Description:TECHNICAL FIELD
[0001] The present disclosure relates to a face recognition technology. More specifically, the present disclosure relates to an autonomous identity authentication system for application document verification, and method thereof.

BACKGROUND
[0002] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] With growing document verification of applications, it takes lot of human efforts and time to verify each and every application one by one. Also, in any application system, it could be difficult to determine if someone is intentionally trying to exploit the system. However, it is possible that some applicants may be using false or stolen identities to apply for services or benefits, as the lack of facial recognition could make it more difficult to verify the identity of the applicant. Additionally, there may be a greater risk of fraud or misuse of personal information if the system does not have the ability to verify the identity of the applicant through facial recognition. It's important for the government and private organizations to put in place strong security measures to prevent such activities.
[0004] Further, the existing document verification mechanism does not take large dataset of facial features into consideration. It is difficult to capture live images during various conditions such as age, noisy background, low light or when a person is wearing glasses or has facial hair.
[0005] There is, therefore, a need in the art for an autonomous driving control system that can overcome at least the above-mentioned challenges in the art.

OBJECTS OF THE PRESENT DISCLOSURE
[0006] It is an object of the present disclosure to provide an autonomous identity authentication system for application document verification, enhances accuracy by accurately match a user’s face to an image or a video in real-time.
[0007] It is an object of the present disclosure to provide an autonomous identity authentication system for application document verification provides improved efficiency and reduce fraud.
[0008] It is an object of the present disclosure to provide an autonomous identity authentication system for application document verification, enhances security and accessibility.
[0009] It is an object of the present disclosure to provide an autonomous identity authentication system for application document verification, provides a robust privacy and security controls.

SUMMARY
[0010] The present disclosure relates to a face recognition technology. More specifically, the present disclosure relates to an autonomous identity authentication system for application document verification, and method thereof.
[0011] The present disclosure provides an autonomous identity authentication system for application document verification. The system comprises one or more processors and a memory coupled to the one or more processors. The memory stores instructions which when executed by the one or more processors causes the system to receive at least one application form pertaining to a user credentials and an user image from at least one user associated with at least one computing device. Further, the system verifies the user image by a face detector, and store the user image in a database based on a predefined conditions. The predefined conditions comprise at least one of a presence of user face, an absence of user face, and a presence multiple user faces. The system generate one or more encrypted face prints based on the user image by an AI digital face print generator, and detect an identical user image in the database. Further, the system compares the user credentials and the user image with an existing user data in at least one validated entity to authenticate the at least one users. The system generates a verification slip for the at least one application based on the authentication of the at least one user. The verification slip comprises at least one of a Quick response (QR) code, the user credentials, and an identification number. Finally, fetch the user credentials and the encrypted face print based on scanning the QR code at a verification center, and verify a live feed data captured by an image capturing device to enable successful authentication of the at least one user.
[0012] In an aspect, the AI digital face print generator can be configured to generate a digitally encrypted vectorized representation for the user image and provide the one or more encrypted face prints.
[0013] In an aspect, the system can be configured to detect the identical user image in the database by a de-duplicator to enable one or more decisions. The one or more decisions comprise at least one of a presence identical user image and an absence of the identical user image.
[0014] In an aspect, the system can be configured to generate a warning notification to the at least one user indicating the presence identical user image, and permit the at least one user to re-upload the user image.
[0015] In an aspect, the system can be configured to extract a registered ID number of the user from at least one validated entity from the user credentials. Followed by, submitting the registered user ID on a portal of the at least one validated entity to retrieve at least one of an information of the at least one user comprising a registered user image, and a registered image ID of the at least one user.
[0016] In an aspect, the system can be configured to store the encrypted face print and the registered ID number in the face recognition model based on verification of the user credentials. Further, notify the at least one user to re-upload the user image based on the mismatch of the encrypted face print and the registered image.
[0017] In an aspect, the at least one user submits the verification slips to enable authentication in the verification center, failing which may result to cancellation of the at least one application form.
[0018] In an aspect, the system can be configured to extract one or more face features from the user image and feed to at least one of the face recognition model and a robust real-spoof discriminator model. The face recognition model matches the extracted face features with the digitally encrypted vectorized representation. The robust real-spoof discriminator model checks whether the extracted face features belong to at least one of a real human face, a spoof face from mobile screens, and a printout.
[0019] In an aspect, the extracted face features are matched with the encrypted face print and approved as the real human face the at least one user is successfully authenticated, the extracted face features are not matched with the encrypted face print and not approved as the real human face the at least one user is not authenticated.
