Contacless portable full hand scanner

Abstract

Methods and systems are provided for capturing a handprint using a handheld hand scanner. The methods and systems establish a communication session between a handheld hand scanner and a mobile device and send, to the handheld hand scanner, an instruction from the mobile device to initiate capture of a handprint. The methods and systems receive, from the handheld hand scanner, a plurality of images of a hand, each of the plurality of images depicting a different portion of the hand and combine the plurality of images into a composite image of the hand. The methods and systems convert the composite image of the hand into the handprint and process a record associated with a subject based on the handprint.

Description

CONTACLESS PORTABLE FULL HAND SCANNERBACKGROUND

[0001] Various systems enable capture of fingerprints and handprints. These systems use high end cameras to capture images of the fingers / hands at very high resolution. Typically oversampling the images is required to meet stringent industry standards regarding image quality specifications. Imaging systems used to capture images of sufficiently high image resolution with quality that meets minimum specifications are expensive and complex.SUMMARY

[0002] In some aspects, the techniques described herein relate to a method including: establishing a communication session between a handheld hand scanner and a mobile device; sending, to the handheld hand scanner, an instruction from the mobile device to initiate capture of a handprint; receiving, from the handheld hand scanner, a plurality of images of a hand, each of the plurality of images depicting a different portion of the hand; combining the plurality of images into a composite image of the hand; converting the composite image of the hand into the handprint; and processing a record associated with a subject (e.g., a user or person) based on the handprint. The plurality of images should overlap parts of other plurality of images to enable the effective and accurate generation of the composite image. It is also possible that the plurality of images can be used without combining them into a composite image.

[0003] In some aspects, the techniques described herein relate to a method, wherein the communication session includes a short-range communication session.

[0004] In some aspects, the techniques described herein relate to a method, wherein capturing the plurality of images of the hand includes: measuring a distance between an image sensor of the handheld hand scanner and an object; determining that the distance corresponds to a threshold distance; and in response to determining that the distance corresponds to the threshold distance, setting a focus of a variable focus lens of the handheld hand scanner based on the measured distance. In some aspects, the lens of thescanner is a fixed focus and the distance used in this system is presented to indicate the acceptable range for capture.

[0005] In some aspects, the techniques described herein relate to a method, further including: activating a first illumination component of the handheld hand scanner for capturing images of the object; capturing a first image of the plurality of images including a first portion of the hand; and sending, via the communication session, the first image to the mobile device for processing the first image.

[0006] In some aspects, the techniques described herein relate to a method, wherein processing the first image includes: sending the first image to a remote server to be used in the initialization and / or generation of the composite image.

[0007] In some aspects, the techniques described herein relate to a method, wherein processing the first image includes: segmenting the first image to identify a portion of the first image that depicts the first portion of the hand; and determining whether the identified portion of the first image satisfies a quality metric.

[0008] In some aspects, the techniques described herein relate to a method, further including: in response to determining that the identified portion of the first image fails to satisfy the quality metric, causing the handheld hand scanner to recapture the portion of the hand corresponding to the first portion of the hand again.

[0009] In some aspects, the techniques described herein relate to a method, wherein determining whether the identified portion of the first image satisfies the quality metric includes at least one of: determining whether the identified portion corresponds to a hand portion (in cases where a full image of the hand was previously collected); determining whether a focus of the first image corresponds to a threshold focus level; determining whether an amount of motion blur in the first image transgresses a motion blur threshold; or determining whether one or more occlusions are depicted in the identified portion.

[0010] In some aspects, the techniques described herein relate to a method, further including: in response to determining that the identified portion of the first image satisfies the quality metric, adding the first image to the composite image; and instructing the handheld hand scanner to capture a second image of the plurality of images.

[0011] In some aspects, the techniques described herein relate to a method, further including: identifying a portion of the composite image that corresponds to the identified portion of the first image; selecting a region of the portion of the composite image that is missing pixel values; and populating the pixel values in the selected region using pixel values of the identified portion of the first image.

[0012] In some aspects, the techniques described herein relate to a method, further including: determining whether the composite image completely represents the hand; and in response to determining that the composite image fails to completely represent the hand, instructing the handheld hand scanner to capture the second image. This operation can be based on one or more previous images of the whole hand or images of typical hands.

[0013] In some aspects, the techniques described herein relate to a method, further including: determining whether the composite image completely represents the hand; and in response to determining that the composite image completely represents the hand, converting the composite image of the hand into the handprint by: performing Contrast Limited Adaptive Histogram Equalization (CLAHE) on the composite image; applying a noise reduction filter to the composite image; stretching a composite image histogram to increase friction ridge contrast; and inverting a composite image grayscale to darken friction ridges of the hand and to brighten friction ridge valleys of the hand. CLAHE is one example algorithm that can be used but any other suitable algorithm can be used in combination or instead of the CLAHE algorithm.

[0014] In some aspects, the techniques described herein relate to a method, wherein processing the record associated with the subject based on the handprint includes: searching a plurality of handprints using the handprint to determine whether any of the plurality of handprints matches the handprint; in response to determining that none of the plurality of handprints matches the handprint, generating the record including the handprint and associating the record with the subject; and in response to determining that the record of the plurality of handprints matches the handprint, obtaining one or more access policies from the record (e.g., for performing identity verification where a print is matched against a known print, performing an action in association with the print, and / or controlling access to a protected resource) based on the one or more access policies.

[0015] In some aspects, the techniques described herein relate to a method, further including adding biometric, demographic, and biographic information to the record of the subject.

[0016] In some aspects, the techniques described herein relate to a method, wherein the handheld hand scanner is held by an operator and moved around to capture the plurality of images.

[0017] In some aspects, the techniques described herein relate to a method, wherein the handheld hand scanner is physically stationary and the subject moves around the hand relative to the handheld scanner while the plurality of images are captured.

[0018] In some aspects, the techniques described herein relate to a method, wherein the handheld hand scanner includes a display, and wherein the handheld hand scanner presents progress and feedback of generating the composite image as the plurality of images are captured by the handheld hand scanner.

[0019] In some aspects, the techniques described herein relate to a method, further including: capturing a full image of the hand including each of the plurality of portion, the full image having a lower image resolution than an image resolution of the plurality of images; and presenting a representation of the full image of the hand to indicate the status with respect capturing all the plurality of images needed to adequately cover the hand (e.g., including disfigured hands missing one or more fingers / digits).

[0020] In some aspects, the techniques described herein relate to a method, further including: visually indicating in the full image which parts of the hand have been added to the composite image from other parts that have not been added to the composite image.

[0021] In some aspects, the techniques described herein relate to a method, further including: visually indicating in the full image an individual portion of the hand for which a corresponding one of the plurality of images fails to satisfy a quality metric.

[0022] In some aspects, the techniques described herein relate to a method, wherein the handheld hand scanner includes a first illumination component and a second illumination component, wherein the handheld hand scanner uses the first illumination component to capture the plurality of images, and wherein the handheld hand scanner presents progressand feedback of generating the composite image using the second illumination component.

[0023] In some aspects, the techniques described herein relate to a method, further including: activating the first illumination component as each of the plurality of images is being captured; and after deactivating the first illumination component, activating the second illumination component to illuminate one or more portions of the hand indicating which parts of the hand have been added to the composite image and which other parts of the hand have not been added to the composite image. In some cases, the second illumination purpose is used to show to the location of the hand where the scanner is pointing so that the operator can more efficiently capture the subject’s hand. It can also provide feedback regarding the distance and quality of the image it is currently seeing in terms of focus, motion blur, contrast and distortion by displaying information, patterns or colors indicating the status.

[0024] In some aspects, the techniques described herein relate to a method, wherein the handheld hand scanner includes an optical bandpass filter in a light path between an image sensor of the handheld hand scanner and a lens, the first illumination component and the second illumination component.

[0025] In some aspects, the techniques described herein relate to a method, further including: simultaneously activating the first and second illumination components; and filtering, by the optical bandpass filter light reflected off the hand having a frequency corresponding to the first illumination component, the image sensor receiving the filtered light reflected off the hand. In this case, the bandpass filter can reject the light of the second illumination component since the hand scanner does not need to image any reflected light from the second illumination component. The first illumination component generates the reflected light with respect to the biometric information from the subject.

[0026] In some aspects, the techniques described herein relate to a method, further including: projecting a pattern of light on the hand using the second illumination component to indicate a target region of the hand that will be captured as one of the plurality of images.

[0027] In some aspects, the techniques described herein relate to a method, further including: projecting a pattern of light on the hand using the second illumination component to indicate a target distance between the handheld hand scanner and the hand.

[0028] In some aspects, the techniques described herein relate to a method, wherein a first color or pattern of the light is projected on the hand to indicate that a distance between the handheld hand scanner and the hand transgresses a threshold range.

[0029] In some aspects, the techniques described herein relate to a method, wherein a second color or pattern of the light is projected on the hand to indicate that the distance is greater than the threshold range, and wherein a third color or pattern of the light is projected on the hand to indicate that the distance is less than the threshold range.

[0030] In some aspects, the techniques described herein relate to a system including: one or more processors configured to perform operations including: establishing a communication session between a handheld hand scanner and a mobile device; sending, to the handheld hand scanner, an instruction from the mobile device to initiate capture of a handprint; receiving, from the handheld hand scanner, a plurality of images of a hand, each of the plurality of images depicting a different portion of the hand; combining the plurality of images into a composite image of the hand; converting the composite image of the hand into the handprint; and processing a record associated with a subject based on the handprint.

[0031] In some aspects, the techniques described herein relate to a non-transitory computer-readable medium including non-transitory computer-readable instructions that, when executed by one or more processors, configure the one or more processors to perform operations including: establishing a communication session between a handheld hand scanner and a mobile device; sending, to the handheld hand scanner, an instruction from the mobile device to initiate capture of a handprint; receiving, from the handheld hand scanner, a plurality of images of a hand, each of the plurality of images depicting a different portion of the hand; combining the plurality of images into a composite image of the hand; converting the composite image of the hand into the handprint; and processing a record associated with a subject based on the handprint, such as to create a new record if one does not exist or verifying identity using existing records.BRIEF DESCRIPTION OF THE DRAWINGS

[0032] FIG. l is a block diagram of an example handprint generation system, according to some examples.

[0033] FIG. 2 is a block diagram of example components of the handheld hand scanner, according to some examples.

[0034] FIG. 3 illustrates example operations of the handheld hand scanner, according to some examples.

[0035] FIG. 4 illustrates example operations of the handprint generation system, according to some examples.

[0036] FIGS. 5-7 illustrate example feedback of the handprint generation system, according to some examples.

[0037] FIGS. 8 and 9 illustrate example methods of operating the handprint generation system, according to some examples.

[0038] FIG. 10 is a block diagram illustrating an example software architecture, which may be used in conjunction with various hardware architectures herein described.

[0039] FIG. 11 is a block diagram illustrating components of a machine, according to some example embodiments.DETAILED DESCRIPTION

[0040] Example methods and systems for generating a handprint using handheld scanners are described. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the disclosed examples. It will be evident, however, to one of ordinary skill in the art, that examples of the disclosure may be practiced without these specific details.

