CN113568934A - Data query method and device, electronic equipment and storage medium - Google Patents

Data query method and device, electronic equipment and storage medium Download PDF

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CN113568934A
CN113568934A CN202110855841.0A CN202110855841A CN113568934A CN 113568934 A CN113568934 A CN 113568934A CN 202110855841 A CN202110855841 A CN 202110855841A CN 113568934 A CN113568934 A CN 113568934A
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image
user
target
feature information
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CN113568934B (en
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王晓澍
刘聃
蔡浩
李靖阳
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Ping An Bank Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2455—Query execution
    • G06F16/24553—Query execution of query operations
    • 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
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • 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
    • G06F21/604—Tools and structures for managing or administering access control systems
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The application relates to data processing and discloses a data query method, a data query device, electronic equipment and a storage medium, wherein the method comprises the following steps: responding to the triggering operation of the first button, and acquiring a face image of the user; when the identity information of the user passes the verification according to the human face image, acquiring target archive information according to the identity information of the user; displaying first information in the target file information and second information after fuzzy processing on a file information display interface; responding to the triggering operation of the second button, and displaying a permission verification interface, wherein the permission verification interface comprises a permission verification input area; responding to the input operation of the authority verification input area, and acquiring information to be verified; and when the information to be verified passes the verification, performing deblurring operation on the second information after the blurring processing so as to display the second information on the archive information display interface. By implementing the embodiment of the application, the efficiency of file query is improved.

Description

Data query method and device, electronic equipment and storage medium
Technical Field
The present application relates to the field of computer technologies, and in particular, to a data query method and apparatus, an electronic device, and a storage medium.
Background
At present, many enterprises or institutions use intelligent file cabinets to store important documents. It can be understood that the intelligent file cabinet is a novel intelligent file storage device which combines Radio Frequency Identification (RFID) technology with an intelligent file management system, realizes functions of file authority management, positioning management, intelligent access, intelligent checking, online monitoring and the like, and simultaneously performs standardized, intelligent and automatic management on file documents. However, if the user needs to refer to the archive, an offline reference is still required. Therefore, the user needs to reach the archive administration department for archive review with time and labor. This way of looking up the file is inefficient.
Disclosure of Invention
The embodiment of the application provides a data query method and device, electronic equipment and a storage medium, and improves the file query efficiency.
The first aspect of the present application provides a data query method, including:
displaying a file information query interface, wherein a first button is displayed on the file information query interface;
responding to the triggering operation of the first button, and acquiring a face image of a user;
when the identity information of the user passes the verification according to the human face image, acquiring target archive information according to the identity information of the user;
displaying first information and second information after fuzzy processing in the target file information on a file information display interface, wherein the importance degree value of the first information is lower than that of the second information, and a second button is displayed on the file information display interface;
responding to the triggering operation of the second button, and displaying an authority verification interface, wherein the authority verification interface comprises authority verification prompt information and an authority verification input area, the authority verification prompt information is used for indicating to-be-verified information to be input in the authority verification input area, and the to-be-verified information is information to be verified when the user uses other application programs;
responding to the input operation of the authority verification input area, and acquiring the information to be verified;
and when the information to be verified passes the verification, performing deblurring operation on the blurred second information so as to display the second information on the archive information display interface.
In a second aspect, the present application provides a data query device, which comprises a display module and an acquisition module,
the display module is used for displaying a file information query interface, and a first button is displayed on the file information query interface;
the acquisition module is used for responding to the triggering operation of the first button and acquiring a face image of a user; when the identity information of the user passes the verification according to the human face image, acquiring target archive information according to the identity information of the user;
the display module is used for displaying first information and second information after fuzzy processing in the target file information on a file information display interface, wherein the importance degree value of the first information is lower than that of the second information, and a second button is displayed on the file information display interface; responding to the triggering operation of the second button, and displaying an authority verification interface, wherein the authority verification interface comprises authority verification prompt information and an authority verification input area, the authority verification prompt information is used for indicating to-be-verified information to be input in the authority verification input area, and the to-be-verified information is information to be verified when the user uses other application programs;
the acquisition module is used for responding to the input operation of the authority verification input area and acquiring the information to be verified;
and the display module is used for performing fuzzy resolving operation on the fuzzy processed second information when the information to be verified passes the verification so as to display the second information on the archive information display interface.
A third aspect of the present application provides a data querying electronic device comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and are generated as instructions to be executed by the processor to perform the steps of any of the methods of a data querying method.
A fourth aspect of the present application provides a computer-readable storage medium for storing a computer program, the stored computer program being executed by the processor to implement the method of any one of the data query methods.
