Image recognition method and device, electronic equipment and readable storage medium

Abstract

The disclosure provides an image recognition method and device, electronic equipment and readable storage medium, which can be applied to the technical fields of image recognition and financial technology. The method comprises: generating transaction evidence file information of a first transaction operation page according to operation information of the first transaction operation page; calling a non-interface browser interface, restoring a second transaction operation page corresponding to the transaction evidence file information according to the transaction evidence file information; generating a to-be-recognized transaction image corresponding to the second transaction operation page according to first attribute information of a preset transaction image, wherein the first attribute information of the to-be-recognized transaction image is consistent with the first attribute information of the preset transaction image; using an image recognition algorithm to match second attribute information of the to-be-recognized transaction image with second attribute information of the preset transaction image to obtain a matching result; and in the case that the matching result is consistent, determining the to-be-recognized transaction image as a target transaction image.

Description

Image recognition methods, devices, electronic devices and readable storage media Technical Field

[0001] This disclosure relates to the fields of image recognition and financial technology, and in particular to an image recognition method, apparatus, electronic device, readable storage medium, and program product. Background Technology

[0002] With the development of digital finance, when a user conducts a transaction through a financial application involving currency trading, related risk assessment, and signing of account opening and closing agreements, the product of these operations can be understood as a digital contract, stored in the transaction system in the form of structured data. However, what customers and relevant business personnel need are visual credentials presented in image form, serving as evidence or documentation of key operational scenarios at the time of the transaction, for easy retrieval and review.

[0003] Traditional visual vouchers can be implemented using two methods: one is to use a program component that can generate images, taking an image template and scene data as input, and outputting an image file. This method requires designing image templates and writing corresponding programs for each business scenario, incurring additional development costs, and cannot be used as electronic vouchers for visual transaction operations.

[0004] Secondly, based on business scenarios, the client identifies key transaction operations requiring credential retention. When a customer executes a transaction using the client, a screenshot function is triggered in the client program to record the customer's current screen display information and output it as an image file. This image is then uploaded to the system server for archiving. However, this method outputs images that are tied to the client's runtime environment, making it impossible to obtain screenshot files with consistent size and display style. Furthermore, storing a large number of image files consumes significant data storage space. Therefore, this method relies on the client to pre-set screenshots for each transaction operation, and the method automatically identifies key transaction scenarios. Summary of the Invention

[0005] In view of the above problems, this disclosure provides an image recognition method, apparatus, electronic device, readable storage medium, and program product.

[0006] According to one aspect of this disclosure, an image recognition method is provided, comprising: generating transaction evidence file information of a first transaction operation page based on operation information of a first transaction operation page; calling a headless browser interface to reconstruct a second transaction operation page corresponding to the transaction evidence file information based on the transaction evidence file information; generating a transaction image to be recognized corresponding to the second transaction operation page based on first attribute information of a preset transaction image, wherein the first attribute information of the transaction image to be recognized is consistent with the first attribute information of the preset transaction image; using an image recognition algorithm to match the second attribute information of the transaction image to be recognized with the second attribute information of the preset transaction image to obtain a matching result; and determining the transaction image to be recognized as the target transaction image if the matching result is consistent.

[0007] According to embodiments of this disclosure, the operation information includes operation page identification information and transaction attribute information.

[0008] According to an embodiment of this disclosure, generating transaction evidence file information for the transaction operation page based on the operation information of the first transaction operation page includes: calling an application service component to generate transaction evidence file information for the transaction operation page based on the operation page identifier information and transaction attribute information.

[0009] According to an embodiment of this disclosure, generating a transaction image to be identified corresponding to a second transaction operation page based on the first attribute information of a preset transaction image includes: calling a headless browser interface to obtain the first attribute information of the preset transaction image; and performing a screenshot operation on the second transaction operation page based on the first attribute information of the preset transaction image to obtain the transaction image to be identified corresponding to the transaction operation page.

[0010] According to embodiments of this disclosure, the method further includes: obtaining operation information from the first transaction operation page.

[0011] According to an embodiment of this disclosure, obtaining operation information of the first transaction operation page includes: obtaining user identification information; and calling a data storage component to obtain operation information of the first transaction operation page corresponding to the user identification information.

