Detection and direction of contactless device interaction location using imaging

Abstract

A method includes a user device, comprising a camera and a first radio frequency antenna, capturing an image of at least a portion of an access device comprising a second radio frequency antenna. The user device can display, by a display screen, the image along with an indicator of a location of the second radio frequency antenna on the access device. Responsive to the displaying, the user device can be moved such that the first radio frequency antenna is proximate to the second radio frequency antenna. The user device can communicate with the access device via the first radio frequency antenna and the second radio frequency antenna.

Description

DETECTION AND DIRECTION OF CONTACTLESS DEVICE INTERACTION LOCATION USING IMAGINGBACKGROUND

[0001] Most access devices have limited area to include extra components, thus leaving radio frequency antennas to be included with the access device at locations that vary between different models of access devices. The radio frequency antenna can be at a location where a user is prompted to tap their user device for device-to-device communication (also referred to as a landing plane). To achieve this, the user is informed that the access device is ready for payment and that the user is to present the user device in the proper location. At this point the user is expected to get the user device as close to the landing plane as possible to achieve payment.

[0002] In some cases, the landing plane can be indicated by a sticker that indicates a location to tap. Even though this area is marked with sticker or sometimes supported by illumination it can be difficult for users to see and identify the landing plane due to a number of reasons, including the following reasons.

[0003] Stress and the pressure to rush when using the access device can negatively affect the user’s ability to quickly identify the landing plane, open their user device, navigate to the correct application on the user device, and bring the user device to the landing plane for authorization.

[0004] Also, sometimes the landing plane can be located far from the actual access device screen making it more difficult for the user to locate the landing plane. This is particularly problematic for some users with a habit of tapping their user device to the access device screen directly.

[0005] Further, most of the time, when the user brings the user device to the access device, the user device blocks the direct line of sight from the user to the landing plane, thus further making tapping the correct location difficult.

[0006] There is also no standard method of illuminating or visually prominent marking the access device’s landing plane, thus making the landing plane more difficult for the user to recognize.

[0007] Embodiments of the disclosure address this problem and other problems individually and collectively.SUMMARY

[0008] One embodiment is related to a method comprising: capturing, by a camera in a user device comprising a first radio frequency antenna, an image of at least a portion of an access device comprising a second radio frequency antenna; displaying, by a display screen of the user device, the image along with an indicator of a location of the second radio frequency antenna on the access device, wherein responsive to the displaying, the user device moves such that the first radio frequency antenna is proximate to the second radio frequency antenna; and communicating, by the user device, with the access device via the first radio frequency antenna and the second radio frequency antenna.

[0009] Another embodiment is related to a user device comprising: a processor; and a computer-readable medium coupled to the processor, the computer-readable medium comprising code executable by the processor for implementing a method comprising: capturing, by a camera in the user device comprising a first radio frequency antenna, an image of at least a portion of an access device comprising a second radio frequency antenna; displaying, by a display screen of the user device, the image along with an indicator of a location of the second radio frequency antenna on the access device, wherein responsive to the displaying, the user device moves such that the first radio frequency antenna is proximate to the second radio frequency antenna; and communicating with the access device via the first radio frequency antenna and the second radio frequency antenna.

[0010] Another embodiment is related to a system comprising: a user device comprising: a first processor; and a first computer-readable medium coupled to the first processor, the first computer-readable medium comprising code executable by the first processor for implementing a first method comprising: capturing, by acamera in the user device comprising a first radio frequency antenna, an image of at least a portion of an access device comprising a second radio frequency antenna; displaying, by a display screen of the user device, the image along with an indicator of a location of the second radio frequency antenna on the access device, wherein responsive to the displaying, the user device moves such that the first radio frequency antenna is proximate to the second radio frequency antenna; and communicating with the access device via the first radio frequency antenna and the second radio frequency antenna; and the access device comprising: a second processor; and a second computer-readable medium coupled to the second processor, the second computer-readable medium comprising code executable by the second processor for implementing a second method comprising: communicating with the user device via the second radio frequency antenna and the first radio frequency antenna.

[0011] Further details regarding embodiments of the disclosure can be found in the Detailed Description and the Figures.BRIEF DESCRIPTION OF THE DRAWINGS

[0012] FIG. 1 shows a block diagram of a contactless device interaction location determination system according to embodiments.

[0013] FIG. 2 shows a block diagram of components of a user device according to embodiments.

[0014] FIG. 3 shows a block diagram of components of an access device according to embodiments.

[0015] FIG. 4 shows a flowchart of an artificial intelligence image recognition for location determination method according to embodiments.

[0016] FIG. 5 shows example images illustrating image element detection according to embodiments.

[0017] FIG. 6 shows an example image of augmented reality based instructions according to embodiments.

[0018] FIG. 7 shows a flowchart of a machine identification code image recognition for location determination method according to embodiments.

[0019] FIG. 8 shows an example image of machine identification code according to embodiments.DETAILED DESCRIPTION

[0020] Prior to discussing embodiments of the disclosure, some terms can be described in further detail.

[0021] A “user” may include an individual. In some embodiments, a user may be associated with one or more personal accounts and / or mobile devices. The user may also be referred to as a cardholder, account holder, or consumer in some embodiments.

[0022] A “user device” may be a device that is operated by a user. Examples of user devices may include a mobile phone, a smart phone, a card, a personal digital assistant (PDA), a laptop computer, a desktop computer, a server computer, a vehicle such as an automobile, a thin-client device, a tablet PC, etc. Additionally, user devices may be any type of wearable technology device, such as a watch, earpiece, glasses, etc. The user device may include one or more processors capable of processing user input. The user device may also include one or more input sensors for receiving user input. As is known in the art, there are a variety of input sensors capable of detecting user input, such as accelerometers, cameras, microphones, etc. The user input obtained by the input sensors may be from a variety of data input types, including, but not limited to, audio data, visual data, or biometric data. The user device may comprise any electronic device that may be operated by a user, which may also provide remote communication capabilities to a network. Examples of remote communication capabilities include using a mobile phone (wireless) network, wireless data network (e.g., 3G, 4G or similar networks), Wi-Fi, Wi-Max, or any other communication medium that may provide access to a network such as the Internet or a private network.

[0023] An “interaction” may include a reciprocal action or influence. An interaction can include a communication, contact, or exchange between parties,devices, and / or entities. Example interactions include a transaction between two parties and a data exchange between two devices. In some embodiments, an interaction can include a user requesting access to secure data, a secure webpage, a secure location, and the like. In other embodiments, an interaction can include a payment transaction in which two devices can interact to facilitate a payment.

[0024] “Interaction data” can include data related to and / or recorded during an interaction. In some embodiments, interaction data can be transaction data of the network data. Transaction data can comprise a plurality of data elements with data values.

[0025] An “access device” may be any suitable device that provides access to a remote system. An access device may also be used for communicating with a coordination computer, a communication network, or any other suitable system. An access device may generally be located in any suitable location, such as at the location of a merchant. An access device may be in any suitable form. Some examples of access devices include POS or point of sale devices (e.g., POS terminals), cellular phones, personal digital assistants (PDAs), personal computers (PCs), tablet PCs, hand-held specialized readers, set-top boxes, electronic cash registers (ECRs), vending machines, automated teller machines (ATMs), virtual cash registers (VCRs), kiosks, security systems, access systems, and the like.

[0026] An access device may use any suitable contact or contactless mode of operation to send or receive data from, or associated with, a mobile communication or payment device. For example, access devices can have card readers that can include electrical contacts, radio frequency (RF) antennas, optical scanners, bar code readers, or magnetic stripe readers to interact with portable devices such as payment cards.

[0027] A “resource provider” may be an entity that can provide a resource such as goods, services, information, and / or access. Examples of resource providers includes merchants, data providers, transit agencies, governmental entities, venue and dwelling operators, etc.

