by adopting a parameter matrix of a noise reduction algorithm, and acquiring the regional image after noise reduction; and the image preprocessing unit is also used for synthesizing the area image subjected to the noise reduction processing and the area image not subjected to the noise reduction processing to generate preprocessed image information. In the technical scheme, the image information is uniformly divided into a plurality of area images through the image preprocessing unit, the divided area images are respectively subjected to motion detection, the obtained motion information is compared with the preset motion threshold information, whether the area images need to be subjected to noise reduction processing is judged, and when the motion information is lower than the motion threshold information, the area images are subjected to noise reduction processing to obtain the area images subjected to the noise reduction processing; and the area image subjected to noise reduction processing by the image preprocessing unit is synthesized with the area image not subjected to noise reduction processing to generate preprocessed image information, so that preprocessing before the image processing module extracts the characteristic information of the image information is realized by the image preprocessing unit of the image processing module in the technical scheme, and the image information is conveniently processed by the subsequent steps of the system.
in one embodiment, the image processing module further comprises an image filtering unit;
the image filtering unit comprises a control subunit, a first filtering subunit, a wavelet filtering subunit and a signal-to-noise ratio detection subunit; the control subunit is used for transmitting the received preprocessed image information acquired by the image preprocessing unit to the first filtering subunit; the first filtering subunit is used for carrying out adaptive filtering processing on the preprocessed image information transmitted by the control subunit and transmitting the image information subjected to the adaptive filtering processing to the signal-to-noise ratio detection subunit; the signal-to-noise ratio detection subunit is used for detecting the signal-to-noise ratio of the processed image information to acquire the signal-to-noise ratio of the image information, and transmitting the image information to the control subunit when the signal-to-noise ratio of the image information after the adaptive filtering processing exceeds a preset signal-to-noise ratio threshold value; when the signal-to-noise ratio of the image information after the self-adaptive filtering processing does not exceed a preset signal-to-noise ratio threshold value, transmitting the image information to a wavelet filtering subunit; the wavelet filtering subunit is used for performing wavelet filtering processing on the image information transmitted by the signal-to-noise ratio detection subunit and transmitting the processed image information to the control subunit; and the control subunit is used for acquiring the image information after filtering processing when receiving the image information transmitted by the signal-to-noise ratio detection subunit or the wavelet filtering subunit. In the technical scheme, the image information after preprocessing acquired by the image preprocessing unit is transmitted to a first filtering subunit through a control subunit of an image filtering unit, the image information is subjected to adaptive filtering processing through the first filtering subunit, the image information after the adaptive filtering processing is transmitted to a signal-to-noise ratio detection subunit for signal-to-noise ratio detection, the acquired signal-to-noise ratio is compared with a preset signal-to-noise ratio threshold value, and when the signal-to-noise ratio of the image information after the adaptive filtering processing exceeds the preset signal-to-noise ratio threshold value, the image information after the processing of the first filtering subunit is transmitted to the first control subunit as the image information after the processing of the image filtering processing unit; when the signal-to-noise ratio of the image information after the adaptive filtering processing does not exceed a preset signal-to-noise ratio threshold value, transmitting the image information to a wavelet filtering subunit for wavelet filtering processing, and transmitting the image information after the wavelet filtering processing to a control subunit as the image information after the image filtering processing unit; therefore, the image filtering processing unit realizes the filtering processing of the image information acquired by the image preprocessing unit, and further improves the efficiency of the subsequent steps of the system for processing the image information.
