CN112434651A - Information analysis method and device based on image recognition and computer equipment - Google Patents
Information analysis method and device based on image recognition and computer equipment Download PDFInfo
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Abstract
The invention discloses an information analysis method and device based on image recognition and computer equipment. In the method, firstly, dynamic information and static information in a target image are identified, clustering processing is carried out to obtain an information set to be identified, secondly, each information to be identified in the information set to be identified is matched with a pre-stored information analysis unit set to obtain a target information analysis unit, wherein the information analysis unit set comprises at least one unit list, each unit list comprises at least one information analysis unit, each unit list corresponds to one datum information, and then, an information analysis result corresponding to the target image is determined according to the datum information corresponding to the unit list to which the target information analysis unit belongs. In this way, the information analysis result is determined by the reference information corresponding to the unit list to which the target information analysis unit belongs, so that the problem that a large amount of time is consumed due to an excessively large information amount can be avoided, and the information analysis efficiency is improved.
Description
Technical Field
The present disclosure relates to the field of information analysis technologies, and in particular, to an information analysis method and apparatus based on image recognition, and a computer device.
Background
At present, in order to obtain the biological characteristic information, the required biological characteristic information can be extracted by identifying the image, and most of the analysis of the biological characteristic information is analyzed by a computer, if the information amount is too large, a large amount of time is consumed, and the efficiency of information analysis is also influenced.
Disclosure of Invention
In order to solve the technical problems in the related art, the present disclosure provides an information analysis method, apparatus and computer device based on image recognition.
The invention provides an information analysis method based on image recognition, which comprises the following steps:
identifying dynamic information and static information in a target image; clustering the dynamic information and the static information in the target image to obtain an information set to be identified;
matching each piece of information to be identified in the information set to be identified with a pre-stored information analysis unit set to obtain a target information analysis unit meeting matching conditions, wherein the information analysis unit set comprises at least one unit list, each unit list comprises at least one information analysis unit, and each unit list corresponds to one piece of reference information;
and determining an information analysis result corresponding to the target image according to the reference information corresponding to the unit list to which the target information analysis unit belongs.
Optionally, before the identifying the dynamic information and the static information in the target image, the method further includes: determining an information database, wherein the information database comprises preset key information, and the preset key information comprises dynamic information of a first analysis node and static information of a second analysis node; the identifying dynamic information and static information in the target image includes: based on the information database, dynamic information and static information in the target image are identified.
Optionally, determining an information analysis result corresponding to the target image according to the reference information corresponding to the unit list to which the target information analysis unit belongs, specifically including:
acquiring an analysis instruction of target information analysis, and extracting analysis parameters corresponding to analysis records carried in the analysis instruction of the target information analysis; determining reference information corresponding to analysis parameters corresponding to analysis records based on corresponding relations between record texts and the analysis parameters in the analysis records and the analysis records; and acquiring a reference analysis record, and determining an information analysis result corresponding to the target image based on the matching of the analysis record and the reference analysis record.
Optionally, the clustering the dynamic information and the static information in the target image to obtain an information set to be identified includes: dividing the dynamic information and the static information in the target image into at least one to-be-identified set according to the ratio of the dynamic information and the static information in the target image, wherein each to-be-identified set comprises one dynamic information and at least one static information, the first group of information of each to-be-identified set is dynamic information, and the last group of information is static information; for a current to-be-identified set to be clustered, clustering dynamic information in the current to-be-identified set with each static information in the current to-be-identified set respectively to obtain to-be-identified information corresponding to the current to-be-identified set; and obtaining a set of information to be identified according to the information to be identified corresponding to each set of information to be identified.
Optionally, the matching each piece of information to be identified in the set of information to be identified with a set of pre-stored information analysis units to obtain a target information analysis unit meeting a matching condition includes: labeling each piece of information to be identified in the information set to be identified and each information analysis unit in a pre-stored information analysis unit set respectively to obtain a labeling interval of each piece of information to be identified and each information analysis unit; and determining an information analysis unit with the labeling interval matched with a preset interval as a target information analysis unit.
