Patent ID: 12204968

The drawings are not necessarily to scale. The drawings are merely schematic representations, not intended to portray specific parameters of the disclosed embodiments. The drawings are intended to depict only typical embodiments of the invention, and therefore should not be considered as limiting in scope.

DETAILED DESCRIPTION OF THE INVENTION

QR (Quick Response) codes are a popular 2D barcode format for encoding machine-readable data. They are widely used for applications such as product tracking, document verification, and URL sharing. However, conventional QR codes have limitations in terms of data capacity and security. The maximum data capacity of a QR code depends on factors including the version, error correction level, and character encoding. Typically, QR codes can store up to around 3 KB of data. This limited capacity can be restrictive for applications needing to embed larger amounts of information. Additionally, the data in a standard QR code is unencrypted and can be read by any QR scanner. This lack of security makes QR codes unsuitable for storing sensitive or confidential information.

Disclosed embodiments address the aforementioned issues with a novel approach that includes employing proprietary compression codebooks to increase information density and provide data security. In disclosed embodiments, a system comprises an encoding engine, a decoding engine, public and private compression codebooks, and/or a QR code encoding library and/or module. The public codebook provides a standard mapping to compress public portions of the input data. The private codebook uses a proprietary mapping to compress private portions of the data. The private codebook provides security through the secrecy of its mapping. The encoding engine separates input data into public and private portions, compresses each using the applicable codebook, combines the encoded data into a single compressed string, and passes it to the QR encoding library and/or module to generate a high-capacity QR code output. The decoding engine reads an encoded QR code, extracts the public and private compressed portions, and decompresses each using the applicable codebook to recover the original public and private data components. Additionally, one or more embodiments may include a key management system to securely distribute the private codebooks to authorized users' devices to enable decoding of the private data portion.

One or more different aspects may be described in the present application. Further, for one or more of the aspects described herein, numerous alternative arrangements may be described; it should be appreciated that these are presented for illustrative purposes only and are not limiting of the aspects contained herein or the claims presented herein in any way. One or more of the arrangements may be widely applicable to numerous aspects, as may be readily apparent from the disclosure. In general, arrangements are described in sufficient detail to enable those skilled in the art to practice one or more of the aspects, and it should be appreciated that other arrangements may be utilized and that structural, logical, software, electrical and other changes may be made without departing from the scope of the particular aspects. Particular features of one or more of the aspects described herein may be described with reference to one or more particular aspects or figures that form a part of the present disclosure, and in which are shown, by way of illustration, specific arrangements of one or more of the aspects. It should be appreciated, however, that such features are not limited to usage in the one or more particular aspects or figures with reference to which they are described. The present disclosure is neither a literal description of all arrangements of one or more of the aspects nor a listing of features of one or more of the aspects that must be present in all arrangements.

Headings of sections provided in this patent application and the title of this patent application are for convenience only, and are not to be taken as limiting the disclosure in any way.

Devices that are in communication with each other need not be in continuous communication with each other, unless expressly specified otherwise. In addition, devices that are in communication with each other may communicate directly or indirectly through one or more communication means or intermediaries, logical or physical.

A description of an aspect with several components in communication with each other does not imply that all such components are required. To the contrary, a variety of optional components may be described to illustrate a wide variety of possible aspects and in order to more fully illustrate one or more aspects. Similarly, although process steps, method steps, algorithms or the like may be described in a sequential order, such processes, methods and algorithms may generally be configured to work in alternate orders, unless specifically stated to the contrary. In other words, any sequence or order of steps that may be described in this patent application does not, in and of itself, indicate a requirement that the steps be performed in that order. The steps of described processes may be performed in any order practical. Further, some steps may be performed simultaneously despite being described or implied as occurring non-simultaneously (e.g., because one step is described after the other step). Moreover, the illustration of a process by its depiction in a drawing does not imply that the illustrated process is exclusive of other variations and modifications thereto, does not imply that the illustrated process or any of its steps are necessary to one or more of the aspects, and does not imply that the illustrated process is preferred. Also, steps are generally described once per aspect, but this does not mean they must occur once, or that they may only occur once each time a process, method, or algorithm is carried out or executed. Some steps may be omitted in some aspects or some occurrences, or some steps may be executed more than once in a given aspect or occurrence.