It can be seen that, in the above technical scheme, a file information query interface can be displayed, the file information query interface displays a first button, so that a face image of a user can be acquired in response to a triggering operation of the user on the first button, and when the user identity information is verified according to the face image, target file information is acquired according to the user identity information, and further first information and second information after fuzzy processing in the target file information can be displayed on a file information display interface, wherein the importance degree value of the first information is lower than that of the second information, so that information with low importance degree is preferentially displayed when the user identity information is verified, and information with high importance degree is hidden. The information display method and the information display device realize selective display and non-display according to the importance degree of the information, thereby improving the safety of the information. Furthermore, the file information display interface is provided with a second button, so that when responding to the triggering operation of the user on the second button, the authority verification interface is displayed, the authority verification interface comprises authority verification prompt information and an authority verification input area, the authority verification prompt information is used for indicating the information to be verified input by the user in the authority verification input area, the information to be verified is the information to be verified when the user uses other application programs, when responding to the input operation of the user on the authority verification input area, the information to be verified is obtained, so that when the information to be verified passes the verification, the fuzzy operation can be performed on the second information after fuzzy processing, the second information is displayed on the file information display interface, namely the user can refer to the information with high importance degree only when the identity verification passes twice, and the risk that the information with high importance degree is leaked is avoided, the safety of the information is improved. Meanwhile, the information to be verified is the information to be verified when the same user uses other application programs, the possibility that other people forge the verification information is reduced, and the safety of the information is improved. In addition, the remote file information query is realized, and the file query efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Wherein:
FIG. 1 is a schematic diagram of a data query system provided by an embodiment of the present application;
FIG. 2 is a schematic flow chart of a data query method provided in an embodiment of the present application;
fig. 3 is a schematic diagram of an archive information query interface according to an embodiment of the present application;
FIG. 4 is a schematic flowchart of another data query method provided in an embodiment of the present application;
FIG. 5 is a schematic diagram of a data query device according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device in a hardware operating environment according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The following are detailed below.
The terms "first" and "second" in the description and claims of the present application and the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Referring first to fig. 1, fig. 1 is a schematic diagram of a data query system according to an embodiment of the present application, and a data query system 100 installed in a target file cabinet may include a data query device 110. The data query device 110 is used for processing and storing the target archive information. The data query system 100 may include an integrated single device or multiple devices, and for convenience of description, the data query system 100 is referred to as an electronic device. It will be apparent that the electronic device may include various handheld devices, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to a wireless modem having wireless communication capability, as well as various forms of User Equipment (UE), Mobile Stations (MS), terminal Equipment (terminal device), and the like.
Referring to fig. 2, fig. 2 is a schematic flowchart of a data query method provided in an embodiment of the present application. The data query method can be applied to an electronic device, as shown in fig. 2, and the method includes:
201. and displaying a file information query interface, wherein a first button is displayed on the file information query interface.
For example, referring to fig. 3, fig. 3 is a schematic diagram of an archive information query interface provided in an embodiment of the present application. As shown in fig. 3, it can be seen that a first button is displayed on the archive information query interface, and a user can click the first button to call out the camera to obtain a face image of the user. It can be understood that, in the present application, the archive information query interface further displays archive information query prompt information, and the archive information query prompt information is used for prompting the archive information query mode, for example, the archive information query prompt information is: please click the lower button to query the file information.
202. And acquiring a face image of the user in response to the triggering operation of the first button.
Optionally, step 202 may include: acquiring video data including a face of a user in response to a trigger operation on a first button; analyzing the video data to obtain a plurality of image frames; performing quality detection on each image frame in the plurality of image frames to obtain a quality detection result corresponding to each image frame; acquiring N image frames with quality detection results sequentially larger than or equal to N thresholds from the plurality of image frames at preset time intervals, wherein N is an integer larger than 1; performing living body detection on the face included in each image frame in the N image frames; the image frame through which the living body detection passes is determined as a face image.
Optionally, the performing quality detection on each image frame of the multiple image frames to obtain a quality detection result corresponding to each image frame includes: and inputting each image frame in the plurality of image frames into the quality detection model to obtain a quality detection result corresponding to each image frame. The quality detection model may be trained using a neural network framework, for example.
The preset time may be set by an administrator or configured in a configuration file, which is not limited herein. The preset time may be, for example, 4 seconds or other time, which is not limited herein.
Optionally, the difference between adjacent thresholds in the N thresholds is different or the same, and is not limited herein. Wherein, the difference between adjacent thresholds in the N thresholds is different, which can be understood as: each of the N thresholds may present an increasing state, without limitation.
For example, the N thresholds may include a first threshold, a second threshold, and a third threshold, and a difference between the second threshold and the first threshold may be different from or the same as a difference between the third threshold and the second threshold. The difference between the second threshold and the first threshold is different from the difference between the third threshold and the second threshold, which can be understood as: the difference between the second threshold and the first threshold may be less than the difference between the third threshold and the second threshold.
It can be seen that, in the above technical solution, by responding to the trigger operation of the user on the first button, the video data including the face of the user is acquired, so that the video data can be analyzed to obtain a plurality of image frames, and then quality detection is performed on each image frame in the plurality of image frames to obtain a quality detection result corresponding to each image frame, and N image frames with quality detection results sequentially greater than or equal to N thresholds are acquired from the plurality of image frames at intervals of preset time, thereby avoiding a situation that live body detection fails due to an excessive quality difference of the image frames, and also avoiding that the acquired image frames are continuous image frames. In addition, the living body detection is carried out on the face included in each image frame in the N image frames, and the image frame passing the living body detection is determined to be the face image, so that the face from a non-living body is prevented from existing in the face image, and the information safety is improved.
Optionally, the performing living body detection on the face included in each image frame of the N image frames includes: acquiring feature information corresponding to each image frame in N image frames, and acquiring first feature information and second feature information, wherein the first feature information is fusion feature information of at least two types of feature information corresponding to a positive sample set, the second feature information is fusion feature information of at least two types of feature information corresponding to a negative sample set, a face image in the positive sample set comprises a living body face, a face image in the negative sample set comprises a non-living body face, and the at least two types of feature information comprise depth information of the face and optical flow information of the face; and according to the first characteristic information and the second characteristic information, performing living body detection on the characteristic information corresponding to each image frame in the N image frames.
The face images in the positive sample set and the face images in the negative sample set are both face images under different environmental light brightness.