[0041] Forensic quality full-hand friction ridge images used for identification purposes usually involve very high-end equipment that consumes a great deal of resources. Full hand image collection requires the capability to scan large areas at high resolutions. The final output image could be 8” by 5.5” with a minimum resolution from 500 pixels per inch (PPI) and up to lOOOppi. Typically oversampling the images is required to meet stringent industry standards regarding image quality specifications. A single sensor conventional optical total internal reflection (TIR) scanner may require a high-qualitylow noise images sensor exceeding 99 megapixels for lOOOppi and exceeding 25 megapixels for 500ppi. These scanner systems are expensive, large, heavy, and are not suitable for field use. Reducing the size, weight and cost is important for mobile in field user scenarios.

[0042] Conventional systems use Thin Film Transistor (TFT) sensor technologies for contact / i palm 500ppi mobile use cases. While such systems reduce size, weight, and cost of high-end systems used to capture handprints, such systems are incapable of capturing a full hand print. In the Yi palm capture scenario, two separate images of each hand are captured without continuous registration between the two images. One image of the palm area and one of the four fingerprint slap. These images may need to be stitched together to make a complete single full handprint. However, such systems require the hand to be pressed on a surface using pressure which can change the quality of the output image. This is problematic being that the applied pressure can cause the friction ridges to crush and destroy the friction ridge image information in the crushed areas.

[0043] Consumer devices (mobile phones, tablets, or webcams) cannot capture handprints in a way that meets certain industry requirements for image quality with respect to noise and image contrast. For example, it is difficult to capture high framerate full resolution images from conventional consumer devices. Also, the illumination on such consumer devices varies significantly from device to device and is inadequate to create the contrast needed to enhance the friction ridge data of the hand.

[0044] The disclosed examples provide an intelligent solution that addresses the above technical problems and challenges. Particularly, the disclosed technical solutions provide a handheld hand scanner (which can be contactless) to capture multiple images of a hand at a very high quality and with a standardized illumination component. These multiple images are communicated to a mobile device and / or server for further processing. Specifically, the images can be combined to generate a composite image of the hand. The composite image can then be further processed to generate a detailed view of the friction ridges and valleys of the hand. This detailed view can then be used to generate a biometric record for a subject and / or search available records to control access to one or more protected resources based on access privileges and / or policies. The detailed view can also be used to perform identity verification, such as to determine whether the subject has an arrest record, has warrants, or is on a watch list.

[0045] Specifically, in some examples, the disclosed techniques establish a communication session between a handheld hand scanner and a mobile device and send, to the handheld hand scanner, an instruction from the mobile device to initiate capture of a handprint. The disclosed techniques receive, from the handheld hand scanner, a plurality of images of a hand, each of the plurality of images depicting a various portions of the hand (in an overlapping, partially overlapping, or non-overlapping manner), and combine the plurality of images into a composite image of the hand. The disclosed techniques convert the composite image of the hand into the handprint and process a record associated with a subject based on the handprint.

[0046] FIG. 1 is a block diagram showing an example handprint generation system 100, according to various examples. The handprint generation system 100 can include a mobile device 120 (also referred to as a client device), a handheld hand scanner 110, and / or a composite image system 140. The mobile device 120, the composite image system 140, and the handheld hand scanner 110 can be communicatively coupled over a wired and / or wireless network 130 (e.g., Internet, Bluetooth Low Energy (BLE), ultra- wideband (UWB) communication protocol, Near Field Communication (NFC), and / or telephony network). In some cases, some of the functionality discussed below with respect to the composite image system 140 can be incorporated or performed at least in part by the handheld hand scanner 110 and / or the mobile device 120 in combination or separately.

[0047] While FIG. 1 illustrates a single instance of the handheld hand scanner 110 and a single mobile device 120, it is understood that a plurality of handheld hand scanners 110 and a plurality of mobile devices 120 can be included in the handprint generation system 100 in other examples.

[0048] The mobile device 120 can include any one or a combination of an loT device, a database, a website, a server hosting a website at a URL address, a physical access control device, logical access control device, governmental entity device, ticketing event device, and residential smart lock and / or other Bluetooth or NFC or UWB based smart device. The mobile device 120 can be any device that can observe a radio signal (e.g., RF signal and / or BLE signal) transmitted by an RF beacon of the handheld hand scanner 110, such as a BLE beacon. Some or all of the components included in the mobile device 120 can be included in the handheld hand scanner 110.

[0049] In general, the mobile device 120 can include one or more of a memory, a processor, one or more antennas, a communication module, a network interface device, a user interface, and a power source or supply. The memory of the mobile device 120 can be used in connection with the execution of application programming or instructions by the processor of the mobile device 120. For example, the memory can contain executable instructions that are used by the processor to run other components of mobile device 120 and communicate with the handheld hand scanner 110 to perform various functions, such as scanning or capturing a plurality of images of different portions or parts of a hand (or other object with unique prints or biometric information, such as a footprint of a foot).

[0050] The memory of the mobile device 120 can comprise a computer-readable medium that can be any medium that can contain, store, communicate, or transport data, program code, or instructions for use by or in connection with mobile device 120. The computer-readable medium can be, for example but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device. More specific examples of suitable computer-readable medium include, but are not limited to, an electrical connection having one or more wires or a tangible storage medium such as a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), Dynamic RAM (DRAM), any solid-state storage device, in general, a compact disc read-only memory (CD-ROM), or other optical or magnetic storage device.

[0051] The processor of the mobile device 120 can correspond to one or more computer processing devices or resources. For instance, the processor can be provided as silicon, as a Field Programmable Gate Array (FPGA), an Application-Specific Integrated Circuit (ASIC), any other type of Integrated Circuit (IC) chip, a collection of IC chips, or the like. As a more specific example, the processor can be provided as a microprocessor, Central Processing Unit (CPU), or plurality of microprocessors or CPUs that are configured to execute instructions sets stored in an internal memory and / or memory of the mobile device 120.

[0052] The antenna of the mobile device 120 can correspond to one or multiple antennas and can be configured to provide for secure and / or unsecure wirelesscommunications between handheld hand scanner 110 and the mobile device 120 and / or composite image system 140 (e.g., implemented on a remote server, such as a car / station-based server, centrally located station server, secure cloud server). The antenna can be arranged to operate using one or more wireless communication protocols and operating frequencies including, but not limited to, the IEEE 802.15.1, Bluetooth, BLE, NFC, ZigBee, GSM, CDMA, Wi-Fi, RF, UWB, and the like. By way of example, the antenna(s) can be RF antenna(s), and as such, may transmit / receive RF signals through free space to be received / transferred by a device having an RF transceiver.

[0053] A communication component of the mobile device 120 can be configured to communicate according to any suitable communications protocol with one or more different systems or devices either remote or local to mobile device 120, such as one or more handheld hand scanners 110. In some cases, the communication module communicates over a secure channel (e.g., secure BLE or NFC channel) with one or more handheld hand scanners 110, in which case all of the exchanged data is encrypted (e.g., end-to-end). In some cases, the communication module communicates over an unsecure channel (e.g., unsecure, public or open BLE or NFC channel) with one or more handheld hand scanners 110, in which case all or a portion of the exchanged data is unencrypted.

[0054] The network interface device of the mobile device 120 includes hardware to facilitate communications with other devices, such as a one or more client devices 120 over a communication network, such as network 130, utilizing any one of a number of transfer protocols (e.g., frame relay, internet protocol (IP), transmission control protocol (TCP), user datagram protocol (UDP), hypertext transfer protocol (HTTP), etc.). Example communication networks can include a local area network (LAN), a wide area network (WAN), a packet data network (e.g., the Internet), mobile telephone networks (e.g., cellular networks), Plain Old Telephone (POTS) networks, wireless data networks (e.g., IEEE 802.11 family of standards known as Wi-Fi, IEEE 802.16 family of standards known as WiMax), IEEE 802.15.4 family of standards, and peer-to-peer (P2P) networks, among others. In some examples, network interface device can include an Ethernet port or other physical jack, a Wi-Fi card, a Network Interface Card (NIC), a cellular interface (e.g., antenna, filters, and associated circuitry), or the like. In some examples, network interface device can include a plurality of antennas to wirelessly communicate using atleast one of single-input multiple-output (SIMO), multiple-input multiple-output (MIMO), or multiple-input single-output (MISO) techniques.

[0055] A user interface of the mobile device 120 can include one or more input devices and / or display devices. Examples of suitable user input devices that can be included in the user interface include, without limitation, one or more buttons, a keyboard, a mouse, a touch-sensitive surface, a stylus, a camera, a microphone, etc. Examples of suitable user output devices that can be included in the user interface include, without limitation, one or more LEDs, an LCD panel, a display screen, a touchscreen, one or more lights, a speaker, and so forth. It should be appreciated that the user interface can also include a combined user input and user output device, such as a touch-sensitive display or the like.

[0056] The network 130 may include, or operate in conjunction with, an ad hoc network, an intranet, an extranet, a virtual private network (VPN), a LAN, a wireless network, a wireless LAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), a metropolitan area network (MAN), BLE, UWB, the Internet, a portion of the Internet, a portion of the Public Switched Telephone Network (PSTN), a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, a Wi-Fi® network, another type of network, or a combination of two or more such networks. For example, a network or a portion of a network may include a wireless or cellular network and the coupling may be a Code Division Multiple Access (CDMA) connection, a Global System for Mobile communications (GSM) connection, or other type of cellular or wireless coupling. In this example, the coupling may implement any of a variety of types of data transfer technology, such as Single Carrier Radio Transmission Technology (IxRTT), Evolution-Data Optimized (EVDO) technology, General Packet Radio Service (GPRS) technology, Enhanced Data rates for GSM Evolution (EDGE) technology, third Generation Partnership Project (3 GPP) including 3G, fourth generation wireless (4G) networks, fifth generation wireless (5G) networks, Universal Mobile Telecommunications System (UMTS), High Speed Packet Access (HSPA), Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) standard, others defined by various standard setting organizations, other short range or long range protocols, or other data transfer technology.

[0057] In some examples, the handheld hand scanners 110 are physically and stationarily installed at different locations in a physical space, such as different rooms ina house or a hospital. In some examples, the handheld hand scanner 110 can be a moveable and mobile component that can be held by an operator and focused on a target region to capture one or more images of a hand (or other object). While the disclosed examples refer to a handprint of a hand, similar techniques can be applied to any other type of print that can be used to uniquely identify a person, such as a footprint of a foot. The handheld hand scanner 110 periodically or continuously receives or observes RF signals transmitted by one or more mobile devices 120. The handheld hand scanner 110 can process the signals to retrieve instructions for initiating capture of a handprint.

[0058] The handheld hand scanner 110 can capture a plurality of images of a hand, such as different overlapping or non-overlapping portions of the hand. The handheld hand scanner 110 sends each of the captured images to the mobile device 120 which can use a locally or remotely implemented composite image system 140 to process the captured images. The processed images can be combined into a composite image and a handprint can be generated based on the composite image of the hand. The handprint can then be associated with a record or profile of a particular person or subject and / or used to control access to a protected resource (physical or logical resource) by matching the handprint to previously registered handprints and their associated access control policies or criteria and / or perform identity verification, such as to determine whether the subject has an arrest record.