[0012] According to embodiments of this disclosure, the method further includes: creating a new preset business scenario; determining a preset transaction image corresponding to the preset business scenario based on the preset business scenario, and storing the first attribute information and the second attribute information of the preset transaction image.

[0013] According to embodiments of this disclosure, the method further includes: storing the target transaction image and transaction evidence file information corresponding to the target transaction image.

[0014] Another aspect of this disclosure provides an image recognition device, comprising: a first generation module, configured to generate transaction evidence file information of a transaction operation page based on operation information of a first transaction operation page; a restoration module, configured to call a headless browser interface to restore a second transaction operation page corresponding to the transaction evidence file information based on the transaction evidence file information; a second generation module, configured to generate a transaction image to be recognized corresponding to the second transaction operation page based on first attribute information of a preset transaction image, wherein the first attribute information of the transaction image to be recognized is consistent with the first attribute information of the preset transaction image; a matching module, configured to use an image recognition algorithm to match the second attribute information of the transaction image to be recognized with the second attribute information of the preset transaction image to obtain a matching result; and a first determination module, configured to determine the transaction image to be recognized as a target transaction image if the matching result is consistent.

[0015] Another aspect of this disclosure provides an electronic device, including: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors perform the methods described above.

[0016] Another aspect of this disclosure provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the methods described above.

[0017] Another aspect of this disclosure provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0018] According to the image recognition method, apparatus, electronic device, readable storage medium, and program product provided in this disclosure, transaction evidence file information is generated based on the operation information of the transaction operation page. Then, using a headless browser interface, the corresponding transaction operation page is restored based on the transaction evidence file information. Based on the attribute information of a preset transaction image, a transaction image to be recognized corresponding to the restored transaction operation page is generated, and the transaction image to be recognized is determined as the target transaction image. Because it uses the attribute information of a preset transaction image to reverse-engineer the transaction operation scenario from the customer's operation data, it automatically identifies important transaction operation images. This at least partially solves the technical problems of traditional solutions that require setting separate image templates and writing corresponding programs for each business scenario, cannot generate standardized transaction images, occupy a large amount of storage space, and cannot automatically identify important transaction operation scenarios. It achieves the technical effect of flexibly responding to various transaction operation scenarios, generating standardized transaction images, saving storage space, and automatically identifying important transaction operation images. Attached Figure Description

[0019] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0020] Figure 1 schematically illustrates an application scenario of the image recognition method and apparatus according to embodiments of the present disclosure;

[0021] Figure 2 schematically illustrates a flowchart of an image recognition method according to an embodiment of the present disclosure;

[0022] Figure 3 schematically illustrates an image recognition method according to an embodiment of the present disclosure;

[0023] Figure 4 schematically illustrates a structural block diagram of an image recognition device according to an embodiment of the present disclosure; and

[0024] Figure 5 schematically illustrates a block diagram of an electronic device suitable for implementing an image recognition method according to an embodiment of the present disclosure. Detailed Implementation

[0025] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0026] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0027] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0028] When using expressions such as "at least one of A, B, and C", they should generally be interpreted in accordance with the meaning that is commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.).

[0029] In the technical solutions disclosed herein, the collection, storage, use, processing, transmission, provision, disclosure, and application of data (including but not limited to user personal information) comply with the provisions of relevant laws and regulations, necessary confidentiality measures have been taken, and they do not violate public order and good morals.

[0030] This disclosure provides an image recognition method, comprising: generating transaction evidence file information of a transaction operation page based on operation information of a first transaction operation page; calling a headless browser interface to restore a second transaction operation page corresponding to the transaction evidence file information based on the transaction evidence file information; generating a transaction image to be recognized corresponding to the second transaction operation page based on first attribute information of a preset transaction image, wherein the first attribute information of the transaction image to be recognized is consistent with the first attribute information of the preset transaction image; using an image recognition algorithm to match the second attribute information of the transaction image to be recognized with the second attribute information of the preset transaction image to obtain a matching result; and determining the transaction image to be recognized as the target transaction image if the matching result is consistent.