[0028] An “authorization request message” may be an electronic message that requests authorization for an interaction. In some embodiments, it is sent to atransaction processing computer and / or an issuer of a payment card to request authorization for a transaction. An authorization request message according to some embodiments may comply with International Organization for Standardization (ISO) 8583, which is a standard for systems that exchange electronic transaction information associated with a payment made by a user using a payment device or payment account. The authorization request message may include an issuer account identifier that may be associated with a payment device or payment account. An authorization request message may also comprise additional data elements corresponding to “identification information” including, by way of example only: a service code, a CW (card verification value), a dCVV (dynamic card verification value), a PAN (primary account number or “account number”), a payment token, a user name, an expiration date, etc. An authorization request message may also comprise “transaction information,” such as any information associated with a current transaction, such as the transaction value, merchant identifier, merchant location, acquirer bank identification number (BIN), card acceptor ID, information identifying items being purchased, etc., as well as any other information that may be utilized in determining whether to identify and / or authorize a transaction.

[0029] An “authorization response message” may be a message that responds to an authorization request. In some cases, it may be an electronic message reply to an authorization request message generated by an issuing financial institution or a transaction processing computer. The authorization response message may include, by way of example only, one or more of the following status indicators: Approval -- transaction was approved; Decline -- transaction was not approved; or Call Center -- response pending more information, merchant must call the toll-free authorization phone number. The authorization response message may also include an authorization code, which may be a code that a credit card issuing bank returns in response to an authorization request message in an electronic message (either directly or through the transaction processing computer) to the merchant's access device (e.g., PCS equipment) that indicates approval of the transaction. The code may serve as proof of authorization.

[0030] An “authorizing entity” may be an entity that authorizes a request. Examples of an authorizing entity may be an issuer, a governmental agency, adocument repository, an access administrator, etc. An authorizing entity may operate an authorizing entity computer. An “issuer” may refer to a business entity (e.g., a bank) that issues and optionally maintains an account for a user. An issuer may also issue payment credentials stored on a user device, such as a cellular telephone, smart card, tablet, or laptop to the consumer, or in some embodiments, a portable device.

[0031] “Credentials” may comprise any evidence of authority, rights, or entitlement to privileges. For example, access credentials may comprise permissions to access certain tangible or intangible assets, such as a building or a file. Examples of credentials may include passwords, passcodes, or secret messages. In another example, payment credentials may include any suitable information associated with and / or identifying an account (e.g., a payment account and / or payment device associated with the account). Such information may be directly related to the account or may be derived from information related to the account. Examples of account information may include an “account identifier” such as a PAN (primary account number or “account number”), a token, a subtoken, a gift card number or code, a prepaid card number or code, a user name, an expiration date, a CW (card verification value), a dCW (dynamic card verification value), a CW2 (card verification value 2), a CVC3 card verification value, etc. An example of a PAN is a 16-digit number, such as “4147 0900 0000 1234”. In some embodiments, credentials may be considered sensitive information.

[0032] An “antenna” can include a device used to transmit and / or receive signals. An antenna can be a rod, a wire, a chip, a chipset, etc. that is capable of receiving and / or transmitting radio signals. An antenna can be a radio frequency antenna or any other suitable type of antenna.

[0033] “A radio frequecy antenna” can include a device used to transmit and / or receive radio based signals. A radio frequency antenna can be an interface between 1 ) radio waves propagating thorugh space and 2) electric currents moving in metal conductors.

[0034] A “near-field communication antenna” can include a device used to transmit and / or receive near-field communication based signals. A near-field communication antenna can be a chip or a chipset that enables short-range wirelesscommunication between two devices. A near-field communication antenna can be a radio frequency antenna. A near-field communication antenna can be a near-field communication reader chip (e.g., active component) or a near-field communication tag (e.g., passive component). A near-field communication antenna that is a near- field communication reader chip can provide power and can send near-field communication commands to a near-field communication tag. Near-field communication is based on inductive coupling between two antennas present on two devices (e.g., on a user device and on an access device). The two dvices can communicate in one or both directions, using a frequency of 13.56 MHz in the globally available unlicensed radio frequency ISM band using the ISO / IEC 14443 air interface standard at data rates ranging from 106 to 848 kbit / s.

[0035] A “machine identification code” can include a machine readable code that includes machine identifying information. A machine identification code can include information that is printed on a surface of an object. In some embodiments, a machine identification code can be imperceivable to the human eye, but can be identified using a camera. A machine identification code can be a printed watermark that encodes information about a machine upon which the machine identification code is printed. A machine identification code can comprise a plurality of dots that are printed in a formation that encodes information. The dots can be small and difficult to notice with the human eye (e.g., 0.1 millimeters, 1 millimeter, etc., in diameter). The use of machine identification code can also be referred to as printer steganography.

[0036] The term "artificial intelligence model" or "Al model" can include a model that may be used to predict outcomes in order achieve a pre-defined goal. The Al model may be developed using a learning algorithm, in which training data is classified based on known or inferred patterns. An Al model may also be referred to as a "machine learning model" or "predictive model."

[0037] "Machine learning" can include an artificial intelligence process in which software applications may be trained to make accurate predictions through learning. The predictions can be generated by applying input data to a predictive model formed from performing statistical analyses on aggregated data. A model can be trained using training data, such that the model may be used to make accuratepredictions. The prediction can be, for example, a classification of an image (e.g., identifying images of cats on the Internet) or as another example, a recommendation (e.g., a movie that a user may like or a restaurant that a consumer might enjoy).

[0038] In some embodiments, a model may be a statistical model, which can be used to predict unknown information from known information. For example, a learning module may be a set of instructions for generating a regression line from training data (supervised learning) or a set of instructions for grouping data into clusters of different classifications of data based on similarity, connectivity, and / or distance between data points (unsupervised learning). The regression line or data clusters can then be used as a model for predicting unknown information from known information. Once model has been built from learning module, the model may be used to generate a predicted output from a new request. A new request may be a request for a prediction associated with presented data.

[0039] A “processor” may include a device that processes something. In some embodiments, a processor can include any suitable data computation device or devices. A processor may comprise one or more microprocessors working together to accomplish a desired function. The processor may include a CPU comprising at least one high-speed data processor adequate to execute program components for executing user and / or system -generated requests. The CPU may be a microprocessor such as AMD's Athlon, Duron and / or Opteron; IBM and / or Motorola's PowerPC; IBM's and Sony's Cell processor; Intel's Celeron, Itanium, Pentium, Xeon, and / or XScale; and / or the like processor(s).

[0040] A “memory” may be any suitable device or devices that can store electronic data. A suitable memory may comprise a non-transitory computer readable medium that stores instructions that can be executed by a processor to implement a desired method. Examples of memories may comprise one or more memory chips, disk drives, etc. Such memories may operate using any suitable electrical, optical, and / or magnetic mode of operation.

[0041] A “server computer” may include a powerful computer or cluster of computers. For example, the server computer can be a large mainframe, a minicomputer cluster, or a group of servers functioning as a unit. In one example, the server computer may be a database server coupled to a Web server. The servercomputer may comprise one or more computational apparatuses and may use any of a variety of computing structures, arrangements, and compilations for servicing the requests from one or more client computers.

[0042] Embodiments can identify a near-field communication antenna location in real time in an interaction between two devices, where one device is handled by a user.

[0043] Embodiments provide for systems and methods of determining a location of a radio frequency antenna in an access device as well as directions regarding how to move a user device into communication range with the radio frequency antenna in the access device. The user device can utilize a camera to capture images that aid in the process of guiding a user of the user device to bring the user device into communication range of the access device.

[0044] The user device can include a first radio frequency antenna. The access device can include a second radio frequency antenna. The user device can capture an image, using the camera, of at least a portion of the access device. The user device can display, on a display screen, the image along with an indicator of a location of the second radio frequency antenna on the access device. Responsive to displaying the image, the user device can be moved (e.g., by the user) such that the first radio frequency antenna is proximate to the second radio frequency antenna. The user device can then communicate with the access device via the first radio frequency antenna and the second radio frequency antenna.

[0045] In some embodiments, the user device can utilize machine learning techniques to analyze the image.

[0046] In an example, after capturing the image the user device can detect a first image region in the image that matches a predetermined template image using a first machine learning model. The user device can then determine a model version of the access device from the image using a second machine learning model. The user device can then determine a second image region in the same image or in another image based on the model version of the access device and a database of access device data. The user device can compare the first image region and the second image region. If the first image region and the second image region match,the user device can identify the location of the second radio frequency antenna on the access device based on the first image region and the second image region.