In one embodiment, the image processing module further comprises an image feature enhancement unit;
The image characteristic enhancement unit comprises an image edge information extraction subunit, a contrast conversion subunit and an image enhancement subunit; the image edge information extraction subunit is used for extracting the image edge information in the image information according to the image information acquired by the image filtering unit and transmitting the image edge information to the image enhancement unit; the contrast conversion subunit is used for carrying out contrast conversion processing on the image information acquired by the image filtering unit, acquiring contrast image information and transmitting the contrast image information to the image enhancement subunit; and the image enhancement unit is used for subtracting the image edge information acquired by the image edge information extraction subunit from the image information transmitted by the image filtering unit to acquire a difference image, and adding the difference image and the contrast image information to acquire the image information after enhancement processing. In the technical scheme, the image edge information is acquired according to the image information by the image edge information extraction subunit of the image feature enhancement unit; the contrast conversion processing of the image information acquired by the image filtering unit is realized through the contrast conversion subunit, and the contrast image information is acquired; the image enhancement unit realizes the enhancement processing of the image information according to the processing of the image information, the image edge information and the contrast image information acquired by the image filtering unit; therefore, the image characteristic enhancement unit can enhance the image information, and the efficiency of the image processing module for extracting the characteristic information of the image information is effectively improved.
in one embodiment, the system further comprises a unique identification code generation module and an identification code encryption module;
The unique identification code generating module is used for generating a unique identification code of the map according to the two-dimensional code information of the map;
The identification code encryption module is used for processing the unique identification code by adopting an RAS asymmetric encryption algorithm and a public key so as to realize encryption processing of the unique identification code;
when a user uses the electronic equipment to scan the unique identification code, the encrypted unique identification code is decrypted through the RSA asymmetric encryption algorithm and the private key, and the unique identification code is acquired.
According to the technical scheme, the unique identification code generation module acquires the unique identification code of the map according to the two-dimensional code information of the map, so that the binding of the two-dimensional code information and the unique identification code is realized; the unique identification code is encrypted through an RSA asymmetric encryption algorithm of an identification code encryption module to generate the encrypted and protected unique identification code, so that the safety of map information is ensured; when a user uses the electronic equipment to scan the unique identification code, the encrypted unique identification code is decrypted by the private key and the RSA asymmetric secret algorithm, so that the unique identification code can be acquired, and the safety of map information is effectively guaranteed.
in one embodiment, a system includes an image enhancement module; the image enhancement module is used for carrying out difference enhancement on the boundary information of the image information;
the image enhancement module is used for converting image information of the map into an image pixel matrix M of N P pixel points, wherein N P indicates that the image of the map has N P pixel points, N is the height when the image of the map is represented by the pixel, P is the length when the image of the map is represented by the pixel, the map pixel matrix M contains N rows and P columns, the value of each position of the map pixel matrix M represents the value of the pixel point corresponding to the position, the value of the pixel point is a set containing R, G, B values of three channels, and the optimization coefficients of R, G, B three channels are obtained by using a formula (1);
P＝{PR＝ρG,B,PG＝ρR,B,PB＝ρG,R}
Where ρ isi,jFor the exchangeability between the ith and jth channels of a map pixel image matrix M, Mi,sThe value of the ith channel which is the s-th position of the map pixel image matrix M, s belongs to the value of the s of the M and is all the positions of the map pixel image matrix M,is the mean value of the ith channel of a map pixel image matrix M, Mj,sis the value of the jth channel at the s-th position of the map pixel image matrix M,Is the mean of the jth channel of the map pixel image matrix M, P is the formed replacement set, PG,B、ρR,B、ρG,RAre respectively rhoi,jwherein i is G, R, G in turn and j is G, R, G in turnvalue at B, B, R, PR、PG、PBseparately mapping the information importance, γ, of the R, G, B channels in the pixel-image matrix Mifor the optimization coefficient of the ith channel in the map pixel image matrix M, sum () is summation, min () is minimum value, max () is maximum value, and i, j can take R, G, B three channels;
the information importance of R, G, B channels in the map pixel image matrix M can be obtained by using the formula (1), so that the optimization coefficient of each channel can be obtained according to the information importance, and R, G, B channels can be converted into a comprehensive channel.