[0031] Figure 1 schematically illustrates an application scenario of the image recognition method and apparatus according to embodiments of the present disclosure.

[0032] As shown in Figure 1, the application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0033] Users can interact with server 105 via network 104 using at least one of the first terminal device 101, second terminal device 102, and third terminal device 103 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, second terminal device 102, and third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0034] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0035] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0036] It should be noted that the image recognition method provided in this embodiment can generally be executed by server 105. Correspondingly, the image recognition device provided in this embodiment can generally be located in server 105. The image recognition method provided in this embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Correspondingly, the image recognition device provided in this embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105.

[0037] It should be understood that the number of terminal devices, networks, and servers shown in Figure 1 is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0038] Figure 2 schematically illustrates a flowchart of an image recognition method according to an embodiment of the present disclosure.

[0039] As shown in Figure 2, the method 200 may include operations S210 to S250.

[0040] In operation S210, transaction evidence file information of the first transaction operation page is generated based on the operation information of the first transaction operation page.

[0041] According to embodiments of this disclosure, the first transaction operation page can be the operation page for a customer when performing a transaction. Operation information may include page content information during the customer's operation on the transaction operation page.

[0042] According to embodiments of this disclosure, the page content information may include, for example, transaction attribute information and operation page identification information for each customer operation transaction. The operation page identification information can characterize the uniqueness of the transaction operation page.

[0043] According to embodiments of this disclosure, transaction attribute information may include transaction time, transaction number, transaction content, transaction type, and user information. Transaction type may include transfer, agreement signing, risk assessment, etc.

[0044] According to embodiments of this disclosure, transaction evidence file information can be text data representing the page content when a customer performs a transaction operation, which can be understood as the information filled in by the customer when operating the transaction page.

[0045] When operating S220, the interface of the headless browser is called to restore the second transaction operation page corresponding to the transaction evidence file information based on the transaction evidence file information.

[0046] According to embodiments of this disclosure, the headless browser interface is an engine-based script interface that uses an engine to compile, interpret, and execute script code. It is not only an invisible browser, providing support for web standards, DOM manipulation, JSON, HTML5, etc., but also provides file I / O operations, enabling reading and writing files to the operating system.

[0047] According to embodiments of this disclosure, by calling the interface of a headless browser, and based on the invisible browsing attribute of the headless browser, the evidence file information generated in the first transaction operation page can be written to the headless browser, and the evidence file information can be accessed to restore the second transaction operation page corresponding to the transaction evidence file information.

[0048] According to embodiments of this disclosure, the second transaction operation page is a transaction operation page restored using evidence storage information obtained from the first transaction operation page. That is, the operation information on the second transaction operation page is consistent with that on the first transaction operation page.

[0049] In operation S230, a transaction image to be identified corresponding to the second transaction operation page is generated based on the first attribute information of the preset transaction image, wherein the first attribute information of the transaction image to be identified is consistent with the first attribute information of the preset transaction image.

[0050] According to embodiments of this disclosure, the preset transaction image can be a standard transaction image for important transaction operation scenarios. A transaction image to be identified can be generated based on the first attribute information of the preset transaction image.

[0051] According to embodiments of this disclosure, the first attribute information may include the operation page style and image size corresponding to the preset transaction image. Based on the operation page style and image size of the preset transaction image, a transaction image to be identified can be generated for the restored second transaction operation page, with the same operation page style and image size as the preset transaction image.

[0052] According to embodiments of this disclosure, the first attribute information of the transaction image to be identified includes the same operation page style and image size as the first attribute information of a preset transaction image. The operation page style may include appearance design style, such as eye protection mode, background color setting, and other features.

[0053] In operation S240, an image recognition algorithm is used to match the second attribute information of the transaction image to be identified with the second attribute information of a preset transaction image to obtain a matching result.

[0054] In operation S250, if the matching result is consistent, the transaction image to be identified is determined as the target transaction image.

[0055] According to embodiments of this disclosure, the second attribute information may include information characterizing the content of the image page. For example, the attribute information characterizing the image page content may include: transaction time, transaction number, transaction content, transaction type, and user information related to the transaction. The transaction type may include transfer, agreement signing, risk assessment, etc.