It can be seen that, in the above technical solution, by acquiring feature information corresponding to each image frame in N image frames and acquiring first feature information and second feature information, where the first feature information is fusion feature information of at least two types of feature information corresponding to a positive sample set, and the second feature information is fusion feature information of at least two types of feature information corresponding to a negative sample set, a face image in the positive sample set includes a living human face, a face image in the negative sample set includes a non-living human face, and the at least two types of feature information include depth information of the human face and optical flow information of the human face, the feature information corresponding to each image frame in the N image frames is subjected to living body detection according to the first feature information and the second feature information, thereby improving accuracy of the living body detection.
Optionally, performing living body detection on feature information corresponding to each image frame in the N image frames according to the first feature information and the second feature information, including: determining the distance between the first characteristic information and the characteristic information corresponding to each image frame in the N image frames; determining the distance between the second characteristic information and the characteristic information corresponding to each image frame in the N image frames; performing living body detection on the feature information corresponding to each image frame in the N image frames according to the difference between the distance between the first feature information and the feature information corresponding to each image frame in the N image frames and a preset first distance, and the difference between the distance between the second feature information and the feature information corresponding to each image frame in the N image frames and a preset second distance; the preset first distance is different from the preset second distance.
Optionally, the preset first distance may be smaller than the preset second distance.
Optionally, determining a distance between the first feature information and feature information corresponding to each of the N image frames may include: determining the distance between the first characteristic information and the characteristic information corresponding to each image frame in the N image frames by adopting the Euclidean distance; determining a distance between the second feature information and feature information corresponding to each of the N image frames may include: and determining the distance between the second characteristic information and the characteristic information corresponding to each image frame in the N image frames by adopting the Euclidean distance.
Optionally, the N image frames include a first image frame, and if a difference between a distance between the first feature information and feature information corresponding to the first image frame and a preset first distance is less than or equal to a difference between a distance between the second feature information and feature information corresponding to the first image frame and a preset second distance, the face in the first image frame is a live face; if the difference value between the distance between the first characteristic information and the characteristic information corresponding to the first image frame and the preset first distance is larger than the difference value between the distance between the second characteristic information and the characteristic information corresponding to the first image frame and the preset second distance, the face in the first image frame is a non-living body face.
According to the technical scheme, the living body detection is performed on the feature information corresponding to each image frame in the N image frames according to the difference value between the distance between the first feature information and the feature information corresponding to each image frame in the N image frames and the preset first distance, and the difference value between the distance between the second feature information and the feature information corresponding to each image frame in the N image frames and the preset second distance, so that the accuracy of the living body detection is improved.
203. And when the identity information of the user passes the verification according to the human face image, acquiring target archive information according to the identity information of the user.
Wherein the target profile information may include one or more of: name, gender, age, year and month of birth, contact information, identification number, student status information, political face information, etc., without limitation.
Optionally, before obtaining the target profile information according to the identity information of the user, the method further includes: acquiring an image to be input, wherein the image to be input comprises archive information to be input, and the archive information to be input is recorded in the image to be input in a form; performing semantic segmentation on an image to be recorded to obtain a plurality of mask images, wherein the plurality of mask images correspond to a plurality of preset segmentation categories one to one, the plurality of preset segmentation categories comprise horizontal lines, vertical lines and oblique lines, and each mask image is used for indicating the probability that each pixel point in the image to be recorded belongs to the preset segmentation category corresponding to each mask image; determining a target connected domain of each mask image according to each mask image, wherein the target connected domain is the probability of the composition of pixel points which belong to preset segmentation categories corresponding to each mask image in each mask image and have the probability greater than a threshold value; determining target archive information according to the target connected domain of each mask map; storing the target archive information to a database; acquiring target archive information according to the identity information of the user, comprising the following steps: and acquiring target archive information from a database according to the identity information of the user.
The image to be recorded can be obtained by shooting a paper archive or by performing PDF scanning on the paper archive.
It can be seen that, in the technical scheme, the paper archives are electronized through the images to be recorded.
Optionally, determining target archive information according to the target connected domain of each mask map includes: fitting the target connected domain in each mask image to obtain horizontal lines, vertical lines and oblique lines in the image to be recorded; drawing horizontal lines, vertical lines and oblique lines in the image to be recorded to obtain a plurality of cells in the image to be recorded; identifying pixel points in each cell to obtain a first type cell and a second type cell in the plurality of cells, wherein the content in the first type cell is a text, and the content in the second type cell is an image; identifying the content in the first type of cell to obtain a text in the first type of cell; intercepting the content in the second type of cell to obtain an image in the second type of cell; and determining target archival information according to the text in the first type of cells and the image in the second type of cells.
Identifying the content in the first type of cell to obtain the text in the first type of cell may include: identifying the content in the first type of cell by adopting an ORC technology to obtain a text in the first type of cell; intercepting the content in the cell of the second type to obtain the image in the cell of the second type, which may include: and intercepting the content in the second type of cell by adopting an ROI technology to obtain an image in the second type of cell.
According to the technical scheme, the paper file is electronized.
Optionally, storing the target archive information in a database includes: determining the file type of the target file information, the file person information of the target file information and the historical query record according to the target file information; determining the heat value of the target file information according to the file type of the target file information; acquiring historical business information of a file person according to file person information contained in the target file information; predicting the possibility that the target archive information is inquired again according to the historical business information of the archives and the historical inquiry record of the target archive information to obtain the access frequency corresponding to the target archive information; and storing the target archive information into a database according to the access frequency corresponding to the target archive information.
The archival information is the person to whom the information recorded in the target archival information belongs.
