System and method for generating an image for a payment device

Abstract

A method for generating a user-designed image for a payment card includes receiving at least one image criterion of a target image associated with a user associated with a payment card; receiving a plurality of preliminary images generated by an artificial intelligence engine based on the at least one image criterion; receiving an image selection of the user, the image selection including an image selected from the plurality of preliminary images; displaying the selected image overlaid on a virtual representation of the payment card on a user interface; and setting at least one size parameter of the selected image to fit a size of the payment card.

Description

Technical Field

[0001] This disclosure generally relates to the field of payment devices, and more specifically, to systems and methods for generating images for payment cards. Background Technology

[0002] Credit cards, debit cards, and similar payment devices are ubiquitous in modern markets due to their convenience, security, and other benefits for users and merchants. As these payment cards increasingly replace cash, many people use them multiple times a day. Therefore, including easily recognizable or personally appealing images on payment cards can be advantageous and desirable. Currently, some issuers allow a degree of personalization for payment cards, allowing users to choose from a stock of images or upload their own. However, these solutions have drawbacks. Using stock images limits the subject matter, and users may struggle to find images that resonate with them. Systems allowing users to upload their own images are often cumbersome and may encounter file type incompatibility. Furthermore, standard-sized photos (such as those taken with a smartphone) may not be the right size for a payment card. Additionally, some users may want unique or novel images not found in the stock image set or in their own portfolio.

[0003] This disclosure relates to systems and methods for addressing the aforementioned and other deficiencies in the existing payment card field. The background description provided herein is intended to provide a general overview of the background of this disclosure. Unless otherwise stated herein, the material described in this section is not prior art to the claims of this application, nor is it admitted as prior art or an implication of prior art by virtue of its inclusion in this section. Summary of the Invention

[0004] One embodiment of this disclosure relates to a method for generating a user-designed image for a payment card. The method includes: receiving, by at least one processor, at least one image criterion for a target image associated with a user associated with the payment card; receiving, by at least one processor, a plurality of preliminary images generated by an artificial intelligence engine based on the at least one image criterion; receiving, by at least one processor, an image selection by the user, the image selection including an image selected from the plurality of preliminary images; displaying, by at least one processor, the selected image overlaid on a virtual representation of the payment card on a user interface; and setting, by at least one processor, at least one size parameter of the selected image to fit the size of the payment card.

[0005] Another embodiment of this disclosure relates to a computer system for generating a user-designed image for a payment card. The computer system includes: at least one memory storing processor-readable instructions; and at least one processor configured to access the memory and execute the processor-readable instructions. When executed by the processor, the instructions configure the processor to perform a plurality of functions, including functions for: receiving at least one image criterion for a target image associated with a user associated with the payment card; receiving a plurality of preliminary images generated by an artificial intelligence engine based on the at least one image criterion; receiving an image selection from the user, the image selection including an image selected from the plurality of preliminary images; displaying the selected image overlaid on a virtual representation of the payment card on a user interface; and setting at least one size parameter of the selected image to fit the size of the payment card.

[0006] Another embodiment of this disclosure relates to a non-transitory computer-readable medium that stores instructions applied to a payment card. The non-transitory computer-readable medium stores instructions that, when executed by at least one processor, configure the at least one processor to perform the following operations: receiving at least one image criterion for a target image associated with a user associated with the payment card; receiving a plurality of preliminary images generated by an artificial intelligence engine based on the at least one image criterion; receiving an image selection from the user, the image selection including an image selected from the plurality of preliminary images; displaying the selected image overlaid on a virtual representation of the payment card on a user interface; and setting at least one size parameter of the selected image to fit the size of the payment card. Attached Figure Description

[0007] The accompanying drawings, which are included in and form part of this specification, illustrate several embodiments of the present disclosure and, together with the following description, illustrate the principles of the disclosure.

[0008] Figure 1 It is an exemplary financial transaction system that includes the generation and use of payment devices, as described in one or more embodiments.

[0009] Figure 2 This is a front view of a payment device according to one or more embodiments.

[0010] Figure 3 This is a schematic diagram of the architecture of an artificial intelligence engine according to one or more embodiments.

[0011] Figure 4 This is a flowchart illustrating an exemplary method for generating an image for a payment device, according to one or more embodiments.

[0012] Figure 5This is a flowchart illustrating another exemplary method for generating an image for a payment device, according to one or more embodiments.

[0013] Figure 6 It is a user interface for generating images for a payment device, as depicted according to one or more embodiments.

[0014] Figure 7 It is a user interface for generating images for a payment device, as depicted according to one or more embodiments.

[0015] Figure 8 It is a user interface for generating images for a payment device, as depicted according to one or more embodiments.

[0016] Figure 9 It is a user interface for generating images for a payment device, as depicted according to one or more embodiments.

[0017] Figure 10 It is a user interface for generating images for a payment device, as depicted according to one or more embodiments.

[0018] Figure 11 It is a computer system for performing the techniques described herein, as shown in one or more embodiments. Detailed Implementation

[0019] The following embodiments describe systems and methods for generating images for payment devices (e.g., credit cards, debit cards, etc.). More specifically, the embodiments described in this disclosure enable users / customers to personalize payment devices by selecting images generated by an artificial intelligence engine based on text input provided by the user / customer.

[0020] Embodiments of this disclosure allow card issuers to leverage artificial intelligence technology to enable users / customers to personalize images on payment devices with virtually unlimited capabilities. Furthermore, embodiments of this disclosure are robust because each generated image is sized to fit a payment card. The ability to personalize payment cards according to the systems and methods of this disclosure can attract customers to open accounts with the issuer, thereby benefiting both the customer and the issuer.