[0056] According to embodiments of this disclosure, the image recognition algorithm can ensure that the visual feature matching algorithm can perform feature matching between the second attribute information of the transaction image to be identified and the second attribute information of a preset transaction image. When the content of the second attribute information is completely matched, it indicates that the transaction image to be identified is the target transaction image.

[0057] According to embodiments of this disclosure, multiple preset transaction images can be set, for example, 10 preset transaction images, each with different first attribute information and second attribute information. Specifically, the process can involve sequentially generating a transaction image to be identified corresponding to the second transaction operation page based on the first attribute information of the first preset transaction image, and then performing visual feature matching between the second attribute information of the transaction image to be identified and the second attribute information of the preset transaction image. If the match is consistent, the transaction image to be identified is considered the target transaction image; if the match is inconsistent, the next transaction image to be identified corresponding to the second transaction operation page is generated using the first attribute information of the second preset transaction image, and then performing feature matching between the second attribute information of the transaction image to be identified and the second attribute information of the preset transaction image. If the match is consistent, the transaction image to be identified is determined to be the target transaction image.

[0058] According to embodiments of this disclosure, the target transaction image can be an image whose operation transaction type is consistent with that of a preset transaction image. For example, if the operation transaction type of the preset transaction image is a transfer, then if the second attribute information of the determined transaction image to be identified matches the second attribute information of the preset transaction image, then the operation transaction type of the transaction image to be identified is considered to be a transfer, and it is an important transaction image, i.e., the target transaction image.

[0059] According to embodiments of this disclosure, transaction evidence file information is generated based on the operation information of the transaction operation page. Then, using a headless browser interface, the corresponding transaction operation page is restored based on the transaction evidence file information. Based on the attribute information of a preset transaction image, a transaction image to be identified corresponding to the restored transaction operation page is generated, and the transaction image to be identified is determined as the target transaction image. Because this method reverse-engineers the transaction operation scenario using the attribute information of a preset transaction image from the customer's operation data, it automatically identifies important transaction operation images. This at least partially solves the technical problems of traditional solutions that require setting separate image templates and writing corresponding programs for each business scenario, failing to generate standardized transaction images, occupying a large amount of storage space, and failing to automatically identify important transaction operation scenarios. It achieves the technical effect of flexibly responding to various transaction operation scenarios, generating standardized transaction images, saving storage space, and automatically identifying important transaction operation images.

[0060] According to an embodiment of this disclosure, generating transaction evidence file information for the transaction operation page based on the operation information of the first transaction operation page includes: calling an application service component to generate transaction evidence file information for the transaction operation page based on the operation page identifier information and transaction attribute information.

[0061] According to embodiments of this disclosure, the application service component can be a component used when a customer performs a transaction. The page identification information can be a unique identifier for the specific transaction page accessed by the customer. The transaction attribute information can characterize the page content of the specific operation page accessed by the customer, and may include, for example, the transaction type, the customer's username, and the main content of the transaction.

[0062] According to embodiments of this disclosure, transaction evidence file information corresponding to the first transaction operation page can be generated based on the operation page identification information and the corresponding transaction attribute information. The transaction evidence file information can represent the operation information of the first transaction operation page in the form of text data.

[0063] According to an embodiment of this disclosure, generating a transaction image to be identified corresponding to a second transaction operation page based on the first attribute information of a preset transaction image includes: calling a headless browser interface to obtain the first attribute information of the preset transaction image; and performing a screenshot operation on the second transaction operation page based on the first attribute information of the preset transaction image to obtain the transaction image to be identified corresponding to the transaction operation page.

[0064] According to embodiments of this disclosure, transaction evidence file information can be accessed from the database, and a second transaction operation page corresponding to the transaction evidence file information can be restored by calling a headless browser interface.

[0065] According to embodiments of this disclosure, a headless browser can be used to obtain a pre-set image script of a preset transaction image. The image script obtains the first attribute information corresponding to one preset transaction image from multiple preset transaction images, namely, the operation page style information and the image size information.