then, converting the R, G, B three-channel value of each position in the map pixel image matrix M into a comprehensive value by using a formula (2), thereby obtaining a comprehensive map pixel matrix Z;
wherein Z issIs the integrated value of the s-th position of the integrated map pixel matrix Z;
the pixel of the image of the map is converted from a three-dimensional channel into a corresponding channel by using the formula (2), so that the calculation workload is reduced, but in the process of synthesizing the channels, the channels with more information content in the channels are given higher weight by integrating the formula (1) and the formula (2), so that the lost information is less, and the structural characteristics can be stored more completely;
meanwhile, the same comprehensive coefficient is adopted for all pixels of the image of the whole map in the process, so that the information of the global structure of the image of the whole map can be better preserved.
Secondly, dividing the comprehensive map pixel matrix Z into K square matrixes with equal size, wherein the row number and the column number of each square matrix are both n, and when the row number or the column number of a certain square matrix is less than n during division, the row number or the column number of the certain square matrix is supplemented by 0;
Finally, carrying out difference enhancement on the boundary information by utilizing the pixel comprehensive value in the formula (3) comprehensive map pixel matrix Z;
Wherein Q issvalue of s-th position, Z, of map image after differential enhancement for line boundary informationmThe method comprises the steps that the value of the mth position of a map pixel matrix Z is synthesized, all positions contained in a square matrix to which the mth position belongs after the map pixel matrix Z is segmented are taken, wherein m belongs to zs, and eta is a preset adjustment coefficient and is generally near 1;
the image corresponding to the matrix Q is the image information of the map after the enhancement of the image information, that is, the image information corresponding to the extraction of the feature information of the image information.
has the advantages that:
The boundary information of the image information can be subjected to difference enhancement by the technology.
In the process, different places in the map image can be better distinguished by enhancing the boundary information, so that the feature information can be better extracted.
in the process, three channels of the map are converted into a comprehensive channel by using the formula (1) and the formula (2), so that the calculated amount can be reduced.
in the process of channel synthesis, the channels with more information content in the channels are given higher weight, so that the lost information is less, and the structural characteristics can be stored more completely.
The same comprehensive coefficient is adopted for all pixels of the image of the whole map in the process of synthesizing the channel, so that the information of the global structure of the image of the whole map can be better preserved.
Before the formula (3) is operated, the map is firstly segmented into a plurality of square matrixes, so that a whole image is converted into a plurality of local images, and when image information is enhanced, each local image is operated, so that each local image can be better matched.
it will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims (10)

1. a map two-dimensional code generation method is characterized by comprising the following steps:
Acquiring image information of a map;
extracting feature information of the image information;
Acquiring current time information;
And generating two-dimensional code information of the map according to the feature information and the current time information.
2. The method of claim 1,
the steps are as follows: extracting feature information of the image information; the method also comprises the following steps:
uniformly dividing the image information into a plurality of area images;
Respectively carrying out motion detection on the plurality of area images to acquire motion information of the plurality of area images;
Comparing the motion information with preset motion threshold information, and judging that the noise reduction processing is not required to be carried out on the region image when the motion information exceeds or equals to the motion threshold information;
When the motion information is lower than the motion threshold information, judging that the noise reduction processing needs to be carried out on the region image;
the noise reduction processing comprises the following specific steps: acquiring local parameter information of the regional image;
Acquiring a parameter matrix of a noise reduction algorithm of the regional image according to the local parameter information of the regional image;
Acquiring a plurality of vector characteristic graphs of the regional image, and synthesizing the vector characteristic graphs by adopting a parameter matrix of the noise reduction algorithm to acquire the regional image after noise reduction;
And synthesizing the area image subjected to the noise reduction processing and the image not subjected to the noise reduction processing to generate preprocessed image information.