[0021] As mentioned above, existing systems and methods for image customization contain certain drawbacks and limitations, such as limited selection of stock images and / or incompatibility with image attributes (e.g., size, resolution, and file type) of user-uploaded images. To address these and other issues, this disclosure describes systems and methods that allow users / customers to generate unique images based on text input using an artificial intelligence engine. Furthermore, the systems and methods provide automatic setting of the image's position on the payment card to suit the card size, image subject, and / or other considerations. Additionally, the systems and methods offer user-defined adjustments to the image's layout on the payment card.

[0022] The subject matter of this disclosure will now be described more fully with reference to the accompanying drawings, which form part of this disclosure and illustrate specific exemplary embodiments by way of illustration. The “exemplary” embodiments or implementations described herein should not be construed as preferred or advantageous over other embodiments or implementations; rather, they are intended to reflect or indicate that the embodiment is an “example” embodiment. The subject matter can be embodied in a variety of different forms, and therefore, the covered or claimed subject matter is intended to be interpreted as not being limited to any of the exemplary embodiments described herein; exemplary embodiments are provided for illustrative purposes only. Similarly, the claimed or covered subject matter should also be reasonably broad. For example, among other things, the subject matter can be embodied as a method, apparatus, component, or system. Accordingly, embodiments can take the form of hardware, software, firmware, or any combination thereof. Therefore, the following detailed description is not intended to be limiting.

[0023] Throughout the specification and claims, terms may imply or carry subtle meanings in the context of their explicit meaning, in addition to their express meaning. Similarly, the phrases “in one embodiment” or “in some embodiments” as used herein do not necessarily refer to the same embodiment, and the phrase “in another embodiment” as used herein does not necessarily refer to different embodiments. For example, it is intended that the claimed subject matter encompasses a combination of all or some exemplary embodiments.

[0024] Although the terminology used below is used in conjunction with specific embodiments of certain examples in this disclosure, these terms can be interpreted in the broadest reasonable sense. In fact, some terms may even be emphasized below; however, this Detailed Description section will provide a clear and specific definition of any term intended to be interpreted in any limiting manner.

[0025] Figure 1This is a diagram of a financial transaction system 100, according to an example embodiment, for settling payments between bank accounts associated with a registered user (e.g., customer 101) and a merchant (e.g., merchant 113). More specifically, system 100 includes the generation and use of payment devices. System 100 includes customer 101, payment instrument 103, issuer 105, communication network 107, transaction processing system 109, database 111, merchant 113, image generation system 115, and user device 117.

[0026] Customer 101 may be an individual, company, or other entity that has one or more accounts with issuer 105. Customer 101 may typically have at least one payment instrument 103 associated with the payment account of issuer 105. In one embodiment, customer 101 is a registered user of payment-related services of transaction processing system 109. Payment instrument 103 may be a credit card, debit card, prepaid card, etc. Payment instrument 103 may be a traditional plastic transaction card, a transaction card containing titanium or other metals, a transparent and / or semi-transparent transaction card, a foldable or other unconventional size transaction card, a radio frequency-enabled transaction card, or other types of transaction cards, such as debit cards, prepaid cards or stored-value cards, electronic rights transfer cards, charge cards, credit cards, or any other similar financial transaction instruments.

[0027] Issuer 105 may be a bank managing a payment account on behalf of customer 101. For example, issuer 105 may hold customer 101's account, and payment instrument 103 may be attached to that account. In another embodiment, issuer 105 is a bank managing a payee's account on behalf of merchant 113. For example, issuer 105 may hold merchant 113's account, and merchant 113 may receive payments for goods and services offered in that account.

[0028] Various components of system 100 can communicate with each other via communication network 107. Communication network 107 can support a variety of different communication protocols and technologies. In one embodiment, communication network 107 allows transaction processing system 109 to communicate with customer 101, issuer 105, and merchant 113. Communication network 107 of system 100 includes one or more networks, such as data networks, wireless networks, telephone networks, or any combination thereof. The data network is contemplated to be any local area network (LAN), metropolitan area network (MAN), wide area network (WAN), public data network (e.g., the Internet), short-range wireless network, or any other suitable packet-switched network, such as commercially owned proprietary packet-switched networks, such as proprietary cable or fiber optic networks, or any combination thereof. Additionally, for example, the wireless network can be a cellular communication network and can employ various technologies, including 5G (fifth generation), 4G, 3G, 2G, LTE, Wi-Fi, Bluetooth®, Internet Protocol (IP) data broadcast, satellite, MANET, CAN bus, or any combination thereof.

[0029] Transaction processing system 109 may be a platform with multiple interconnected components. Transaction processing system 109 may include one or more servers, smart networked devices, computing devices, components, and corresponding software for settling payments between bank accounts associated with customer 101 and merchant 113 involved in the transaction. Transaction processing system 109 may verify customer 101's access credentials to authorize access to payment-related services.

[0030] Merchant 113 may be a merchant providing goods and / or services to customer 101. Merchant 113 may be equipped with a POS device (not shown) configured to receive payment information from payment instrument 103 and forward the received payment information to transaction processing system 109. Merchant 113 may be any type of merchant, such as a physical retail store or an e-commerce / online merchant equipped with a POS device or online payment interface. In one embodiment, merchant 113 registers with transaction processing system 109 to obtain payment-related services.

[0031] Image generation system 115 may be owned, contracted to, or otherwise attached to issuer 105 and may be configured to generate images for payment instrument 103. Specifically, image generation system 115 is configured to generate background images and / or patterns to be displayed on payment instrument 103. Customer 101 may access image generation system 115 through an online portal attached to issuer 105. In some embodiments, customer 101 may access image generation system 115 during account setup with issuer 105, after application for payment instrument 103 is approved, and / or at other times during the duration of the relationship between customer 101 and issuer 105. Image generation system 115 may perform various processes, such as generating images using an artificial intelligence engine that will be described herein.