Optionally, determining a profile type to which the target profile information belongs, profile person information of the target profile information, and a history query record according to the target profile information, includes: determining keywords contained in the target archive information and business information related to the target archive information according to the archive information of the target archive information; determining archival information and historical query records of the target archival information according to keywords contained in the target archival information; and determining the file type of the target file information according to the keywords contained in the target file information and the service information related to the target file information.
Optionally, predicting the possibility that the target profile information is queried again according to the historical service information of the profile person and the historical query record of the target profile information to obtain the access frequency corresponding to the target profile information, where the method includes: determining the transaction progress of the recently transacted business of the archives according to the historical business information of the archives; determining the total query times of the target file information in the corresponding service according to the historical query record of the target file information; and predicting the possibility that the target archive information is inquired again according to the business handling progress corresponding to the target archive information and the total inquiry times of the target archive information in the corresponding business to obtain the access frequency corresponding to the target archive information.
The access frequency corresponding to the target archive information can be represented by the following formula:
Figure BDA0003184142700000081
wherein g represents the access frequency corresponding to the target archive information, and a represents the archive type to which the target archive information belongs; b represents the transaction progress of the recently transacted business of the archives of the target archive information; f. ofa，b(i) The number of events for calling the files again under the condition that the files of the type a are in the progress b is represented; f. ofa，bRepresents the total number of events for a type a profile in the case of progress b; h isaRepresenting the total query times of the target file information in the service; p is a radical ofaRepresenting the average query times of the archives of the type a in the service; k is constant, in order to prevent fa，bIs 0, and usually 1 is desirable.
Optionally, storing the target archive information in a database according to the access frequency corresponding to the target archive information, includes: if the access frequency corresponding to the target archive information is higher than the threshold value, storing the target archive information into a first storage area of a database; and if the access frequency corresponding to the target archive information is less than or equal to the threshold value, compressing the target archive information and storing the compressed target archive information in a second storage area of the database.
It can be seen that, in the above technical solution, the target archive information is stored in the database according to the access frequency corresponding to the target archive information, that is, the archive information is differentially stored according to the access frequency.
Optionally, before obtaining the target profile information from the database according to the identity information of the user, the method further includes: acquiring attribute information of a user according to the face image; filtering the characteristic information included in the database according to the attribute information of the user; and verifying the identity information of the user according to the feature information corresponding to the face image and the feature information included in the filtered database.
The attribute information of the user may include, for example, age, gender, and the like, which is not limited herein.
It can be seen that, in the above technical solution, the attribute information of the user is obtained according to the face image, and the feature information included in the database is filtered according to the attribute information of the user, so that the feature information different from the attribute information of the user in the database is filtered, and the retrieval efficiency of retrieving the feature information is improved. In addition, the identity information of the user is verified according to the feature information corresponding to the face image and the feature information included in the filtered database, so that the verification of the identity information of the user is realized.
204. And displaying first information and second information after fuzzy processing in the target file information on a file information display interface, wherein the importance degree value of the first information is lower than that of the second information, and a second button is displayed on the file information display interface.
Wherein, the first information may include, for example, one or more of the following: name, gender, age, year of birth, etc., without limitation.
Wherein, the second information may comprise one or more of the following items: contact information, identification number, student status information, political aspect information, etc., without limitation.
205. And responding to the triggering operation of the second button, and displaying an authority verification interface, wherein the authority verification interface comprises authority verification prompt information and an authority verification input area, the authority verification prompt information is used for indicating to-be-verified information to be input in the authority verification input area, and the to-be-verified information is information to be verified when the user uses other application programs.
The number of other applications may be one or more, and is not limited herein. The other application programs may be, for example, an application program with a navigation function, an application program with a specific instant messaging function, an application program with a shopping function, and the like, which is not limited herein.
The information to be verified may be, for example: an account used for logging in another application, an identifier of a device used for browsing another application, and the like, which are not limited herein.
206. And responding to the input operation of the authority verification input area, and acquiring the information to be verified.
207. And when the information to be verified passes the verification, performing deblurring operation on the second information after the blurring processing so as to display the second information on the archive information display interface.
It can be seen that, in the above technical scheme, a file information query interface can be displayed, the file information query interface displays a first button, so that a face image of a user can be acquired in response to a triggering operation of the user on the first button, and when the user identity information is verified according to the face image, target file information is acquired according to the user identity information, and further first information and second information after fuzzy processing in the target file information can be displayed on a file information display interface, wherein the importance degree value of the first information is lower than that of the second information, so that information with low importance degree is preferentially displayed when the user identity information is verified, and information with high importance degree is hidden. The information display method and the information display device realize selective display and non-display according to the importance degree of the information, thereby improving the safety of the information. Furthermore, the file information display interface is provided with a second button, so that when responding to the triggering operation of the user on the second button, the authority verification interface is displayed, the authority verification interface comprises authority verification prompt information and an authority verification input area, the authority verification prompt information is used for indicating the information to be verified input by the user in the authority verification input area, the information to be verified is the information to be verified when the user uses other application programs, when responding to the input operation of the user on the authority verification input area, the information to be verified is obtained, so that when the information to be verified passes the verification, the fuzzy operation can be performed on the second information after fuzzy processing, the second information is displayed on the file information display interface, namely the user can refer to the information with high importance degree only when the identity verification passes twice, and the risk that the information with high importance degree is leaked is avoided, the safety of the information is improved. Meanwhile, the information to be verified is the information to be verified when the same user uses other application programs, the possibility that other people forge the verification information is reduced, and the safety of the information is improved. In addition, the remote file information query is realized, and the file query efficiency is improved.