3. the method of claim 2,
the steps are as follows: synthesizing the area image subjected to noise reduction processing and the image not subjected to noise reduction processing to generate preprocessed image information; then, the method further comprises the following steps:
Carrying out self-adaptive filtering processing on the preprocessed image information;
Detecting the signal-to-noise ratio of the image information after the self-adaptive filtering processing to obtain the signal-to-noise ratio of the image information;
when the signal-to-noise ratio of the image information after the self-adaptive filtering processing exceeds the preset signal-to-noise ratio threshold, taking the image information after the self-adaptive filtering processing as the image information after the filtering processing;
when the signal-to-noise ratio of the image information after the self-adaptive filtering processing does not exceed the preset signal-to-noise ratio threshold, performing wavelet filtering processing on the image information to obtain the image information after the filtering processing;
The steps are as follows: acquiring image information after filtering processing; then, the method further comprises the following steps:
Extracting image edge information in the image information;
acquiring contrast image information of the image information;
Subtracting the image edge information from the image information to obtain a difference image; and adding the difference image and the contrast image information to obtain the image information after enhancement processing.
4. The method of claim 1,
the steps are as follows: generating two-dimensional code information of the map according to the feature information and the current time information, and then further comprising:
Generating a unique identification code of the map according to the two-dimensional code information of the map;
Encrypting the unique identification code by using a public key and adopting an RSA asymmetric encryption algorithm to generate an encrypted unique identification code;
when the encrypted unique identification code is scanned, the encrypted unique identification code is decrypted by using a private key and adopting an RSA asymmetric secret algorithm, so that the unique identification code is acquired.
5. the method of claim 1,
the steps are as follows: extracting feature information of the image information; the method also comprises the following steps:
performing difference enhancement on boundary information of the image information; the following steps are carried out:
Firstly, converting the image information of the map into an image pixel matrix M of N P pixel points, wherein N P indicates that the image of the map has N P pixel points, N is the height when the image of the map is represented by the pixel, P is the length when the image of the map is represented by the pixel, the map pixel matrix M contains N rows and P columns, the value of each position of the map pixel matrix M represents the value of the pixel point corresponding to the position, the value of the pixel point is a set containing R, G, B three-channel values, and the optimization coefficients of R, G, B three channels are obtained by using a formula (1);
P＝{PR＝ρG,B,PG＝ρR,B,PB＝ρG,R}
Where ρ isi,jFor the exchangeability between the ith and jth channels of a map pixel image matrix M, Mi,sThe value of the ith channel for the s-th position of the map pixel image matrix M, s ∈The values of M being s are all the positions of the map pixel image matrix M,is the mean value of the ith channel of a map pixel image matrix M, Mj,sis the value of the jth channel at the s-th position of the map pixel image matrix M,Is the mean of the jth channel of the map pixel image matrix M, P is the formed replacement set, PG,B、ρR,B、ρG,RAre respectively rhoi,jWherein i is G, R, G, j is B, B, R, PR、PG、PBSeparately mapping the information importance, γ, of the R, G, B channels in the pixel-image matrix MiFor the optimization coefficient of the ith channel in the map pixel image matrix M, sum () is summation, min () is minimum value, max () is maximum value, and i, j can take R, G, B three channels;
Then, converting the R, G, B three-channel value of each position in the map pixel image matrix M into a comprehensive value by using a formula (2), thereby obtaining a comprehensive map pixel matrix Z;
wherein Z issis the integrated value of the s-th position of the integrated map pixel matrix Z;
secondly, the pixel matrix Z of the comprehensive map is segmented into K square matrixes with equal size, the row number and the column number of each square matrix are both n, and when the row number or the column number of a certain square matrix is less than n during segmentation, 0 is used for completing the segmentation;
Finally, carrying out difference enhancement on the boundary information by utilizing the pixel comprehensive value in the formula (3) comprehensive map pixel matrix Z;
wherein Q issvalue of s-th position, Z, of map image after differential enhancement for line boundary informationmthe method comprises the steps that the value of the mth position of a map pixel matrix Z is synthesized, all positions contained in a square matrix to which the mth position belongs after the map pixel matrix Z is segmented are taken, wherein m belongs to zs, and eta is a preset adjustment coefficient and is generally near 1;
the image corresponding to the matrix Q is the image information of the map after the enhancement of the image information, that is, the image information corresponding to the extraction of the feature information of the image information.