[0020] The present disclosure provides a method for application document verification by using an autonomous identity authentication system. The method comprises receiving at least one application form pertaining to a user credentials and an user image from at least one user associated with at least one computing device. The method comprises verifying the user image by a face detector, and storing the user image in a database based on a predefined conditions. The predefined condition comprises at least one of a presence of user face, an absence of user face, and a presence multiple user faces. The method comprises generating one or more encrypted face prints based on the user image by an AI digital face print generator, and detect an identical user image in the database. The method comprises comparing, by the system, the user credentials and the user image with an existing user data in at least one validated entity to authenticate the at least one users. The method comprises generating, by the system, a verification slip for the at least one application based on the authentication of the at least one user, wherein the verification slip comprises at least one of a QR code, the user credentials, and an identification number. The method comprises fetching, by the system, the usezr credentials and the encrypted face print based on scanning the QR code at a verification center, and verify a live feed data captured by an image capturing device to enable successful authentication of the at least one user.

BRIEF DESCRIPTION OF THE DRAWINGS
[0021] The accompanying drawings are included to provide a further understanding of the present disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.
[0022] The diagrams are for illustration only, which thus is not a limitation of the present disclosure, and wherein:
[0023] FIG. 1 illustrates exemplary functional components of an autonomous identity authentication system for application document verification, in accordance with an embodiment of the present disclosure.
[0024] FIG. 2 illustrates exemplary representations of network architecture of the autonomous identity authentication system for application document verification, in accordance with an embodiment of the present disclosure.
[0025] FIG. 3 illustrates a block diagram of the autonomous identity authentication system, in accordance with an embodiment of the present disclosure.
[0026] FIG. 4 illustrates exemplary representations of a user registration using the autonomous identity authentication system, in accordance with an embodiment of the present disclosure.
[0027] FIG. 5 illustrates exemplary representations of a digital face print generation and identifying de-duplication of the applications using the autonomous identity authentication system, in accordance with an embodiment of the present disclosure.
[0028] FIG. 6 illustrates exemplary representations of verification with a validated entity using the autonomous identity authentication system, in accordance with an embodiment of the present disclosure.
[0029] FIG. 7 illustrates exemplary representations of verification slip generation using the autonomous identity authentication system, in accordance with an embodiment of the present disclosure.
[0030] FIG. 8 illustrates exemplary representations of on–premise authentication using the autonomous identity authentication system and the smart device, in accordance with an embodiment of the present disclosure.
[0031] FIG. 9 illustrates an exemplary computer system to implement the proposed system in accordance with embodiments of the present disclosure.

DETAILED DESCRIPTION
[0032] In the following description, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the present invention. It will be apparent to one skilled in the art that embodiments of the present invention may be practiced without some of these specific details.
[0033] Embodiments of the present invention include various steps, which will be described below. The steps may be performed by hardware components or may be embodied in machine-executable instructions, which may be used to cause a general-purpose or special-purpose processor programmed with the instructions to perform the steps. Alternatively, steps may be performed by a combination of hardware, software, firmware and/or by human operators.
[0034] Embodiments of the present invention may be provided as a computer program product, which may include a machine-readable storage medium tangibly embodying thereon instructions, which may be used to program a computer (or other electronic devices) to perform a process. The machine-readable medium may include, but is not limited to, fixed (hard) drives, magnetic tape, floppy diskettes, optical disks, compact disc read-only memories (CD-ROMs), and magneto-optical disks, semiconductor memories, such as ROMs, PROMs, random access memories (RAMs), programmable read-only memories (PROMs), erasable PROMs (EPROMs), electrically erasable PROMs (EEPROMs), flash memory, magnetic or optical cards, or other type of media/machine-readable medium suitable for storing electronic instructions (e.g., computer programming code, such as software or firmware).
[0035] Various methods described herein may be practiced by combining one or more machine-readable storage media containing the code according to the present invention with appropriate standard computer hardware to execute the code contained therein. An apparatus for practicing various embodiments of the present invention may involve one or more computers (or one or more processors within a single computer) and storage systems containing or having network access to computer program(s) coded in accordance with various methods described herein, and the method steps of the invention could be accomplished by modules, routines, subroutines, or subparts of a computer program product.
[0036] If the specification states a component or feature “may”, “can”, “could”, or “might” be included or have a characteristic, that particular component or feature is not required to be included or have the characteristic.
[0037] As used in the description herein and throughout the claims that follow, the meaning of “a,” “an,” and “the” includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein, the meaning of “in” includes “in” and “on” unless the context clearly dictates otherwise.