[0032] In some embodiments, the image generation system 115 may include, or communicate with, various third-party services (not shown) that generate images based on input received from the client 101. The image generation system 115 may be accessed via a user equipment 117 associated with the client 101.

[0033] User equipment 117 typically includes input / output devices (e.g., touchscreen display, keyboard, monitor, etc.) that enable client 101 to access and / or interact with other components in system 100. For example, user equipment 117 may be a computer system, such as a desktop computer, laptop computer, server, mobile device, tablet, etc. In some embodiments, user equipment 117 may include one or more electronic applications, such as programs, plugins, browser extensions, etc., installed on the memory of user equipment 117. In some embodiments, the electronic applications may be associated with one or more other components in system 100. For example, the electronic applications may allow client 101 to interact with image generation system 115.

[0034] Now refer to Figure 2 An exemplary payment device 200 (such as...) is shown. Figure 1 Payment instrument 103). Payment device 200 can be used as a payment method, allowing cardholders (e.g., Figure 1 Customer 101) from merchants (e.g., Figure 1 Merchant 113) purchases goods and / or services. Transaction funds may be withdrawn from the issuer of payment device 200 (e.g., Figure 1The payment device 200 obtains a credit line from the issuer (105) extending credit to the cardholder, and / or from a bank account maintained by the issuer of the payment device 200 in the cardholder's name. The payment device 200 includes various identification markers, such as an account number 210 associated with the credit line and / or bank account, and the cardholder's name 220. The payment device 200 may also include a chip 230 or other readable element that allows a reader / scanner of a merchant device (not shown) to communicate with the issuer of the payment device 200 to verify that the cardholder has sufficient credit and / or funds to pay for the purchase. The payment device 200 may also include an expiry date 240. The payment device 200 includes a background image 250 covering part or all of the payment device 200. In some embodiments, the payment device 200 may generally be rectangular, having a length of approximately 3.375 inches and a height of approximately 2.125 inches, but it should be understood that the scope of this disclosure also covers other shapes and sizes.

[0035] Now refer to Figure 3 It shows the methods for generating images (such as those used for...). Figure 1 Payment instruments 103 and / or Figure 2 The architecture 300 (image of payment device 200). Architecture 300 may be, for example, Figure 1 An image generation system 115 is implemented. Architecture 300 includes an input module 310 that receives input from one or more sources. For example, the input may include at least one image criterion defining the target image attributes desired by a user (e.g., client 101). For example, the input module 310 may be configured to receive user input to a user device (e.g., ...). Figure 1 The text prompt in the user device 117). In the example shown, the input includes the text "an astronaut on horseback", which prompts the architecture 300 to generate an image including an astronaut on horseback.

[0036] Continue to refer to Figure 3 Architecture 300 also includes an artificial intelligence module 320, which receives input from input module 310 and applies one or more artificial intelligence models 326 to the input to generate one or more images. In some embodiments, the artificial intelligence module 320 may include an encoder-decoder architecture, such as... Figure 3As shown in the diagram, other architectures may also be used. Artificial intelligence module 320 includes an embedding module 322 that generates embeddings based on text from input module 310. Embedding module 322 may receive data from database 330. Data in database 330 may include multiple existing images from one or more sources, such as images from multiple web pages available on the Internet. Generally, the more data points from database 330 analyzed by embedding module 322, the more robust artificial intelligence module 320 becomes. For example, using more data points allows embedding module 322 to increase the dimensionality of the generated embeddings. While database 330 may include images obtained from the Internet, other sources such as proprietary image databases may also be used to form database 330.

[0037] Continue to refer to Figure 3 The artificial intelligence module 320 also includes an encoder 324 that generates a vector representation of the input from the input module 310 based on the embedding generated by the embedding module 322. The encoder 324 sends the vector representation to one or more artificial intelligence models (AI models) 326. In some embodiments, the AI ​​model 326 includes a pixel and image diffusion model, but other models may be used alternatively or additionally. In some embodiments, the AI ​​model 326 includes a pixel space and a latent space. The AI ​​model 326 can generate new, unique images based on the input from the input module 310 using a set of training images from an external database 340. The AI ​​model 326 can perform various functions, such as conditionalization, denoising, cross-fading, etc., to generate one or more images based on the vector representation received from the encoder 324.

[0038] Continue to refer to Figure 3 The artificial intelligence module 320 also includes a decoder 328, which is configured to output one or more images 350 based on the output of the AI ​​model 326. That is, each image 350 includes a subject and any other attributes provided by the input module 310. Each image 350 is unique (i.e., it is generated for the first time by the AI ​​model 326).

[0039] In some embodiments, the artificial intelligence module 320 can be a third-party system, such as DALL-E, DALL-E 2, or Stable Diffusion. It can be accessed via... Figure 1 The user devices associated with customer 101 and / or issuer 105 (e.g., Figure 1 The user equipment 117) accesses such a system through its application programming interface (API). Therefore, the input to the input module 310 can be accessed via... Figure 1The user device 117 receives the input and sends it to the third-party artificial intelligence module 320 via API. One or more images 350 can be returned to the user device 117 via API for further use and / or processing by the client 101 and / or the issuer 105.

[0040] Now refer to Figure 4 It shows the method for generating payment devices (such as...) Figure 1 Payment instruments 103 and / or Figure 2 A flowchart of a method 400 for generating an image of a payment device 200. Each step in steps 401-410 of method 400 may be automatically executed by at least one processor, such as a controller 1100 associated with the image generation system 115 and / or the user equipment 117 (see [link to flowchart]). Figure 11 The various steps 401-410 of method 400 may include displaying or performing in conjunction with one or more user interfaces on user equipment 117. Accordingly, in the following description of method 400, reference is made to... Figures 6 to 10 The user interface numbers are 600, 620, 640, 660, and 680.