Optionally, the matching of each piece of information to be identified in the set of information to be identified and a set of pre-stored information analysis units includes: for current information to be identified to be matched in the information set to be identified, determining an information analysis unit to be matched in the pre-stored information analysis unit set, wherein the information analysis unit to be matched comprises dynamic information and/or static information corresponding to the current information to be identified; and matching each piece of information to be identified in the information set to be identified with the corresponding information analysis unit to be matched.
Optionally, the method further comprises: and transmitting the information analysis result corresponding to the target image as a first image to be transmitted.
The present invention also provides an information analysis apparatus based on image recognition, the apparatus comprising:
the image identification module is used for identifying dynamic information and static information in the target image; clustering the dynamic information and the static information in the target image to obtain an information set to be identified;
the information matching module is used for matching each piece of information to be identified in the information set to be identified with a pre-stored information analysis unit set to obtain a target information analysis unit meeting matching conditions, the information analysis unit set comprises at least one unit list, each unit list comprises at least one information analysis unit, and each unit list corresponds to one piece of reference information;
and the result determining module is used for determining an information analysis result corresponding to the target image according to the reference information corresponding to the unit list to which the target information analysis unit belongs.
The invention also provides a computer device comprising a processor and a memory communicating with each other, the processor being configured to retrieve a computer program from the memory and to implement the method of any one of the preceding claims by running the computer program.
The invention also provides a computer-readable storage medium having stored thereon a computer program which, when run, implements the method of any of the above.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects.
The invention provides an information analysis method, an information analysis device and computer equipment based on image recognition. In this way, the reference information corresponding to the unit list to which the target information analysis unit belongs is used to determine the information analysis result, so that the problem that a large amount of time is consumed due to an excessively large amount of information can be avoided, and the efficiency of information analysis is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a flowchart of an information analysis method based on image recognition according to an embodiment of the present invention.
Fig. 2 is a block diagram of an information analysis apparatus based on image recognition according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a hardware structure of a computer device according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
Referring to fig. 1, a flow chart of an information analysis method based on image recognition is provided, and the following steps S110 to S130 are specifically performed when the method is implemented.
Step S110, identifying dynamic information and static information in a target image; and clustering the dynamic information and the static information in the target image to obtain an information set to be identified.
Step S120, matching each piece of information to be identified in the information set to be identified with a pre-stored information analysis unit set to obtain a target information analysis unit meeting matching conditions, wherein the information analysis unit set comprises at least one unit list, each unit list comprises at least one information analysis unit, and each unit list corresponds to one piece of reference information.
Step S130, determining an information analysis result corresponding to the target image according to the reference information corresponding to the unit list to which the target information analysis unit belongs.
The following advantageous effects can be achieved when the method described in the above steps S110 to S130 is performed: firstly, identifying dynamic information and static information in a target image, clustering the dynamic information and the static information to obtain an information set to be identified, secondly, matching each information to be identified in the information set to be identified with a pre-stored information analysis unit set to obtain a target information analysis unit, wherein the information analysis unit set comprises at least one unit list, each unit list comprises at least one information analysis unit, each unit list corresponds to one datum information, and then, according to the datum information corresponding to the unit list to which the target information analysis unit belongs, determining an information analysis result corresponding to the target image. In this way, the reference information corresponding to the unit list to which the target information analysis unit belongs is used to determine the information analysis result, so that the problem that a large amount of time is consumed due to an excessively large amount of information can be avoided, and the efficiency of information analysis is improved.
In practical implementation, in order to accurately identify the dynamic information and the static information in the target image, before the identifying the dynamic information and the static information in the target image described in step S110, the method further includes: determining an information database, wherein the information database comprises preset key information, and the preset key information comprises dynamic information of a first analysis node and static information of a second analysis node; the identifying dynamic information and static information in the target image includes: based on the information database, dynamic information and static information in the target image are identified.