[0047] In other embodiments, the user device can identify a machine identification code included on the access device with the image.

[0048] In another example, after capturing the image, the user device can determine the location of the second radio frequency antenna of the access device using the machine identification code printed on the access device. The machine identification code can encode information about the access device, such as the location of the second radio frequency antenna. The machine identification code can be printed on the surface of the access device on the location of the second radio frequency antenna.

[0049] FIG. 1 shows a system 100 according to embodiments of the disclosure. The system 100 comprises a user device 102, an access device 104, a resource provider computer 106, a transport computer 108, a network processing computer 110, and an authorizing entity computer. The user device 102 can be in operative communication with the access device 104, which can be in operative communication with the resource provider computer 106. The resource provider computer can be in operative communication with the transport computer 108. The transport computer 108 can be in operative communication with the network processing computer 110, which can be in operative communication with the authorizing entity computer 112.

[0050] For simplicity of illustration, a certain number of components are shown in FIG. 1 . It is understood, however, that embodiments of the invention may include more than one of each component. In addition, some embodiments of the invention may include fewer than or greater than all of the components shown in FIG. 1 .

[0051] Messages between the devices in the system 100 illustrated in FIG. 1 can be transmitted using a communications protocols such as, but not limited to, File Transfer Protocol (FTP); HyperText Transfer Protocol (HTTP); Secure Hypertext Transfer Protocol (HTTPS), SSL, ISO (e.g., ISO 8583) and / or the like. The communications network include any one and / or the combination of the following: a direct interconnection; the Internet; a Local Area Network (LAN); a Metropolitan AreaNetwork (MAN); an Operating Missions as Nodes on the Internet (OMNI); a secured custom connection; a Wide Area Network (WAN); a wireless network (e.g., employing protocols such as, but not limited to a Wireless Application Protocol (WAP), l-mode, and / or the like); and / or the like. The communications network can use any suitable communications protocol to generate one or more secure communication channels. A communications channel may, in some instances, comprise a secure communication channel, which may be established in any known manner, such as through the use of mutual authentication and a session key, and establishment of a Secure Socket Layer (SSL) session.

[0052] The user device 102 can include one or more computers, portable computers, laptop computers, tablet computers, mobile devices, cellular phones, wearable devices (e.g., watches, glasses, lenses, clothing, etc.), personal digital assistants (PDAs), Internet of Things (loT) devices, and / or the like. The user device 102 can initiate interactions (e.g., transactions) with resource provider computers and / or access devices. For example, the user device 102 can select one or more items for the interaction at a resource provider location (e.g., a grocery store).During checkout, the user can be instructed to tap (e.g., bring into near-field communication range) the user device 102 against the access device 104. The user device 102 can utilize a camera to aid the user in bringing the user device 102 into a correct location (e.g., a landing plane) using direction instructions. In some embodiments, the user device 102 can utilize machine learning models to determine the correct location. In other embodiments, the user device 102 can utilize machine identification code to determine the correct location. Once in range, the user device 102 can communicate data, such as credentials, to the access device 104 for the interaction.

[0053] The access device 104 can include a device operated by a resource provider. The access device 104, for example, can include a mobile device, a POS terminal, a laptop, etc. The access device 104 can communicate with another device (e.g., a user device 102) to perform an interaction. During the interaction, the access device 104 can receive credentials from the user device and can provide interaction data to the resource provider computer 106 for authorization of the interaction. In some embodiments, the access device 104 can generate anauthorization request message comprising at least the interaction data. The access device 104 can provide the authorization request message to the resource provider computer 106.

[0054] The resource provider computer 106 can include any suitable computational apparatus operated by a resource provider (e.g., a merchant). In some embodiments, the resource provider computer 106 may include one or more server computers that may host one or more websites associated with the resource provider (e.g., a merchant). In some embodiments, the resource provider computer 106 may be configured to send data to the network processing computer 110 via the transport computer 108 as part of a payment verification and / or authentication process for a transaction between the user (e.g., consumer) and the resource provider. The resource provider computer 106 may also be configured to generate authorization request messages for transactions between a resource provider and a user, and route the authorization request messages to the authorizing entity computer 112 for transaction processing.

[0055] The transport computer 108 can include a server computer. The transport computer 108 may be associated with an acquirer, which may be an entity (e.g., a commercial bank) that has a business relationship with a particular merchant or other entity. Some entities can perform both issuer and acquirer functions. Some embodiments may encompass such single entity issuer-acquirers.

[0056] The network processing computer 110 can include a server computer. The network processing computer 110 may be disposed between the transport computer 108 and the authorizing entity computer 112. The network processing computer 110 may include data processing subsystems, networks, and operations used to support and deliver authorization services, exception file services, and clearing and settlement services. For example, the network processing computer 110 may comprise a server coupled to a network interface (e.g., by an external communication interface), and databases of information. The network processing computer 110 may be representative of a transaction processing network. An exemplary transaction processing network may include VisaNet™. Transaction processing networks such as VisaNet™ are able to process credit card transactions, debit card transactions, and other types of commercial transactions. VisaNet™, inparticular, includes a VIP system (Visa Integrated Payments system) which processes authorization requests and a Base II system which performs clearing and settlement services. The network processing computer 110 may use any suitable wired or wireless network, including the Internet.

[0057] The authorizing entity computer 112 can include a server computer operated by an authorizing entity. The authorizing entity computer 112 may be associated with an authorizing entity, which may be an entity that authorizes a request. An example of an authorizing entity may be an issuer, which may typically refer to a business entity (e.g., a bank) that maintains an account for a user. An issuer may also issue and manage an account associated with the user device 102.

[0058] FIG. 2 shows a block diagram of the user device 102 according to embodiments. The exemplary user device 102 may comprise a processor 204. The processor 204 may be coupled to a memory 202, a network interface 206, a computer readable medium 208, a camera 210, and a radio frequency antenna 212. The user device 102 may also include a long range antenna for cellular communications if the user device 102 is a mobile phone. The computer readable medium 208 can comprise an image processing module 208A, a display module 208B, and an interaction module 208C.

[0059] The memory 202 can be used to store data and code. For example, the memory 202 can store credentials, tokens, image data, instructions, etc. The memory 202 may be coupled to the processor 204 internally or externally (e.g., cloud based data storage), and may comprise any combination of volatile and / or nonvolatile memory, such as RAM, DRAM, ROM, flash, or any other suitable memory device.

[0060] The computer readable medium 208 may comprise code, executable by the processor 204, for performing a method comprising: capturing, by a camera in a user device comprising a first radio frequency antenna, an image of at least a portion of an access device comprising a second radio frequency antenna; displaying, by a display screen of the user device, the image along with an indicator of a location of the second radio frequency antenna on the access device, wherein responsive to the displaying, the user device moves such that the first radio frequency antenna is proximate to the second radio frequency antenna; andcommunicating, by the user device, with the access device via the first radio frequency antenna and the second radio frequency antenna.

[0061] The image processing module 208A may comprise code or software, executable by the processor 204, for processing images. The image processing module 208A, in conjunction with the processor 204, can obtain images from the camera 210 and process the images. The image processing module 208A, in conjunction with the processor 204, can analyze an image that includes at least a portion of an access device. In some embodiments, the image processing module 208A, in conjunction with the processor 204, can process the images using a machine learning model locally or in conjunction with a remote computer. In other embodiments, the image processing module 208A, in conjunction with the processor 204, can process the images by detecting machine identification codes.

[0062] For example, the image processing module 208A, in conjunction with the processor 204, can detect a first image region in a first image that matches a predetermined template image using a first machine learning model. The first image region can include an image of a location of a radio frequency antenna in the access device, the predetermined template image can include an image of a logo (e.g., an NFC logo) indicating a location of the radio frequency antenna, and the first machine learning model can be a quality-aware template matching (QATM) model for deep learning. The first machine learning model is described in further detail below.