[0041] Continue to refer to Figure 4 Method 400 includes: in step 401, receiving a user (e.g., Figure 1 Customer 101) and payment card (e.g., Figure 1 Payment instruments 103 and / or Figure 2 The identifier associated with the payment device 200. This identifier may include, for example, the user's account (e.g., ...). Figure 2 The identifier may include the user's account number 210, user PIN, user login credentials, or other information that explicitly links the user to the payment card. By associating the user with the payment card in this way, subsequent steps of method 400 are linked to the specific payment card associated with that identifier.

[0042] Continue to refer to Figure 4Method 400 includes: in step 402, receiving at least one image criterion for a target image associated with a user associated with a payment card. In some aspects, the at least one image criterion includes one or more of the following: the subject of the target image, the color scheme of the target image, the artistic style of the target image, or the content criterion of the target image. The subject of the target image may include one or more people, animals, objects, landscapes, backgrounds, shapes, etc., included in the target image. The color scheme of the target image may include a palette of one or more colors used in the target image. In some aspects, the color scheme may include one or more colors associated with a specific component of the subject (e.g., a red house). In some aspects, the color scheme may include a monochrome palette, such as black and white, grayscale, sepia, etc. The artistic style of the target image may include one or more different styles, such as line drawing, photography, graphic art, oil painting, etc.

[0043] The aforementioned image criteria (subject, color scheme, and artistic style) can all be derived from... Figure 1 User equipment 117 receives user input. Therefore, it allows users (e.g., Figure 1 Customer 101) selects and customizes the attributes of the target image based on using at least one image criterion. Specifically, the image criteria can be input into... Figure 6 In the text field 602 of the user interface 600.

[0044] In some aspects, the at least one image guideline may also include non-user input guidelines, such as image content guidelines. Non-user input guidelines include one or more image guidelines that prevent users from selecting, deviating from, or covering the image. For example, the content guidelines may include restrictions on the target image, prohibiting the use of themes that may be considered profane, offensive, threatening, or otherwise unsuitable for public display.

[0045] After the image criteria have been received, they are sent as input to the artificial intelligence engine, for example, to... Figure 3 The input module 310 of the architecture 300. Users can select... Figure 6 The user interface 600 uses command element 604 to initiate the sending of the image guidelines.

[0046] Continue to refer to Figure 4 Method 400 includes: in step 404, receiving an artificial intelligence engine (e.g., Figure 3The artificial intelligence module 320 generates multiple preliminary images based on the at least one image criterion received in step 402. Each of the multiple preliminary images satisfies all the image criteria of the at least one image criterion in step 402. For example, if the image criterion includes the themes "beach" and "sunrise," then all the preliminary images include beach and sunrise. Similarly, if the image criterion includes the art style of oil painting, then all the preliminary images are generated in the style of oil painting. Similarly, all the preliminary images do not contain any content prohibited by the content criterion.

[0047] Each preliminary image is uniquely generated for the purposes of method 400. That is, the preliminary image is not (or does not include) a stock image. Furthermore, each preliminary image can be unique for a particular iteration of method 400. That is, the preliminary image generated in step 404 will not be reproducible during another iteration of method 400.

[0048] The initial image generated by the artificial intelligence engine (e.g., Figure 3 Image 350) is sent to user equipment 117 for display to client 101. For example, the preliminary image is displayed as... Figure 7 Images 622 and 624 of the user interface 620.

[0049] Continue to refer to Figure 4 Method 400 includes: in step 406, receiving a user (e.g., Figure 1 Image selection for customer 101. This image selection includes selecting an image from multiple preliminary images. This image selection can correspond to... Figure 7 One of images 622 and 624 is displayed on the user interface 620. Specifically, the user (e.g., Figure 1 Customer 101) can select a preferred image from images 622 and 624.

[0050] Continue to refer to Figure 4 Method 400 includes: in step 408, displaying a selected image superimposed on a virtual representation of the payment card. For example... Figure 8 As shown, the selected image 642 is overlaid on the virtual representation of the payment card 644. The selected image 642 is arranged to completely cover the virtual representation of the payment card 644. The selected image 642 may be larger than the virtual representation of the payment card 644 to allow the virtual representation of the payment card 644 to adjust the selected image 642, as described herein.

[0051] Continue to refer to Figure 4Method 400 includes: in step 410, setting at least one size parameter of the selected image to fit the size of the payment card. The at least one size parameter may include, for example, the resolution of the selected image, the size of the selected image, and the orientation of the selected image. Setting the size parameter ensures that the size of the selected image is sufficient to cover a designated area of ​​the payment card, such as the entire payment device. Alternatively, setting the size parameter may ensure that the resolution of the selected image is sharp when adjusted to fit the size of the payment card. Furthermore, setting the size parameter may ensure that a specific portion of the image covers the payment card. For example, the selected image 642 may be set such that the sun is located at the center focal point of a virtual representation of the payment card 644, such as... Figure 8 As shown.

[0052] Now refer to Figure 5 It shows the method for generating payment devices (such as...) Figure 1 Payment instruments 103 and / or Figure 2 A flowchart of another method 500 for generating an image of a payment device 200. Each step in steps 502-528 of method 500 may be automatically executed by at least one processor, such as a controller 1100 associated with the image generation system 115 and / or user equipment 117 (see [link to flowchart]). Figure 11 In the following description of method 500, various steps 502-528 may include displaying or performing in conjunction with one or more user interfaces on user equipment 117. Accordingly, in the following description of method 500, reference is made to... Figures 6 to 10 The user interface numbers are 600, 620, 640, 660, and 680.