6. A map two-dimensional code generation system, comprising: the device comprises an image acquisition module, an image processing module, a time acquisition module and a two-dimensional code generation module; wherein,
the image acquisition module is used for acquiring the image information of the map and transmitting the image information to the image processing module; the image processing module is used for extracting the characteristic information of the image information and transmitting the characteristic information to the two-dimensional code generating module; the time acquisition module is used for acquiring current time information and transmitting the current time information to the two-dimensional code generation module;
The two-dimension code generating module is used for generating the two-dimension code information of the map according to the feature information transmitted by the image processing module and the current time information transmitted by the clock acquiring module.
7. the system of claim 6,
the image processing module comprises an image preprocessing unit;
The image preprocessing unit is used for uniformly dividing the image information into a plurality of area images, respectively carrying out motion detection on the area images and acquiring the motion information of the area images; comparing the motion information with preset motion threshold information, and judging that the noise reduction processing is not required to be carried out on the image of the area when the motion information exceeds or equals to the motion threshold information; when the motion information is lower than the motion threshold information, judging that the regional image needs to be subjected to noise reduction processing; the noise reduction treatment comprises the following specific steps: acquiring local parameter information of the regional image, and acquiring a parameter matrix of a noise reduction algorithm of the regional image according to the local parameter information of the regional image; acquiring a plurality of vector characteristic graphs of the regional image, and synthesizing the vector characteristic graphs by adopting a parameter matrix of the noise reduction algorithm to acquire the regional image after noise reduction; the image preprocessing unit is further configured to synthesize the area image subjected to noise reduction processing and the area image not subjected to noise reduction processing, and generate preprocessed image information.
8. the system of claim 7,
The image processing module also comprises an image filtering unit;
the image filtering unit comprises a control subunit, a first filtering subunit, a wavelet filtering subunit and a signal-to-noise ratio detection subunit; the control subunit is configured to transmit the received preprocessed image information acquired by the image preprocessing unit to the first filtering subunit; the first filtering subunit is configured to perform adaptive filtering processing on the preprocessed image information transmitted by the control subunit, and transmit the image information after the adaptive filtering processing to the signal-to-noise ratio detection subunit; the signal-to-noise ratio detection subunit is configured to detect a signal-to-noise ratio of the processed image information, acquire the signal-to-noise ratio of the image information, and transmit the image information to the control subunit when the signal-to-noise ratio of the image information after the adaptive filtering processing exceeds a preset signal-to-noise ratio threshold; when the signal-to-noise ratio of the image information after the self-adaptive filtering processing does not exceed the preset signal-to-noise ratio threshold, transmitting the image information to the wavelet filtering subunit; the wavelet filtering subunit is configured to perform wavelet filtering processing on the image information transmitted by the signal-to-noise ratio detection subunit, and transmit the processed image information to the control subunit; the control subunit is configured to, when receiving the image information transmitted by the signal-to-noise ratio detection subunit or the wavelet filtering subunit, obtain the image information after filtering processing;
the image processing module also comprises an image characteristic enhancement unit;
the image characteristic enhancement unit comprises an image edge information extraction subunit, a contrast conversion subunit and an image enhancement subunit; the image edge information extracting subunit is configured to extract image edge information in the image information according to the image information obtained by the image filtering unit, and transmit the image edge information to the image enhancement subunit; the contrast conversion subunit is configured to perform contrast conversion processing on the image information obtained by the image filtering unit, obtain contrast image information, and transmit the contrast image information to the image enhancement subunit; the image enhancement unit is configured to subtract the image edge information acquired by the image edge information extraction subunit from the image information transmitted by the image filtering unit to obtain a difference image, and add the difference image and the contrast image information to acquire the image information after enhancement processing.