[0059] FIG. 2 is a block diagram of example components 200 of the handheld hand scanner 110 (e.g., shown as the handheld contactless capture device 210), according to some examples. The components 200 can be part of the handheld hand scanner 110 and / or the mobile device 120. The block diagram of example components 200 can include a user input interface 220 (e.g., a display and / or touchscreen), a controller 230 (e.g., a hardware processing device), one or more storage devices 240, a Micro-Electro- Mechanical System (MEMS) accelerometer / magnetometer 250, a communication device, such as a wireless radio 260, an image sensor 270 (e.g., a camera), a distance sensor 280, a first illumination component 292, and a second illumination component 290 (also referred to as pointing and feedback illumination). The magnetometer 250, with one or both of a 3D accelerometer and 3D magnetometer, can include measurement capabilities to determine the motion, activity, position and / or scanning direction of the handheld contactless capture device 210.

[0060] The communication device 260 can detect a signal from an RF transmitter of the mobile device 120. For example, the mobile device 120 can transmit / broadcast a packet of information including an instruction to initiate capture of a handprint. The controller 230 can process the packet of information and control various components of the handheld hand scanner 110 to capture a handprint. For example, the controller 230 can instruct the image sensor 270 to capture a plurality of images of a hand after the controller 230 determines that a hand is in the field of view of the image sensor 270.

[0061] The controller 230 can vary in computing power depending on the need to process images inside the handheld contactless capture device 210 before transmitting the data to a receiving device or system. The controller 230 may also contain a trusted platform module (TPM) to provides hardware-based security capabilities. The communication device 260 serves to provide connectivity to external devices (e.g., using the external connectivity interface 245) such as wired serial interfaces, external power used for charging rechargeable batteries or providing power in the case of dead batteries, or attachments which might aid in the capture of the hand features, such as a display to be worn on the wrist with or without a touchscreen or a card reader. The handheld contactless capture device 210 can also include buttons and switches to power on / off the handheld contactless capture device 210, initiate Bluetooth pairing, etc. such as in cases where there is no touchscreen. The handheld contactless capture device 210 can include an audible device as part of the communication device 260 connectivity interface and / or user input interface 220.

[0062] The controller 230 can instruct the distance sensor 280 to compute a distance between the image sensor 270 and the hand that is in the field of view. The distance sensor 280 could be one of the following types: ultrasonic, Infrared Sensors, time-of- flight sensors, laser sensor, or stereo vision. The controller 230 can then compare the distance to a threshold. In response to determining that the distance is within a threshold range to the image sensor 270 (e.g., is more than a first distance and less than a second distance), the controller 230 can instruct the image sensor 270 to control a lens to clearly focus on the object in the view based on the measured distance. The lens can be static or dynamic. Once the variable focus optical lens is adjusted based on the distance measured by the distance sensor 280, the controller 230 can instruct the first illumination component 292 to activate and project a visible or non-visible light (e.g., IR light) on thehand within the field of view. After activating the first illumination, the controller 230 can send signals to the variable focus optical lens to optimize the focus and improve image quality.

[0063] For example, the first illumination component 292 (also referred to as the illumination for capturing hi-resolution hand images) can include a narrow band single color, a mix of multiple colors, or processor for sequencing through multiple colors and positions. The handheld contactless capture device 210 could contain filters to improve performance in high ambient light conditions and / or a combination of polarized filters to minimize or enhance surface reflections in order to optimize hand features and friction ridge contrast. In some cases, the first illumination component 292 can continuously be activated to project the light on the hand. The controller 230 can then instruct the image sensor 270 to capture a first image of the portion of the hand that is in the field of view. The image sensor 270 can include one or more of the following configurations: monochrome, RGB, RGB-IR. The size of the image sensor 270 can be selected to accommodate requirements for capture area, resolution, frame rate, quantum efficiency, size and cost.

[0064] After capturing the first image, the controller 230 can store the first image in the one or more storage devices 240. The controller 230 can transmit the first image wirelessly to the mobile device 120 via the communication device 260. The mobile device 120 can process the first image to determine whether the first image satisfies one or more quality metrics. In response to determining that the first image satisfies the one or more quality metrics, the mobile device 120 can add the first image to a composite image of the hand and can instruct the handheld contactless capture device 210 to capture a second image of a different portion of the hand, such as by causing the capture device 210 to generate an alert to an operator to move the device to point at the different portion of the hand. In some cases, the frame rate of the capture device 210 is fast enough to enable the operator to continuously move the capture device 210 to capture different portions of the hand while the mobile device 120 performs the processing of the captured frames. In response to determining that the first image fails to satisfy the one or more quality metrics, the mobile device 120 can instruct the handheld contactless capture device 210 to recapture an image of a same portion of the hand depicted in the first image again. In some cases, if the first image fails to satisfy the one or more qualitymetrics, the next image is processed and the first image is ignored. Depending on the failure, there may be feedback provided to the operator and / or subject to perform the needed corrections, such as modifying the focus (e.g., continuously). In this way, the composite image can be generated piecemeal as each single image of a plurality of images of different parts of the hand is captured. This avoids having to wait for all of the images of all parts of the hand to be captured before initiating the generation of the composite image.

[0065] In some cases, the mobile device 120 can determine whether the composite image is complete (e.g., all portions of the hand are available in the composite image and there are no missing portions of the hand that remain to be captured and added to the composite image). If the composite image includes all desired or intended portions of the hand, the mobile device 120 can process the composite image to generate a handprint. If the composite image fails to depict all desired or intended portions of the hand, the mobile device 120 instructs the handheld contactless capture device 210 to capture another portion of the hand that is missing from the composite image.

[0066] The handheld contactless capture device 210 can again instruct the distance sensor 280 to compute a distance between the image sensor 270 and second portion of the hand that is in the field of view. The controller 230 can then compare the distance to a threshold. In response to determining that the distance is within a threshold range to the image sensor 270 (e.g., is more than a first distance and less than a second distance), the controller 230 can instruct the image sensor 270 to control a lens to clearly focus on the object (e.g., second portion of the hand) in the view based on the measured distance. The lens can be static or dynamic. Once the variable focus optical lens is adjusted based on the distance measured by the distance sensor 280, the controller 230 can instruct the first illumination component 292 to activate and project a visible or non-visible light (e.g., IR light) on the second portion of the hand within the field of view. The controller 230 can then instruct the image sensor 270 to capture a second image of the portion of the hand that is in the field of view. The distance can be important for determining resolution so that the composite matchable print can meet the required image resolution (500ppi or lOOOppi) depending on the use case.

[0067] After capturing the first image, the controller 230 can store the second image in the one or more storage devices 240. The controller 230 can transmit the second imagewirelessly to the mobile device 120 via the communication device 260. The mobile device 120 can process the second image to determine whether the second image satisfies one or more quality metrics. In response to determining that the second image satisfies the one or more quality metrics, the mobile device 120 can add the second image to the composite image of the hand and can instruct the handheld contactless capture device 210 to capture a third image of a different portion of the hand (e.g., if the composite image is still incomplete). In response to determining that the second image fails to satisfy the one or more quality metrics, the mobile device 120 can instruct the handheld contactless capture device 210 to recapture an image of a same second portion of the hand depicted in the second image.

[0068] In some examples, the handheld contactless capture device 210 can present on the user input interface 220 a target region of the hand to capture. In some cases, the user input interface 220 can visually depict which portions of the hand have previously been captured and which portions of the hand remain to be captured. The operator of the handheld contactless capture device 210 can reposition the handheld contactless capture device 210 and / or instruct a subject to reposition their hand so that the target portion of the hand is within the field of view of the image sensor 270.

[0069] In some examples, the handheld contactless capture device 210 can activate the second illumination component 290 to project a visible light or pattern on the hand of the subject. The projected light can guide the subject or operator on positioning the portion of the hand within focus or field of view of the image sensor 270. The projected light can also visually identify which portion of the hand will be captured by the image sensor 270. The projected light can be of a particular pattern to represent which portions of the hand have previously been captured and which portions of the hand remain to be captured. The projected light can also identify portions of the hand for which the corresponding image fails to satisfy one or more quality metrics. These portions can be provided using different patterns of light and / or different colors of light.

[0070] In some cases, the handheld contactless capture device 210 can communicate to the mobile device 120 various information and / or records including some or all of the following: hand images, hand friction ridge images, demographics, biographic, facial images, notes, location, operator information, and other data. The mobile device 120 can send this information to servers where this information can be processed for verificationand / or identification. The server can respond with data regarding verification, identification status, and may instruct the operator on policies and procedures for dealing with the subject being scanned.

[0071] In some examples, the second illumination component 290 and the first illumination component 292 can be active at the same time. For example, the second illumination component 290 can project visible light on the hand of the subject to inform the subject and / or operator about which portion of the hand will be depicted in the image captured by the handheld contactless capture device 210. While the second illumination component 290 projects the visible light in a wavelength band different from the first illumination component 292, the first illumination component 292 can project visible light to aid or improve the image quality of the image captured by the image sensor 270. In such cases, as shown in the diagram 300 of FIG. 3, an optical bandpass filter 310 can be placed in the light path between the image sensor 270 and the imaging lens and second illumination component 290 and the first illumination component 292. The optical bandpass filter 310 can be configured to filter out light having the wavelength corresponding to the second illumination component 290 and to allow only light having the wavelength of the first illumination component 292. In some cases, the bandpass filter can also be designed to reject unwanted ambient light as well, such as ultraviolet and infrared light. In some cases, the ultraviolet and infrared blocking filters are separate filter components with respect to optical bandpass filter 310.

[0072] In some cases, as shown in diagram 301 of FIG. 3, the first illumination component 292 and the second illumination component 290 can be alternatively activated where only one of the first illumination component 292 and the second illumination component 290 projects light at a time. In some cases, the second illumination component 290 can project visible light on the hand of the subject to inform the subject and / or operator about which portion of the hand will be depicted in the image captured by the handheld contactless capture device 210. Once the handheld contactless capture device 210 is ready to capture an image of the portion of the hand within the field of view, the handheld contactless capture device 210 can turn off or deactivate the second illumination component 290 and activate the first illumination component 292. While the first illumination component 292 is activated, the handheld contactless capture device 210 instructs the image sensor 270 to capture the image including the portion onwhich the first illumination component 292 projects visible light. In such circumstances, the optical bandpass filter 310 can be omitted which saves costs and processing resources. In some cases, ultraviolet and / or infrared blocking filters may be used to improve image quality.

[0073] FIG. 4 illustrates example operations 400 of the handprint generation system 100, according to some examples. The operations 400 can be performed by any one or combination of the handheld hand scanner 110, mobile device 120 and / or composite image system 140.

