Financial payment management system

By obtaining the geometric shape and brightness information of financial payment devices and using a deep feedforward network model for intelligent judgment, the problem of identifying counterfeit devices is solved and the security of the payment environment is improved.

CN120612083AInactive Publication Date: 2025-09-09NANJING AOWUSHENG SOFTWARE TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202510749679.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Priority Date
2025-01-23
Filing Date
2025-06-06
Publication Date
2025-09-09
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

In the existing technology, counterfeit financial payment devices are difficult to accurately identify, resulting in their long-term presence in the financial payment environment, affecting payment security.

Method used

By obtaining information such as the geometric shape, brightness value distribution, and imaging depth of field of financial payment devices, a deep feedforward network model is used to make intelligent judgments and identify counterfeit devices.

Benefits of technology

It realizes intelligent judgment of the geometric parameters of financial payment devices, avoids the existence of counterfeit devices, and improves the security of the payment environment.

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Abstract

The invention relates to a financial payment management system which comprises a data acquisition mechanism, a multiple optimization mechanism, a first analysis device, a second analysis device, a third analysis device and an object judgment device. The financial payment management system is stable in operation and simple and convenient to control.
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Description

Technical Field

[0001] The present invention relates to the field of financial payment, and more particularly, to a financial payment management system. Background Art

[0002] In financial payment processes, electronic contracts, owing to their efficiency, convenience, and security, are gradually becoming the mainstream contract signing method. Technology companies offer various electronic contract solutions to ensure the legitimacy and immutability of the contract signing process. Generally, encryption technology and real-name authentication mechanisms are employed to safeguard contract data security and the rights and interests of both parties involved in the transaction. Through technology companies' platforms, financial institutions can easily implement online contract signing, accelerating business processes, reducing operating costs, and improving the customer experience. This facilitates the digital transformation of the financial industry and makes contract signing simpler and more reliable.

[0003] Due to the existence of the automatic financial payment function of financial payment devices, some people place counterfeit financial payment devices in the financial payment environment to guide payment personnel to make payments. The sophistication of these financial payment devices is often so great that they are indistinguishable from the real ones. How to improve the identification accuracy of genuine and fake financial payment devices to avoid the long-term existence of counterfeit financial payment devices in the financial payment environment is one of the technical problems that need to be solved at present. Summary of the Invention

[0004] In order to solve technical problems in related fields, the present invention provides a financial payment management system that can obtain multiple basic information for performing intelligent judgment of surface distribution area. Specifically, the geometric shape corresponding to the known outline of the financial payment device is obtained, and the geometric shape is a closed curve and includes various curvature values ​​at different positions of the closed curve. The occupied area of ​​the financial payment device in the received multiple optimized images is detected according to the brightness value distribution range of the financial payment device, and the total number of pixels occupied by the occupied area is obtained as a reference acquisition number; and based on the various curvature values ​​at different positions of the closed curve, the reference acquisition number, the shooting focal length corresponding to the multiple optimized images, and the imaging depth of field of the financial payment device, a deep feedforward network model is used to intelligently judge the surface distribution area corresponding to the financial payment device, thereby realizing intelligent judgment of the geometric parameters of the financial payment device and preventing counterfeit financial payment devices from being placed in the financial payment environment for a long time.