[0066] According to embodiments of this disclosure, a screenshot operation can be performed on a second transaction operation page based on the operation page style information and image size information corresponding to a preset transaction image. The transaction image to be identified has a sound field size consistent with the operation page style. The transaction image to be identified includes images of all page content when the customer operates the transaction page.

[0067] According to embodiments of this disclosure, a transaction operation page can be reverse-engineered from transaction evidence file information by using a preset operation page style and image size of the transaction image, thereby generating a transaction image that can restore the customer's operation of the transaction page, and ensuring that the transaction image has a uniform size and consistent operation page style.

[0068] According to embodiments of this disclosure, the image recognition method described above may further include: obtaining operation information from a first transaction operation page.

[0069] According to embodiments of this disclosure, obtaining operation information of the first transaction operation page includes: obtaining user identification information; and calling a data storage component to obtain operation information of the first transaction operation page corresponding to the user identification information.

[0070] According to embodiments of this disclosure, before generating transaction evidence file information, the operation information of the transaction operation page can be obtained from the customer when performing the transaction operation.

[0071] According to embodiments of this disclosure, the user's identification information can be the user's username, user ID, or other information, and is unique.

[0072] According to embodiments of this disclosure, after a user logs into the transaction operation page, they perform transaction operations on the transaction operation page, and at the same time, the transaction operations performed by the user are stored in the data.

[0073] According to embodiments of this disclosure, a data storage component can be invoked to retrieve operation information of a first transaction operation page corresponding to the user's identification information from a database. The operation information may include operation page identification information and transaction attribute information.

[0074] According to embodiments of this disclosure, the image recognition method may further include: creating a new preset business scenario; determining a preset transaction image corresponding to the preset business scenario based on the preset business scenario, and storing first attribute information and second attribute information of the preset transaction image.

[0075] According to embodiments of this disclosure, the preset business scenarios may include business scenarios where customers conduct different business transactions, such as signing agreements, buying and selling transactions, transferring funds, and making inquiries.

[0076] According to embodiments of this disclosure, important transaction scenarios can be determined based on each preset business scenario, and the transaction image of the important transaction scenario can be uploaded as a preset transaction image. Simultaneously, the first attribute information and second attribute information of the preset transaction image are saved. Specifically, the first attribute information includes operation page style information and image size information, while the second attribute information includes transaction attribute information, which may include operation transaction time, operation transaction number, operation transaction content, operation transaction type, and user information of the operation transaction. The operation transaction type can be transfer, agreement signing, risk assessment, etc.

[0077] According to embodiments of this disclosure, the image recognition method described above may further include: storing a target transaction image and transaction evidence file information corresponding to the target transaction image.

[0078] According to embodiments of this disclosure, after identifying the transaction image to be identified as the target transaction image, the target transaction image and the corresponding evidence storage information are archived and stored so as to retrieve the electronic certificate as a digital contract.

[0079] Figure 3 schematically illustrates an image recognition method according to an embodiment of the present disclosure.

[0080] As shown in Figure 3, in method 300, operation S301 obtains the user's identification information. Operation S302 obtains the operation information of the first transaction operation page corresponding to the user's identification information based on the user's identification information. Operation S303 creates a new preset business scenario. Operation S304 determines a preset transaction image based on the preset business scenario. Operation S304-1 stores the first attribute information of the preset transaction image; operation S304-2 stores the second attribute information of the preset transaction image. Operation S305 generates transaction evidence file information for the first transaction operation page based on operation S302, i.e., the operation information of the first transaction operation page. Operation S306 restores the second transaction operation page corresponding to the transaction evidence file information based on the transaction evidence file information. Operation S307 generates a transaction image to be identified corresponding to the second transaction operation page based on the first attribute information of the preset transaction image. Operation S308 matches the transaction image to be identified with the second attribute information of the preset transaction image to obtain a matching result. In step S309, if a match is found, the transaction image to be identified is determined as the target transaction image; if a mismatch is found, steps S307 through S308 are executed. In step S310, the target transaction image and the corresponding transaction evidence file information are stored as electronic credentials for the digital contract.

[0081] Based on the image recognition method described above, this disclosure also provides an image recognition device. The device will be described in detail below with reference to FIG4.