In the implementation of the above, through the key information in the information database, the dynamic information and the static information in the target image can be accurately identified,
optionally, determining an information analysis result corresponding to the target image according to the reference information corresponding to the unit list to which the target information analysis unit belongs, specifically including:
acquiring an analysis instruction of target information analysis, and extracting analysis parameters corresponding to analysis records carried in the analysis instruction of the target information analysis; determining reference information corresponding to analysis parameters corresponding to analysis records based on corresponding relations between record texts and the analysis parameters in the analysis records and the analysis records; and acquiring a reference analysis record, and determining an information analysis result corresponding to the target image based on the matching of the analysis record and the reference analysis record.
In specific implementation, in order to obtain information to be identified in time and avoid omission of the obtained information to be identified due to confusion of an identification time sequence, the step S110 of clustering the dynamic information and the static information in the target image to obtain an information set to be identified may specifically include: dividing the dynamic information and the static information in the target image into at least one to-be-identified set according to the ratio of the dynamic information and the static information in the target image, wherein each to-be-identified set comprises one dynamic information and at least one static information, the first group of information of each to-be-identified set is dynamic information, and the last group of information is static information; for a current to-be-identified set to be clustered, clustering dynamic information in the current to-be-identified set with each static information in the current to-be-identified set respectively to obtain to-be-identified information corresponding to the current to-be-identified set; and obtaining a set of information to be identified according to the information to be identified corresponding to each set of information to be identified.
The content described above is executed, and the dynamic information and the static information are divided into at least one to-be-identified set according to the proportion of the dynamic information and the static information in the target image, so that the dynamic information and the static information can be identified according to the proportion in a time sequence, the to-be-identified information can be obtained in time, and meanwhile, the omission of the obtained to-be-identified information due to the chaos of the identification time sequence can be avoided.
In specific implementation, the step S120 of matching each piece of information to be identified in the set of information to be identified with a pre-stored set of information analysis units to obtain a target information analysis unit meeting a matching condition specifically includes: labeling each piece of information to be identified in the information set to be identified and each information analysis unit in a pre-stored information analysis unit set respectively to obtain a labeling interval of each piece of information to be identified and each information analysis unit; and determining an information analysis unit with the labeling interval matched with a preset interval as a target information analysis unit.
In specific implementation, in order to ensure the accuracy of matching each piece of information to be identified with a set of pre-stored information analysis units, the matching of each piece of information to be identified in the set of information to be identified with a set of pre-stored information analysis units described in step S120 includes: for current information to be identified to be matched in the information set to be identified, determining an information analysis unit to be matched in the pre-stored information analysis unit set, wherein the information analysis unit to be matched comprises dynamic information and/or static information corresponding to the current information to be identified; and matching each piece of information to be identified in the information set to be identified with the corresponding information analysis unit to be matched.
Through the description content, firstly, the information analysis unit to be matched is determined in the information analysis unit set stored in advance, and secondly, each piece of information to be identified in the information set to be identified is respectively matched with the information analysis unit to be matched, so that the matching accuracy of each piece of information to be identified and the information analysis unit set stored in advance can be ensured through matching one by one.
On the basis of the above, the present invention may further include step S140: and transmitting the information analysis result corresponding to the target image as a first image to be transmitted.
Further, the step S140 of transmitting the information analysis result corresponding to the target image as the first image to be transmitted may further include the following steps.
Step 141, obtaining first transmission strategy information of the first image to be transmitted in the first transmission channel.
In this embodiment, the first transmission channel is a transmission channel in which the first image to be transmitted is located in a plurality of transmission channels included in an image set, and the first image to be transmitted is an image to be transmitted in the image set.
Step 142, acquiring a first matching relationship between the first transmission strategy information and the target description object in the image set; and acquiring a matching ratio corresponding to the first matching relation according to a preset matching relation.
In this embodiment, the preset matching relationship is used to indicate a corresponding association relationship between a matching relationship between the transmission policy information of the first image to be transmitted in the transmission channel and the target description object and a matching ratio.
Step 143, matching the historical transmission channel of the first image to be transmitted according to the matching percentage corresponding to the first matching relationship, so as to obtain a sample transmission channel of the first image to be transmitted.
In this embodiment, the number of the sample transmission channels is related to a matching relationship between the first transmission policy information and the target description object.