9. The system of claim 6,
the system also comprises a unique identification code generating module and an identification code encrypting module;
the unique identification code generating module is used for generating a unique identification code of the map according to the two-dimensional code information of the map;
The identification code encryption module is used for encrypting the unique identification code by adopting an RAS asymmetric encryption algorithm and a public key, so that the encryption processing of the unique identification code is realized;
When the user uses the electronic equipment to scan the unique identification code, the encrypted unique identification code is decrypted through the RSA asymmetric encryption algorithm and the private key, and the unique identification code is acquired.
10. the system of claim 6,
the system comprises an image enhancement module; the image enhancement module is used for carrying out difference enhancement on the boundary information of the image information;
the image enhancement module is used for converting the image information of the map into an image pixel image matrix M of N P pixel points, wherein N P indicates that the image of the map has N P pixel points, N is the height when the image of the map is represented by pixels, P is the length when the image of the map is represented by pixels, the image pixel image matrix M contains N rows and P columns, the value of each position of the image pixel matrix M represents the value of the pixel point corresponding to the position, the value of the pixel point is a set containing R, G, B values of three channels, and the optimization coefficients of R, G, B three channels are obtained by using a formula (1);
P＝{PR＝ρG,B,PG＝ρR,B,PB＝ρG,R}
where ρ isi,jFor the exchangeability between the ith and jth channels of a map pixel image matrix M, Mi,sthe value of the ith channel which is the s-th position of the map pixel image matrix M, s belongs to the value of the s of the M and is all the positions of the map pixel image matrix M,is the mean value of the ith channel of a map pixel image matrix M, Mj,sis the value of the jth channel at the s-th position of the map pixel image matrix M,is the mean of the jth channel of the map pixel image matrix M, P is the formed replacement set, PG,B、ρR,B、ρG,RAre respectively rhoi,jWherein i is G, R, G, j is B, B, R, PR、PG、PBseparately mapping the information importance, γ, of the R, G, B channels in the pixel-image matrix MiFor the optimization coefficient of the ith channel in the map pixel image matrix M, sum () is summation, min () is minimum value, max () is maximum value, and i, j can take R, G, B three channels;
then, converting the R, G, B three-channel value of each position in the map pixel image matrix M into a comprehensive value by using a formula (2), thereby obtaining a comprehensive map pixel matrix Z;
wherein Z issis the integrated value of the s-th position of the integrated map pixel matrix Z;
Secondly, the pixel matrix Z of the comprehensive map is segmented into K square matrixes with equal size, the row number and the column number of each square matrix are both n, and when the row number or the column number of a certain square matrix is less than n during segmentation, 0 is used for completing the segmentation;
Finally, carrying out difference enhancement on the boundary information by utilizing the pixel comprehensive value in the formula (3) comprehensive map pixel matrix Z;
Wherein Q issValue of s-th position, Z, of map image after differential enhancement for line boundary informationmthe method comprises the steps that the value of the mth position of a map pixel matrix Z is synthesized, all positions contained in a square matrix to which the mth position belongs after the map pixel matrix Z is segmented are taken, wherein m belongs to zs, and eta is a preset adjustment coefficient and is generally near 1;
the image corresponding to the matrix Q is the image information of the map after the enhancement of the image information, that is, the image information corresponding to the extraction of the feature information of the image information.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112383818A (en) * 2021-01-12 2021-02-19 发明之家(北京)科技有限公司 Intelligent television system and intelligent control method thereof