[0074] In some cases, the handheld contactless capture device 210 can be positioned to capture an image, such as a low-resolution image, of a hand 401 of a subject. The low- resolution image can depict the entire hand of the subject and can be subsequently used to accurately map high-resolution images of individual portions or parts of the hand. The low-resolution image of the hand 401 can be provided to the composite image system 140, such as via the mobile device 120. Next, the handheld contactless capture device 210 can be adjusted to cause a first portion of the hand 401 to be within the field of view of the image sensor 270. In some cases, the hand 401 is moved (in cases where the image sensor 270 is stationary) to cause the first portion of the hand 401 to be within the field of view of the image sensor 270. Feedback can be provided in the form of a display on a screen of the handheld contactless capture device 210 and / or by projecting visible light on the hand 401 to aid the subject in placing the first portion of the hand 401 in the field of view.

[0075] Once the first portion is within the field of view, the handheld contactless capture device 210 can capture a first image 411 that depicts the first portion 420 of the hand 401 that is within the field of view of the handheld contactless capture device 210. The first image 411 is sent to the composite image system 140 for processing. (In some examples, this sending may be via mobile device 120, which may forward the image from the capture device 210 to the composite image system 140.) For example, the composite image system 140 can generate a segmentation 402 of the first portion 430 to remove the background and other portions of the hand 401 that may appear or be depicted in the first image 411. If the segmented image hand area is of inferior quality the composite image system 140 stops processing the captured image and responds to the mobile device 120 indicating that the previously captured image failed the qualityrequirements. This could happen, for example, because no hand was found, poor focus, motion blur, hand occlusion, or other factors related to image quality. It is possible that information could be passed back to the mobile device 120 which could be used to instruct the operator in ways to improve quality. If the segmented image is of acceptable quality the composite image system 140 can add the image or portions of the image to the composite image. It is possible that for any given captured image segment there might not be a correlated identifiable place in the composite image until more images are captured. The composite image system 140 can continue to determine where the best fit for all captured images are within the composite image during the collection process.

[0076] In some examples, the segmentation 402 of the first portion 430 can be processed by the composite image system 140 based on the low-resolution image of the hand 401 to identify which part of a composite image corresponds to the portion of the hand 401 depicted in the segmentation 402 of the first portion 430. For example, a partially complete composite 403 image can be made up of multiple high-resolution images 440 and 442 of different portions of the hand 401. The composite image system 140 can determine which pixels of the partially complete composite 403 correspond to pixel locations of the segmentation 402 of the first portion 430. The composite image system 140 can exclude pixel locations in the segmentation 402 of the first portion 430 that are already included in the partially complete composite 403. This way, in some examples, the composite image system 140 can retrieve only pixels from the segmentation 402 of the first portion 430 that are missing from the partially complete composite 403. Additional images are captured for different portions of the 401 in a similar manner. Once all of the high-resolution images portions of the different portions of the hand 401 are added to the partially complete composite 403, a completed composite image 404 is generated.

[0077] Multiple algorithms can be used for combining the multiple images into a single composite image. These algorithms can include stitching or panoramic stitching processes. For example, the processes can include feature detection and matching, such as using algorithms like Scale-Invariant Feature Transform (SIFT) or Speeded-Up Robust Features (SURF) to detect distinctive keypoints and descriptors in images. These keypoints are then matched across images to find corresponding points. The processes can include image registration. Specifically, once keypoints are matched betweenimages, the next step is to align the images properly. Techniques such as RANSAC (Random Sample Consensus) can be used to estimate the transformation (such as rotation, translation, and scaling) needed to align images based on the matched keypoints. The processes can include homography estimation. In many cases, a planar assumption is made, which means the scene is assumed to be flat. In such cases, homography estimation techniques can be used to find a transformation matrix that maps points from one image to another. This transformation can be used to warp one image onto another, aligning them properly.

[0078] In some examples, the images can be combined using panoramic stitching (e.g., mosaicking). In such cases, from the overlap between the images, a homographic transform is estimated, which, once applied to the next image to be added to the single image, allows for seamless stitching. To do this, salient points are identified in both images and a matching relationship between those points on both images is found. In some examples a process is used to apply panoramic stitching to high resolution images which cover only parts of the palm. This process involves calculating salient features in the multiple images (e.g., Akaze, Sift, Suft, and so forth) and finding matching pairs of salient feature points. From the matching pairs (at least 4 may be necessary) the process estimates a best fitting homographic transform, which is represented by a 3x3 matrix or other suitable size matrix. The algorithm for the estimation process can include the RANSAC (random sample consensus) algorithm. Then, the process applies the homography to one of the images and stitches the image to other images together.

[0079] In situations with few salient features or features with bad quality of saliency, feature pairs are often mismatched, which leads to an incorrect estimation of the homography matrix, and finally unnaturally looking stitching artifacts. For this reason, a plausibility check can be applied to the homography matrix. Since it may not be possible to decompose a homography in its atomic transforms (4 possible solutions exist for this problem), a different approach can be used. The homography is first applied to only the 4 corners of the image, which describes the quadrangle filled out by the image, after the transformation. The following plausibility checks can be applied in the case of palm stitching: verify that adjacent sides of the transformed quadrangle still form close to 90- degree angles; verify opposite sides of the transformed quadrangle still close to parallel; verify the length of every side of the transformed quadrangle change maximally by acertain percentage as compared to the original rectangle; and / or verify there a minimum overlap between the original rectangle and the transformed quadrangle. If any of these plausibility checks fail, the image can be discarded and another image can be collected.

[0080] In some cases, a hue-based segmentation approach may additionally or alternatively used to segment the images. This segmentation can be performed by transforming the input image to HSV space and then finding an area entirely contained in the object to be segmented. In case of hand, the triangle described by landmarks of the hand can be used. The process calculates the mean hue value of the area defined and the absolute difference between hue channel of the HSV image and the mean hue value calculated. The image calculated in the previous step shows high contrast between the desired object and the background and can be used to threshold, e.g. using Otsu's method. After thresholding, the process performs some cleanup steps of the final image if necessary, using tools like morphological operations and / or connected component analysis.

[0081] In some cases, the processes can include blending. Namely, after aligning the images, the images can be blended seamlessly to create a smooth transition between them. Several blending techniques can be used, such as linear blending, gradient-based blending, or multi-band blending, to ensure natural-looking transitions between images. Exposure Compensation and Color Correction can be applied. Sometimes, images used for stitching may have variations in exposure or color. To create a visually pleasing composite image, exposure compensation and color correction techniques can be applied to ensure consistency across images. Seam Finding and Removal processes can be performed because even with careful alignment and blending seams may still be visible in the composite image. Algorithms can be used to detect and remove these seams, ensuring a smooth and seamless final result. Various optimization techniques may be employed to improve the stitching process, such as optimizing the blending parameters or refining the alignment based on global consistency.

[0082] When the handheld hand scanner 110 is placed on a stationary surface beneath the hand, the hand can be moved above the handheld hand scanner 110 until the requested hand surface area is completely captured. The frame rate and exposure time is such that the hand can be moved around above the capture device without creating motion blur. The handheld hand scanner 110 automatically captures images and canindicate the status during the capture process so that the operator is informed about when the capture is complete or if there are any issues during the capture process.

[0083] The completed composite image 404 (depicted as showing only part of the hand but can, in some cases, show the entire hand or disfigured hands) can then be processed to generate a handprint representing friction ridges and / or friction ridge valleys of the hand 401. For example, if it is determined that the completed composite image 404 is complete then the composite image system 140 can begin converting the composite image into a matchable print. There are multiple methods for converting a composite image into a matchable print. One such method starts with performing a Contrast Limited Adaptive Histogram Equalization (CLAHE) on the composite image. CLAHE is a technique used in image processing and computer vision to improve the contrast of an image while preserving its overall brightness. Slight filtering may be performed to reduce image noise generated by the CLAHE function.

[0084] Next, a slight noise reduction filter can be applied to the completed composite image 404. Next the composite image histogram is stretched to increase the friction ridge contrast. Finally, to complete the processing for the matchable print the composite image grayscale is inverted so that the friction ridges are dark, and the friction ridge valleys are light which mimics convention inked print images, as shown in final image 405. Depending on the illumination system the inversion step might not be required.

[0085] This handprint can then be used to search a database of previously registered handprints. If a matching handprint is found in the database, access policies associated with a record containing the matching handprint are retrieved and used to control access to one or more protected resources. If no matching handprint is found, a new record can be generated to include the handprint and / or any information about a subject received from the handheld hand scanner 110. Such a record may then be stored and categorized for future matching using techniques known in the art. This may be the case where the subject is enrolling in the database of records for future verifications. It might also be the case where the subject is not enrolled because they are not supposed to have access grated to them. There are other use cases where the subject is tested for identification in one or more databases.

[0086] In some cases, generation of the composite image can be skipped. In such cases, multiple single images of different parts of the hand can be stored in association with a particular record. As each image is captured, it is processed in the manner discussed above to obtain a print of the section of the hand depicted in the image. That print of the individual section of the hand is then processed with a record (e.g., to create a new record or to search existing records) to perform a specified action. Specifically, the record can contain the plurality of images and no composite image is generated. Each of the plurality of images can be converted to the handprint section of the hand that it represents. In this case, each of the plurality of the images can be processed for verification or identification as needed.

[0087] After adding the captured image to the composite image, the composite image system 140 can determine if all the desired or intended areas of the hand have been captured (composite image is complete). It is possible that only the palm area is required instead of the full hand. Likewise, it is also possible that only the four fingers or single thumb needs to be captured. Depending on the desired capture sequence the mobile device 120 will control the handheld hand scanner 110 accordingly.

[0088] This allows for capturing up to full handprints in the field without the need to carry expensive heavy equipment out into the field and serves the purpose for being able to identify a subject in the field rather than spending the time and effort to transport individuals to a central processing office.

[0089] In some examples, to aid in capturing the high-resolution images of the various portions of the hand 401, feedback can be provided on a display of the handheld contactless capture device 210 and / or by projecting light on a subject’s hand. FIGS. 5-7 illustrate example feedback of the handprint generation system, according to some examples. The feedback enables the operator performing the capture of the subject’s hand to know when all the desired or required areas of the hand have been captured with adequate quality. The feedback can also represent the distance and quality of the image currently being seen in terms of focus, motion blur, contrast and distortion by displaying information, patterns or colors indicating the status. While the diagrams shown in connection with FIG. 5 present visually information regarding which parts of the hand have already been captured, such information can be excluded (at least in part) from thedisplay or illumination depending on the cost, size, and / or batter power associated with the capture device.

[0090] As shown in diagrams 500, 501 and 502, various feedback can be presented on a display of the handheld contactless capture device 210 and / or a display of the mobile device 120 that controls the handheld contactless capture device 210. Specifically, as shown in diagram 500 the handheld contactless capture device 210 can be held further away from the subject’s hand so that a lower resolution image of the full hand view 510 can be captured. This full hand view 510 can be used to indicate which parts of the hand have been scanned and also indicate a quality level if needed as well. The full hand view 520 can be presented on a display of the mobile device 120 and / or a display of the handheld contactless capture device 210.