[0038] Exemplary embodiments will now be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments are shown. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. These embodiments are provided so that this invention will be thorough and complete and will fully convey the scope of the invention to those of ordinary skill in the art. Moreover, all statements herein reciting embodiments of the invention, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents as well as equivalents developed in the future (i.e., any elements developed that perform the same function, regardless of structure).
[0039] While embodiments of the present invention have been illustrated and described, it will be clear that the invention is not limited to these embodiments only. Numerous modifications, changes, variations, substitutions, and equivalents will be apparent to those skilled in the art, without departing from the spirit and scope of the invention, as described in the claim.
[0040] FIG. 1 illustrates exemplary functional components of an autonomous identity authentication system for application document verification, in accordance with an embodiment of the present disclosure.
[0041] Referring to FIG. 1, the exemplary network architecture 100 is depicted in which or with which an autonomous identity authentication system (also known as “system) 102 for application document verification may be implemented, in accordance with an embodiment of the present disclosure.
[0042] In an embodiment, the system 102 can incorporate an Artificial Intelligence (AI) Engine 104 to facilitate with face recognition systems to authenticate the application system by using machine learning algorithms to analyze and compare images of user image to confirm a person's identity. The system can be connected to a network 106, which is further connected to at least one computing devices 108-1, 108-2, … 108-N (collectively referred as computing device 108, herein) associated with one or more users devices 110-1, 110-2, … 110-N (collectively referred as computing device 110, herein). The computing device 108 can be personal computers, laptops, tablets. Further, the network 104 can be configured with a centralized server 112. This architecture allows various facilities in the facial recognition technology to synchronize the user data in one central database 218 (FIG. 2) which is easily accessible via the above network 104.
[0043] In an embodiment, the system 102 may receive at least one input data from the at least one computing devices 108. A person of ordinary skill in the art will understand that the at least one computing devices 108 may be individually referred to as computing device 108 and collectively referred to as computing devices 108. In an embodiment, the computing device 110 may also be referred to as User Equipment (UE). Accordingly, the terms “computing device” and “User Equipment” may be used interchangeably throughout the disclosure.
[0044] In an embodiment, the computing device 108 may receive the response and provide to the users 110 over a point-to-point or point-to-multipoint communication channel or network 104 to the system 102.
[0045] In an embodiment, the computing device 108 may involve collection, analysis, and sharing of data received from the system 102 via the communication network 104.
[0046] In an embodiment, the system 102 may execute one or more instructions, through the computing device 110, using machine learning algorithms to analyze and compare images of user image to confirm a person's identity.
[0047] In an exemplary embodiment, the communication network 106 may include, but not be limited to, at least a portion of one or more networks having one or more nodes that transmit, receive, forward, generate, buffer, store, route, switch, process, or a combination thereof, etc. one or more messages, packets, signals, waves, voltage or current levels, some combination thereof, or so forth. In an exemplary embodiment, the communication network 104 may include, but not be limited to, a wireless network, a wired network, an internet, an intranet, a public network, a private network, a packet-switched network, a circuit-switched network, an ad hoc network, an infrastructure network, a Public-Switched Telephone Network (PSTN), a cable network, a cellular network, a satellite network, a fiber optic network, or some combination thereof.
[0048] In an embodiment, the one or more computing devices 110 may communicate with the system 102 via a set of executable instructions residing on any operating system. In an embodiment, the one or more computing devices 110 may include, but not be limited to, any electrical, electronic, electro-mechanical, or an equipment, or a combination of one or more of the above devices such as mobile phone, smartphone, Virtual Reality (VR) devices, Augmented Reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other computing device, wherein the one or more computing devices 110 may include one or more in-built or externally coupled accessories including, but not limited to, a visual aid device such as camera, audio aid, a microphone, a keyboard, input devices such as touch pad, touch enabled screen, electronic pen, receiving devices for receiving any audio or visual signal in any range of frequencies, and transmitting devices that can transmit any audio or visual signal in any range of frequencies. It may be appreciated that the one or more computing devices 110 may not be restricted to the mentioned devices and various other devices may be used.
[0049] In an embodiment, the system is connected to a network 106, which is connected to the at least one computing device 110 may include but not limited to personal computers, smartphones, laptops, tablets, smart watches as well as other IoT devices that support a display. The one or more users 110 may include but not limited to: an applicant, a customer, a contractor, and the likes.
[0050] In an embodiment, the network 104 is further configured with a centralized server 112 including a database 218 (FIG.2), where all output is stored as part of document verification of the user 110. In an embodiment, the computing device 108 may involve collection, analysis, and sharing of data received from the system 102 via the communication network 104.