[0053] Continue to refer to Figure 5 Method 500 includes: in step 501, receiving a user (e.g., Figure 1 The method 500 further includes, in step 502, receiving the identifier associated with the payment card (e.g., customer 101). Figure 1 The method 500 further includes: in step 504, receiving a plurality of preliminary images generated by an artificial intelligence engine. Steps 501, 502, and 504 may substantially correspond to at least one image criterion associated with the target image of customer 101. Figure 4 Method 400 includes steps 401, 402, and 404.

[0054] Continue to refer to Figure 5 Step 502 can precede step 520, which includes generating a user profile associated with the payment card. This user profile can be linked to... Figure 1The system is associated with customer 101 and allows customer 101 access to image generation system 115. After customer 101's credit limit is approved by issuer 105, a user profile can be generated. For example, user profile generation can be performed during the setup process of payment instrument 103.

[0055] Continue to refer to Figure 5 Method 500 may further include: in step 522, receiving user feedback on the preliminary image set received in step 504. The user feedback indicates to the user (e.g., Figure 1 The user 101) decides whether they want to replace any or all of the preliminary images with a new image. In step 524, if the user does not request a new image, method 500 proceeds to step 506: receiving the user's image selection. This image selection includes an image chosen from the plurality of preliminary images. Step 506 may substantially correspond to step 406 of method 400.

[0056] In step 524, if the user requests one or more new images, method 500 continues to step 526: receiving a replacement image of at least one of the plurality of preliminary images based on the user feedback from step 522. In some embodiments, receiving the replacement image in step 526 may be similar to receiving the preliminary image in step 504. Specifically, the at least one image criterion received in step 502 is sent as input to an artificial intelligence engine (e.g., Figure 3 The artificial intelligence module 302), and the artificial intelligence engine then generate the replacement image. In some embodiments, the user can correct or modify the at least one image criterion (e.g., by modifying...). Figure 6 The text in field 602 of the user interface 620 is used to prompt the AI ​​engine to generate an image with an improved theme, color scheme, art style, etc., relative to the preliminary image received in step 504.

[0057] Method 500 then proceeds to step 506. In this case, the selected image in step 506 may be one of the preliminary images received in step 504 or one of the replacement images received in step 526.

[0058] Continue to refer to Figure 5 Method 500 may further include: in step 508, displaying a selected image superimposed on a virtual representation of the payment card. Method 500 may further include: in step 510, setting at least one size parameter of the selected image to fit the size of the payment card. Steps 508 and 510 may substantially correspond to steps 408 and 410 of method 400, respectively.

[0059] Continue to refer to Figure 5The method 500 may further include: in step 528, adjusting at least one layout parameter of the selected image based on user feedback. The at least one layout parameter may include, for example, the position of the target image relative to the payment card, the scaling level of the target image, etc. In some embodiments, the user (e.g., customer 101) can... Figure 8 One or more image manipulation commands 646 (and / or) of the user interface 640 Figure 9 The user interface 660 provides user feedback through similar image manipulation commands 666. For example, image manipulation commands 646 may include: one or more zoom commands to zoom in or out of the selected image 642 relative to a virtual representation of the payment card 644; one or more commands to move the selected image 642 to a position relative to a virtual representation of the payment card 644; one or more rotation commands to rotate the selected image 642 relative to a virtual representation of the payment card 644; one or more flip commands to flip (i.e., mirror) the selected image 642 relative to a virtual representation of the payment card 644; and a reset command to return the selected image 642 to its default position and / or orientation relative to a virtual representation of the payment card 644.

[0060] As mentioned above, Figures 6-10 Depicting in Figure 2 During the generation of the payment device 200, in the device (e.g., Figure 1 A series of user interfaces 600, 620, 640, 660, and 680 are displayed on the user device 117. For example, they can be accessed from the issuer of the payment device (e.g., Figure 1 The online portal associated with the issuer (105) provides access to user interfaces 600, 620, 640, 660, and 680. In some respects, such as during the account setup process, after the user has applied for and been granted a credit line by the issuer, the user can access user interfaces 600, 620, 640, 660, and 680.

[0061] Specific reference Figure 6Field 602 may be an unstructured text field where a user can input natural language text, such as “a painting of people watching the sunset”. In other embodiments, field 602 may include dropdown menus or other structured inputs to facilitate input of the at least one image criterion. In the example shown, all of the criteria provided by the user are input into the same field 602. For example, the user may input a theme, color scheme, and art style as part of the same text string into field 602. In the example shown, field 602 includes a theme (“people watching the sunset”) and an art style (“a painting”). When the at least one image criterion is input as an unstructured text string, the user device and / or artificial intelligence engine may parse the unstructured text to identify specific attributes of the at least one image criterion (e.g., theme, color scheme, art style). In some embodiments, field 602 may include a speech-to-text function that generates text input based on the user’s speech (e.g., the user may speak “people watching the sunset” into a microphone associated with user device 117, and the processor may generate an equivalent text string for field 602).

[0062] Continue to refer to Figure 6 The user interface 600 may also include a command element 604 (e.g., a button) to initiate a transition from field 602 to the artificial intelligence engine (e.g., Figure 3 The transmission of input to the artificial intelligence module 320.

[0063] Now refer to Figure 7 Images 622 and 624 of the user interface 620 may represent all or a portion of the preliminary images received in step 404 of method 400. In some embodiments, the user interface 620 may be scrollable to display additional images from the set of preliminary images received in step 404 of method 400.