CN113112856A (en) * 2021-03-31 2021-07-13 北京万集科技股份有限公司 Path generation method and device
CN114022513A (en) * 2021-11-02 2022-02-08 深圳百广科科技有限公司 Billiard game cheating identification method

Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1814454A (en) * 2006-02-21 2006-08-09 江苏国盾科技实业有限责任公司 Two-dimensional encrypted seal
US20110235942A1 (en) * 2010-03-23 2011-09-29 Sony Corporation Image processing apparatus, image processing method, and program
CN102348047A (en) * 2010-07-26 2012-02-08 索尼公司 Method and device for adaptive noise measurement of video signal
CN103685255A (en) * 2013-12-06 2014-03-26 上海众人网络安全技术有限公司 File encryption method based on two-dimension code scanning
CN103793990A (en) * 2012-11-02 2014-05-14 航天信息股份有限公司 Invoice verification method and system
CN103914778A (en) * 2014-03-24 2014-07-09 深圳市威富多媒体有限公司 Anti-fake method and device based on mobile communication terminal
CN104598800A (en) * 2015-01-21 2015-05-06 浪潮通用软件有限公司 Authentication method and authentication system for identity information of grain depot and terminal equipment
CN106648499A (en) * 2016-11-01 2017-05-10 深圳市幻实科技有限公司 Presentation method, device and system for augmented reality terrestrial globe
CN108304593A (en) * 2018-04-19 2018-07-20 北京星球时空科技有限公司 The method that paper map is shown with electronic map interactive
CN108334915A (en) * 2018-01-12 2018-07-27 熵易科技有限公司 A kind of anti-fake and encryption method, electronic equipment and storage medium based on Quick Response Code
CN108830628A (en) * 2018-07-28 2018-11-16 宁波亿诺维信息技术有限公司 A kind of food quality anti-fake two-dimension code traceability system
CN108961615A (en) * 2018-06-05 2018-12-07 华北理工大学 A kind of book information classification of information management system
CN109993877A (en) * 2019-03-07 2019-07-09 北京航天泰坦科技股份有限公司 Anti-fake bill recognition methods based on location information

Patent Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1814454A (en) * 2006-02-21 2006-08-09 江苏国盾科技实业有限责任公司 Two-dimensional encrypted seal
US20110235942A1 (en) * 2010-03-23 2011-09-29 Sony Corporation Image processing apparatus, image processing method, and program
CN102348047A (en) * 2010-07-26 2012-02-08 索尼公司 Method and device for adaptive noise measurement of video signal
CN103793990A (en) * 2012-11-02 2014-05-14 航天信息股份有限公司 Invoice verification method and system
CN103685255A (en) * 2013-12-06 2014-03-26 上海众人网络安全技术有限公司 File encryption method based on two-dimension code scanning
CN103914778A (en) * 2014-03-24 2014-07-09 深圳市威富多媒体有限公司 Anti-fake method and device based on mobile communication terminal
CN104598800A (en) * 2015-01-21 2015-05-06 浪潮通用软件有限公司 Authentication method and authentication system for identity information of grain depot and terminal equipment
CN106648499A (en) * 2016-11-01 2017-05-10 深圳市幻实科技有限公司 Presentation method, device and system for augmented reality terrestrial globe
CN108334915A (en) * 2018-01-12 2018-07-27 熵易科技有限公司 A kind of anti-fake and encryption method, electronic equipment and storage medium based on Quick Response Code
CN108304593A (en) * 2018-04-19 2018-07-20 北京星球时空科技有限公司 The method that paper map is shown with electronic map interactive
CN108961615A (en) * 2018-06-05 2018-12-07 华北理工大学 A kind of book information classification of information management system
CN108830628A (en) * 2018-07-28 2018-11-16 宁波亿诺维信息技术有限公司 A kind of food quality anti-fake two-dimension code traceability system
CN109993877A (en) * 2019-03-07 2019-07-09 北京航天泰坦科技股份有限公司 Anti-fake bill recognition methods based on location information

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112383818A (en) * 2021-01-12 2021-02-19 发明之家(北京)科技有限公司 Intelligent television system and intelligent control method thereof
CN113112856A (en) * 2021-03-31 2021-07-13 北京万集科技股份有限公司 Path generation method and device
CN114022513A (en) * 2021-11-02 2022-02-08 深圳百广科科技有限公司 Billiard game cheating identification method

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