Referring to fig. 4, fig. 4 is a schematic flowchart of another data query method provided in an embodiment of the present application. The data query method can be applied to an electronic device, as shown in fig. 4, and the method includes:
401. and displaying a file information query interface, wherein a first button is displayed on the file information query interface.
Step 401 may refer to step 201 in fig. 2, which is not described herein again.
402. In response to a trigger operation on the first button, video data including a face of a user is acquired.
403. And analyzing the video data to obtain a plurality of image frames.
404. And performing quality detection on each image frame in the plurality of image frames to obtain a quality detection result corresponding to each image frame.
Optionally, the performing quality detection on each image frame of the multiple image frames to obtain a quality detection result corresponding to each image frame includes: and inputting each image frame in the plurality of image frames into the quality detection model to obtain a quality detection result corresponding to each image frame. The quality detection model may be trained using a neural network framework, for example.
405. Acquiring N image frames with quality detection results sequentially larger than or equal to N thresholds from the plurality of image frames at preset time intervals, wherein N is an integer larger than 1.
The preset time may be set by an administrator or configured in a configuration file, which is not limited herein. The preset time may be, for example, 4 seconds or other time, which is not limited herein.
Optionally, the difference between adjacent thresholds in the N thresholds is different or the same, and is not limited herein. Wherein, the difference between adjacent thresholds in the N thresholds is different, which can be understood as: each of the N thresholds may present an increasing state, without limitation.
For example, the N thresholds may include a first threshold, a second threshold, and a third threshold, and a difference between the second threshold and the first threshold may be different from or the same as a difference between the third threshold and the second threshold. The difference between the second threshold and the first threshold is different from the difference between the third threshold and the second threshold, which can be understood as: the difference between the second threshold and the first threshold may be less than the difference between the third threshold and the second threshold.
406. And performing living body detection on the human face included in each image frame in the N image frames.
Optionally, the performing living body detection on the face included in each image frame of the N image frames includes: acquiring feature information corresponding to each image frame in N image frames, and acquiring first feature information and second feature information, wherein the first feature information is fusion feature information of at least two types of feature information corresponding to a positive sample set, the second feature information is fusion feature information of at least two types of feature information corresponding to a negative sample set, a face image in the positive sample set comprises a living body face, a face image in the negative sample set comprises a non-living body face, and the at least two types of feature information comprise depth information of the face and optical flow information of the face; and according to the first characteristic information and the second characteristic information, performing living body detection on the characteristic information corresponding to each image frame in the N image frames.
The face images in the positive sample set and the face images in the negative sample set are both face images under different environmental light brightness.
It can be seen that, in the above technical solution, by acquiring feature information corresponding to each image frame in N image frames and acquiring first feature information and second feature information, where the first feature information is fusion feature information of at least two types of feature information corresponding to a positive sample set, and the second feature information is fusion feature information of at least two types of feature information corresponding to a negative sample set, a face image in the positive sample set includes a living human face, a face image in the negative sample set includes a non-living human face, and the at least two types of feature information include depth information of the human face and optical flow information of the human face, the feature information corresponding to each image frame in the N image frames is subjected to living body detection according to the first feature information and the second feature information, thereby improving accuracy of the living body detection.
Optionally, performing living body detection on feature information corresponding to each image frame in the N image frames according to the first feature information and the second feature information, including: determining the distance between the first characteristic information and the characteristic information corresponding to each image frame in the N image frames; determining the distance between the second characteristic information and the characteristic information corresponding to each image frame in the N image frames; performing living body detection on the feature information corresponding to each image frame in the N image frames according to the difference between the distance between the first feature information and the feature information corresponding to each image frame in the N image frames and a preset first distance, and the difference between the distance between the second feature information and the feature information corresponding to each image frame in the N image frames and a preset second distance; the preset first distance is different from the preset second distance.
Optionally, the preset first distance may be smaller than the preset second distance.
Optionally, determining a distance between the first feature information and feature information corresponding to each of the N image frames may include: determining the distance between the first characteristic information and the characteristic information corresponding to each image frame in the N image frames by adopting the Euclidean distance; determining a distance between the second feature information and feature information corresponding to each of the N image frames may include: and determining the distance between the second characteristic information and the characteristic information corresponding to each image frame in the N image frames by adopting the Euclidean distance.
Optionally, the N image frames include a first image frame, and if a difference between a distance between the first feature information and feature information corresponding to the first image frame and a preset first distance is less than or equal to a difference between a distance between the second feature information and feature information corresponding to the first image frame and a preset second distance, the face in the first image frame is a live face; if the difference value between the distance between the first characteristic information and the characteristic information corresponding to the first image frame and the preset first distance is larger than the difference value between the distance between the second characteristic information and the characteristic information corresponding to the first image frame and the preset second distance, the face in the first image frame is a non-living body face.
According to the technical scheme, the living body detection is performed on the feature information corresponding to each image frame in the N image frames according to the difference value between the distance between the first feature information and the feature information corresponding to each image frame in the N image frames and the preset first distance, and the difference value between the distance between the second feature information and the feature information corresponding to each image frame in the N image frames and the preset second distance, so that the accuracy of the living body detection is improved.
407. The image frame through which the living body detection passes is determined as a face image.
408. And when the identity information of the user passes the verification according to the human face image, acquiring target archive information according to the identity information of the user.
Step 408 may refer to step 203 in fig. 2, which is not described herein again.
409. And displaying first information and second information after fuzzy processing in the target file information on a file information display interface, wherein the importance degree value of the first information is lower than that of the second information, and a second button is displayed on the file information display interface.