[0063] The image processing module 208A, in conjunction with the processor 204, can then determine a model version of the access device from a second image using a second machine learning model. The second machine learning model can be a quality-aware template matching (QATM) model for deep learning and can compare the obtained second image to stored images of access devices. The image processing module 208A, in conjunction with the processor 204, can then determine a second image region in the second image based on model version of the access device and a database access device data. The second image region can include an image of a location of the radio frequency antenna in the access device. The image processing module 208A, in conjunction with the processor 204, can compare the first image region and the second image region to more accurately identify the location in the image of the radio frequency antenna of the access device.

[0064] For example, the image processing module 208A, in conjunction with the processor 204, can compare the first image region to the second image region by determining to what extent do image elements included in the first image region match image elements included in the second image region. The first image region and the second image region can include the NFC logo, a portion of a screen of the access device, text on the access device, an edge of the access device, a stylus of the access device, a sticker on the access device, a keypad on the access device, a cord on the access device, and / or any other potion of the access device. The image processing module 208A, in conjunction with the processor 204, can compare the image elements in the first image region to the image elements in the second image region to determine how well the two image regions match one another in terms of layout of image elements.

[0065] The image processing module 208A, in conjunction with the processor 204, can compare the first image region to the second image region using one or more image comparison techniques.

[0066] One image comparison technique can include using the second image region as a template image in a quality-aware template matching model. The quality-aware template matching model can output a similarity score based on how similar the first image region is to the template (e.g., the second image region). Quality-aware template matching can assess quality of a matching pair using soft- ranking among all matching pairs as described in Cheng, Jiaxin, et al. "QATM: Quality-aware template matching for deep learning." Proceedings of the IEEE / CVF Conference on Computer Vision and Pattern Recognition. 2019. As an example, the image processing module 208A, in conjunction with the processor 204, can utilize a quality-aware template matching process determine a similarity score between a first image region, which includes an NFC logo, a portion of a screen, and a top edge of an access device, and a second image region, which includes an NFC logo, a portion of the screen, and a top edge of the access device. If the similarity score exceeds a predetermined threshold (e.g., > 80), then the image processing module 208A, in conjunction with the processor 204, can determine that the first image region matches the second image region.

[0067] Other template matching methods include sum-of-squared-differences (SSD) and / or normalized cross correlation (NCC) to calculate the similarity score between the template and the image. Additional example quality-aware template matching methods can include 1 ) a best-buddies-similarity (BBS) measure, which focuses on the nearest-neighbor (NN) matches to exclude potential and bad matches caused by background pixels, 2) deformable diversity similarity (DDIS), which explicitly considers possible template deformation and uses the diversity of NN feature matches between a template and a potential matching region in the search image, and 3) cooccurrence based template matching (CoTM), which quantifies the dissimilarity between a template and a potential matched region in the search image.

[0068] Another image comparison technique can include detecting key points in the first image region and the second image region that contain rich visual information. Key points with rich visual information can include edges and corners of objects in the images. The image processing module 208A, in conjunction with the processor 204, can utilize key point detectors (e.g., a Harris corner detector, scaleinvariant feature transform (SIFT), and speeded up robust features (SURF)) to determine the key points. The image processing module 208A, in conjunction with the processor 204, can then determine local descriptors of each detected key point. The local descriptors can include a 1 -dimensional vector that describes the visual appearance of the key point. The image processing module 208A, in conjunction with the processor 204, can determine the local descriptors in each image region using, for example, the scale-invariant feature transform (SIFT) and / or the speeded up robust features (SURF) methods. The image processing module 208A, in conjunction with the processor 204, can then iteratively compare the local descriptors in the first image region to the second image region to discover pairs that of local descriptors that are similar. If the number of similar pairs is greater than a predetermined threshold number of pairs, then the image processing module 208A, in conjunction with the processor 204, can determine that the first image region matches the second image region.

[0069] As another example, the image processing module 208A, in conjunction with the processor 204, can identify a machine identification code included in the image. The access device can include a machine identification codethat is printed on the access device. The machine identification code can be printed on a surface of the access device over a location at which the radio frequency antenna is located. The image processing module 208A, in conjunction with the processor 204, can determine the location of the second radio frequency antenna of the access device using the machine identification code.

[0070] The display module 208B can include may comprise code or software, executable by the processor 204, for displaying information. The display module 208B, in conjunction with the processor 204, can display visuals on a display screen of the user device 102 to a user. The display module 208B, in conjunction with the processor 204, can display instructions of how to move the user device 102 towards a radio frequency antenna of an access device based on image data processed by the image processing module 208A. The display module 208B, in conjunction with the processor 204, can display instructions including images and indicators of a location of the second radio frequency antenna on the access device.

[0071] In some embodiments, the display module 208B, in conjunction with the processor 204, can display the image captured by the camera with an overlaid arrow indicator that points to the determined location of the location of the second radio frequency antenna in the image.

[0072] In other embodiments, the display module 208B, in conjunction with the processor 204, can display a stream of images captured by the camera (e.g., a video). The display module 208B, in conjunction with the processor 204, can display an augmented reality display.

[0073] The interaction module 208C can include may comprise code or software, executable by the processor 204, for performing interactions. The interaction module 208C, in conjunction with the processor 204, can obtain data (e.g., a credential or a token) related to the interaction. The interaction module 208C, in conjunction with the processor 204, can provide the credential or the token to a relevant device (e.g., an access device) to process the interaction. For example, the interaction module 208C, in conjunction with the processor 204, can provide the credential or the token to the access device 104.

[0074] The network interface 206 may include an interface that can allow the user device 102 to communicate with external computers. The network interface 206 may enable the user device 102 to communicate data to and from another device (e.g., an access device, etc.). Some examples of the network interface 206 may include a modem, a physical network interface (such as an Ethernet card or other Network Interface Card (NIC)), a virtual network interface, a communications port, a Personal Computer Memory Card International Association (PCMCIA) slot and card, or the like. The wireless protocols enabled by the network interface 206 may include Wi-Fi™. Data transferred via the network interface 206 may be in the form of signals which may be electrical, electromagnetic, optical, or any other signal capable of being received by the external communications interface (collectively referred to as “electronic signals” or “electronic messages”). These electronic messages that may comprise data or instructions may be provided between the network interface 206 and other devices via a communications path or channel. As noted above, any suitable communication path or channel may be used such as, for instance, a wire or cable, fiber optics, a telephone line, a cellular link, a radio frequency (RF) link, a WAN or LAN network, the Internet, or any other suitable medium.

[0075] The camera 210 can include a device for recording visual images in the form of photographs or video signals. The camera 210 can capture image data that can include any suitable data relating to an image. The image data can originate from or be associated with still pictures or from videos. In some embodiments, the image data may be data representing an image of a at least a portion of the access device. The image data may be in any suitable form (e.g., JPEG, PNG, DNG, GIF, BMP, SVG, etc. files) and may include a number of pixels that may be arranged in a rectangular array and an intensity of a color (e.g., color data) for each pixel.

[0076] The radio frequency antenna 212 can include an antenna configured to utilize radio frequencies. The radio frequency antenna 212 can be a near-field communication antenna and can be configured to utilize near-field communication frequencies. Near-field communication can include a set of communication protocols that enable communication between two electronic devices over a distance of 4 cm or less. Near-field communication is based on inductive coupling between twoantennas present on near-field communication-enabled devices communicating in one or both directions, using a frequency of 13.56 MHz in the globally available unlicensed radio frequency ISM band using the ISO / IEC 14443 air interface standard at data rates ranging from 106 to 848 kbit / s.

[0077] The radio frequency antenna 212 can be connected to an interface and driver circuits. The interface and driver circuits can connect the radio frequency antenna 212 to the processor 204. The interface and driver circuits can include a circuit that has specialized features and capabilities that allow it to be the physical interface between a source circuit (e.g., the processor 204) and a load (e.g., the radio frequency antenna 212) that has specific, unique characteristics that must be met, in order to get the signal source to control the load. For example, a driver can provide these functions with respect to the load: 1 ) supply appropriate voltage levels, 2) supply voltage at sufficient current levels, and 3) provide that voltage and current change at a rate the load needs (slew rate).