[0064] Now refer to Figure 8 The selected image 642 is displayed as an overlay on a virtual representation of the payment card 644. Clearly, the selected image 642 can be larger than the payment card to allow for automatic and / or manual repositioning. The processor (e.g., Figure 11 The processor of controller 1100 automatically sets the default position of the selected image 642 relative to the virtual representation of payment card 644, as described in step 410 of method 400. The default position can be determined according to the principle of making a specific subject of the selected image 642 stand out and not be obscured by the markings of the payment card (e.g., customer name, account number, chip, etc.).

[0065] Now refer to Figure 9After the user manipulates the image layout, the selected image 662 is displayed as a virtual representation overlaid on the payment card 664, as described in step 528 of method 500. Specifically, according to Figure 8 The selected image 642 is reduced to the selected image 662, so that more of the selected image falls within the boundary of the payment card.

[0066] Figure 10 The user interface 680 shows the final version of the payment card as printed, where the selected image is cropped to the size of a virtual representation of the payment card 684.

[0067] Unless otherwise specified, it will be apparent from the discussion below that throughout the discussion of this specification that the use of terms such as “processing,” “operation,” “calculation,” “determine,” “analysis,” or similar terms refers to the operation and / or process of a computer or computing system or similar electronic computing device that manipulates and / or converts data expressed in physical quantities (such as electronic quantities) into other data expressed in the same physical quantities.

[0068] In a similar manner, the term "processor" can refer to any device or part of a device that processes electronic data, for example, processing electronic data from registers and / or memory, or converting that electronic data into other electronic data that can be stored in registers and / or memory. "Computer," "computing machine," "computing platform," "computing device," or "server" can include one or more processors.

[0069] Figure 11 It shows the use of devices (e.g.) Figure 1 The controller 1100 is used in the image generation system 115 and / or user equipment 117. The controller 1100 may include a set of instructions that, when executed, cause the controller 1100 to perform any one or more methods or computer-based functions disclosed herein. The controller 1100 may operate as a stand-alone device or may be connected to other computer systems or peripheral devices via networks or other means.

[0070] In a network deployment, controller 1100 may operate as a server, or as a client computer in a server-client user network environment, or as a peer-to-peer computer system in a point-to-point (or distributed) network environment. Controller 1100 may also be implemented as or incorporated into various devices, such as personal computers (PCs), tablet computers, set-top boxes (STBs), personal digital assistants (PDAs), mobile devices, handheld computers, laptop computers, desktop computers, communication equipment, cordless phones, landline phones, control systems, cameras, scanners, fax machines, printers, pagers, personal trusted devices, global network devices, network routers, switches, or bridges, or any other machine capable of executing a set of instructions (sequential or other instructions) specifying the actions to be performed by that machine. In certain embodiments, controller 1100 may be implemented using electronic devices that provide voice, video, or data communication. Furthermore, while a single controller 1100 is shown, the term "controller" should also be considered as including any collection of systems or subsystems that may individually or collectively execute one or more sets of instructions to perform one or more computer functions.

[0071] like Figure 11 As shown, controller 1100 may include processor 1102, such as a central processing unit (CPU), graphics processing unit (GPU), or both. The processor 1102 can be a component in various systems. For example, the processor 1102 may be part of a standard personal computer or workstation. The processor 1102 may be one or more general-purpose processors, digital signal processors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), servers, networks, digital circuits, analog circuits, combinations thereof, or other currently known or later-developed devices for analyzing and processing data. The processor 1102 can execute software programs, such as manually generated (i.e., programmed) code.

[0072] The controller 1100 may include a memory 1104 communicatable via a bus 1108. The memory 1104 may be main memory, static memory, or dynamic memory. The memory 1104 may include, but is not limited to, computer-readable storage media, such as various types of volatile and non-volatile storage media, including but not limited to random access memory, read-only memory, programmable read-only memory, electrically programmable read-only memory, electrically erasable read-only memory, flash memory, magnetic tape or disk, optical media, etc. In one embodiment, the memory 1104 includes a cache or random access memory for the processor 1102. In alternative embodiments, the memory 1104 is decoupled from the processor 1102, such as the processor's cache memory, system memory, or other memory. The memory 1104 may be an external storage device or database for storing data. Examples include hard disk drives, optical discs (“CDs”), digital video discs (“DVDs”), memory cards, memory sticks, floppy disks, universal serial bus (“USB”) storage devices, or any other device that can be used to store data. The memory 1104 is operable to store instructions executable by the processor 1102. The functions, behaviors, or tasks shown in the figures or described herein can be executed by the programmed processor 1102, which executes instructions stored in the memory 1104. Each function, behavior, or task is independent of a specific type of instruction set, storage medium, processor, or processing strategy, and can be executed by software, hardware, integrated circuits, firmware, microcode, etc., running individually or in combination. Similarly, processing strategies can include multiprocessing, multitasking, parallel processing, etc.

[0073] As shown in the figure, the controller 1100 may further include a display unit 1110, such as a liquid crystal display (LCD), an organic light-emitting diode (OLED), a flat panel display, a solid-state display, a cathode ray tube (CRT), a projector, a printer, or other currently known or later-developed display devices for outputting determined information. The display 1110 may serve as an interface for the user to view the operation of the processor 1102, or specifically as an interface with software stored in the memory 1104 or the drive unit 1106.

[0074] Alternatively, the controller 1100 may also include an input device 1112 configured to allow a user to interact with any component of the controller 1100. The input device 1112 may be a numeric keypad, keyboard, or cursor control device, such as a mouse, joystick, touchscreen display, remote control, or any other device that interacts with the controller 1100.

[0075] The controller 1100 may also (or alternatively) include a disk drive unit or an optical drive unit 1106. The disk drive unit 1106 may include a computer-readable medium 1122 in which one or more sets of instructions 1124, such as software, may be embedded. Furthermore, the instructions 1124 may embody one or more methods or logic described herein. During execution by the controller 1100, the instructions 1124 may be wholly or partially located in the memory 1104 and / or the processor 1102. As mentioned above, the memory 1104 and the processor 1102 may also include computer-readable media.