[0051] In an embodiment, the system 102 can be configured to receive at least one application form pertaining to a user credentials and an user image 404 from at least one user 110 associated with at least one computing device 108. Further, the system 102 verifies the user image 404 by a face detector 406, and stores the user image 404 in a database 218 based on a predefined conditions. The predefined conditions of the user image 404 comprise at least one of a presence of user face, an absence of user face, and a presence multiple user faces. Followed by, generation of a digitally encrypted vectorized representation 504 by an AI digital face print generator 502 based on the user image 404. The one or more encrypted face print 702 (interchangeably used as encrypted digital face print, herein)can be provided to a de-duplicator 506 to detect an identical user image in the database 218. Further, the de-duplicator 506 can be configured to enable one or more decisions, where the one or more decisions including but not limited to: a presence identical user image and an absence of the identical user image. The system 102 generates a warning notification to the at least one user 110 indicating the presence identical user image, and permits the at least one user 110 to re-upload the user image 410.
[0052] Further, based on the absence of the identical user image, the system 102 to compare the user credentials and the user image 404 with an existing user data in at least one validated entity 602 to authenticate the at least one users 110. Furthermore, the system 102 can be configured to generate a verification slip 708 for the at least one application based on the authentication of the at least one user 110. The verification slip 708 can comprises at least one of a QR code, the user credentials, and an identification number. Finally, the system 102 fetches the user credentials and the encrypted face print 702 based on scanning the QR code at a verification center, and verify a live feed data captured by an image capturing device to enable successful authentication of the at least one user.
[0053] Although FIG. 1 shows exemplary components of the network architecture 100, in other embodiments, the network architecture 100 may include fewer components, different components, differently arranged components, or additional functional components than depicted in FIG. 1. Additionally, or alternatively, one or more components of the network architecture 100 may perform functions described as being performed by one or more other components of the network architecture 100.
[0054] FIG. 2 illustrates exemplary representations of network architecture of the autonomous identity authentication system for application document verification, in accordance with an embodiment of the present disclosure.
[0055] FIG. 2 with reference to FIG. 1, illustrates an exemplary representation of the system 102 for facilitating training of a artificial neural network, in accordance with an embodiment of the present disclosure. In an aspect, the system 102 may comprise one or more processor(s) 202. The one or more processor(s) 202 may be implemented as one or more microprocessors, microcomputers, microcontrollers, edge or fog microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that process data based on operational instructions. Among other capabilities, the one or more processor(s) 202 may be configured to fetch and execute computer-readable instructions stored in a memory 204 of the system 102. The memory 204 may be configured to store one or more computer-readable instructions or routines in a non-transitory computer readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory 204 may comprise any non-transitory storage device including, for example, volatile memory such as Random Access Memory (RAM), or non-volatile memory such as Erasable Programmable Read-Only Memory (EPROM), flash memory, and the like.
[0056] Referring to FIG. 2, the system 102 may include an interface(s) 206. The interface(s) 206 may comprise a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) 206 may facilitate communication to/from the system 102. The interface(s) 206 may also provide a communication pathway for one or more components of the system 102. Examples of such components include, but are not limited to, processing unit/engine(s) 208 and a local database 218.
[0057] In an embodiment, the processing unit/engine(s) 208 may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) 208. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) 208 may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) 208 may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) 208. In such examples, the system 102 may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the system 102 and the processing resource. In other examples, the processing engine(s) 208 may be implemented by electronic circuitry.
[0058] In an embodiment, the local database 218 may comprise data that may be either stored or generated as a result of functionalities implemented by any of the components of the processor 202 or the processing engines 208. In an embodiment, the local database 218 may be separate from the system 102.
[0059] In an exemplary embodiment, the processing engine 208 may include one or more engines selected from any of a face detector module 210, a de-duplicator module 212, a face feature extractor module 214, and other modules 216 having functions that may include but are not limited to testing, storage, and peripheral functions, such as wireless communication unit for remote operation, audio unit for alerts and the like.
[0060] In an embodiment, the face detector module 210 may verify the user image 404, and store the user image in a database 218 based on predefined conditions. The predefined conditions comprise at least one of a presence of user face, an absence of user face, and a presence multiple user faces.
[0061] In an embodiment, the de-duplicator module 212 may be configured to detect identical user images by the face recognition system by running over the encrypted face prints.
[0062] In an embodiment, the face feature extractor 214 may be configured to extract the face features in a vectorized numerical format during live feed 806 of the on-premise authentication.