Step 144, determining a first transmission rate corresponding to the target description object according to the sample transmission channel, and taking the first transmission rate as a target transmission rate; the target transmission rate is related to a matching relation between the first transmission strategy information and the target description object, and the target transmission rate is different from a second transmission rate corresponding to the target description object determined according to the historical transmission channel; determining security index information of the first transmission policy information based on the target transmission rate; and when the target transmission rate is judged to meet the set conditions through the safety index information, the first transmission channel is adopted to transmit the first image to be transmitted based on the target transmission rate and the first transmission strategy information.
The following advantageous effects can be achieved when the method described in the above steps 141 to 144 is performed: firstly, matching the historical transmission channel of the first image to be transmitted according to the matching occupation ratio corresponding to the first matching relation to obtain a sample transmission channel. And secondly, determining a first transmission rate corresponding to the target description object in the image set according to the sample transmission channel, taking the first transmission rate as a target transmission rate, and further determining the safety index information of the first transmission strategy information based on the target transmission rate. And then, when the target transmission rate is judged to meet the set conditions through the safety index information, a first image to be transmitted is transmitted by adopting a first transmission channel.
Thus, a first matching relation between the target description objects in the first transmission strategy information image set is obtained, the matching occupation corresponding to the first matching relation is used for carrying out complete matching on the historical transmission channel of the first image to be transmitted, the deviation of the obtained sample transmission channel caused by error information in the matching process is avoided, on the premise that the sample transmission channel is accurately determined, the first transmission rate corresponding to the target description objects in the image set is determined based on the sample transmission channel, the first transmission rate is used as the target transmission rate, the safety index information of the first transmission strategy information is determined according to the target transmission rate, the corresponding safety index corresponding to the corresponding transmission rate is realized, the potential safety hazard in the transmission process caused by overhigh or overlow transmission rate is avoided, after the safety index information is determined, when the target transmission rate is judged to meet the set conditions through the safety index information, potential safety hazards can be avoided when the first image to be transmitted is transmitted through the first transmission channel based on the target transmission rate and the first transmission strategy information.
In specific implementation, the determining, according to the sample transmission channel, a first transmission rate corresponding to the target description object in step S144, and taking the first transmission rate as a target transmission rate includes: and loading the sample transmission channel to a target description object in the image set to obtain a first transmission rate.
Further loading the sample transmission channel to a target description object in the image set to obtain a first transmission rate, which specifically includes: and acquiring the image category information of the first image to be transmitted. Wherein the image category information is used to indicate that the sample transmission channel loads a category attribute on the target description object; and loading the sample transmission channel to the target description object according to the class attribute indicated by the image class information to obtain the first transmission rate.
In this embodiment, before acquiring the first transmission policy information of the first image to be transmitted in the first transmission channel, the method further includes: analyzing the image category information of each first image to be transmitted in the first transmission channel; the first image to be transmitted is one of a plurality of images to be transmitted; the image category information indicates category information of one of a plurality of images to be transmitted.
In a specific implementation, in order to save time for acquiring different transmission policy information, the acquiring of the first transmission policy information of the first image to be transmitted in the first transmission channel described in step 141 may specifically include the following contents described in sub-steps 1411 to 1412:
substep 1411, when the first image to be transmitted exists in a second transmission channel at a time before the current time, obtaining second transmission strategy information of the first image to be transmitted in the second transmission channel, and determining the first transmission strategy information according to the second transmission strategy information and the image size of the first image to be transmitted; the first image to be transmitted exists in the first transmission channel at the current moment, and the second transmission channel is a transmission channel of the plurality of transmission channels, where the first image to be transmitted exists at a moment before the current moment;
a sub-step 1412, obtaining the first transmission policy information configured for the first image to be transmitted in the first transmission channel when the first image to be transmitted does not exist in the second transmission channel at a time before the current time.
By performing the operations described in sub-steps 1411-1412, first obtaining the second transmission policy information of the first image to be transmitted in the second transmission channel, and then determining the first transmission policy information according to the second transmission policy information and the image size of the first image to be transmitted, the time consumption for obtaining different transmission policy information can be saved.