[0076] In some systems, computer-readable medium 1122 includes instructions 1124, or receives and executes instructions 1124 in response to a propagating signal, enabling devices connected to network 1170 to transmit voice, video, audio, images, or any other data through network 1170. Furthermore, the instructions 1124 can be sent or received through network 1170 via communication port or interface 1120 and / or using bus 1108. The communication port or interface 1120 can be part of processor 1102 or a separate component. The communication port 1120 can be created in software or as a physical connection in hardware. The communication port 1120 can be configured to connect to network 1170, external media, display 1110, or any other component or combination thereof in controller 1100. The connection to network 1170 can be a physical connection, such as a wired Ethernet connection, or it can be established wirelessly, as described below. Similarly, additional connections to other components of controller 1100 can be physical connections or can be established wirelessly. The network 1170 can alternatively be directly connected to the bus 1108.

[0077] Although computer-readable medium 1122 is shown as a single medium, the term "computer-readable medium" can include a single medium or multiple media, such as a centralized or distributed database, and / or associated caches and servers storing one or more sets of instructions. The term "computer-readable medium" can also include any medium capable of storing, encoding, or carrying a set of instructions that can be executed by a processor or cause a computer system to perform any one or more methods or operations disclosed herein. The computer-readable medium 1122 can be a non-transitory computer-readable medium and can be a tangible computer-readable medium.

[0078] The computer-readable medium 1122 may include solid-state memory, such as a memory card or other package containing one or more non-volatile read-only memories. The computer-readable medium 1122 may be random access memory or other volatile rewritable memory. Alternatively or additionally, the computer-readable medium 1122 may include magneto-optical or optical media, such as disks, magnetic tapes, or other storage devices, for capturing carrier signals, such as signals transmitted via a transmission medium. Digital file attachments to emails or other independent information archives or sets of archives can be considered distribution media, i.e., tangible storage media. Accordingly, this disclosure can be considered as including any one or more of computer-readable media or distribution media, and other equivalent and subsequent media, in which data or instructions can be stored.

[0079] In alternative implementations, dedicated hardware implementations, such as application-specific integrated circuits (ASICs), programmable logic arrays (PLA), and other hardware devices, can be constructed to implement one or more methods described herein. Applications of devices and systems that may include various implementations can broadly encompass a wide range of electronic and computer systems. One or more implementations described herein may utilize two or more specific interconnected hardware modules or devices to achieve functionality, employing associated control and data signals that can be transferred between or through modules, or as part of an ASIC. Accordingly, this system encompasses software, firmware, and hardware implementations.

[0080] Controller 1100 can be connected to one or more networks 1170. Network 1170 can define one or more networks, including wired or wireless networks. The wireless network can be a cellular telephone network, 802.11, 802.16, 802.20, or WiMAX network. Furthermore, such networks can also include public networks (such as the Internet), private networks (such as intranets), or combinations thereof, and can utilize various existing or subsequently developed network protocols, including but not limited to TCP / IP-based network protocols. Network 1170 can include a wide area network (WAN) (such as the Internet), a local area network (LAN), a campus network, a metropolitan area network, a direct connection (such as via a universal serial bus (USB) port), or any other network capable of data communication. Network 1170 can be configured to couple one computing device to another to enable inter-device data communication. Typically, this enables network 1170 to use any form of machine-readable medium for transmitting information from one device to another. Network 1170 can include communication methods for transmitting information between computing devices. Network 1170 can be divided into subnetworks. The subnetwork may allow access to all other components connected to it, or the subnetwork may restrict access between components. The network 1170 may be considered a public or private network connection and may include, for example, encryption or other security mechanisms used on the public Internet, such as a virtual private network.

[0081] According to various embodiments of this disclosure, the methods described herein can be implemented by a computer system executable software program. Furthermore, in exemplary, non-limiting embodiments, implementations may include distributed processing, component / object distributed processing, and parallel payments. Alternatively, virtual computer system processing can be constructed to implement one or more methods or functions described herein.

[0082] Although this specification describes components and functions that can be implemented in specific embodiments with reference to particular standards and protocols, this disclosure is not limited to such standards and protocols. For example, Internet and other packet-switched network transport standards (e.g., TCP / IP, UDP / IP, HTML, HTTP, etc.) represent examples of the current state of technology. Such standards are periodically superseded by equivalent standards that are substantially the same in function but faster or more efficient. Accordingly, alternative standards and protocols that have the same or similar functions as the standards and protocols disclosed herein can be considered their equivalents.

[0083] It should be understood that, in one embodiment, the steps of the method in question are performed by a suitable processor of a processing (i.e., computer) system that executes instructions (computer-readable code) stored in memory. It should also be understood that the disclosed embodiments are not limited to any particular implementation method or programming technique, and the disclosed embodiments can be implemented using any suitable technique to achieve the functions described herein. The disclosed embodiments are not limited to any particular programming language or operating system.

[0084] It should be understood that in the foregoing description of exemplary embodiments, various features of the embodiments are sometimes concentrated in a single embodiment, drawing, or description in order to simplify this disclosure and aid in understanding one or more different aspects of the invention. However, this approach to disclosure should not be construed as reflecting an intention that the claimed embodiment requires more features than are expressly set forth in each claim. Rather, as reflected in the following claims, the inventiveness of this disclosure lies in not fully encompassing all features of the single disclosed embodiment described above. Therefore, the claims following the detailed description are hereby expressly incorporated into this detailed description, each claim existing independently as a separate embodiment.