[0063] FIG. 3 illustrates a block diagram various functionalities of the autonomous identity authentication system, in accordance with an embodiment of the present disclosure.
[0064] In an embodiment, the system 102 performs various functionalities which include a user registration 302, a duplication of the applications 304, a verification with validated entity 306, a verification slip generation 308, and a on-premise authentication 310.
[0065] In an embodiment, the system 102 is configured to receive at least one application form pertaining to a user credentials and user image from the user associated with the computing device. The user registration 302 can be performed by applying for the registration process by the user 110 using online portal for that particular registration. Further, the system 102 detects identical user image 404 i.e. the duplication of the applications 304 by the de-duplicator 506. Furthermore, the system 102 enables the verification slip generation 308. Finally, the system 102 fetches the user credentials and the encrypted face print based on scanning the QR code at a verification center enabling the on-premise authentication 310.
[0066] FIG. 4 illustrates exemplary representations of a user registration using the autonomous identity authentication system, in accordance with an embodiment of the present disclosure.
[0067] In an embodiment, the user 110 applies for the registration process by opening a online portal 402 for a particular registration. The user 110 will sign up to the portal with his/her valid credentials (also known as user credentials, herein). The user credentials can include email ID, phone number, a password. A user ID is generated and sent to the user 110 via email. Thus, the user 110 is signed up successfully. Further, the user 110 logins to the account in the online portal 402 with the user ID and the set password. The user 110 completes the entire registration process by filling up the form with the user credentials. The user 110 has to upload an user image 404 including but not limited to a digital passport size photo, a scanned photo, a photograph, and the likes. The uploaded user image 404 will be passed through a face detector 406 based on one or more conditions. The one or more conditions can include at least one of a presence of user face, an absence of user face, and a presence multiple user faces. If the face detector 406 unable to detect any face in the uploaded user image 404, and then the user 110 will be notified to re-upload the user image 410. Once, the user data is verified after all the checks, the user image 404 and the user credentials will be pushed to the database 218.
[0068] FIG. 5 illustrates exemplary representations of a digital face print generation and identifying de-duplication of the applications using the autonomous identity authentication system, in accordance with an embodiment of the present disclosure.
[0069] In an embodiment, the system 102 fetches the user image 404 from the database 218 and passed through a AI Digital Face Print Generator 502 to generate digitally encrypted vectorized representation for each of the user image 404. These encrypted face prints will be unique for each user image 404. Further, a de-duplicator detects the identical user image in the database 218 to enable one or more decisions, wherein the one or more decisions comprises at least one of a presence identical user image and an absence of the identical user image. If presence of identical user image is found a warning message/email 508 is sent to the user 110, whose uploaded user image 404 are found to be duplicates with other users. The user 110 shall get a span of at least 7 days to re-upload the user image 404. If no user image 404 are uploaded within 7 days, or again duplicates are found with the re-uploaded user image 404, then the at least one application shall get cancelled.
[0070] In another embodiment, if absence of the identical user image exists, then the digitally encrypted face prints 504 are pushed into the database 218 as final for the next stages and no changes will be allowed further.
[0071] FIG. 6 illustrates exemplary representations of verification with a validated entity using the autonomous identity authentication system, in accordance with an embodiment of the present disclosure.
[0072] In an embodiment, the verification with a validated entity 602 using the system 102 can be performed by fetching the user credentials and the encrypted print 612 of the user 110 from the database 218. The system 110 will extract a registered credentials 606 and a registered user image 608 of the user 110 from the portal of the validated entity 602 by maintaining the API protocols. The validated entity 602 can include but not limited to: a government organization, a private organization, an institution, and the likes. Further, the user 110 provided credentials will be matched with the information which has been collected from the validated entity 602. If there is a successful match with the credentials and the information from the validated entity 602, no warning is generated, the at least one application is clear to proceed to the next step. If match is unsuccessful then the user 110 will be asked to fill the credentials again and the process goes back to stage I. After verification of the credentials, the system will push both the encrypted print 612 and the registered user image 608 into the face recognition unit 610. Further, if the encrypted print 612 matches with the registered user image 608, then it retains the face print in the database 218. If the encrypted print 612 does not match with the registered user image 608, a warning message/email 508 is sent to the user 110, and then the user 110 will be notified to re-upload the user image 410.
[0073] FIG. 7 illustrates exemplary representations of verification slip generation using the autonomous identity authentication system, in accordance with an embodiment of the present disclosure.