[0078] Communication between the radio frequency antenna 212 and a second radio frequency antenna can take place between an active initiator device and a target device which may either be passive or active. If the target device is passive, then the initiator device provides a carrier field to the target device. The target device, acting as a transponder, communicates by modulating the incident field. In this mode, the target device may draw its operating power from the initiator- provided magnetic field. If the target device is active, then both the initiator device and the target device communicate by alternately generating their own fields, where a device stops transmitting in order to receive data from the other. This mode requires that both devices include power supplies.

[0079] FIG. 3 shows a block diagram of the access device 104 according to embodiments. The exemplary access device 104 may comprise a processor 304. The processor 304 may be coupled to a memory 302, a network interface 306, a computer readable medium 308, and a radio frequency antenna 312 (e.g., an NFC antenna). The computer readable medium 308 can comprise an interaction module 308A.

[0080] The memory 302 can be used to store data and code and may be similar to the memory 202 as described herein. For example, the memory 302 can store cryptographic keys, interaction data, etc.

[0081] The computer readable medium 308 may comprise code, executable by the processor 304, for performing a method comprising: communicating with the user device via the second radio frequency antenna and the first radio frequency antenna; receiving a credential or a token from the user device; and providing the credential or the token to a resource provider computer, which can generate an authorization request message using the credential or the token.

[0082] The interaction module 308A may comprise code or software, executable by the processor 304, for performing interactions. The interaction module 308A, in conjunction with the processor 304, can obtain data (e.g., interaction data) related to the interaction. The interaction data can include a timestamp, an amount, a list of resources involved in the interaction, and / or other data related to the interaction and / or related to processing the interaction. The interaction module 308A, in conjunction with the processor 304, can receive a credential or a token from a user device. The interaction module 308A, in conjunction with the processor 304, can include the credential or the token into the interaction data.

[0083] In some embodiments, the interaction module 308A, in conjunction with the processor 304, can provide the interaction data to a resource provider computer for processing of the interaction.

[0084] In other embodiments, the interaction module 308A, in conjunction with the processor 304, can generate an authorization request message comprising the interaction data. The interaction module 308A, in conjunction with the processor 304, can then provide the authorization request message to the resource provider computer.

[0085] The network interface 306 may be similar to the network interface 206 and will not be repeated here.

[0086] The radio frequency antenna 312 can be similar to the radio frequency antenna 212 and the description of thus will not be repeated here. The radiofrequency antenna 312 can be connected to an interface and driver circuits. The interface and driver circuits can connect the radio frequency antenna 312 to the processor 304.

[0087] FIG. 4 shows a flowchart of an artificial intelligence image recognition for location determination method according to embodiments. The method illustrated in FIG. 4 will be described in the context of a user device performing an interaction with an access device, where the user device detects a location of a radio frequency antenna location using imaging and machine learning and directs a user of the user device to bring the user device proximate to the radio frequency antenna location.

[0088] Prior to step 402, a user of the user device 102 can initiate an interaction with a resource provider of the access device 104. For example, the user can select one or more resource that are provided by the resource provider. The user can proceed to the access device 104, which is located at the resource provider location. The user can utilize a resource provider computer 106 that is connected to the access device 104 to scan (e.g., using a barcode, a QR code, etc.) the one or more resource, or otherwise identify the one or more resources. After identifying the one or more resources to the resource provider computer 106, the user can select to complete the interaction (e.g., to checkout). The resource provider computer 106 can generate and provide interaction data including a time, a list of the one or more resources, an amount, etc. to the access device 104. The resource provider computer 106 can notify the user to complete the interaction with the access device 104.

[0089] At step 402, the user can activate an interaction application on the user device 102. The interaction application can be a transaction application. The interaction application can initiate near-field communication tap to pay capabilities.

[0090] The user device 102 can include a first radio frequency antenna that is capable of communicating with a second radio frequency antenna in the access device 104.

[0091] In some embodiments, the interaction application can detect a model of the user device 102. The interaction application can retrieve a relative location (e.g., distance and direction, in two dimensions as they are considered on the samesurface plane) between the camera and the first radio frequency antenna, if precise guidance is desired. The relative location can be taken into account when determining how the user is to move the user device towards the second radio frequency antenna in the access device 104.

[0092] In some embodiments, if no user device model information is stored in the memory, then the user device 102 can utilize a distance of zero (e.g., at the same location) between the first radio frequency antenna and the camera in the user device 102. As such, the relative location between the first radio frequency antenna and the camera in the user device 102 would be zero as the user device 102 is assuming that the components are at the same position.

[0093] At step 404, after the interaction application is activated, the interaction application of the user device 102 can capture an image using a camera of the user device 102. For example, the user device can capture an image of at least a portion of the access device 104 comprising the second radio frequency antenna. In some embodiments, the user device 102 can prompt the user of the user device 102, via a display screen, to direct the camera towards the access device 104.

[0094] At step 406, after capturing the image, the user device 102 can detect a first image region in the image. The first image region can be a portion of the image. The first image region can be a portion of the image that includes a logo, or other graphic, that indicates a radio frequency antenna location in the access device 104. The user device 102 can analyze the image to determine the first image region.

[0095] The user device 102 can determine the first image region using a first machine learning model. For example, the user device 102 can utilize quality-aware template matching (QATM) for deep learning. The target of the QATM can be a predetermined template image (e.g., an image of the target symbol, such as an NFC logo, etc.). The detection of the first image region can be performed locally on the user device 102 or can be implemented using cloud based service like Azure cognitive services computer vision API for brand detection.

[0096] FIG. 5 shows example images illustrating image element detection according to embodiments. FIG. 5 includes three example images including a nearfield communication logo template image 502, a first image 504 including a firstimage logo region 506, and a second image 508 including access device identification regions 510. FIG. 5 also includes a first image region 512 of the first image 504 and a second image region 514 of the second image 508.

[0097] The near-field communication logo template image 502 illustrates an example logo that represents a radio frequency antenna tapping location. The near- field communication logo template image 502 can be printed onto the access device 104 at a location where the access device’s radio frequency antenna is placed. The near-field communication logo template image 502 can be the predetermined template image that the user device 102 is trying to find a match for in the image.

[0098] The first image 504 can be the image captured by the user device 102. The first image 504 can be an image of the access device 104. The user device 102 can determine the first image logo region 506 in the first image 504 that matches the near-field communication logo template image 502 using the first machine learning model. The image logo region 506 can be included in the first image region 512 of the first image. The first image region 512 can be a region of the first image 504 that includes an image of the landing plane. The image logo region 506 can include an image of the logo that matches the near-field communication logo template image 502.

[0099] Referring back to FIG. 4, in some embodiments, at step 408, after detecting the first image region in the image, the user device can detect a model version of the access device 104 in the image. The user device 102 can determine a model version of the access device 104 using a second machine learning model. The user device can then determine a second image region in the image. The second image region can include an image of a location of where the radio frequency antenna is located in the access device 104.

[0100] FIG. 5 illustrates an example second image 508 including access device identification regions 510 and the second image region. The second image 508 can be the image captured by the user device 102. In some embodiments, the second image 508 can be the same image as the first image 504. In other embodiments, the second image 508 can be an image captured before or after the first image 504.

[0101] The access device identification regions 510 can be locations in the second image 508 identified as including the access device 104. The user device 102 can identify the access device identification regions 510 in the second image 508, and then compare the access device identification regions 510 to template images of various access device models.

[0102] For example, the user device 102 can use a second machine learning model that is a quality-aware template matching for deep learning machine learning model. The second machine learning model can match a template image from an online database of access device images to an access device image region in the image. The online database can include detailed information regarding the location of radio frequency antennas in a plurality of different access device models. The online database can include images of a plurality of different access device model versions with labeled data indicating where the radio frequency antenna is located in the image.

[0103] The online database of radio frequency antenna locations can include a plurality of template images of access devices with radio frequency antenna location data associated with each template image of an access device. The radio frequency antenna location data can indicate a region of the template image of the access device that corresponds with a landing plane. The radio frequency antenna location data can include a second template image that includes a close up image of the access device’s landing plane. The radio frequency antenna location data can include details related to the position of the landing plane in relation to other components of the access device (e.g., above the screen, to the left of the ‘tap to pay’ text, etc.).