[0091] As shown in diagram 501, after capturing various portions of the hand 401, the handheld contactless capture device 210 can be positioned to capture another portion of the hand 401 that has yet to be captured. Specifically, a display 530 can be provided on the mobile device 120 and / or on the handheld contactless capture device 210. The display 530 can depict the full hand view 520 and can visually identify a first set of portions 532 that have previously been captured, such as by coloring the first set of portions 532 with a first color. The display 530 can visually identify a particular portion 534 of the hand 401 that needs to be captured in an image. The handheld contactless capture device 210 can be positioned to direct the camera of the handheld contactless capture device 210 towards the corresponding portion 536 on the hand 401. After capturing the image of the corresponding portion 536, the composite image system 140 can process the image to determine whether the image satisfies one or more quality metrics.

[0092] In some cases, the composite image system 140 can identify a particular part of the image that fails to satisfy the one or more quality metrics. The composite image system 140 can specify pixel locations of the particular part and provide that information to the mobile device 120 and / or handheld hand scanner 110. The mobile device 120 and / or the handheld hand scanner 110 can update the display 530 to visually identify the particular part 540 that failed to satisfy the one or more quality metrics or criteria. This aids the operator in positioning the handheld contactless capture device 210 to recapture an image of just that particular part 540, as shown in diagram 502. Various colors,textures, or patterns can be used to indicate various levels of quality in the display 530. There could be an intermediate color between green and red, such as yellow which would indicate low quality which may or may not need to be addressed depending on the subject’s hand condition.

[0093] In some cases, as shown in the diagrams 600, 601, and 602 of FIG. 6, the operator can be visually informed about what area of the subject is being captured. In the case of the contactless capture of a hand, visible light can be used to indicate the area being captured. To enhance the contactless capture process, it is advantageous to provide feedback to the operator indicating the exact area the contactless capture device is pointing at with respect to the subject. Without such feedback, it may be difficult and timely to complete the contactless capture process.

[0094] In some examples, depending on the distance between the hand 401 and the handheld contactless capture device 210, the hand 401 may be fully or partially illuminated as seen in diagram 600 by the second illumination component 290 which projects visible light. Specifically, the handheld contactless capture device 210 can project light visible in a particular pattern 610 on the hand 401 of the subject. The projected light may be excluded from other parts of the hand 401. The portions of the hand illuminated by the projected light can correspond to those portions of the hand that are expected to be depicted in an image captured by the handheld contactless capture device 210.

[0095] In some cases, as shown in diagram 601, a different pattern 620 can be projected from the handheld contactless capture device 210 by the second illumination component 290. This pattern can frame the area of the subject’s hand which is to be imaged. In this case, portions of the hand that are not expected to be depicted in the image captured by the handheld contactless capture device 210 can be illuminated by the light projected by the second illumination component 290 and the portion that is expected to be depicted remains non-illuminated. Namely, the visible light is only projected on portions of the hand 401 that are not expected to be captured in an image by the handheld contactless capture device 210 and non-visible light projected by the first illumination component 292 can be directed towards the portion that is expected to be captured in the image by the handheld contactless capture device 210. While not limited to such examples, diagram 602 shows alternative example projected patterns 630, 632, and 634 on the hand401 that can be used in place of the patterns discussed in connection with diagrams 600 and 601 from various configurations of the handheld contactless capture device 210. These configurations may depend on constraints regarding size, cost and power requirements.

[0096] In some cases, the handheld contactless capture device 210 can project light to visually inform an operator about various conditions, such as appropriate distance between the handheld contactless capture device 210 and the hand 401. In this case, as shown in the diagrams 700 and 701 of FIG. 7, the color of the projected pattern (discussed in connection with FIG. 6) may be changed to indicate the state of the distance between the subject’s hand 401 and the handheld contactless capture device. For example, with respect to distance DI and D3, shown in diagram 700, the hand 401 is either too close or too far away from the handheld contactless capture device 210. In such cases, the pattern 710 and 730 can be, for example, red in color providing feedback to the operator that the distance needs to change. When the distance is acceptable, as in the case for D2, the projected pattern 720 color can be changed to, for example, green which indicates to the operator that the handheld contactless capture device 210 is at an acceptable distance.

[0097] In some cases, the projected pattern can be additionally or alternatively changed in a way to provide feedback to the operator so that it is informative if the hand 401 needs to be moved closer to the handheld contactless capture device 210 or further away from the handheld contactless capture device 210. For example, as shown diagram 701, the pattern of X’s (DI) 740 can indicate that the subject’s hand 401 needs to be moved closer to the handheld contactless capture device 210. Specifically, the pattern of X’s (DI) 740 can be projected on the hand 401 in response to determining the distance measured by the distance sensor 280 is greater than a first distance threshold. The pattern of O’s (D3) 750 can indicate that the hand 401 needs to be moved away from the handheld contactless capture device 210. Namely, the pattern of O’s (D3) 750 can be projected on the hand 401 in response to determining the distance measured by the distance sensor 280 is less than a second distance threshold. The solid patten (D2) 720 can indicate that the distance between the subject’s hand 401 is at an acceptable distance (e.g., the distance measured by the distance sensor 280 is between the first and second distance thresholds) from the handheld contactless capture device 210. It is also possibleto modulate the light projected by the second illumination component 290 such that it provides feedback to the operator for any of the previously described scenarios, such as a simple one second on and off flashing of the projected light.

[0098] FIG. 8 is a flowchart illustrating example method 800 of the handprint generation system 100, according to some examples. The method 800 may be embodied in computer-readable instructions for execution by one or more processors such that the operations of the method 800 (or process) may be performed in part or in whole by the functional components of the handprint generation system 100; accordingly, the method 800 is described below by way of example with reference thereto. However, in other embodiments, at least some of the operations of the method 800 may be deployed on various other hardware configurations. Some or all of the operations of method 800 can be in parallel, out of order, or entirely omitted.

[0099] At operation 801, the handprint generation system 100 establishes a communication session between a handheld hand scanner (e.g., the handheld hand scanner 110) and the mobile device 120, as discussed above.

[0100] At operation 802, the handprint generation system 100 sends, to the handheld hand scanner 110, an instruction from the mobile device 120 to initiate capture of a handprint, as discussed above.

[0101] At operation 803, the handprint generation system 100 receives, from the handheld hand scanner 110, a plurality of images of a hand, each of the plurality of images depicting a different portion of the hand, as discussed above. The plurality of images can be received one at a time or all at once depending on the implementation.

[0102] At operation 804, the handprint generation system 100 combines the plurality of images into a composite image of the hand, as discussed above.

[0103] At operation 805, the handprint generation system 100 converts the composite image of the hand into the handprint, as discussed above.

[0104] At operation 806, the handprint generation system 100 processes a record associated with a subject based on the handprint, as discussed above.

[0105] FIG. 9 is a flowchart illustrating example method 900 of the handprint generation system 100, according to some examples. The method 900 may be embodied in computer-readable instructions for execution by one or more processors such that theoperations of the method 900 (or process) may be performed in part or in whole by the functional components of the handprint generation system 100; accordingly, the method 900 is described below by way of example with reference thereto. However, in other embodiments, at least some of the operations of the method 900 may be deployed on various other hardware configurations. Some or all of the operations of method 900 can be in parallel, out of order, or entirely omitted.

[0106] At operation 910, the mobile device 120 is in a idle state until a request is received to initiate capture of a handprint, as discussed above. In such cases, the mobile device 120 performs operation 920 to start capturing the handprint and initializes the composite image at operation 921. The mobile device 120 instructs the handheld hand scanner 110 to begin capturing images of the hand 401. For example, the handheld hand scanner 110 can obtain a distance between the handheld hand scanner 110 and the hand 401 at operation 922.

[0107] The handheld hand scanner 110, at operation 923, determines if the object (e.g., the hand) is in the range (is between a first and second distance threshold). If not, the handheld hand scanner 110 waits for the distance computed in the operation 922 to be in the suitable range until a timeout period is reached at operation 914. In some cases, the handheld hand scanner 110 continues trying to determine if the object is in range until either the hand is in range or there is a timeout. If the hand is not within the suitable range prior to expiration of the timeout, the handheld hand scanner 110 and / or the mobile device 120 performs a timeout operation 912 and returns to the idle state.

[0108] Once the hand is within the suitable range, the handheld hand scanner 110 performs operation 924 to set the focus. The handheld hand scanner 110 performs operation 925 to turn on or activate the first illumination component 292 and capture the image at operation 926. Then, the handheld hand scanner 110 turns off or deactivates the first illumination component 292 at operation 927. The handheld hand scanner 110 provides the captured image to the mobile device 120 for processing at operation 930. In some cases, the handheld hand scanner 110 keeps the first illumination component 292 active until a complete scan of the hand is finished rather than deactivating the component as each image is captured.

[0109] The mobile device 120 and / or the composite image system 140 can perform operation 930 to process the image. For example, the mobile device 120 and / or the composite image system 140 (e.g., a server) can perform operation 931 to segment the hand or portion of interest. The mobile device 120 and / or the composite image system 140 can determine at operation 932 whether the segmented image is of good quality (e.g., satisfies one or more quality metrics). If so, the mobile device 120 and / or the composite image system 140 proceed to perform operation 934 to add the segmented image to the composite image. If not, the mobile device 120 and / or the composite image system 140 perform operation 914 to cause the handheld hand scanner 110 to recapture an image depicting a same portion of the hand 401.

[0110] At operation 936, the mobile device 120 and / or the composite image system 140 determine whether the composite image is complete. If not, the mobile device 120 and / or the composite image system 140 instruct the handheld hand scanner 110 to capture an image of an additional portion of the hand 401. If the composite image is complete, the mobile device 120 and / or the composite image system 140 perform operation 937 where the CLAHE is applied to the composite image. Then, the operation938 is performed to apply noise reduction filter to the composite image and at operation939 a histogram stretch is applied to the composite image. Any other suitable image processing algorithm or technique can be performed to process the composite image not limited to CLAHE. The composite image is added to a record at operation 940 and, at operation 942, a biometric record is verified or identified based on a handprint detected in the processed composite image. The mobile device 120 and / or the composite image system 140 perform operation 944 to process the record that corresponds to the handprint to obtain the corresponding access policy and perform suitable actions according to the access policy.

[0111] FIG. 10 is a block diagram illustrating an example software architecture 1006, which may be used in conjunction with various hardware architectures herein described. FIG. 10 is a non-limiting example of a software architecture and it will be appreciated that many other architectures may be implemented to facilitate the functionality described herein. The software architecture 1006 may execute on hardware such as machine 1100 of FIG. 11 that includes, among other things, processors 1104, memory 1114, and input / output (I / O) components 1118. A representative hardware layer 1052 isillustrated and can represent, for example, the machine 1100 of FIG. 11. The representative hardware layer 1052 includes a processing unit 1054 having associated executable instructions 1004. Executable instructions 1004 represent the executable instructions of the software architecture 1006, including implementation of the methods, components, and so forth described herein. The hardware layer 1052 also includes memory and / or storage devices memory / storage 1056, which also have executable instructions 1004. The hardware layer 1052 may also comprise other hardware 1058. The software architecture 1006 may be deployed in any one or more of the components shown in FIG. 1.