In this embodiment, the obtaining of the first matching relationship between the first transmission policy information and the target description object in the image set in step 142 specifically includes:
determining the text recognition degree of the protocol text of the first transmission strategy information, and determining the text data capacity with the text recognition degree smaller than or equal to the preset text recognition degree according to the text recognition degree of the protocol text;
and calculating a matching value between the text data capacity and the target description object in the image set, and determining a first matching relation according to the matching value.
Further, in order to improve the efficiency of calculating the matching ratio of the first matching relationship, the step 142 of obtaining the matching ratio corresponding to the first matching relationship according to the preset matching relationship may specifically include the following contents described in sub-steps 1421 to 1423:
substep 1421, for one of the prestored multiple matching relationships, performing matching deviation calculation on the first matching relationship by using the latest updated calculation thread to obtain a current deviation value;
in the substep 1422, clustering current deviation values satisfying the matching relationship among the obtained current deviation values to obtain a deviation set;
substep 1423, calculating a matching success rate according to the deviation set, and determining a matching proportion corresponding to the first matching relationship based on the matching success rate.
The contents described in substeps 1421-1423 are executed, a matching success rate is calculated according to the obtained deviation set, and then a matching proportion corresponding to the first matching relationship is determined according to the matching success rate. Therefore, the matching success rate can be beneficial to improving the efficiency of calculating the matching ratio of the first matching relation.
In a specific implementation, in order to match each node tag corresponding to each piece of sub-event matching information one by one, and improve accuracy of matching a sample transmission channel, the step 143, which is described in the step of matching the historical transmission channel of the first image to be transmitted according to the matching percentage corresponding to the first matching relationship, obtains the sample transmission channel of the first image to be transmitted, and may specifically include the contents described in the following sub-steps 1431 to 1434:
substep 1431, dividing a plurality of continuous matching nodes according to the matching proportion corresponding to the first matching relationship, and setting the first image to be transmitted as an image to be matched in the plurality of matching nodes; the image to be matched is matched with each matching node respectively;
substep 1432 of generating, for each of the divided matching nodes, matching event information corresponding to the matching node, respectively; the matching event information represents an event corresponding to each node label in a preset label set, wherein each piece of generated matching event information is executed according to the following mode:
substep 1433, acquiring a node label matched with each matching node from the preset label set according to the matching node corresponding to the matching event information; matching the acquired node label with a historical transmission channel of the first image to be transmitted; acquiring a node label matched with each matching node from the preset label set according to the matching node corresponding to the matching event information, wherein the method specifically comprises the following steps: according to the matching nodes corresponding to the matching event information, distributing the matching event information into a plurality of pieces of sub-event matching information with event priorities;
and a substep 1434, sequentially obtaining each node label corresponding to each piece of sub-event matching information according to the label attribute value of the node label in the preset label set and the priority of the plurality of pieces of sub-event matching information, so that a first label attribute value of each node label corresponding to each piece of sub-event matching information is matched with a second label attribute value of each node label corresponding to the previous sub-event matching information of the current sub-event matching information, and matching according to the node label and a historical transmission channel of the first image to be transmitted, so as to obtain a sample transmission channel of the first image to be transmitted.
By performing what is described in sub-steps 1431-1434, a plurality of matching nodes are first partitioned from the first matching relationship in order to achieve integrity matching of the first matching relationship. And then generating matching event information corresponding to each matching node, further obtaining a node label matched with each matching node, so that the matching event information corresponding to each matching node can be conveniently searched subsequently, then distributing the matching event information into a plurality of pieces of sub-event matching information with event priorities, and further successively obtaining each node label corresponding to each piece of sub-event matching information according to the label attribute value of the node label and the priority of the plurality of pieces of sub-event matching information, so that each node label corresponding to each piece of sub-event matching information can be matched one by one, further each node label can be matched with a historical transmission channel of the first image to be transmitted according to the node label, and the accuracy of matching the sample transmission channel can be improved.