[0104] Once a match has been found within a predetermined confidence threshold (e.g., > 75%), then the user device 102 can utilize the online database of radio frequency antenna locations. The user device 102 can identify the second image region 514 in the image that corresponds to the radio frequency antenna location using the second machine learning model and the online database.

[0105] For example, the second machine learning model can determine a template image from the online database that matches the image of at least a portion of the access device. The template image can have a label that indicates where inthe image (e.g., a region of the image) the second radio frequency antenna is located. The second machine learning model can output the region in the image that matches the location of the template image corresponding to the second radio frequency antenna. The output region can be the second image region 514 of the second image 508.

[0106] At step 410, after determining the first image region and, in some embodiments, the second image region, the user device 102 can identify a location of the radio frequency antenna.

[0107] If only a first image region has been obtained, then the user device 102 can identify the first image region as being the region within which the location of the radio frequency antenna resides.

[0108] If both a first image region and a second image region have been obtained, then the user device 102 can compare the first image region to the second image region to determine whether or not the first image region matches the second image region within a predetermined difference threshold. If the image regions match, then the image regions identify the location of the radio frequency antenna. If the image regions do not match, then the user device 102 can repeat the image capture and detection process starting at step 404.

[0109] The user device 102 can compare the first image region to the second image region in any suitable manner. For example, if the first image (used for determining the logo region in the image) and the second image (used for determining the access device model) are the same image, then the user device 102 can determine a first center point of the first image region (e.g., as indicated by a pixel location in the image). The user device 102 can determine a second center point of the second image region. The user device 102 can determine a distance between the first center point and the second center point. If the distance between the first center point and the second center point is less than the predetermined center point, then the user device 102 can determine that the first image region matches the second image region.

[0110] As another example, the first image region (e.g., the first image region 512 of FIG. 5) and the second image region (e.g., the second image region 514 ofFIG. 5) can each include the NFC logo, a portion of a screen of the access device, text on the access device, and an edge of the access device. The user device 102 can compare the image elements in the first image region 512 to the image elements in the second image region 514 using a quality aware template matching process. The user device 102 can determine a similarity score that indicates how well the image elements in the first image region 512 match the image elements in the second image region 514. For example, the first image region 512 includes an image element of an NFC logo generally in the center of the first image region 512. Similarly, the second image region 514 includes an image element of an NFC logo generally in the center of the second image region 514. Additionally, both the first image region 512 and the second image region 514 include images of text to the right of the NFC logo (e.g., "Ta” appears on the right side of the image regions).Both the first image region 512 and the second image region 514 include images of a portion of the access device screen in the bottom right portion of the image regions. Both the first image region 512 and the second image region 514 include images of an edge of the access device 104 that separate the image of the access device from the background behind the access device 104, where the background is generally in the upper left corner in both image regions. Due to these similarities, the user device 102 can determine that the first image region 512 matches the second image region 514.

[0111] As another example, the user device 102 can compare further details of the first image region to the second image region. For example, the user device 102 can compare the image regions based on an average color in each image region. If the average color in each image region is within a predetermined difference threshold, then the first image region matches the second image region. Further, the user device 102 can analyze the average color per quadrant or section of the image regions to further increase comparison accuracy.

[0112] At step 412, after determining the location of the radio frequency antenna, the user device 102 can display instructions to the user of the user device 102. The user device 102 can display the instructions using a display screen on the user device 102. The instructions can include the image and an indicator. The user device 102 can display the image along with the indicator of the location of the radiofrequency antenna on the access device 104. The displayed image can be an image of a particular point in time. However, the image can be updated over time using the camera. As such, the user device 102 can display images in sequence over time. The user device 102 can display a video streamed from the camera. The user device 102 can display augmented reality based instructions to the user of the user device 102.

[0113] The user can move the user device 102 based on the displayed instructions. The user can move the user device 102 such that the first radio frequency antenna of the user device 102 is proximate to the second radio frequency antenna of the access device 104.

[0114] FIG. 6 shows an example image of augmented reality based instructions according to embodiments. FIG. 6 includes the user device 102 and the access device 104. The user device 102 includes a display screen 602 that is displaying movement instructions including an access device image 604 of the access device 104 and an indicator 606. The access device 104 includes a landing plane 608, which can be where the radio frequency antenna of the access device is located. The user device 102 can display the instructions on the display screen 602 for the user to bring the user device 102 into communication range with the access device 104 at the landing plane 608.

[0115] The user device 102 can continuously capture images with a camera to display updated access device images 604 on the display screen 602 over time. Displaying the continuously captured images solves the problem of the user device 102 blocking the user’s line of sight to the access device 104 as the user can see on the display screen 602 what is behind the user device 102.

[0116] The user device 102 can add an augmented reality overlay onto the access device image 604. In particular, the user device 102 can display the indicator 606 along with the access device image 604. The indicator 606 can be a directional indicator that can point the user towards the landing plane 608. The indicator 606 can be updated with each access device image 604 to point towards the correct location in the access device image 604 that corresponds with the landing plane 608.

[0117] Referring back to FIG. 4, at step 414, after displaying the instructions, the user device can be moved by the user, and the user device 102 can determine whether or not the first radio frequency antenna and the second radio frequency antenna are in communication range of one another. For example, the user device 102 can determine whether or not a signal has been received from the radio frequency antenna in the access device 104. The user device 102 can attempt to communicate with the second radio frequency antenna using the first radio frequency antenna.

[0118] If the first radio frequency antenna and the second radio frequency antenna are not in communication range, then the user device 102 can proceed to step 404. In some embodiments, the user device 102 can utilize sensors included in the user device 102 to detect phone’s movement. The sensors can include an accelerometer gyroscope, etc. If movement is detected, then the user device 102 can return to step 404 to repeat capturing a new image from the new location.

[0119] In some embodiments, communication range can refer to a range at which the first near-field communication antenna and the second near-field communication antenna can communicate at a particular communication field strength. The communication field strength can increase as the two antennas are brought closer to one another. If the first near-field communication antenna and the second near-field communication antenna are not in a communication range that provides a field-strength strong enough to complete a full transaction, then the user device 102 can proceed to step 510 to instruct the user to move the user device 102 closer to the access device 104.

[0120] If the first radio frequency antenna and the second near-field communication are in communication range, then the user device 102 can proceed to step 416.

[0121] At step 416, after the first radio frequency antenna and the second near-field communication are in communication range, the user device 102 can display a successful connection notification to the user of the user device 102 on a display screen. The successful connection notification can indicate that the first radio frequency antenna and the second near-field communication are in communication range and have successfully begun communicating. In someembodiments, the user device 102 can display the successful connection notification to the user of the user device 102 once the interaction is complete, ss

[0122] The first radio frequency antenna and the second near-field communication can communicate data related to the interaction between the user device 102 and the access device 104. For example, the user device 102 can provide a credential or a token stored in the user device 102 to the access device 104.

[0123] The access device 104 can provide the credential or the token along with interaction data for the interaction between the user device 102 and the access device 104 to a resource provider computer 106.

[0124] The resource provider computer 106 can generate an authorization request message comprising the interaction data and the credential or the token. The resource provider computer 106 can provide the authorization request message to the transport computer 108.

[0125] After receiving the authorization request message from the resource provider computer 106, the transport computer 108 can provide the authorization request message to the network processing computer 110.

[0126] The network processing computer 110, after receiving the authorization request message can provide the authorization request message to the authorizing entity computer 112.

[0127] The authorizing entity computer 112 can determine whether or not to authorize the interaction based on the authorization request message. The authorizing entity computer 112 can generate an indication of whether or not the interaction is authorized. The authorizing entity computer 112 can generate an authorization response message comprising the indication of whether or not the interaction is authorized. The authorization response message can also include the interaction data and the credential or the token from the authorization request message. The authorizing entity computer 112 can provide the authorization response message to the network processing computer 110.

[0128] After receiving the authorization response message from the authorizing entity computer 112, the network processing computer 110 can provide the authorization response message to the transport computer 108.

[0129] The transport computer 108 can provide the authorization response message to the resource provider computer 106.

[0130] At a later time, a clearing and settlement process can take place between the transport computer 108, the network processing computer 110, and the authorizing entity computer 112.