[0112] In the example architecture of FIG. 10, the software architecture 1006 may be conceptualized as a stack of layers where each layer provides particular functionality. For example, the software architecture 1006 may include layers such as an operating system 1002, libraries 1020, frameworks / middl eware 1018, applications 1016, and a presentation layer 1014. Operationally, the applications 1016 and / or other components within the layers may invoke API calls 1008 through the software stack and receive messages 1012 in response to the API calls 1008. The layers illustrated are representative in nature and not all software architectures have all layers. For example, some mobile or special purpose operating systems may not provide a frameworks / middl eware 1018 layer, while others may provide such a layer. Other software architectures may include additional or different layers.

[0113] The operating system 1002 may manage hardware resources and provide common services. The operating system 1002 may include, for example, a kernel 1022, services 1024, and drivers 1026. The kernel 1022 may act as an abstraction layer between the hardware and the other software layers. For example, the kernel 1022 may be responsible for memory management, processor management (e.g., scheduling), component management, networking, security settings, and so on. The services 1024 may provide other common services for the other software layers. The drivers 1026 are responsible for controlling or interfacing with the underlying hardware. For instance, the drivers 1026 include display drivers, camera drivers, BLE drivers, UWB drivers, Bluetooth® drivers, flash memory drivers, serial communication drivers (e.g., Universal Serial Bus (USB) drivers), Wi-Fi® drivers, audio drivers, power management drivers, and so forth depending on the hardware configuration.

[0114] The libraries 1020 provide a common infrastructure that is used by the applications 1016 and / or other components and / or layers. The libraries 1020 provide functionality that allows other software components to perform tasks in an easier fashion than to interface directly with the underlying operating system 1002 functionality (e.g., kernel 1022, services 1024 and / or drivers 1026). The libraries 1020 may include system libraries 1044 (e.g., C standard library) that may provide functions such as memory allocation functions, string manipulation functions, mathematical functions, and the like. In addition, the libraries 1020 may include API libraries 1046 such as media libraries (e.g., libraries to support presentation and manipulation of various media format such as MPREG4, H.264, MP3, AAC, AMR, JPG, PNG), graphics libraries (e.g, an OpenGL framework that may be used to render two-dimensional and three-dimensional in a graphic content on a display), database libraries (e.g., SQLite that may provide various relational database functions), web libraries (e.g., WebKit that may provide web browsing functionality), and the like. The libraries 1020 may also include a wide variety of other libraries 1048 to provide many other APIs to the applications 1016 and other software components / devices.

[0115] The frameworks / middl eware 1018 (also sometimes referred to as middleware) provide a higher-level common infrastructure that may be used by the applications 1016 and / or other software components / devices. For example, the frameworks / middleware 1018 may provide various graphic user interface functions, high-level resource management, high-level location services, and so forth. The frameworks / middleware 1018 may provide a broad spectrum of other APIs that may be utilized by the applications 1016 and / or other software components / devices, some of which may be specific to a particular operating system 1002 or platform.

[0116] The applications 1016 include built-in applications 1038 and / or third-party applications 1040. Examples of representative built-in applications 1038 may include, but are not limited to, a contacts application, a browser application, a book reader application, a location application, a media application, a messaging application, and / or a game application. Third-party applications 1040 may include an application developed using the ANDROID™ or IOS™ software development kit (SDK) by an entity other than the vendor of the particular platform, and may be mobile software running on a mobile operating system such as IOS™, ANDROID™, WINDOWS® Phone, or othermobile operating systems. The third-party applications 1040 may invoke the API calls 1008 provided by the mobile operating system (such as operating system 1002) to facilitate functionality described herein.

[0117] The applications 1016 may use built-in operating system functions (e.g., kernel 1022, services 1024, and / or drivers 1026), libraries 1020, and frameworks / middl eware 1018 to create UIs to interact with subjects (e.g., users) of the system. Alternatively, or additionally, in some systems, interactions with a subject may occur through a presentation layer, such as presentation layer 1014. In these systems, the application / component "logic" can be separated from the aspects of the application / component that interact with a subject.

[0118] FIG. 11 is a block diagram illustrating components of a machine 1100, according to some example embodiments, able to read instructions from a machine- readable medium (e.g., a machine-readable storage medium) and perform any one or more of the methodologies discussed herein. Specifically, FIG. 11 shows a diagrammatic representation of the machine 1100 in the example form of a computer system, within which instructions 1110 (e.g., software, a program, an application, an applet, an app, or other executable code) for causing the machine 1100 to perform any one or more of the methodologies discussed herein may be executed.

[0119] As such, the instructions 1110 may be used to implement devices or components described herein. The instructions 1110 transform the general, non-programmed machine 1100 into a particular machine 1100 programmed to carry out the described and illustrated functions in the manner described. In alternative embodiments, the machine 1100 operates as a standalone device or may be coupled (e.g., networked) to other machines. In a networked deployment, the machine 1100 may operate in the capacity of a server machine or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine 1100 may comprise, but not be limited to, a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a STB, a PDA, an entertainment media system, a cellular telephone, a smart phone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), other smart devices, a web appliance, a network router, a network switch, a network bridge, or any machine capable of executing the instructions 1110, sequentially orotherwise, that specify actions to be taken by machine 1100. Further, while only a single machine 1100 is illustrated, the term "machine" shall also be taken to include a collection of machines that individually or jointly execute the instructions 1110 to perform any one or more of the methodologies discussed herein.

[0120] The machine 1100 may include processors 1104, memory / storage 1106, and I / O components 1118, which may be configured to communicate with each other such as via a bus 1102. In an example embodiment, the processors 1104 (e.g., a CPU, a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a graphics processing unit (GPU) (e.g., neural processor unit (NPU), Al Accelerators (Inference, Transformers, Generative), and / or vision processors), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a radiofrequency integrated circuit (RFIC), another processor, or any suitable combination thereof) may include, for example, a processor 1108 and a processor that may execute the instructions 1110. The term “processor” is intended to include multi-core processors 1104 that may comprise two or more independent processors (sometimes referred to as “cores”) that may execute instructions contemporaneously. Although FIG. 11 shows multiple processors 1104, the machine 1100 may include a single processor with a single core, a single processor with multiple cores (e.g., a multi-core processor), multiple processors with a single core, multiple processors with multiple cores, or any combination thereof.

[0121] The memory / storage 1106 may include a memory 1114, such as a main memory, or other memory storage, instructions 1110, and a storage unit 1116, both accessible to the processors 1104 such as via the bus 1102. The storage unit 1116 and memory 1114 store the instructions 1110 embodying any one or more of the methodologies or functions described herein. The instructions 1110 may also reside, completely or partially, within the memory 1114, within the storage unit 1116, within at least one of the processors 1104 (e.g., within the processor’s cache memory), or any suitable combination thereof, during execution thereof by the machine 1100. Accordingly, the memory 1114, the storage unit 1116, and the memory of processors 1104 are examples of machine-readable media.

[0122] The I / O components 1118 may include a wide variety of components to receive input, provide output, produce output, transmit information, exchange information,capture measurements, and so on. The specific I / O components 1118 that are included in a particular machine 1100 will depend on the type of machine. For example, portable machines such as mobile phones will likely include a touch input device or other such input mechanisms, while a headless server machine will likely not include such a touch input device. It will be appreciated that the I / O components 1118 may include many other components that are not shown in FIG. 11. The I / O components 1118 are grouped according to functionality merely for simplifying the following discussion and the grouping is in no way limiting. In various example embodiments, the I / O components 1118 may include output components 1126 and input components 1128. The output components 1126 may include visual components (e.g., a display such as a plasma display panel (PDP), a LED display, a LCD, a projector, or a cathode ray tube (CRT)), acoustic components (e.g., speakers), haptic components (e.g., a vibratory motor, resistance mechanisms, acoustic haptic transducers which can create a structured pulse that the subject’s hand can feel in the air and this can be used to provide the feedback discussed above), other signal generators, and so forth. The input components 1128 may include alphanumeric input components (e.g., a keyboard, a touch screen configured to receive alphanumeric input, a photo-optical keyboard, or other alphanumeric input components), point-based input components (e.g., a mouse, a touchpad, a trackball, a joystick, a motion sensor, or other pointing instrument), tactile input components (e.g., a physical button, a touch screen that provides location and / or force of touches or touch gestures, or other tactile input components), audio input components (e.g., a microphone), and the like.

[0123] In further example embodiments, the I / O components 1118 may include biometric components 1139, motion components 1134, environmental components 1136, or position components 1138 among a wide array of other components. For example, the biometric components 1139 may include components to detect expressions (e.g., hand expressions, facial expressions, vocal expressions, body gestures, or eye tracking), measure biosignals (e.g., blood pressure, heart rate, body temperature, perspiration, or brain waves), identify a person (e.g., voice identification, retinal identification, facial identification, fingerprint identification, or electroencephalogram based identification), and the like. The motion components 1134 may include acceleration sensor components (e.g., accelerometer), gravitation sensor components, rotation sensor components (e.g.,gyroscope), and so forth. The environmental components 1136 may include, for example, illumination sensor components (e.g., photometer), temperature sensor components (e.g., one or more thermometer that detect ambient temperature), humidity sensor components, pressure sensor components (e.g., barometer), acoustic sensor components (e.g., one or more microphones that detect background noise), proximity sensor components (e.g., infrared sensors that detect nearby objects), gas sensors (e.g., gas detection sensors to detection concentrations of hazardous gases for safety or to measure pollutants in the atmosphere), or other components that may provide indications, measurements, or signals corresponding to a surrounding physical environment. The position components 1138 may include location sensor components (e.g., a GPS receiver component), altitude sensor components (e.g., altimeters or barometers that detect air pressure from which altitude may be derived), orientation sensor components (e.g., magnetometers), and the like.

[0124] Communication may be implemented using a wide variety of technologies. The I / O components 1118 may include communication components 1140 operable to couple the machine 1100 to a network 1137 or devices 1129 via coupling 1124 and coupling 1122, respectively. For example, the communication components 1140 may include a network interface component or other suitable device to interface with the network 1137. In further examples, communication components 1140 may include wired communication components, wireless communication components, cellular communication components, Near Field Communication (NFC) components, Bluetooth® components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and other communication components to provide communication via other modalities. The devices 1129 may be another machine or any of a wide variety of peripheral devices (e.g., a peripheral device coupled via a USB).

[0125] Moreover, the communication components 1140 may detect identifiers or include components operable to detect identifiers. For example, the communication components 1140 may include RFID tag reader components, NFC smart tag detection components, optical reader components (e.g., an optical sensor to detect one-dimensional bar codes such as Universal Product Code (UPC) bar code, multi-dimensional bar codes such as Quick Response (QR) code, Aztec code, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2D bar code, and other optical codes), or acousticdetection components (e.g., microphones to identify tagged audio signals). In addition, a variety of information may be derived via the communication components 1140, such as location via Internet Protocol (IP) geo-location, location via Wi-Fi® signal triangulation, location via detecting an NFC beacon signal that may indicate a particular location, and so forth.EXAMPLES

[0126] Example 1. A method comprising: establishing a communication session between a handheld hand scanner and a mobile device; sending, to the handheld hand scanner, an instruction from the mobile device to initiate capture of a handprint; receiving, from the handheld hand scanner, a plurality of images of a hand, each of the plurality of images depicting a different portion of the hand.