Step 409 may refer to step 204 in fig. 2, which is not described herein.
410. And responding to the triggering operation of the second button, and displaying an authority verification interface, wherein the authority verification interface comprises authority verification prompt information and an authority verification input area, the authority verification prompt information is used for indicating to-be-verified information to be input in the authority verification input area, and the to-be-verified information is information to be verified when the user uses other application programs.
Step 410 may refer to step 205 in fig. 2, which is not described herein again.
411. And responding to the input operation of the authority verification input area, and acquiring the information to be verified.
Step 411 may refer to step 206 in fig. 2, and is not described herein again.
412. And when the information to be verified passes the verification, performing deblurring operation on the second information after the blurring processing so as to display the second information on the archive information display interface.
Step 412 may refer to step 207 in fig. 2, which is not described herein again.
Therefore, in the technical scheme, the situation that the live body detection is not passed due to the over-poor quality of the image frames is avoided, and the acquired image frames are also avoided to be continuous image frames. In addition, the living body detection is carried out on the face included in each image frame in the N image frames, the image frame passing the living body detection is determined to be the face image, the face from a non-living body is prevented from existing in the face image, the information safety is improved, the information with low importance degree is preferentially displayed when the identity information of the user passes the verification, and the information with high importance degree is hidden. The information display method and the information display device realize selective display and non-display according to the importance degree of the information, thereby improving the safety of the information. Furthermore, when the information to be verified passes the verification, the fuzzy operation is performed on the second information after the fuzzy processing, so that the second information is displayed on the archive information display interface, namely, the user can look up the information with high importance degree when the two times of identity verification passes, the risk that the information with high importance degree is leaked is avoided, and the safety of the information is improved. Meanwhile, the information to be verified is the information to be verified when the same user uses other application programs, the possibility that other people forge the verification information is reduced, and the safety of the information is improved. In addition, the remote file information query is realized, and the file query efficiency is improved.
Referring to fig. 5, fig. 5 is a schematic diagram of a data query apparatus according to an embodiment of the present application. As shown in fig. 5, a data query apparatus 500 provided in an embodiment of the present application includes a display module 501, an obtaining module 502,
the display module 501 is configured to display a file information query interface, where the file information query interface displays a first button;
an obtaining module 502, configured to obtain a face image of a user in response to a trigger operation on a first button; when the identity information of the user passes the verification according to the human face image, target archive information is obtained according to the identity information of the user;
the display module 501 is configured to display first information and second information after the fuzzy processing in the target archive information on an archive information display interface, where an importance level value of the first information is lower than an importance level value of the second information, and a second button is displayed on the archive information display interface; responding to the triggering operation of the second button, and displaying an authority verification interface, wherein the authority verification interface comprises authority verification prompt information and an authority verification input area, the authority verification prompt information is used for indicating to-be-verified information to be input in the authority verification input area, and the to-be-verified information is information to be verified when a user uses other application programs;
an obtaining module 502, configured to obtain information to be verified in response to an input operation to an authority verification input area;
and the display module 501 is configured to perform a deblurring operation on the blurred second information when the information to be verified passes the verification, so as to display the second information on the archive information display interface.
Optionally, when the face image of the user is acquired in response to the triggering operation of the first button, the acquiring module 502 is configured to acquire video data including a face of the user in response to the triggering operation of the first button; analyzing the video data to obtain a plurality of image frames; performing quality detection on each image frame in the plurality of image frames to obtain a quality detection result corresponding to each image frame; acquiring N image frames with quality detection results sequentially larger than or equal to N thresholds from the plurality of image frames at preset time intervals, wherein N is an integer larger than 1; performing living body detection on the face included in each image frame in the N image frames; the image frame through which the living body detection passes is determined as a face image.
Optionally, when a face included in each of the N image frames is subjected to live body detection, the obtaining module 502 is configured to obtain feature information corresponding to each of the N image frames, and obtain first feature information and second feature information, where the first feature information is fusion feature information of at least two types of feature information corresponding to a positive sample set, the second feature information is fusion feature information of at least two types of feature information corresponding to a negative sample set, a face image in the positive sample set includes a live body face, a face image in the negative sample set includes a non-live body face, and the at least two types of feature information include depth information of the face and optical flow information of the face; and according to the first characteristic information and the second characteristic information, performing living body detection on the characteristic information corresponding to each image frame in the N image frames.
Optionally, when the living body detection is performed on the feature information corresponding to each image frame in the N image frames according to the first feature information and the second feature information, the obtaining module 502 is configured to determine a distance between the first feature information and the feature information corresponding to each image frame in the N image frames; determining the distance between the second characteristic information and the characteristic information corresponding to each image frame in the N image frames; performing living body detection on the feature information corresponding to each image frame in the N image frames according to the difference between the distance between the first feature information and the feature information corresponding to each image frame in the N image frames and a preset first distance, and the difference between the distance between the second feature information and the feature information corresponding to each image frame in the N image frames and a preset second distance; the preset first distance is different from the preset second distance.
Optionally, when acquiring the target archive information according to the identity information of the user, the acquiring module 502 is configured to acquire an image to be entered, where the image to be entered includes the archive information to be entered, and the archive information to be entered is recorded in the image to be entered in a form; performing semantic segmentation on an image to be recorded to obtain a plurality of mask images, wherein the plurality of mask images correspond to a plurality of preset segmentation categories one to one, the plurality of preset segmentation categories comprise horizontal lines, vertical lines and oblique lines, and each mask image is used for indicating the probability that each pixel point in the image to be recorded belongs to the preset segmentation category corresponding to each mask image; determining a target connected domain of each mask image according to each mask image, wherein the target connected domain is the probability of the composition of pixel points which belong to preset segmentation categories corresponding to each mask image in each mask image and have the probability greater than a threshold value; determining target archive information according to the target connected domain of each mask map; storing the target archive information to a database; acquiring target archive information according to the identity information of the user, comprising the following steps: and acquiring target archive information from a database according to the identity information of the user.