[0005] According to the present invention, a financial payment management system is provided, the system comprising: A data collection mechanism, configured to collect directional visual data from a financial payment device placed in a financial payment environment to obtain and output a corresponding payment environment image, wherein the financial payment device placed in the financial payment environment is a financial payment device placed above a financial payment stand or located in a financial payment area; a multiple optimization mechanism connected to the data acquisition mechanism, configured to sequentially perform gamma correction processing, nonlinear transformation processing based on exponential transformation, and guided filtering processing on the received payment environment image, so as to obtain and output corresponding multiple optimized images; a first analysis device, connected to the multi-optimization mechanism, for obtaining a geometric shape corresponding to a known profile of the financial payment device, wherein the geometric shape is a closed curve and includes various curvature values ​​at various positions of the closed curve; a second analyzing device, connected to the first analyzing device, configured to detect an occupied area of ​​the financial payment device in the received multiple optimized images based on a brightness value distribution range of the financial payment device, and obtain a total number of pixels occupied in the occupied area as a reference collection quantity; a third analyzing device, connected to the first analyzing device and the second analyzing device, respectively, for intelligently determining the surface distribution area corresponding to the financial payment device using a deep feedforward network model based on the curvature values ​​at different positions of the closed curve, the number of reference acquisitions, the shooting focal lengths corresponding to the multiple optimized images, and the imaging depth of field of the financial payment device; an object determination device, connected to the third analysis device, configured to determine, when the surface distribution area corresponding to the received financial payment device is not within the set area range, that the financial payment device placed in the financial payment environment does not belong to the set financial institution and is a counterfeit of the financial payment device of the set financial institution; Wherein, when the surface distribution area corresponding to the received financial payment device is not within the set area range, determining that the financial payment device placed in the financial payment environment does not belong to the set financial institution and is a counterfeit of the financial payment device of the set financial institution includes: the surface distribution area of ​​the financial payment device of the set financial institution is within the set area range; Among them, based on the curvature values ​​at different positions of the closed curve, the reference acquisition number, the shooting focal length corresponding to the multiple optimized images, and the imaging depth of field of the financial payment device, a deep feedforward network model is used to intelligently determine the surface distribution area corresponding to the financial payment device, including: the deep feedforward network model is a deep feedforward network after multiple learning operations, and the number of times the deep feedforward network learns is monotonically positively correlated with the area span of the set area interval corresponding to the financial payment device of the set financial institution.

[0006] Therefore, the present invention has at least the following three beneficial technical effects: First, the deep feedforward network model that performs intelligent judgment of surface distribution area is a deep feedforward network that has performed multiple learning cycles, and the number of times the deep feedforward network has been learned is monotonically positively correlated with the area span of a set area interval corresponding to the financial payment device of a set financial institution; Second, obtaining multiple pieces of basic information for intelligently determining the surface distribution area. Specifically, obtaining a geometric shape corresponding to the known outline of the financial payment device, where the geometric shape is a closed curve and includes various curvature values ​​at different positions on the closed curve. Detecting the occupied area of ​​the financial payment device in the received multiple optimized images based on the distribution range of the brightness values ​​of the financial payment device, and obtaining the total number of pixels occupied by the occupied area as a reference acquisition quantity. Third: Based on the curvature values ​​at different positions of the closed curve, the number of reference acquisitions, the shooting focal lengths corresponding to the multiple optimized images, and the imaging depth of field of the financial payment device, a deep feedforward network model is used to intelligently judge the surface distribution area corresponding to the financial payment device, thereby realizing intelligent judgment of the geometric parameters of the financial payment device.

[0007] The financial payment management system of the present invention operates stably and is easy to operate. By acquiring multiple pieces of basic information for intelligently determining surface distribution areas, it uses a deep feedforward network model to intelligently determine the surface distribution areas corresponding to financial payment devices. This enables intelligent determination of the geometric parameters of financial payment devices, preventing counterfeit financial payment devices from being placed in financial payment environments for extended periods of time. DETAILED DESCRIPTION

[0008] The implementation scheme of the financial payment management system of the present invention will be described in detail below.