[0131] In some embodiments, the resource provider computer 106 can display the indication of whether or not the interaction is authorized to the user of the user device 102 on a display screen.

[0132] In some embodiments, the resource provider computer 106 can provide the authorization response message to the access device 104. The access device 04 can display the indication of whether or not the interaction is authorized to the user of the user device 102 on a display screen.

[0133] In some embodiments, the access device 104 can provide the authorization response message to the user device 102. The user device 102 can display the indication of whether or not the interaction is authorized to the user of the user device 102 on a display screen.

[0134] FIG. 7 shows a flowchart of a machine identification code image recognition for location determination method according to embodiments. The method illustrated in FIG. 7 will be described in the context of a user device performing an interaction with an access device, where the user device detects a location of a radio frequency antenna location using a machine identification code and directs a user of the user device to bring the user device proximate to the radio frequency antenna location.

[0135] Prior to step 702, a user of the user device 102 can initiate an interaction with a resource provider of the access device 104. For example, the user can select one or more resource that are provided by the resource provider. The user can proceed to the access device 104, which is located at the resource providerlocation. The user can utilize a resource provider computer 106 that is connected to the access device 104 to scan (e.g., using a barcode, a QR code, etc.) the one or more resource, or otherwise identify the one or more resources. After identifying the one or more resources to the resource provider computer 106, the user can select to complete the interaction (e.g., to checkout). The resource provider computer 106 can generate and provide interaction data including a time, a list of the one or more resources, an amount, etc. to the access device 104. The resource provider computer 106 can notify the user to complete the interaction with the access device 104.

[0136] At step 702, the user can activate an interaction application on the user device 102. The interaction application can be a transaction application. The interaction application can initiate near-field communication tap to pay capabilities.

[0137] The user device 102 can include a first radio frequency antenna that is capable of communicating with a second radio frequency antenna in the access device 104.

[0138] In some embodiments, the user device 102 can prompt the user of the user device 102, via a display screen, to direct the camera towards the access device 104 to capture the image of the access device 104.

[0139] At step 704, the user device 102 can capture an image using a camera in the user device 102. The user device 102 can capture an image that includes the access device 104 and a machine identification code on the access device 104.

[0140] FIG. 8 shows an example image of machine identification code according to embodiments. FIG. 8 includes a machine identification code 802 that includes a plurality of dots including the dot 804. The machine identification code 802 can encode information about the access device 104 upon which the machine identification code 802 can be printed. Each dot of the plurality of dots in the machine identification code 802 can be arranged such that information is encoded based on the arrangement.

[0141] The machine identification code 802 can include information relating to the location of the radio frequency antenna in the access device 104. For example, the machine identification code 802 can be printed and / or placed on a surface of theaccess device 104 above the radio frequency antenna. In some embodiments, the machine identification code 802 can include information relating to a model version of the access device 104.

[0142] The machine identification code 802 can be printed on the access device 104 itself or can be printed on something attached to the access device 104 (e.g., a sticker). The machine identification code 802 cannot be visible to human eyes. Each dot of the plurality of dots can be printed with a small diameter (e.g., 0.1 mm, 1 mm, 5 mm, etc.) to make them difficult to see with the human eye. Each dot of the plurality of dots can be printed in an identifiable color (e.g., yellow). The plurality of dots can be printed on a dot matrix, where some grid coordinates include a dot and other grid coordinates do not include a dot. The dot matrix can have a set amount of space between dots in each row and column (e.g., 1 mm, 2 mm, 5 mm, etc. spacing).

[0143] As an example, the arrangement of the dots can encode a serial number of the access device 104, a date and time of the printing, an indication that the dot location is over the radio frequency antenna, and / or any other information related to the access device 104. The arrangement of the dots can be repeated several times across the printing area in case of errors. For example, if the code consists of 8 x 16 dots in a square or hexagonal pattern, the repeating pattern can spread over a surface of about 4 square centimeters. Thus, the machine identification code 802 can be analyzed even if only fragments or excerpts are available.

[0144] At step 706, after capturing the image of the access device 104, the user device 102 can detect the machine identification code 802 in the image. The user device 102 can search the image for the plurality of dots based on the color and spacing of the dots.

[0145] The user device 102 can analyze the image to identify the dots of the machine identification code 802. For example, in some embodiments, the user device 102 can apply a color filter to the image that filters out all colors except for a predetermined color used to print the dots (e.g., yellow). By applying the color filter, the dots can be more easily detected in the image. The user device 102 can alsoenhance or otherwise boost the color information in the color filter channel (e.g., increase the saturation).

[0146] Furthermore, the user device 102 can capture an image of the machine identification code 802 with a camera that can increase optical magnification (e.g., zoom-in). Having the camera zoom-in can provide more accurate details to the user device 102.

[0147] In some embodiments, providing additional illumination on the machine identification code 802 from a light color that contrasts with the dot color (e.g., yellow and blue) can allow the user device to detect the machine identification code 802 more easily. For example, a light on the user device 102 (e.g., a flash on the camera) can emit a blue tinted light to provide additional contrast between the dots of the machine identification code and the background around the dots.

[0148] At step 708, if the user device 102 detects machine identification code in the image, then the user device 102 can proceed to step 710. If the user device 102 does not detect machine identification code in the image, then the user device can return to step 704 to capture a new image.

[0149] At step 710, after detecting the machine identification code in the image, the user device can decode the machine identification code into one or more instructions and display them to the user of the user device 102 using a display screen. The instructions can include the image and an indicator. The user device 102 can display the image along with the indicator of the location of the radio frequency antenna on the access device 104. The displayed image can be an image of a particular point in time.

[0150] In some embodiments, the image can be updated over time using the camera. As such, the user device 102 can display a video streamed from the camera wherein the video shows the access device in real time. The user device 102 can display augmented reality based instructions to the user of the user device 102 over the displayed video. For example, the augmented reality based instructions can include an interactive visual that combines the real world and computer-generated content. The augmented reality based instructions includes the video captured from the camera, such that the video gives the user the experience ofseeing through the user device 102. The augmented reality based instructions also includes the indicator that indicates the location of the radio frequency antenna on the access device 104. The indicator can be overlayed onto the video such that the indicator appears, to the user, to be floating in space. The image of the access device 104 will be shown on the display of the user device and the indicator (e.g., an arrow) can continually point to the location of the radio frequency antenna on the access device 104 even though the user moves the user device 102 and the access device 104 changes position on the display screen.

[0151] The user can move the user device 102 based on the displayed instructions. The user can move the user device 102 such that the first radio frequency antenna of the user device 102 is proximate to the second radio frequency antenna of the access device 104.

[0152] At step 712, after displaying the instructions, the user device 102 can move according to the instructions, and the user device 102 can determine whether or not the first radio frequency antenna and the second radio frequency antenna are in communication range of one another. For example, the user device 102 can determine whether or not a signal has been received from the radio frequency antenna in the access device 104. The user device 102 can attempt to communicate with the second radio frequency antenna using the first radio frequency antenna.

[0153] If the first radio frequency antenna and the second near-field communication are not in communication range, then the user device 102 can proceed to step 704. In some embodiments, the user device 102 can utilize sensors included in the user device 102 to detect phone’s movement. The sensors can include an accelerometer gyroscope, etc. If movement is detected, then the user device 102 can return to step 704 to repeat capturing a new image from the new location. For example, the user device 102 can obtain sensor data from an accelerometer and a gyroscope. The user device 102 can then determine movement of the user device 102 based on the sensor data.

[0154] If the first radio frequency antenna and the second near-field communication are in communication range, then the user device 102 can proceed to step 714.

[0155] At step 714, after the first radio frequency antenna and the second near-field communication are in communication range, the user device 102 can display a successful connection notification to the user of the user device 102 on a display screen. The successful connection notification can indicate that the first radio frequency antenna and the second near-field communication are in communication range and have successfully begun communicating.

[0156] The first radio frequency antenna and the second near-field communication can communicate data related to the interaction between the user device 102 and the access device 104, as described herein.

[0157] Embodiments of the disclosure have a number of advantages. For example, embodiments provide for a technical solution to the technical problem of identifying a near-field communication antenna location in real time between two devices, where one device is handled by a user.