[0085] Furthermore, those skilled in the art will understand that while some embodiments described herein include certain features, they do not include other features included in other embodiments. However, combinations of features from different embodiments fall within the scope of this disclosure and form different embodiments. For example, any claimed embodiment can be used in any combination within the following claims.

[0086] Many specific details are set forth in the description provided herein. However, it should be understood that embodiments of this disclosure may be practiced without these specific details. In other instances, well-known methods, structures, and techniques have not been shown in detail so as not to affect the understanding of this description.

[0087] The subject matter disclosed above should be considered illustrative rather than restrictive, and the appended claims are intended to cover all such modifications, enhancements, and other embodiments that fall within the true spirit and scope of this disclosure. Therefore, to the maximum extent permitted by law, the scope of this disclosure should be determined by the broadest interpretation of the following claims and their equivalents, and should not be construed as limited by the foregoing specific embodiments. While various embodiments of this disclosure have been described, it will be apparent to those skilled in the art that further embodiments are possible within the scope of this disclosure. Accordingly, this disclosure is not limited except by the appended claims and their equivalents.

Claims

1. A method for generating a user-designed image for a payment card, the method comprising: At least one processor receives at least one image criterion for a target image associated with a user associated with a payment card; At least one processor receives multiple preliminary images generated by an artificial intelligence engine based on the at least one image criterion; The image selection by the user is received by at least one processor, the image selection comprising an image selected from a plurality of preliminary images; A selected image is displayed on a user interface by at least one processor overlaid on a virtual representation of the payment card; as well as At least one processor sets at least one size parameter of the selected image to fit the size of the payment card.

2. The method of claim 1, wherein the at least one image criterion comprises at least one of the following: The subject of the target image; The color scheme of the target image; The artistic style of the target image; or The content criteria of the image.

3. The method of claim 1, wherein the at least one dimensional parameter comprises at least one of the following: The resolution of the selected image; The size of the selected image; or The orientation of the target image.

4. The method according to claim 1, further comprising: User feedback on the initial image set is received by at least one processor; as well as A replacement image is received by at least one of the plurality of preliminary images based on the user feedback by at least one processor.

5. The method according to claim 1, further comprising: The at least one processor adjusts at least one layout parameter of the selected image based on user feedback. The at least one layout parameter includes at least one of the following: The position of the target image relative to the payment card; or The scaling levels of the target image.

6. The method of claim 1, wherein each of the plurality of preliminary images is uniquely generated by the artificial intelligence engine.

7. The method according to claim 1, further comprising: Before receiving the at least one image criterion, at least one processor generates a user profile associated with the payment card.

8. A computer system for generating user-designed images for payment cards, the computer system comprising: At least one memory, wherein the at least one memory stores processor-readable instructions; as well as At least one processor is configured to access the memory and execute processor-readable instructions, which, when executed by the processor, configure the processor to perform a plurality of functions, including functions for the following: At least one image criterion for receiving the target image; Receive multiple preliminary images generated by the artificial intelligence engine based on the at least one image criterion; Receive image selection, the image selection including an image selected from the plurality of preliminary images; Display a selected image overlaid on the virtual representation of the payment card on the user interface; and Set at least one size parameter of the selected image to fit the size of the payment card.

9. The system of claim 8, wherein the at least one image criterion comprises at least one of the following: The subject of the target image; The color scheme of the target image; The artistic style of the target image; or The content criteria of the image.

10. The system of claim 8, wherein the at least one dimensional parameter comprises at least one of the following: The resolution of the selected image; The size of the selected image; or The orientation of the target image.

11. The system of claim 8, wherein the plurality of functions includes functions for: Receive user feedback on the initial image set; and Receive a replacement image of at least one of the plurality of preliminary images based on the user feedback.

12. The system of claim 8, wherein the plurality of functions includes the function of adjusting at least one layout parameter of the selected image based on user feedback; and The at least one layout parameter includes at least one of the following: The position of the target image relative to the payment card; or The scaling levels of the target image.

13. The system of claim 8, wherein each of the plurality of preliminary images is uniquely generated by the artificial intelligence engine.

14. The system of claim 8, wherein the plurality of functions includes a function for generating a user profile associated with the payment card by at least one processor prior to receiving the at least one image criterion.

15. A non-transitory computer-readable medium comprising instructions for generating a user-designed image for a payment card, the non-transitory computer-readable medium storing the instructions, which, when executed by at least one processor, configure the at least one processor to perform the following operations: Receive at least one image criterion for a target image associated with a user associated with a payment card; Receive multiple preliminary images generated by the artificial intelligence engine based on the at least one image criterion; Receive the user's image selection, the image selection including an image selected from the plurality of preliminary images; Display a selected image overlaid on the virtual representation of the payment card on the user interface; and Set at least one size parameter of the selected image to fit the size of the payment card.

16. The non-transitory computer-readable medium of claim 15, wherein the at least one image criterion comprises at least one of the following: The subject of the target image; The color scheme of the target image; The artistic style of the target image; or The content criteria of the image.

17. The non-transitory computer-readable medium of claim 15, wherein the at least one dimensional parameter includes at least one of the following: The resolution of the selected image; The size of the selected image; or The orientation of the target image.

18. The non-transitory computer-readable medium of claim 15, wherein the instructions configure the at least one processor to perform the following operations: Receive user feedback on the initial image set; and Receive a replacement image of at least one of the plurality of preliminary images based on the user feedback.

19. The non-transitory computer-readable medium of claim 15, wherein the instructions configure the at least one processor to perform an adjustment of at least one layout parameter of the selected image based on user feedback; and The at least one layout parameter includes at least one of the following: The position of the target image relative to the payment card; or The scaling levels of the target image.

20. The non-transitory computer-readable medium of claim 15, wherein each of the plurality of preliminary images is uniquely generated by the artificial intelligence engine.

Images