Optionally, when determining the target archive information according to the target connected domain of each mask image, the obtaining module 502 is configured to fit the target connected domain in each mask image to obtain a horizontal line, a vertical line, and a diagonal line in the image to be recorded; drawing horizontal lines, vertical lines and oblique lines in the image to be recorded to obtain a plurality of cells in the image to be recorded; identifying pixel points in each cell to obtain a first type cell and a second type cell in the plurality of cells, wherein the content in the first type cell is a text, and the content in the second type cell is an image; identifying the content in the first type of cell to obtain a text in the first type of cell; intercepting the content in the second type of cell to obtain an image in the second type of cell; and determining target archival information according to the text in the first type of cells and the image in the second type of cells.
Optionally, when the target archive information is acquired from the database according to the identity information of the user, the acquiring module 502 is configured to acquire the attribute information of the user according to the face image; filtering the characteristic information included in the database according to the attribute information of the user; and verifying the identity information of the user according to the feature information corresponding to the face image and the feature information included in the filtered database.
Referring to fig. 6, fig. 6 is a schematic structural diagram of an electronic device in a hardware operating environment according to an embodiment of the present application.
Embodiments of the present application provide an electronic device for data query, comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor to perform instructions including steps in any of the data query methods. As shown in fig. 6, an electronic device of a hardware operating environment according to an embodiment of the present application may include:
a processor 601, such as a CPU.
The memory 602 may alternatively be a high speed RAM memory or a stable memory such as a disk memory.
A communication interface 603 for implementing connection communication between the processor 601 and the memory 602.
Those skilled in the art will appreciate that the configuration of the electronic device shown in fig. 6 is not intended to be limiting and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
As shown in fig. 6, the memory 602 may include an operating system, a network communication module, and one or more programs. An operating system is a program that manages and controls the server hardware and software resources, supporting the execution of one or more programs. The network communication module is used for communication among the components in the memory 602 and with other hardware and software in the electronic device.
In the electronic device shown in fig. 6, the processor 601 is configured to execute one or more programs in the memory 602, and implement the following steps:
displaying a file information query interface, wherein a first button is displayed on the file information query interface;
responding to the triggering operation of the first button, and acquiring a face image of the user;
when the identity information of the user passes the verification according to the human face image, acquiring target archive information according to the identity information of the user;
displaying first information and second information after fuzzy processing in target file information on a file information display interface, wherein the importance degree value of the first information is lower than that of the second information, and a second button is displayed on the file information display interface;
responding to the triggering operation of the second button, displaying an authority verification interface, wherein the authority verification interface comprises authority verification prompt information and an authority verification input area, the authority verification prompt information is used for indicating to-be-verified information to be input in the authority verification input area, and the to-be-verified information is information to be verified when a user uses other application programs;
responding to the input operation of the authority verification input area, and acquiring information to be verified;
and when the information to be verified passes the verification, performing deblurring operation on the second information after the blurring processing so as to display the second information on the archive information display interface.
For specific implementation of the electronic device related to the present application, reference may be made to various embodiments of the data query method, which are not described herein again.
The present application also provides a computer readable storage medium for storing a computer program, the stored computer program being executable by a processor to perform the steps of:
displaying a file information query interface, wherein a first button is displayed on the file information query interface;
responding to the triggering operation of the first button, and acquiring a face image of the user;
when the identity information of the user passes the verification according to the human face image, acquiring target archive information according to the identity information of the user;
displaying first information and second information after fuzzy processing in target file information on a file information display interface, wherein the importance degree value of the first information is lower than that of the second information, and a second button is displayed on the file information display interface;
responding to the triggering operation of the second button, displaying an authority verification interface, wherein the authority verification interface comprises authority verification prompt information and an authority verification input area, the authority verification prompt information is used for indicating to-be-verified information to be input in the authority verification input area, and the to-be-verified information is information to be verified when a user uses other application programs;
responding to the input operation of the authority verification input area, and acquiring information to be verified;
and when the information to be verified passes the verification, performing deblurring operation on the second information after the blurring processing so as to display the second information on the archive information display interface.
For specific implementation of the computer-readable storage medium related to the present application, reference may be made to the embodiments of the data query method, which are not described herein again.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art should understand that the present application is not limited by the order of acts described, as some steps may be performed in other orders or simultaneously according to the present application. Further, those skilled in the art should also appreciate that the embodiments described in this specification are preferred embodiments and that the acts and modules involved are not necessarily required for this application.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.

Claims (10)

1. A method for querying data, comprising:
displaying a file information query interface, wherein a first button is displayed on the file information query interface;
responding to the triggering operation of the first button, and acquiring a face image of a user;
when the identity information of the user passes the verification according to the human face image, acquiring target archive information according to the identity information of the user;
displaying first information and second information after fuzzy processing in the target file information on a file information display interface, wherein the importance degree value of the first information is lower than that of the second information, and a second button is displayed on the file information display interface;
responding to the triggering operation of the second button, and displaying an authority verification interface, wherein the authority verification interface comprises authority verification prompt information and an authority verification input area, the authority verification prompt information is used for indicating to-be-verified information to be input in the authority verification input area, and the to-be-verified information is information to be verified when the user uses other application programs;
responding to the input operation of the authority verification input area, and acquiring the information to be verified;
and when the information to be verified passes the verification, performing deblurring operation on the blurred second information so as to display the second information on the archive information display interface.