[0082] Figure 4 schematically illustrates a structural block diagram of an image recognition device according to an embodiment of the present disclosure.

[0083] As shown in Figure 4, the device 400 may include a first generation module 410, a restoration module 420, a second generation module 430, a matching module 440, and a first determination module 450.

[0084] The first generation module 410 is used to generate transaction evidence file information for the transaction operation page based on the operation information of the first transaction operation page. In one embodiment, the first generation module 410 can be used to execute the operation S210 described above, which will not be repeated here.

[0085] The restoration module 420 is used to call the headless browser interface to restore the second transaction operation page corresponding to the transaction evidence file information based on the transaction evidence file information. In one embodiment, the restoration module 420 can be used to perform the operation S220 described above, which will not be repeated here.

[0086] The second generation module 430 is used to generate a transaction image to be identified corresponding to the second transaction operation page based on the first attribute information of the preset transaction image, wherein the first attribute information of the transaction image to be identified is consistent with the first attribute information of the preset transaction image. In one embodiment, the second generation module 430 can be used to perform the operation S230 described above, which will not be repeated here.

[0087] The matching module 440 is used to match the second attribute information of the transaction image to be identified with the second attribute information of a preset transaction image using an image recognition algorithm to obtain a matching result. In one embodiment, the matching module 440 can be used to perform the operation S240 described above, which will not be repeated here.

[0088] The first determining module 450 is used to determine the transaction image to be identified as the target transaction image when the matching result is consistent. In one embodiment, the first determining module 450 can be used to perform the operation S250 described above, which will not be repeated here.

[0089] According to embodiments of this disclosure, the operation information includes operation page identification information and transaction attribute information.

[0090] According to embodiments of this disclosure, the first generation module 410 may include: a first calling submodule.

[0091] The first calling submodule is used to call the application service component to generate transaction evidence file information for the transaction operation page based on the operation page identifier information and transaction attribute information.

[0092] According to embodiments of this disclosure, the second generation module 430 may include an acquisition submodule and an execution submodule.

[0093] The `get` submodule is used to call the headless browser interface to obtain the first attribute information of the preset transaction image.

[0094] The execution submodule is used to perform a screenshot operation on the second transaction operation page based on the first attribute information of the preset transaction image, so as to obtain the transaction image to be identified corresponding to the transaction operation page.

[0095] According to embodiments of this disclosure, the image recognition device 400 may further include an acquisition module.

[0096] The acquisition module is used to obtain operation information from the first transaction operation page.

[0097] According to embodiments of this disclosure, the acquisition module may include: an acquisition submodule and a second invocation submodule.

[0098] The `get` submodule is used to obtain the user's identification information.

[0099] The second calling submodule is used to call the data storage component and obtain the operation information of the first transaction operation page corresponding to the user's identification information.

[0100] According to embodiments of this disclosure, the image recognition device 400 may further include: a new creation module and a second determination module.

[0101] Create a new module for creating preset business scenarios.

[0102] The second determining module is used to determine the preset transaction image corresponding to the preset business scenario based on the preset business scenario, and to store the first attribute information and the second attribute information of the preset transaction image.

[0103] According to embodiments of this disclosure, the image recognition device 400 may further include a storage module.

[0104] The storage module is used to store the target transaction image and the corresponding transaction evidence file information.

[0105] According to embodiments of this disclosure, any plurality of modules among the first generation module 410, restoration module 420, second generation module 430, matching module 440, and first determination module 450 may be combined into one module, or any one of these modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the first generation module 410, restoration module 420, second generation module 430, matching module 440, and first determination module 450 may be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any appropriate combination of any of these three implementation methods. Alternatively, at least one of the first generation module 410, restoration module 420, second generation module 430, matching module 440 and first determination module 450 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0106] Figure 5 schematically illustrates a block diagram of an electronic device suitable for implementing an image recognition method according to an embodiment of the present disclosure.

[0107] As shown in FIG. 5, an electronic device 500 according to an embodiment of the present disclosure includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage portion 508 into a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0108] RAM 503 stores various programs and data required for the operation of electronic device 500. Processor 501, ROM 502, and RAM 503 are interconnected via bus 504. Processor 501 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 502 and / or RAM 503. It should be noted that programs may also be stored in one or more memories other than ROM 502 and RAM 503. Processor 501 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in one or more memories.