[0127] Example 2. The method of Example 1 comprising combining the plurality of images into a composite image of the hand; converting the composite image of the hand into the handprint; and processing a record associated with a subject based on the handprint.

[0128] Example 3. The method of Example 2, wherein converting the plurality of images of the hand into the handprint comprises processing a record associated with a subject based on the plurality of handprint images individually or based on a composite image of the plurality of images.

[0129] Example 4. The method of Example 1-3, wherein the communication session comprises a short-range communication session.

[0130] Example 5. The method of any one of Examples 1-4, wherein capturing the plurality of images of the hand comprises: measuring a distance between an image sensor of the handheld hand scanner and an object; determining that the distance corresponds to a threshold distance; and in response to determining that the distance corresponds to the threshold distance, setting a focus of a variable focus lens of the handheld hand scanner based on the measured distance.

[0131] Example 6. The method of Example 5, further comprising: activating a first illumination component of the handheld hand scanner for capturing images of the object; capturing a first image of the plurality of images comprising a first portion of the hand;and sending, via the communication session, the first image to the mobile device for processing the first image.

[0132] Example 7. The method of Example 6, wherein processing the first image comprises: sending, by the mobile device over a network, the first image to a remote server to generate the composite image.

[0133] Example 8. The method of any one of Examples 5-7, wherein processing the first image comprises: segmenting the first image to identify a portion of the first image that depicts the first portion of the hand; and determining whether the identified portion of the first image satisfies a quality metric.

[0134] Example 9. The method of Example 8, further comprising: in response to determining that the identified portion of the first image fails to satisfy the quality metric, causing the handheld hand scanner to recapture a portion of the hand corresponding to the first portion of the hand.

[0135] Example 10. The method of any one of Examples 8-9, wherein determining whether the identified portion of the first image satisfies the quality metric comprises at least one of: determining whether the identified portion corresponds to a hand portion; determining whether a focus of the first image corresponds to a threshold focus level; determining whether an amount of motion blur in the first image transgresses a motion blur threshold; or determining whether one or more occlusions are depicted in the identified portion.

[0136] Example 11. The method of any one of Examples 8-10, further comprising: in response to determining that the identified portion of the first image satisfies the quality metric, adding the first image to a composite image; and instructing the handheld hand scanner to capture a second image of the plurality of images.

[0137] Example 12. The method of Example 11, further comprising: identifying a portion of the composite image that corresponds to the identified portion of the first image; selecting a region of the portion of the composite image that is missing pixel values; and populating the pixel values in the selected region using pixel values of the identified portion of the first image.

[0138] Example 13. The method of any one of Examples 11-12, further comprising: determining whether the composite image completely represents the hand; and inresponse to determining that the composite image fails to completely represent the hand, instructing the handheld hand scanner to capture the second image.

[0139] Example 14. The method of any one of Examples 11-13, further comprising: determining whether the composite image, or selected plurality of images, completely represents the hand; and in response to determining that the composite image completely represents the hand, converting the composite image of the hand into the handprint by: performing Contrast Limited Adaptive Histogram Equalization (CLAHE) on the composite image; applying a noise reduction filter to the composite image; stretching a composite image histogram to increase friction ridge contrast; and inverting a composite image grayscale to darken friction ridges of the hand and to brighten friction ridge valleys of the hand.

[0140] Example 15. The method of any one of Examples 1-14, wherein processing the record associated with the subject based on the handprint comprises: searching a plurality of handprints using the handprint to determine whether any of the plurality of handprints matches the handprint; in response to determining that none of the plurality of handprints matches the handprint, generating the record comprising the handprint and associating the record with the subject; and in response to determining that the record of the plurality of handprints matches the handprint, obtaining one or more access policies from the record.

[0141] Example 16. The method of Example 15, further comprising adding biometric, demographic, and biographic information to the record of the subject to enroll the subject in a database and to perform subsequent identity verification of the subject using the handprint.

[0142] Example 17. The method of any one of Examples 1-16, wherein the handheld hand scanner is held by an operator and moved around to capture the plurality of images.

[0143] Example 18. The method of any one of Examples 1-17, wherein the handheld hand scanner is physically stationary and the subject moves around the hand relative to the handheld scanner while the plurality of images are captured.

[0144] Example 19. The method of any one of Examples 1-18, wherein the handheld hand scanner comprises a display, and wherein the handheld hand scanner presentsprogress and feedback of generating the composite image as the plurality of images are captured by the handheld hand scanner.

[0145] Example 20. The method of Example 19, further comprising: capturing a full image of the hand including each of the plurality of portion, the full image having a lower image resolution than an image resolution of the plurality of images; and presenting the full image of the hand on the display of the handheld hand scanner.

[0146] Example 21. The method of Example 20, further comprising: visually indicating in the full image which parts of the hand have been added to the composite image, or are selected to represent a portion of the hand, from other parts that have not been added to the composite image or selected to represent a position of the hand.

[0147] Example 22. The method of Example 21, further comprising: visually indicating in the full image an individual portion of the hand for which a corresponding one of the plurality of images fails to satisfy a quality metric.

[0148] Example 23. The method of any one of Examples 1-22, wherein the handheld hand scanner comprises a first illumination component and a second illumination component, wherein the handheld hand scanner uses the first illumination component to capture the plurality of images, and wherein the handheld hand scanner presents progress and feedback of generating the composite image using the second illumination component.

[0149] Example 24. The method of Example 23, further comprising: activating the first illumination component as each of the plurality of images is being captured; and after deactivating the first illumination component, activating the second illumination component to illuminate one or more portions of the hand indicating which parts of the hand have been added to the composite image and which other parts of the hand have not been added to the composite image.

[0150] Example 25. The method of Example 24, wherein the handheld hand scanner comprises an optical bandpass filter in a light path between an image sensor of the handheld hand scanner and a lens, the first illumination component and the second illumination component.

[0151] Example 26. The method of Example 25, further comprising: simultaneously activating the first and second illumination components; and filtering, by the opticalbandpass filter light reflected off the hand having a frequency corresponding to the second illumination component, the image sensor receiving the filtered light reflected off the hand.

[0152] Example 27. The method of any one of Examples 23-26, further comprising: projecting a pattern of light on the hand using the second illumination component to indicate a target region of the hand that will be captured as one of the plurality of images.

[0153] Example 28. The method of any one of Examples 23-27, further comprising: projecting a pattern of light on the hand using the second illumination component to indicate a target distance between the handheld hand scanner and the hand.

[0154] Example 29. The method of Example 28, wherein a first color or pattern of the light is projected on the hand to indicate that a distance between the handheld hand scanner and the hand transgresses a threshold range.

[0155] Example 30. The method of Example 29, wherein a second color or pattern of the light is projected on the hand to indicate that the distance is greater than the threshold range, and wherein a third color or pattern of the light is projected on the hand to indicate that the distance is less than the threshold range.

[0156] Example 31. A system comprising: one or more processors configured to perform operations comprising: establishing a communication session between a handheld hand scanner and a mobile device; sending, to the handheld hand scanner, an instruction from the mobile device to initiate capture of a handprint; receiving, from the handheld hand scanner, a plurality of images of a hand, each of the plurality of images depicting a different portion of the hand; combining the plurality of images into a composite image of the hand; converting the composite image of the hand into the handprint; and processing a record associated with a subject based on the handprint.

[0157] Example 32. A non-transitory computer-readable medium comprising non- transitory computer-readable instructions that, when executed by one or more processors, configure the one or more processors to perform operations comprising: establishing a communication session between a handheld hand scanner and a mobile device; sending, to the handheld hand scanner, an instruction from the mobile device to initiate capture of a handprint; receiving, from the handheld hand scanner, a plurality of images of a hand,each of the plurality of images depicting a different portion of the hand; combining the plurality of images into a composite image of the hand; converting the composite image of the hand into the handprint; and processing a record associated with a subject based on the handprint.

[0158] Example 33. A method comprising: establishing a communication session between a handheld hand scanner and a mobile device; sending, to the handheld hand scanner, an instruction from the mobile device to initiate capture of a handprint; receiving, from the handheld hand scanner, a plurality of images of a hand, each of the plurality of images depicting a different portion of the hand; converting the plurality of images of the hand into portions of the handprint; and processing a record associated with a subject based on the handprint.

[0159] Example 34: Systems and non-transitory computer-readable medium for performing any of the above Examples.Glossary:

[0160] " CARRIER SIGNAL" in this context refers to any intangible medium that is capable of storing, encoding, or carrying transitory or non-transitory instructions for execution by the machine, and includes digital or analog communications signals or other intangible medium to facilitate communication of such instructions. Instructions may be transmitted or received over the network using a transitory or non-transitory transmission medium via a network interface device and using any one of a number of well-known transfer protocols.

[0161] "COMMUNICATIONS NETWORK" in this context refers to one or more portions of a network that may be an ad hoc network, an intranet, an extranet, a VPN, a LAN, a BLE network, a UWB network, a WLAN, a WAN, a WWAN, a metropolitan area network (MAN), the Internet, a portion of the Internet, a portion of the PSTN, a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, a Wi-Fi® network, another type of network, or a combination of two or more such networks. For example, a network or a portion of a network may include a wireless or cellular network and the coupling may be a Code Division Multiple Access (CDMA) connection, a Global System for Mobile communications (GSM) connection, or othertype of cellular or wireless coupling. In this example, the coupling may implement any of a variety of types of data transfer technology, such as Single Carrier Radio Transmission Technology (IxRTT), Evolution-Data Optimized (EVDO) technology, General Packet Radio Service (GPRS) technology, Enhanced Data rates for GSM Evolution (EDGE) technology, third Generation Partnership Project (3 GPP) including 3G, fourth generation wireless (4G) networks, Universal Mobile Telecommunications System (UMTS), High Speed Packet Access (HSPA), Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) standard, others defined by various standard setting organizations, other long range protocols, or other data transfer technology.

[0162] "MACHINE -RE AD ABLE MEDIUM" in this context refers to a component, device, or other tangible media able to store instructions and data temporarily or permanently and may include, but is not limited to, RAM, ROM, buffer memory, flash memory, optical media, magnetic media, cache memory, other types of storage (e.g., Erasable Programmable Read-Only Memory [EEPROM]) and / or any suitable combination thereof. The term "machine-readable medium" should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, or associated caches and servers) able to store instructions. The term "machine-readable medium" shall also be taken to include any medium, or combination of multiple media, that is capable of storing instructions (e.g., code) for execution by a machine, such that the instructions, when executed by one or more processors of the machine, cause the machine to perform any one or more of the methodologies described herein.Accordingly, a "machine-readable medium" refers to a single storage apparatus or device, as well as "cloud-based" storage systems or storage networks that include multiple storage apparatus or devices. The term "machine-readable medium" excludes signals per se.