[0009] First embodiment

[0010] The financial payment management system according to the first embodiment of the present invention includes: A data collection mechanism, configured to collect directional visual data from a financial payment device placed in a financial payment environment to obtain and output a corresponding payment environment image, wherein the financial payment device placed in the financial payment environment is a financial payment device placed above a financial payment stand or located in a financial payment area; For example, a data acquisition mechanism is used to perform directional visual data acquisition on a financial payment device placed in a financial payment environment to obtain and output a corresponding payment environment image. The financial payment device placed in the financial payment environment is a financial payment device placed above a financial payment stand or located in a financial payment area. The data acquisition mechanism includes a built-in CMOS sensor for sensing the original image of the payment environment. a multiple optimization mechanism connected to the data acquisition mechanism, configured to sequentially perform gamma correction processing, nonlinear transformation processing based on exponential transformation, and guided filtering processing on the received payment environment image, so as to obtain and output corresponding multiple optimized images; a first analysis device, connected to the multi-optimization mechanism, for obtaining a geometric shape corresponding to a known profile of the financial payment device, wherein the geometric shape is a closed curve and includes various curvature values ​​at various positions of the closed curve; a second analyzing device, connected to the first analyzing device, configured to detect an occupied area of ​​the financial payment device in the received multiple optimized images based on a brightness value distribution range of the financial payment device, and obtain a total number of pixels occupied in the occupied area as a reference collection quantity; a third analyzing device, connected to the first analyzing device and the second analyzing device, respectively, for intelligently determining the surface distribution area corresponding to the financial payment device using a deep feedforward network model based on the curvature values ​​at different positions of the closed curve, the number of reference acquisitions, the shooting focal lengths corresponding to the multiple optimized images, and the imaging depth of field of the financial payment device; an object determination device, connected to the third analysis device, configured to determine, when the surface distribution area corresponding to the received financial payment device is not within the set area range, that the financial payment device placed in the financial payment environment does not belong to the set financial institution and is a counterfeit of the financial payment device of the set financial institution; Wherein, when the surface distribution area corresponding to the received financial payment device is not within the set area range, determining that the financial payment device placed in the financial payment environment does not belong to the set financial institution and is a counterfeit of the financial payment device of the set financial institution includes: the surface distribution area of ​​the financial payment device of the set financial institution is within the set area range; The method includes using a deep feedforward network model to intelligently determine the surface distribution area corresponding to the financial payment device based on the curvature values ​​at different positions of the closed curve, the reference acquisition quantity, the shooting focal length corresponding to the multiple optimized images, and the imaging depth of field of the financial payment device, wherein the deep feedforward network model is a deep feedforward network that has been trained multiple times, and the number of times the deep feedforward network has been trained is monotonically positively correlated with the area span of a set area interval corresponding to the financial payment device of the set financial institution; The object determination device is further configured to determine, when the surface distribution area corresponding to the received financial payment device is within a set area range, that the financial payment device placed in the financial payment environment belongs to a set financial institution and is not a replica of the financial payment device of the set financial institution; The geometric shape corresponding to the known outline of the financial payment device is a closed curve and includes various curvature values ​​at different positions of the closed curve, including: the known outline of the financial payment device is a rectangle or a combination of rectangles.

[0011] Second embodiment

[0012] The financial payment management system according to the second embodiment of the present invention may further include the following components: a count monitoring component connected to the object determination device, the third parsing device, the first parsing device, and the second parsing device, respectively, for measuring the number of operations per unit time of each of the object determination device, the third parsing device, the first parsing device, and the second parsing device; The number monitoring component is connected to the object judgment device, the third parsing device, the first parsing device, and the second parsing device, respectively, and is used to measure the number of operations per unit time of the object judgment device, the third parsing device, the first parsing device, and the second parsing device, respectively. The number monitoring component includes a plurality of operation measurement units, which are used to be connected to the object judgment device, the third parsing device, the first parsing device, and the second parsing device, respectively, to complete the measurement of the number of operations per unit time of the object judgment device, the third parsing device, the first parsing device, and the second parsing device, respectively. The number monitoring component includes a plurality of operation measurement units, which are respectively connected to the object determination device, the third analysis device, the first analysis device, and the second analysis device to respectively measure the number of operations per unit time of the object determination device, the third analysis device, the first analysis device, and the second analysis device. The plurality of operation measurement units are a plurality of operation sensing circuits, which are respectively connected to the object determination device, the third analysis device, the first analysis device, and the second analysis device to respectively measure the number of operations per unit time of the object determination device, the third analysis device, the first analysis device, and the second analysis device. The plurality of operation measurement units are a plurality of operation sensing circuits, respectively connected to the object determination device, the third analysis device, the first analysis device, and the second analysis device, to respectively measure the number of operations per unit time of the object determination device, the third analysis device, the first analysis device, and the second analysis device, including: the plurality of operation sensing circuits having the same structure; Among them, the multiple operation measurement units are multiple operation sensing circuits, which are used to connect to the object judgment device, the third analysis device, the first analysis device and the second analysis device respectively to complete the separate measurement of the number of unit time operations of the object judgment device, the third analysis device, the first analysis device and the second analysis device respectively, and also include: the multiple operation sensing circuits have the same operation measurement upper limit value and operation measurement lower limit value.