[0109] According to embodiments of this disclosure, the electronic device 500 may further include an input / output (I / O) interface 505, which is also connected to a bus 504. The electronic device 500 may also include one or more of the following components connected to the input / output (I / O) interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the input / output (I / O) interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 510 as needed so that computer programs read from it can be installed into the storage section 508 as needed.

[0110] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0111] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 502 and / or RAM 503 and / or one or more memories other than ROM 502 and RAM 503 described above.

[0112] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code enables the computer system to implement the image recognition method provided in the embodiments of this disclosure.

[0113] When the computer program is executed by the processor 501, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0114] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 509, and / or installed from a removable medium 511. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0115] In such an embodiment, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by processor 501, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0116] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0117] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0118] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0119] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. An image recognition method, comprising: Based on the operation information on the first transaction operation page, generate transaction evidence file information for the first transaction operation page; The system invokes a headless browser interface to reconstruct the second transaction operation page corresponding to the transaction evidence file information. Based on the first attribute information of a preset transaction image, it generates a transaction image to be identified corresponding to the second transaction operation page. The first attribute information of the transaction image to be identified is consistent with the first attribute information of the preset transaction image. The first attribute information includes the operation page style and image size, and the operation page style includes the appearance design style. Using an image recognition algorithm, the second attribute information of the transaction image to be identified is matched with the second attribute information of the preset transaction image to obtain a matching result. The second attribute information includes information representing the content of the image page, including: transaction time, transaction number, transaction content, transaction type, and user information. If the matching result is consistent, the transaction image to be identified is determined as the target transaction image.

2. The method according to claim 1, wherein, The operation information includes operation page identification information and transaction attribute information; generating transaction evidence file information of the transaction operation page based on the operation information of the first transaction operation page includes: calling an application service component to generate transaction evidence file information of the transaction operation page based on the operation page identification information and transaction attribute information.

3. The method according to claim 1 or 2, wherein, The step of generating a transaction image to be identified corresponding to the second transaction operation page based on the first attribute information of the preset transaction image includes: calling the headless browser interface to obtain the first attribute information of the preset transaction image; and performing a screenshot operation on the second transaction operation page based on the first attribute information of the preset transaction image to obtain the transaction image to be identified corresponding to the transaction operation page.

4. The method according to claim 1, further comprising: Obtain the operation information from the first transaction operation page.

5. The method according to claim 4, wherein, The step of obtaining the operation information of the first transaction operation page includes: obtaining the user's identification information; calling the data storage component to obtain the operation information of the first transaction operation page corresponding to the user's identification information.

6. The method according to claim 1, further comprising: Create a new preset business scenario; Based on the preset business scenario, a preset transaction image corresponding to the preset business scenario is determined, and the first attribute information and the second attribute information of the preset transaction image are stored.

7. The method according to claim 1, further comprising: Store the target transaction image and the corresponding transaction evidence file information.

8. An image recognition device, comprising: The first generation module is used to generate transaction evidence file information of the transaction operation page based on the operation information of the first transaction operation page; The system comprises the following modules: a restoration module, which calls a headless browser interface to restore the second transaction operation page corresponding to the transaction evidence file information; a second generation module, which generates a transaction image to be identified corresponding to the second transaction operation page based on the first attribute information of a preset transaction image, wherein the first attribute information of the transaction image to be identified is consistent with the first attribute information of the preset transaction image, and the first attribute information includes the operation page style and image size, and the operation page style includes the appearance design style; a matching module, which uses an image recognition algorithm to match the second attribute information of the transaction image to be identified with the second attribute information of the preset transaction image to obtain a matching result, wherein the second attribute information includes information representing the content of the image page, and the information representing the content of the image page includes: operation transaction time, operation transaction number, operation transaction content, operation transaction type, and operation transaction user information; and a first determination module, which, if the matching result is consistent, determines the transaction image to be identified as the target transaction image.

9. An electronic device, comprising: One or more processors; A memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 7.

11. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 7.

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