In an implementation, in order to improve the accuracy and reliability of determining the security evaluation information and facilitate identifying the security index information from the security evaluation information, the determining, based on the target transmission rate, of the security index information of the first transmission policy information described in step 144 may specifically include the contents described in sub-steps 1441 to 1444:
substep 1441, determining, according to the obtained first transmission rate and second transmission rate for marking the target transmission rate, a period weight value of a plurality of signal periods to be analyzed for marking the target transmission rate and a correlation parameter between different signal periods;
sub-step 1442, analyzing the multiple signal cycles based on the determined cycle weight values of the multiple signal cycles and the correlation parameters between different signal cycles, so that the analyzed cycle weight values of the signal cycles are greater than the first weight values, and the analyzed correlation parameters between the signal cycles are smaller than the second weight values;
a substep 1443, determining, for the transmission rate identifier of the first image to be transmitted, whether the transmission rate identifier of the first image to be transmitted matches the target transmission rate according to the value of the transmission rate identifier of the first image to be transmitted in each signal period in the analyzed signal period;
in sub-step 1444, if it is determined that the transmission rate identifier of the first to-be-transmitted image matches the target transmission rate, determining, according to the target transmission rate and the transmission rate identifier, security evaluation information of the first transmission policy information, and determining, based on the security evaluation information, security index information.
Performing the operations described in sub-steps 1441-1444, a period weight value for a plurality of signal periods and a correlation parameter between different signal periods of a target transmission rate can be determined according to the first transmission rate and the second transmission rate. Secondly, analyzing a plurality of signal periods, so that the period weight values of the signal periods and the relevance between the signal periods can be accurately analyzed, then judging whether the transmission rate identification of the first image to be transmitted is matched with the target transmission rate or not according to the value of each signal period in the analyzed signal periods, and if so, improving the accuracy and reliability of the safety evaluation information through the target transmission rate and the transmission rate identification, and further being beneficial to identifying the safety index information from the safety evaluation information.
In order to save the time for transmitting the first image to be transmitted and improve the efficiency of transmitting the first image to be transmitted, when the target transmission rate is determined to satisfy the setting condition by the security index information, the step 144 of transmitting the first image to be transmitted by using the first transmission channel based on the target transmission rate and the first transmission policy information may specifically include the following steps a 1-a 8:
a1, acquiring a first index parameter and a second index parameter aiming at the safety index information; wherein the noise value of the second index parameter is less than the noise value of the first index parameter;
a2, determining a security level corresponding to the security index information according to the index description information of the second index parameter, and acquiring the security measurement information of the security index information from the first index parameter according to the security level;
step a3, determining the relevance of the information source of the security metric information and each information sequence in a preset information source library; the preset information source library comprises a plurality of information sequences, and each information sequence corresponds to a corresponding information description record;
a4, screening a plurality of groups of information sequences from the preset information source library based on the relevance of the information sources and each information sequence; judging whether the target transmission rate meets a set condition or not according to the safety index information based on the information description records of a plurality of groups of information sequences;
for example, based on the correlation degree between the information source and each information sequence, screening multiple groups of information sequences from the preset information source library, including: screening multiple groups of information sequences with the maximum relevance degree from the preset information source library based on the relevance degree of each information sequence in the information source and the preset information source library;
for example, the determining, according to the safety index information, whether the target transmission rate satisfies a set condition based on the information description records of the multiple sets of information sequences includes: if the information description record is a first record identifier or a second record identifier, clustering the first record identifier and the second record identifier based on the information description records of a plurality of groups of information sequences to obtain a clustering result; judging whether the target transmission rate meets a set condition or not according to the obtained clustering result and the safety index information;
a5, when the target transmission rate is judged to meet the set condition according to the clustering result and the safety index information, summarizing the target transmission rate and the first transmission strategy information into image transmission authority information;
a6, when summarizing image transmission authority information, acquiring the relevant element information of the summarized image transmission authority information; analyzing related element information of the image transmission permission information to determine whether the image transmission permission information contains a permission code of abnormal information;
a7, if the image transmission permission information contains the permission code of the abnormal information, modifying the permission code, and verifying the modified permission code to obtain a verification result; judging whether the transmission of the first transmission channel and the target transmission rate and the first transmission strategy information can be distributed in the same image transmission authority information or not based on a check result; if yes, the first to-be-transmitted image is transmitted by adopting the first transmission channel based on the target transmission rate and the first transmission strategy information;
a8, if the image transmission authority information does not contain the authority code of abnormal information, determining whether the first transmission channel transmission and the target transmission rate and the first transmission strategy information can be distributed in the same image transmission authority information; and if so, transmitting the first image to be transmitted by adopting the first transmission channel based on the target transmission rate and the first transmission strategy information.