[0074] In an embodiment, all the user credentials and the encrypted face prints would be fetched from the database. A second level of encryption layer encapsulates the user credentials and the level-1 encrypted digital face prints to generate a QR code for each user 110. After the QR code generation, the system 102 will generate a verification Slip 706 for each of the application where the credentials of the applicant will be embedded on it with the QR code which has been generated in step 2 and a unique identification number. Further, generating the verification slips 706 for each of the applications, these slips will be released in the online portal 402. The soft copy of the verification slips will be available for download once released, and can be downloaded by the users 110 by logging into the portal 402. It is mandatory for the users 110 to present the verification slips 706 issued to them while the on-premise authentication 310 takes place, failing which may result to cancellation of the application.
[0075] FIG. 8 illustrates exemplary representations of on–premise authentication using the autonomous identity authentication system and the smart device, in accordance with an embodiment of the present disclosure.
[0076] In an embodiment, at the Verification Center, authentication is taken forward by the user 110 interaction with the smart device 816. The user 110 presents the issued verification slip 706 containing a QR code to the smart device 816, which is scanned by the QR code scanner 814 equipped with the smart device 816. The system 102 fetches the credentials and the encrypted face print of the applicant from the QR code. If it does exist, the camera equipped with the smart device 816 starts capturing the user face for live feed 806 processing within the smart device 816. Further, the captured live feed 806 is passed through a face detector model 406 which extracts face features in a vectorized numerical format. The fetched information will be checked in the system pipeline whether it exists in the database 218. If the information does not exist in the database, then the authentication of the applicant will fail. If the information exists in the database 218 the user 110 will either to stand in front of an image capturing unit 804, else the camera attached to the smart device 816 will capture the applicants’ face, where the live feed 806 will be processing in backend through our system.
[0077] In an embodiment, the live feed 806 will pass through our face detector 406 where the face features will be extracted in a vectorized numerical format. Further, the extracted face features will go through the following two parallel processes. The system 102 will feed the face features into our face recognition model 610 where the features will be matched with the digitally encrypted face print 612 which has already been fetched. On the other hand, the face features will also be fed into our robust real-spoof discriminator 810 where it will be validated whether the features are belonging to a real human face or a spoof face from mobile screens, printouts or cut-outs etc.
[0078] In an embodiment, the parallel processes will lead to the following decisions. In the face recognition model 610, if the face features do not match with the encrypted face print 612, then the authentication of the user 110 will fail. If the real-spoof discriminator 810 detects the face features to be a spoof face, then the authentication of the applicant will fail. If the face features are matched with the encrypted face print and also found to be a real human face, then the authentication of the user 110 is successful. The monitor equipped with the smart device can display the final authentication result.
[0079] In an embodiment, the face recognition model 610 the AI-based digital face print generator can be configured to generate a unique, vectorized, and encrypted numerical representation of a specific face that will not match with any other face's representation. This representation is referred as a digital face print. The face recognition model 610 can accurately recognize a person's face when trained on an old image of the user 110. The face recognition model 610 can handle variations such as the person wearing glasses, facial hair, headwear, or having a different hairstyle. The system 102 will generate warnings and alerts if it detects a partial face, eyes covered (e.g. by sunglasses), or any form of veiling (e.g. masks or scarves).The face recognition model 610 can also efficiently recognize faces even when the background is busy or noisy, or when the photo is of low resolution or black and white.
[0080] In an embodiment, the real-spoof discriminator 810 is capable of determining whether a face is that of a real human or a replica, such as an image on a mobile screen, printout, or cut-out. The system 102 does not require the applicant to perform any specific actions, such as looking in a certain direction, and therefore, validation is quick. The real-spoof discriminator 810 uses texture analysis, depth analysis, and color space analysis on the face to quickly determine if it is a real or spoof face as soon as a picture is captured.
[0081] In an embodiment, the system 102 provides a human intervention less and a foolproof architecture where the users 110 cannot upload the user image 404 with no face or multiple faces on the fly, which prevents spamming of applications with irrelevant photos. The de-duplicator eliminates the possibility of multiple applications with the same person's photograph. Further, by fetching validated entity 602 credentials from the ID provided by the user and matching them to the information provided on the form, we ensure that no applicant applies with someone else's credentials or photo.
[0082] In an embodiment, the integration of QR codes eliminates the need for manual checking of credentials at on-premise authentication, reducing the need for human intervention and labor costs. The real-spoof discriminator 810 ensures that no false proxies take place at on-premise verification by requiring the applicant to present in person. This makes it impossible to fool the face authentication system with someone else's spoof face presentation.
[0083] FIG. 9 illustrates an exemplary computer system 500 to implement the proposed system in accordance with embodiments of the present disclosure.