2. The method of claim 1, wherein the obtaining the face image of the user in response to the triggering operation of the first button comprises:
responding to the triggering operation of the first button, and acquiring video data comprising the face of the user;
analyzing the video data to obtain a plurality of image frames;
performing quality detection on each image frame in the plurality of image frames to obtain a quality detection result corresponding to each image frame;
acquiring N image frames with quality detection results sequentially larger than or equal to N thresholds from the plurality of image frames at intervals of preset time, wherein N is an integer larger than 1;
performing living body detection on the face included in each image frame in the N image frames;
and determining the image frame passing the living body detection as the face image.
3. The method according to claim 2, wherein the live body detection of the face included in each of the N image frames comprises:
acquiring feature information corresponding to each image frame in the N image frames, and acquiring first feature information and second feature information, wherein the first feature information is fusion feature information of at least two types of feature information corresponding to a positive sample set, the second feature information is fusion feature information of at least two types of feature information corresponding to a negative sample set, a face image in the positive sample set comprises a living face, a face image in the negative sample set comprises a non-living face, and the at least two types of feature information comprise depth information of the face and optical flow information of the face;
and according to the first characteristic information and the second characteristic information, performing living body detection on the characteristic information corresponding to each image frame in the N image frames.
4. The method according to claim 3, wherein the performing the living body detection on the feature information corresponding to each of the N image frames according to the first feature information and the second feature information comprises:
determining a distance between the first feature information and feature information corresponding to each of the N image frames;
determining a distance between the second feature information and feature information corresponding to each of the N image frames;
performing living body detection on the feature information corresponding to each image frame in the N image frames according to the difference between the distance between the first feature information and the feature information corresponding to each image frame in the N image frames and a preset first distance, and the difference between the distance between the second feature information and the feature information corresponding to each image frame in the N image frames and a preset second distance;
wherein the preset first distance is different from the preset second distance.
5. The method of claim 1, wherein prior to said obtaining target profile information based on identity information of said user, said method further comprises:
acquiring an image to be input, wherein the image to be input comprises archive information to be input, and the archive information to be input is recorded in the image to be input in a form of a table;
identifying the image to be recorded and performing semantic segmentation to obtain a plurality of mask images, wherein the plurality of mask images correspond to a plurality of preset segmentation categories one to one, the plurality of preset segmentation categories comprise horizontal lines, vertical lines and oblique lines, and each mask image is used for indicating the probability that each pixel point in the image to be recorded belongs to the preset segmentation category corresponding to each mask image;
determining a target connected domain of each mask map according to each mask map, wherein the target connected domain is the probability of the composition of pixel points which belong to preset segmentation categories corresponding to each mask map and have a probability greater than a threshold value in each mask map;
determining target archive information according to the target connected domain of each mask map;
storing the target archive information to a database;
the acquiring target archive information according to the identity information of the user comprises:
and acquiring the target archive information from the database according to the identity information of the user.
6. The method of claim 5, wherein determining target profile information from the target connected component of each mask map comprises:
fitting the target connected domain in each mask image to obtain a horizontal line, a vertical line and a diagonal line in the image to be recorded;
drawing horizontal lines, vertical lines and oblique lines in the image to be recorded to obtain a plurality of cells in the image to be recorded;
identifying pixel points in each cell to obtain a first type cell and a second type cell in the plurality of cells, wherein the content in the first type cell is a text, and the content in the second type cell is an image;
identifying the content in the first type of cell to obtain a text in the first type of cell;
intercepting the content in the second type of cell to obtain an image in the second type of cell;
and determining the target archive information according to the texts in the cells of the first type and the images in the cells of the second type.
7. The method of claim 5, wherein prior to said obtaining the target profile information from the database based on the identity information of the user, the method further comprises:
acquiring attribute information of the user according to the face image;
filtering the characteristic information included in the database according to the attribute information of the user;
and verifying the identity information of the user according to the feature information corresponding to the face image and the feature information included in the filtered database.
8. A data query device is characterized by comprising a display module and an acquisition module,
the display module is used for displaying a file information query interface, and the file information query interface is provided with a first button;
the acquisition module is used for responding to the triggering operation of the first button and acquiring a face image of a user; when the identity information of the user passes the verification according to the human face image, acquiring target archive information according to the identity information of the user;
the display module is used for displaying first information and fuzzy-processed second information in the target file information on a file information display interface, wherein the importance degree value of the first information is lower than that of the second information, and the file information display interface is provided with a second button for deblurring the fuzzy-processed second information; responding to the triggering operation of the second button, and displaying an authority verification interface, wherein the authority verification interface comprises authority verification prompt information and an authority verification input area, the authority verification prompt information is used for indicating to-be-verified information to be input in the authority verification input area, and the to-be-verified information is information to be verified when the user uses other application programs;
the acquisition module is used for responding to the input operation of the authority verification input area and acquiring the information to be verified;
and the display module is used for performing fuzzy resolving operation on the fuzzy processed second information when the information to be verified passes the verification so as to display the second information on the archive information display interface.
9. An electronic device for data querying, comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and are generated as instructions to be executed by the processor to perform the steps of the method of any of claims 1-7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium is used to store a computer program, which is executed by the processor, to implement the method of any of claims 1-7.
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