[0158] Current access devices have limited area to include extra components, thus leaving near-field communication antennas to be included with the access device at locations that vary between different models of access devices. The user of the user device is expected to get the user device as close to the near-field communication antenna in the access device as possible to achieve payment. However, the user might not know where the near-field communication antenna is located in many different access device models.

[0159] To solve such technical problems as well as make the process more effective and comfortable for users, embodiments provide for systems and methods of identifying near-field communication antennas using imaging techniques and displaying instructions regarding the location of the near-field communication antennas to the user.

[0160] Embodiments provide for an advantage of not needing to modify existing access devices with additional electrical hardware to allow the user device to detect the location of the access device’s near-field communication antenna.

[0161] Embodiments provide for additional advantages, for example, embodiments provide for user device displayed instructions that reduce the problem of the user device blocking the user’s line of sight to the access device. In particular,the user device can display instructions to the user that describe how to move the user device towards the access device.

[0162] Although the steps in the flowcharts and process flows described above are illustrated or described in a specific order, it is understood that embodiments of the invention may include methods that have the steps in different orders. In addition, steps may be omitted or added and may still be within embodiments of the invention.

[0163] Any of the software components or functions described in this application may be implemented as software code to be executed by a processor using any suitable computer language such as, for example, Java, C, C++, C#, Objective-C, Swift, or scripting language such as Perl or Python using, for example, conventional or object-oriented techniques. The software code may be stored as a series of instructions or commands on a computer readable medium for storage and / or transmission, suitable media include random access memory (RAM), a read only memory (ROM), a magnetic medium such as a hard-drive or a floppy disk, or an optical medium such as a compact disk (CD) or DVD (digital versatile disk), flash memory, and the like. The computer readable medium may be any combination of such storage or transmission devices.

[0164] Such programs may also be encoded and transmitted using carrier signals adapted for transmission via wired, optical, and / or wireless networks conforming to a variety of protocols, including the Internet. As such, a computer readable medium according to an embodiment of the present invention may be created using a data signal encoded with such programs. Computer readable media encoded with the program code may be packaged with a compatible device or provided separately from other devices (e.g., via Internet download). Any such computer readable medium may reside on or within a single computer product (e.g. a hard drive, a CD, or an entire computer system), and may be present on or within different computer products within a system or network. A computer system may include a monitor, printer, or other suitable display for providing any of the results mentioned herein to a user.

[0165] The above description is illustrative and is not restrictive. Many variations of the invention will become apparent to those skilled in the art uponreview of the disclosure. The scope of the invention should, therefore, be determined not with reference to the above description, but instead should be determined with reference to the pending claims along with their full scope or equivalents.

[0166] One or more features from any embodiment may be combined with one or more features of any other embodiment without departing from the scope of the invention.

[0167] As used herein, the use of "a," "an," or "the" is intended to mean "at least one," unless specifically indicated to the contrary.

Claims

WHAT IS CLAIMED IS:1 . A method comprising: capturing, by a camera in a user device comprising a first radio frequency antenna, an image of at least a portion of an access device comprising a second radio frequency antenna; displaying, by a display screen of the user device, the image along with an indicator of a location of the second radio frequency antenna on the access device, wherein responsive to the displaying, the user device moves such that the first radio frequency antenna is proximate to the second radio frequency antenna; and communicating, by the user device, with the access device via the first radio frequency antenna and the second radio frequency antenna.

2. The method of claim 1 , wherein the image is displayed using augmented reality.

3. The method of claim 1 , wherein the location of the second radio frequency antenna is determined after a machine learning model determines a model of the access device, and then determines the location of the second radio frequency antenna based on data associated with the model of the access device.

4. The method of claim 3 further comprising: displaying, by the user device, an indicator of the location of the second radio frequency antenna on the display screen to instruct a user of the user device to move the user device towards the access device such that the first radio frequency antenna and the second radio frequency antenna are communicatively coupled.

5. The method of claim 1 , wherein the access device comprises a machine identification code, and the image of the access device includes the machine identification code, and the method further comprises: determining the location of the second radio frequency antenna of the access device using the machine identification code.

6. The method of claim 5, wherein the machine identification code includes a dot matrix which is not visible to human eyes.

7. The method of claim 1 , wherein after capturing the image, the method further comprises: detecting, by the user device, a first image region in the image that matches a predetermined template image using a first machine learning model; determining, by the user device, a model version of the access device from the image using a second machine learning model; and determining, by the user device, a second image region in the image based on model version of the access device and a database access devices.

8. The method of claim 7 further comprising: comparing, by the user device, the first image region and the second image region; and if the first image region and the second image region match, identifying the location of the second radio frequency antenna on the access device based on the first image region and the second image region.

9. The method of claim 7, wherein the predetermined template image is a logo.

10. The method of claim 1 , wherein prior to capturing the image, a user of the user device initiates an interaction with a resource provider of the access device, wherein communicating with the access device comprises: providing, by the user device, a token or a credential from the first radio frequency antenna to the second radio frequency antenna, wherein the access device utilizes the token or the credential to request authorization of the interaction.

11. A user device comprising: a processor; and a computer-readable medium coupled to the processor, the computer- readable medium comprising code executable by the processor for implementing a method comprising:capturing, by a camera in the user device comprising a first radio frequency antenna, an image of at least a portion of an access device comprising a second radio frequency antenna; displaying, by a display screen of the user device, the image along with an indicator of a location of the second radio frequency antenna on the access device, wherein responsive to the displaying, the user device moves such that the first radio frequency antenna is proximate to the second radio frequency antenna; and communicating with the access device via the first radio frequency antenna and the second radio frequency antenna.

12. The user device of claim 11 , wherein the method further comprises: obtaining sensor data from an accelerometer and a gyroscope; and determining movement of the user device based on the sensor data.

13. The user device of claim 12, wherein the image is a first image, and wherein the method further comprises: capturing a second image of at least a portion of the access device comprising the second radio frequency antenna; and displaying, the second image along with the indicator of the location of the second radio frequency antenna on the access device.

14. The user device of claim 11 further comprising: the camera coupled to the processor; and the first radio frequency antenna coupled to the processor.

15. The user device of claim 11 , wherein communicating with the access device comprises: providing a credential or a token to the access device.

16. The user device of claim 15, wherein the access device generates an authorization request message comprising interaction data and the credential or the token for authorization of an interaction between the user device and the access device.

17. The user device of claim 11 , wherein the displayed image is an image or a video and wherein the indicator of the location of the second radio frequency antenna on the access device is a visual overlayed onto the displayed image.

18. A system comprising: a user device comprising: a first processor; and a first computer-readable medium coupled to the first processor, the first computer-readable medium comprising code executable by the first processor for implementing a first method comprising: capturing, by a camera in the user device comprising a first radio frequency antenna, an image of at least a portion of an access device comprising a second radio frequency antenna; displaying, by a display screen of the user device, the image along with an indicator of a location of the second radio frequency antenna on the access device, wherein responsive to the displaying, the user devices moves the user device such that the first radio frequency antenna is proximate to the second radio frequency antenna; and communicating with the access device via the first radio frequency antenna and the second radio frequency antenna; and the access device comprising: a second processor; and a second computer-readable medium coupled to the second processor, the second computer-readable medium comprising code executable by the second processor for implementing a second method comprising: communicating with the user device via the second radio frequency antenna and the first radio frequency antenna.

19. The system of claim 18 wherein communicating with the access device, by the user device, comprises:providing, by the user device, a credential or a token to the access device, wherein the second method further comprises: receiving, by the access device, the credential or the token from the user device; and providing, by the access device, the credential or the token and interaction data for an interaction between the user device and the access device to a resource provider computer associated with the access device, wherein the resource provider computer generates an authorization request message comprising the interaction data and the credential or the token and provides the authorization request message to an authorizing entity computer via a transport computer and a network processing computer, wherein the authorizing entity computer determines whether or not to authorize the interaction.

20. The system of claim 18, wherein the location of the second radio frequency antenna is determined after a machine learning model determines a model of the access device, and then determines the location of the second radio frequency antenna based on data associated with the model of the access device.

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