[0084] As shown in FIG. 9, a computer system can include an external storage device 910, a bus 920, a main memory 930, a read only memory 940, a mass storage device 950, communication port 960, and a processor 970. A person skilled in the art will appreciate that computer system may include more than one processor and communication ports. Examples of processor 970 include, but are not limited to, an Intel® Itanium® or Itanium 2 processor(s), or AMD® Opteron® or Athlon MP® processor(s), Motorola® lines of processors, FortiSOC™ system on a chip processors or other future processors. Processor 570 may include various modules associated with embodiments of the present invention. Communication port 560 can be any of an RS-232 port for use with a modem based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. Communication port 960 may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which the computer system connects.
[0085] Memory 930 can be Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. Read only memory 940 can be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or BIOS instructions for processor 970. Mass storage 950 may be any current or future mass storage solution, which can be used to store information and/or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or external, e.g., having Universal Serial Bus (USB) and/or Firewire interfaces), e.g. those available from Seagate (e.g., the Seagate Barracuda 7102 family) or Hitachi (e.g., the Hitachi Deskstar 7K1000), one or more optical discs, Redundant Array of Independent Disks (RAID) storage, e.g. an array of disks (e.g., SATA arrays), available from various vendors including Dot Hill Systems Corp., LaCie, Nexsan Technologies, Inc. and Enhance Technology, Inc.
[0086] Bus 920 communicatively couples processor(s) 970 with the other memory, storage and communication blocks. Bus 920 can be, e.g. a Peripheral Component Interconnect (PCI) / PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), USB or the like, for connecting expansion cards, drives and other subsystems as well as other buses, such a front side bus (FSB), which connects processor 970 to software system.
[0087] Optionally, operator and administrative interfaces, e.g. a display, keyboard, and a cursor control device, may also be coupled to bus 920 to support direct operator interaction with computer system. Other operator and administrative interfaces can be provided through network connections connected through communication port 960. External storage device 510 can be any kind of external hard-drives, floppy drives, IOMEGA® Zip Drives, Compact Disc - Read Only Memory (CD-ROM), Compact Disc - Re-Writable (CD-RW), Digital Video Disk - Read Only Memory (DVD-ROM). Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system limit the scope of the present disclosure.
[0088] Embodiments of the present disclosure may be implemented entirely hardware, entirely software (including firmware, resident software, micro-code, etc.) or combining software and hardware implementation that may all generally be referred to herein as a “circuit,” “module,” “component,” or “system.” Furthermore, aspects of the present disclosure may take the form of a computer program product comprising one or more computer readable media having computer readable program code embodied thereon.
[0089] Thus, it will be appreciated by those of ordinary skill in the art that the diagrams, schematics, illustrations, and the like represent conceptual views or processes illustrating systems and methods embodying this invention. The functions of the various elements shown in the figures may be provided through the use of dedicated hardware as well as hardware capable of executing associated software. Similarly, any switches shown in the figures are conceptual only. Their function may be carried out through the operation of program logic, through dedicated logic, through the interaction of program control and dedicated logic, or even manually, the particular technique being selectable by the entity implementing this invention. Those of ordinary skill in the art further understand that the exemplary hardware, software, processes, methods, and/or operating systems described herein are for illustrative purposes and, thus, are not intended to be limited to any particular.
[0090] As used herein, and unless the context dictates otherwise, the term "coupled to" is intended to include both direct coupling (in which two elements that are coupled to each other contact each other) and indirect coupling (in which at least one additional element is located between the two elements). Therefore, the terms "coupled to" and "coupled with" are used synonymously. Within the context of this document terms "coupled to" and "coupled with" are also used euphemistically to mean “communicatively coupled with” over a network, where two or more devices are able to exchange data with each other over the network, possibly via one or more intermediary device.
[0091] It should be apparent to those skilled in the art that many more modifications besides those already described are possible without departing from the inventive concepts herein. The inventive subject matter, therefore, is not to be restricted except in the spirit of the appended claims. Moreover, in interpreting both the specification and the claims, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms “comprises” and “comprising” should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced. Where the specification claims refer to at least one of something selected from the group consisting of A, B, C …. and N, the text should be interpreted as requiring only one element from the group, not A plus N, or B plus N, etc.
[0092] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.

ADVANTAGES OF THE INVENTION
[0093] The present disclosure provides an autonomous identity authentication system for application document verification, enhances accuracy by accurately match a user’s face to an image or a video in real-time.
[0094] The present disclosure provides an an autonomous identity authentication system for application document verification provides improved efficiency and reduce fraud.
[0095] The present disclosure provides an autonomous identity authentication system for application document verification, enhances security and accessibility.