[0163] " COMPONENT" in this context refers to a device, physical entity, or logic having boundaries defined by function or subroutine calls, branch points, APIs, or other technologies that provide for the partitioning or modularization of particular processing or control functions. Components may be combined via their interfaces with other components to carry out a machine process. A component may be a packaged functional hardware unit designed for use with other components and a part of a program thatusually performs a particular function of related functions. Components may constitute either software components (e.g., code embodied on a machine-readable medium) or hardware components. A "hardware component" is a tangible unit capable of performing certain operations and may be configured or arranged in a certain physical manner. In various example embodiments, one or more computer systems (e.g., a standalone computer system, a client computer system, or a server computer system) or one or more hardware components of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a hardware component that operates to perform certain operations as described herein.

[0164] A hardware component (e.g., Al accelerators) may also be implemented mechanically, electronically, or any suitable combination thereof. For example, a hardware component may include dedicated circuitry or logic that is permanently configured to perform certain operations. A hardware component may be a specialpurpose processor, such as a FPGA or an ASIC. A hardware component may also include programmable logic or circuitry that is temporarily configured by software to perform certain operations. For example, a hardware component may include software executed by a general-purpose processor or other programmable processor. Once configured by such software, hardware components become specific machines (or specific components of a machine) uniquely tailored to perform the configured functions and are no longer general-purpose processors. It will be appreciated that the decision to implement a hardware component mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations. Accordingly, the phrase "hardware component"(or "hardware-implemented component") should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. Considering embodiments in which hardware components are temporarily configured (e.g., programmed), each of the hardware components need not be configured or instantiated at any one instance in time. For example, where a hardware component comprises a general-purpose processor configured by software to become a special-purpose processor, the general-purpose processor may be configured as respectively different special-purpose processors (e.g.,comprising different hardware components) at different times. Software accordingly configures a particular processor or processors, for example, to constitute a particular hardware component at one instance of time and to constitute a different hardware component at a different instance of time.

[0165] Hardware components can provide information to, and receive information from, other hardware components. Accordingly, the described hardware components may be regarded as being communicatively coupled. Where multiple hardware components exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) between or among two or more of the hardware components. In embodiments in which multiple hardware components are configured or instantiated at different times, communications between such hardware components may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware components have access. For example, one hardware component may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware component may then, at a later time, access the memory device to retrieve and process the stored output.

[0166] Hardware components may also initiate communications with input or output devices and can operate on a resource (e.g., a collection of information). The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented components that operate to perform one or more operations or functions described herein. As used herein, "processor-implemented component" refers to a hardware component implemented using one or more processors. Similarly, the methods described herein may be at least partially processor-implemented, with a particular processor or processors being an example of hardware. For example, at least some of the operations of a method may be performed by one or more processors or processor-implemented components. Moreover, the one or more processors may also operate to support performance of the relevant operations in a "cloud computing" environment or as a "software as a service" (SaaS). For example, at least some of the operations may beperformed by a group of computers (as examples of machines including processors), with these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., an API). The performance of certain of the operations may be distributed among the processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processors or processor-implemented components may be located in a single geographic location (e.g., within a home environment, an office environment, or a server farm). In other example embodiments, the processors or processor-implemented components may be distributed across a number of geographic locations.

[0167] " PROCESSOR" in this context refers to any circuit or virtual circuit (a physical circuit emulated by logic executing on an actual processor) that manipulates data values according to control signals (e.g., "commands," "op codes," "machine code," etc.) and which produces corresponding output signals that are applied to operate a machine. A processor may, for example, be a CPU, a RISC processor, a CISC processor, a GPU, a DSP, an ASIC, a RFIC, or any combination thereof. A processor may further be a multicore processor having two or more independent processors (sometimes referred to as "cores") that may execute instructions contemporaneously.

[0168] Changes and modifications may be made to the disclosed embodiments without departing from the scope of the present disclosure. These and other changes or modifications are intended to be included within the scope of the present disclosure, as expressed in the following claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter may lie in less than all features of a single disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment.

Claims

WHAT IS CLAIMED IS:

1. A method comprising: establishing a communication session between a handheld hand scanner and a mobile device; sending, to the handheld hand scanner, an instruction from the mobile device to initiate capture of a handprint; receiving, from the handheld hand scanner, a plurality of images of a hand, each of the plurality of images depicting a different portion of the hand; converting the plurality of images of the hand into portions of the handprint; and processing a record associated with a subject based on the handprint.

2. The method of claim 1, wherein the communication session comprises a short-range communication session, further comprising combining the plurality of images into a composite image of the hand.

3. The method of claim 2, wherein capturing the plurality of images of the hand comprises: measuring a distance between an image sensor of the handheld hand scanner and an object; determining that the distance corresponds to a threshold distance; and in response to determining that the distance corresponds to the threshold distance, setting a focus of a variable focus lens of the handheld hand scanner based on the measured distance.

4. The method of claim 3, further comprising: activating a first illumination component of the handheld hand scanner for capturing images of the object; capturing a first image of the plurality of images comprising a first portion of the hand; and sending, via the communication session, the first image to the mobile device for processing the first image.

5. The method of claim 4, wherein processing the first image comprises: sending, by the mobile device, the first image to a remote server to generate the composite image via a network.

6. The method of claim 4, wherein processing the first image comprises: segmenting the first image to identify a portion of the first image that depicts the first portion of the hand; and determining whether the identified portion of the first image satisfies a quality metric.

7. The method of claim 6, further comprising: in response to determining that the identified portion of the first image fails to satisfy the quality metric, causing the handheld hand scanner to recapture a portion of the hand corresponding to the first portion of the hand.

8. The method of claim 6, wherein determining whether the identified portion of the first image satisfies the quality metric comprises at least one of: determining whether the identified portion corresponds to a hand portion; determining whether a focus of the first image corresponds to a threshold focus level; determining whether the distance between the hand and capture device meets predetermined threshold limits; determining whether an amount of motion blur in the first image transgresses a motion blur threshold; or determining whether one or more occlusions are depicted in the identified portion.

9. The method of claim 6, further comprising: in response to determining that the identified portion of the first image satisfies the quality metric, adding the first image to the composite image; and instructing the handheld hand scanner to capture a second image of the plurality of images.

10. The method of claim 9, further comprising:identifying a portion of the composite image that corresponds to the identified portion of the first image; selecting a region of the portion of the composite image that is missing pixel values; and populating the pixel values in the selected region using pixel values of the identified portion of the first image.

11. The method of claim 9, further comprising: determining whether the composite image completely represents the hand; and in response to determining that the composite image fails to completely represent the hand, instructing the handheld hand scanner to capture the second image.

12. The method of claim 9, further comprising: determining whether the composite image completely represents the hand; and in response to determining that the composite image completely represents the hand, converting the composite image of the hand into the handprint by: performing Contrast Limited Adaptive Histogram Equalization (CLAHE) on the composite image; applying a noise reduction filter to the composite image; stretching a composite image histogram to increase friction ridge contrast; and inverting a composite image grayscale to darken friction ridges of the hand and to brighten friction ridge valleys of the hand.

13. The method of claim 1, wherein processing the record associated with the subject based on the handprint comprises: searching a plurality of handprints using the handprint to determine whether any of the plurality of handprints matches the handprint; in response to determining that none of the plurality of handprints matches the handprint, generating the record comprising the handprint and associating the record with the subject; and in response to determining that the record of the plurality of handprints matches the handprint, obtaining one or more access policies from the record.

14. The method of claim 13, further comprising adding biometric, demographic, and biographic information to the record of the subject to enroll the subject in a database and to perform subsequent identity verification of the subject using the handprint.

15. The method of claim 1, wherein the handheld hand scanner is held by an operator and moved around to capture the plurality of images, and wherein the handheld scanner comprises a fixed focus image capture device.

16. The method of claim 1, wherein the handheld hand scanner is physically stationary and the subject moves around the hand relative to the handheld scanner while the plurality of images are captured.

17. The method of claim 1, wherein the handheld hand scanner comprises a display, and wherein the handheld hand scanner presents progress and feedback of generating a composite image as the plurality of images are captured by the handheld hand scanner.

18. The method of claim 17, further comprising: capturing a full image of the hand including each of the plurality of images, the full image having a lower image resolution than an image resolution of the plurality of images; and presenting the full image of the hand on the display of the handheld hand scanners or a display of the mobile device.

19. The method of claim 18, further comprising: visually indicating in the full image which parts of the hand have been added to the composite image from other parts that have not been added to the composite image.

20. The method of claim 19, further comprising: visually indicating in the full image an individual portion of the hand for which a corresponding one of the plurality of images fails to satisfy a quality metric.

21. The method of claim 1, wherein the handheld hand scanner comprises a first illumination component and a second illumination component, wherein the handheld hand scanner uses the first illumination component to capture the plurality of images, and wherein the handheld hand scanner presents progress and feedback of generating a composite image using the second illumination component.

22. The method of claim 21, further comprising: activating the first illumination component as each of the plurality of images is being captured; and after deactivating the first illumination component, activating the second illumination component to illuminate one or more portions of the hand indicating which parts of the hand have been added to the composite image and which other parts of the hand have not been added to the composite image.

23. The method of claim 22, wherein the handheld hand scanner comprises an optical bandpass filter in a light path between an image sensor of the handheld hand scanner and a lens, the first illumination component and the second illumination component.

24. The method of claim 23, further comprising: simultaneously activating the first and second illumination components; and filtering, by the optical bandpass filter light reflected off the hand having a frequency corresponding to the first illumination component, the image sensor receiving the filtered light reflected off the hand.

25. The method of claim 21, further comprising: projecting a pattern of light on the hand using the second illumination component to indicate a target region of the hand that will be captured as one of the plurality of images.

26. The method of claim 21, further comprising: projecting a pattern of light on the hand using the second illumination component to indicate a target distance between the handheld hand scanner and the hand.

27. The method of claim 26, wherein a first color or pattern of the light is projected on the hand to indicate that a distance between the handheld hand scanner and the hand transgresses a threshold range.

28. The method of claim 27, wherein a second color or pattern of the light is projected on the hand to indicate that the distance is greater than the threshold range, and wherein a third color or pattern of the light is projected on the hand to indicate that the distance is less than the threshold range.

29. A system comprising: one or more processors configured to perform operations comprising: establishing a communication session between a handheld hand scanner and a mobile device; sending, to the handheld hand scanner, an instruction from the mobile device to initiate capture of a handprint; receiving, from the handheld hand scanner, a plurality of images of a hand, each of the plurality of images depicting a different portion of the hand; converting the plurality of images of the hand into portions of the handprint; and processing a record associated with a subject based on the handprint.

30. A non-transitory computer-readable medium comprising non-transitory computer- readable instructions that, when executed by one or more processors, configure the one or more processors to perform operations comprising: establishing a communication session between a handheld hand scanner and a mobile device; sending, to the handheld hand scanner, an instruction from the mobile device to initiate capture of a handprint; receiving, from the handheld hand scanner, a plurality of images of a hand, each of the plurality of images depicting a different portion of the hand; converting the plurality of images of the hand into portions of the handprint; and processing a record associated with a subject based on the handprint.

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