Executing the contents described in the steps a 1-a 8, firstly determining the safety level corresponding to the safety index information according to the acquired index description information of the second index parameter, and further acquiring the safety metric information of the safety index information from the acquired first index parameter according to the safety level. And secondly, determining the relevance between the information source of the safety measurement information and each information sequence in the preset information source library, further screening multiple groups of information sequences from the preset information source library, and accurately judging whether the target transmission rate meets the set conditions or not by screening the multiple groups of information sequences, so that the judgment efficiency is improved, and meanwhile, the judgment result of the target transmission rate due to the interference of other abnormal data in the judgment process is avoided. And then when the target transmission rate is judged to meet the set condition, summarizing the target transmission rate and the first transmission strategy information into image transmission authority information, further acquiring and analyzing related element information of the image transmission authority information, and judging whether the image transmission authority information contains an authority code of abnormal information. And further, on the premise that the first transmission channel transmits the target transmission rate and the first transmission strategy information can be distributed in the same image transmission authority information, the first image to be transmitted is transmitted through the first transmission channel, so that the time for transmitting the first image to be transmitted can be saved, and the efficiency for transmitting the first image to be transmitted can be improved.
Based on the same inventive concept, please refer to fig. 2, the present invention further provides a block diagram of an information analysis apparatus 200 based on image recognition, the apparatus comprising:
an image recognition module 210 for recognizing dynamic information and static information in the target image; clustering the dynamic information and the static information in the target image to obtain an information set to be identified;
the information matching module 220 is configured to match each piece of information to be identified in the set of information to be identified with a pre-stored set of information analysis units to obtain a target information analysis unit meeting a matching condition, where the set of information analysis units includes at least one unit list, each unit list includes at least one information analysis unit, and each unit list corresponds to one piece of reference information;
and a result determining module 230, configured to determine an information analysis result corresponding to the target image according to the reference information corresponding to the unit list to which the target information analyzing unit belongs.
And an information transmission module 240, configured to transmit an information analysis result corresponding to the target image as the first image to be transmitted.
On the basis of the above, please refer to fig. 3 in combination, there is provided a computer device 110, which includes a processor 111, and a memory 112 and a bus 113 connected to the processor 111; wherein, the processor 111 and the memory 112 complete the communication with each other through the bus 113; the processor 111 is used to call program instructions in the memory 112 to perform the above-described method.
Further, a readable storage medium is provided, on which a program is stored, which when executed by a processor implements the method described above.
It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (10)
1. An information analysis method based on image recognition, characterized in that the method comprises:
identifying dynamic information and static information in a target image; clustering the dynamic information and the static information in the target image to obtain an information set to be identified;
matching each piece of information to be identified in the information set to be identified with a pre-stored information analysis unit set to obtain a target information analysis unit meeting matching conditions, wherein the information analysis unit set comprises at least one unit list, each unit list comprises at least one information analysis unit, and each unit list corresponds to one piece of reference information;
and determining an information analysis result corresponding to the target image according to the reference information corresponding to the unit list to which the target information analysis unit belongs.
2. The method of claim 1, wherein prior to identifying dynamic information and static information in a target image, the method further comprises: determining an information database, wherein the information database comprises preset key information, and the preset key information comprises dynamic information of a first analysis node and static information of a second analysis node; the identifying dynamic information and static information in the target image includes: based on the information database, dynamic information and static information in the target image are identified.
3. The method according to claim 1, wherein determining the information analysis result corresponding to the target image according to the reference information corresponding to the unit list to which the target information analysis unit belongs specifically comprises:
acquiring an analysis instruction of target information analysis, and extracting analysis parameters corresponding to analysis records carried in the analysis instruction of the target information analysis; determining reference information corresponding to analysis parameters corresponding to analysis records based on corresponding relations between record texts and the analysis parameters in the analysis records and the analysis records; and acquiring a reference analysis record, and determining an information analysis result corresponding to the target image based on the matching of the analysis record and the reference analysis record.