[0096] The present disclosure provides an autonomous identity authentication system for application document verification, provides a robust privacy and security controls.
, Claims:1. An autonomous identity authentication system (102) and smart device for application document verification, the system (102) comprises:
one or more processors (202); and
a memory (204) coupled to the one or more processors (202), wherein said memory (204) stores instructions which when executed by the one or more processors (202) causes the system to:
receive at least one application form pertaining to a user credentials and an user image (404) from at least one user (110) associated with at least one computing device (108);
verify the user image (404) by a face detector (406), and store the user image (404) in a database (218) based on a predefined conditions, wherein the predefined conditions comprises at least one of a presence of user face, an absence of user face, and a presence multiple user faces;
generate one or more encrypted face prints (504) based on the user image (404) by an AI digital face print generator (502), and detect an identical user image in the database (218);
compare the user credentials and the user image (404) with an existing user data in at least one validated entity to authenticate the at least one users (110);
generate a verification slip (706) for the at least one application based on the authentication of the at least one user (110), wherein the verification slip (706) comprises at least one of a QR code, the user credentials, and an identification number; and
fetch the user credentials and the encrypted face print (504) based on scanning the QR code at a verification center by a smart device (816), and verify a live feed (806) data captured by an image capturing device (804) by the smart device (816)to enable successful authentication of the at least one user (110).

2. The system (102) as claimed in claim 1, wherein the AI digital face print generator (502) is configured to:
generate a digitally encrypted vectorized representation for the user image (404) and provide the one or more encrypted face prints.
3. The system (102) as claimed in claim 1, wherein the system (102) is configured to:
detect the identical user image in the database (218) by a de-duplicator (506) to enable one or more decisions, wherein the one or more decisions comprises at least one of a presence identical user image and an absence of the identical user image.
4. The system (102) as claimed in claim 3, wherein the system (102) is configured to:
generate a warning notification to the at least one user (110) indicating the presence identical user image, and permit the at least one user to re-upload the user image.
5. The system (102) as claimed in claim 1, wherein the system (102) is configured to:
extract a registered ID number of the user (110) from at least one validated entity (602) from the user credentials; and
submit the registered user ID (604) on a portal of the at least one validated entity (602) to retrieve at least one of an information of the at least one user comprising a registered user image (608), and a registered image ID (606) of the at least one user (110).
6. The system (102) as claimed in claim 1, wherein the system (102) is configured to:
store the encrypted face print (504) and the registered ID number in the face recognition model based on verification of the user credentials; and
notify the at least one user (110) to re-upload the user image based on the mismatch of the encrypted face print and the registered image.

7. The system (102) as claimed in claim 1, wherein the at least one user (110) submits the verification slips (706) to the smart device (816) for enabling authentication in the verification center, failing which may result to cancellation of the at least one application form.
8. The system (102) as claimed in claim 1, wherein the system (102) is configured to:
extract one or more face features from the user image (404) and feed to at least one of the face recognition model (610) and a robust real-spoof discriminator model (810),
wherein the face recognition model (610) matches the extracted face features with the digitally encrypted vectorized representation,
wherein the robust real-spoof discriminator model (810) checks whether the extracted face features belong to at least one of a real human face, a spoof face from mobile screens, and a printout.
9. The system (102) as claimed in claim 8, wherein the extracted face features are matched with the encrypted face print and approved as the real human face the at least one user is successfully authenticated,
wherein the extracted face features are not matched with the encrypted face print and not approved as the real human face the at least one user is not authenticated.
10. A method for application document verification using a autonomous identity authentication system (102) as claimed in claim 1, the method comprises:
receiving at least one application form pertaining to a user credentials and an user image (404) from at least one user (110) associated with at least one computing device (108);
verifying the user (110) image by a face detector (406), and storing the user image (404) in a database based on a predefined conditions, wherein the predefined conditions comprises at least one of a presence of user face, an absence of user face, and a presence multiple user faces;
generating one or more encrypted face prints (504) based on the user image (110) by an AI digital face print generator (502), and detect an identical user image in the database (218);
comparing, by the system (102), the user credentials and the user image (404) with an existing user data in at least one validated entity to authenticate the at least one users;
generating, by the system (102), a verification slip for the at least one application based on the authentication of the at least one user, wherein the verification slip comprises at least one of a QR code, the user credentials, and an identification number; and
fetching, by the system (102), the user credentials and the encrypted face print (504) based on scanning the QR code at a verification center, and verify a live feed (806) data captured by an image capturing device (804) to enable successful authentication of the at least one user (110).