[0013] Third embodiment

[0014] The financial payment management system according to the third embodiment of the present invention may further include the following components: a communication service mechanism, disposed below the object determination device, the third parsing device, the first parsing device, and the second parsing device, for providing bottom support services for the object determination device, the third parsing device, the first parsing device, and the second parsing device, respectively; The communication service mechanism is provided below the object determination device, the third parsing device, the first parsing device, and the second parsing device, and is used to provide bottom support services for the object determination device, the third parsing device, the first parsing device, and the second parsing device, respectively. The communication service mechanism includes: a plurality of slots are provided on the communication service mechanism to respectively accommodate the object determination device, the third parsing device, the first parsing device, and the second parsing device; And wherein, a plurality of slots are provided on the communication service mechanism to respectively accommodate the object judgment device, the third analysis device, the first analysis device and the second analysis device, including: the opening cross-sectional area of ​​the plurality of slots is the same to respectively accommodate the object judgment device, the third analysis device, the first analysis device and the second analysis device.

[0015] In addition, in the financial payment management system, the use of a deep feedforward network model to intelligently determine the surface distribution area corresponding to the financial payment device based on the curvature values ​​at different positions of the closed curve, the reference acquisition number, the shooting focal length corresponding to the multiple optimized images, and the imaging depth of field of the financial payment device also includes: synchronously inputting the curvature values ​​at different positions of the closed curve, the reference acquisition number, the shooting focal length corresponding to the multiple optimized images, and the imaging depth of field of the financial payment device into the deep feedforward network model, and running the deep feedforward network model to obtain the surface distribution area corresponding to the financial payment device output by the deep feedforward network model.

[0016] While the present invention has been described with reference to certain exemplary embodiments thereof, it will be understood by those skilled in the art that various modifications and changes may be made thereto without departing from the spirit or scope of the invention as defined in the appended claims and their equivalents.

Claims

1. A financial payment management system, characterized in that the system include: A data collection mechanism, configured to collect directional visual data from a financial payment device placed in a financial payment environment to obtain and output a corresponding payment environment image, wherein the financial payment device placed in the financial payment environment is a financial payment device placed above a financial payment stand or located in a financial payment area; a multiple optimization mechanism connected to the data acquisition mechanism, configured to sequentially perform gamma correction processing, nonlinear transformation processing based on exponential transformation, and guided filtering processing on the received payment environment image, so as to obtain and output corresponding multiple optimized images; A first analysis device, connected to the multiple optimization mechanism, is used to obtain a geometric shape corresponding to a known contour of the financial payment device, where the geometric shape is a closed curve and includes various curvature values ​​at various positions on the closed curve; a second analyzing device, connected to the first analyzing device, configured to detect an occupied area of ​​the financial payment device in the received multiple optimized images based on a distribution range of brightness values ​​of the financial payment device, and obtain a total number of pixels occupied in the occupied area as a reference collection quantity; a third analyzing device, connected to the first analyzing device and the second analyzing device, respectively, for intelligently determining the surface distribution area corresponding to the financial payment device using a deep feedforward network model based on curvature values ​​at different positions of the closed curve, the number of reference acquisitions, the shooting focal lengths corresponding to the multiple optimized images, and the imaging depth of field of the financial payment device, wherein the deep feedforward network model is a deep feedforward network that has undergone multiple learning cycles, and the number of times the deep feedforward network has been learned is monotonically positively correlated with the area span of a set area interval corresponding to the financial payment device of the set financial institution; The object judgment device is connected to the third analysis device and is used to judge that the financial payment device placed in the financial payment environment does not belong to the set financial institution and is a replica of the financial payment device of the set financial institution when the surface distribution area corresponding to the received financial payment device is not within the set area range, wherein the surface distribution area of ​​the financial payment device of the set financial institution is within the set area range.