4. The method according to claim 1, wherein the clustering the dynamic information and the static information in the target image to obtain a set of information to be identified comprises: dividing the dynamic information and the static information in the target image into at least one to-be-identified set according to the ratio of the dynamic information and the static information in the target image, wherein each to-be-identified set comprises one dynamic information and at least one static information, the first group of information of each to-be-identified set is dynamic information, and the last group of information is static information; for a current to-be-identified set to be clustered, clustering dynamic information in the current to-be-identified set with each static information in the current to-be-identified set respectively to obtain to-be-identified information corresponding to the current to-be-identified set; and obtaining a set of information to be identified according to the information to be identified corresponding to each set of information to be identified.
5. The method according to claim 1, wherein the matching of each piece of information to be identified in the set of information to be identified with a pre-stored set of information analysis units to obtain a target information analysis unit meeting a matching condition comprises: labeling each piece of information to be identified in the information set to be identified and each information analysis unit in a pre-stored information analysis unit set respectively to obtain a labeling interval of each piece of information to be identified and each information analysis unit; and determining an information analysis unit with the labeling interval matched with a preset interval as a target information analysis unit.
6. The method according to claim 1, wherein the matching each piece of information to be identified in the set of information to be identified with a pre-stored set of information analysis units comprises: for current information to be identified to be matched in the information set to be identified, determining an information analysis unit to be matched in the pre-stored information analysis unit set, wherein the information analysis unit to be matched comprises dynamic information and/or static information corresponding to the current information to be identified; and matching each piece of information to be identified in the information set to be identified with the corresponding information analysis unit to be matched.
7. The method of claim 1, further comprising: and transmitting the information analysis result corresponding to the target image as a first image to be transmitted.
8. An information analysis apparatus based on image recognition, the apparatus comprising:
the image identification module is used for identifying dynamic information and static information in the target image; clustering the dynamic information and the static information in the target image to obtain an information set to be identified;
the information matching module is used for matching each piece of information to be identified in the information set to be identified with a pre-stored information analysis unit set to obtain a target information analysis unit meeting matching conditions, the information analysis unit set comprises at least one unit list, each unit list comprises at least one information analysis unit, and each unit list corresponds to one piece of reference information;
and the result determining module is used for determining an information analysis result corresponding to the target image according to the reference information corresponding to the unit list to which the target information analysis unit belongs.
9. A computer device comprising a processor and a memory in communication with each other, the processor being configured to retrieve a computer program from the memory and to implement the method of any one of claims 1 to 7 by running the computer program.
10. A computer-readable storage medium, on which a computer program is stored which, when executed, implements the method of any of claims 1-7.
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| CN202011429132.8A CN112434651A (en) | 2020-12-09 | 2020-12-09 | Information analysis method and device based on image recognition and computer equipment |
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| CN202011429132.8A CN112434651A (en) | 2020-12-09 | 2020-12-09 | Information analysis method and device based on image recognition and computer equipment |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113159246A (en) * | 2021-04-15 | 2021-07-23 | 中物(北京)物流信息服务有限公司 | Steel mill cargo identification method and device based on two-dimensional code label and computer equipment |
| CN115048068A (en) * | 2022-05-25 | 2022-09-13 | 中仪英斯泰克进出口有限公司 | 4KLED display screen image display control system |
-
2020
- 2020-12-09 CN CN202011429132.8A patent/CN112434651A/en not_active Withdrawn
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113159246A (en) * | 2021-04-15 | 2021-07-23 | 中物(北京)物流信息服务有限公司 | Steel mill cargo identification method and device based on two-dimensional code label and computer equipment |
| CN115048068A (en) * | 2022-05-25 | 2022-09-13 | 中仪英斯泰克进出口有限公司 | 4KLED display screen image display control system |
| CN115048068B (en) * | 2022-05-25 | 2023-06-23 | 中仪英斯泰克进出口有限公司 | 4KLED display screen image display control system |
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