2. The financial payment management system according to claim 1, wherein: The object determination device is further configured to determine, when the surface distribution area corresponding to the received financial payment device is within a set area range, that the financial payment device placed in the financial payment environment belongs to the set financial institution and is not a replica of the financial payment device of the set financial institution; The geometric shape corresponding to the known outline of the financial payment device is a closed curve and includes various curvature values ​​at different positions of the closed curve, including: the known outline of the financial payment device is a rectangle or a combination of rectangles.

3. The financial payment management system according to claim 2, characterized in that: The system also includes: a count monitoring component connected to the object determination device, the third parsing device, the first parsing device, and the second parsing device, respectively, for measuring the number of operations per unit time of the object determination device, the third parsing device, the first parsing device, and the second parsing device; Among them, the number monitoring component is respectively connected to the object judgment device, the third analysis device, the first analysis device and the second analysis device, and is used to respectively measure the number of unit time operations of the object judgment device, the third analysis device, the first analysis device and the second analysis device, including: the number monitoring component includes multiple operation measurement units, which are used to be respectively connected to the object judgment device, the third analysis device, the first analysis device and the second analysis device to complete the respective measurement of the number of unit time operations of the object judgment device, the third analysis device, the first analysis device and the second analysis device.

4. The financial payment management system according to claim 3, wherein: The number monitoring component includes multiple operation measurement units, which are used to be connected to the object judgment device, the third analysis device, the first analysis device and the second analysis device respectively to complete the separate measurement of the number of unit time operations of the object judgment device, the third analysis device, the first analysis device and the second analysis device respectively. The multiple operation measurement units are multiple operation sensing circuits, which are used to be connected to the object judgment device, the third analysis device, the first analysis device and the second analysis device respectively to complete the separate measurement of the number of unit time operations of the object judgment device, the third analysis device, the first analysis device and the second analysis device respectively.

5. The financial payment management system according to claim 4, characterized in that: The multiple operation measurement units are multiple operation sensing circuits, which are used to connect to the object judgment device, the third analysis device, the first analysis device and the second analysis device respectively to complete the separate measurement of the number of unit time operations of the object judgment device, the third analysis device, the first analysis device and the second analysis device respectively, including: the structures of the multiple operation sensing circuits are the same.

6. The financial payment management system according to claim 5, characterized in that: The multiple operation measurement units are multiple operation sensing circuits, which are used to connect to the object judgment device, the third analysis device, the first analysis device and the second analysis device respectively to complete the separate measurement of the number of unit time operations of the object judgment device, the third analysis device, the first analysis device and the second analysis device respectively. It also includes: the multiple operation sensing circuits have the same operation measurement upper limit value and operation measurement lower limit value.

7. The financial payment management system according to claim 3, wherein: The system also includes: The communication service mechanism is arranged below the object judgment device, the third analysis device, the first analysis device and the second analysis device, and is used to provide bottom support services for the object judgment device, the third analysis device, the first analysis device and the second analysis device respectively.

8. The financial payment management system according to claim 7, wherein: The communication service mechanism is arranged below the object judgment device, the third analysis device, the first analysis device and the second analysis device, and is used to provide bottom support services for the object judgment device, the third analysis device, the first analysis device and the second analysis device respectively, including: multiple slots are set on the communication service mechanism to accommodate the object judgment device, the third analysis device, the first analysis device and the second analysis device respectively.

9. The financial payment management system according to claim 8, characterized in that: Multiple slots are set on the communication service mechanism to respectively accommodate the object judgment device, the third analysis device, the first analysis device and the second analysis device, including: the opening cross-sectional area of ​​the multiple slots is the same to respectively accommodate the object judgment device, the third analysis device, the first analysis device and the second analysis device.