When a single device or article is described herein, it will be readily apparent that more than one device or article may be used in place of a single device or article. Similarly, where more than one device or article is described herein, it will be readily apparent that a single device or article may be used in place of the more than one device or article.

The functionality or the features of a device may be alternatively embodied by one or more other devices that are not explicitly described as having such functionality or features. Thus, other aspects need not include the device itself.

Techniques and mechanisms described or referenced herein will sometimes be described in singular form for clarity. However, it should be appreciated that particular aspects may include multiple iterations of a technique or multiple instantiations of a mechanism unless noted otherwise. Process descriptions or blocks in figures should be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps in the process. Alternate implementations are included within the scope of various aspects in which, for example, functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those having ordinary skill in the art.

Definitions

The term “bit” refers to the smallest unit of information that can be stored or transmitted. It is in the form of a binary digit (either 0 or 1). In terms of hardware, the bit is represented as an electrical signal that is either off (representing 0) or on (representing 1).

The term “hash” refers to a mathematical function that converts input data into a fixed-size string of bytes or characters, which typically represents a shorter, more manageable version of the input. This output is commonly referred to as a “hash value,” “hash code,” or simply “hash.”

The term “QR Code” refers to a quick response code, which is a two-dimensional barcode that offers high-speed and omni-directional reading, and has a large information capacity, high reliability, and is compatible with diverse characters and image information.

The term ‘codebook’ refers to a dictionary or table that maps input symbols (such as characters or pixels) to specific codewords. Codewords are typically binary sequences (0s and 1s) that represent the input symbols in a more compact form.

Conceptual Architecture

FIG.1is a diagram showing an exemplary system architecture, according to an embodiment, utilizing a QR encoding module. The system100includes a QR encoding module102that can include functions and/or instructions for encoding input data103into a QR code112. In embodiments, the input data includes public data and private data. In embodiments, QR encoding module102includes a hash engine116, and the public data and private data is input to both the hash engine116, and the compression engine104. The hash engine116can include functions, instructions, and/or hardware to compute a hash of the input data. In embodiments, the hash engine116operates on a concatenation of the public data and the private data. In embodiments, the hash engine116generates an md5 hash value, or a SHA1 hash value. Other hashing schemes may be used in one or more embodiments. The compression engine104can include functions, instructions, and/or hardware to compress the input data103using a public codebook and/or a private codebook. In embodiments, a public codebook may be retrieved via a computer network from public codebook library106. In embodiments, a private codebook may be retrieved via a computer network from private codebook library108. In embodiments, QR encoding module102includes a QR Code Render engine110, that can include functions and/or instructions for encoding the output of the compression engine104, along with the hash values from hash engine116, into a QR code112. In one or more embodiments, the QR Code Render engine110may render QR code112according to ISO/IEC 18004, ISO/IEC 21471, JIS X 0510, and/or other suitable standards. In one or more embodiments, the QR code is sent to an output device158. In one or more embodiments, the output device158can include an electronic display, printer, and/or other suitable output device. Thus, embodiments can include rendering the QR code on an electronic display.

FIG.2is a diagram showing an exemplary system architecture, according to an embodiment, utilizing a QR decoding module202. The QR decoding module202can include functions and/or instructions for decoding QR code212into a QR code compressed data string215. The QR code compressed data string215is input to decompression engine204. The decompression engine204can include functions and/or instructions for decompressing the QR code compressed data string. In embodiments, decompression engine204can include functions and/or instructions for accessing a public codebook from public codebook library106, and/or accessing a private codebook from private codebook library108. In embodiments, the public codebook library106and/or the private codebook library108may be connected to a QR code reading device (e.g., a smartphone) via a computer network, such as a local area network (LAN), wide area network (WAN), and/or other suitable network. In one or more embodiments, the network includes the Internet. The decompression engine204outputs QR code uncompressed data string225. The QR code uncompressed data string225is input to QR code data output engine210, which outputs the QR code uncompressed data string to an output device208. In one or more embodiments, the output device208can include an electronic display, printer, and/or other suitable output device.

FIG.3is a diagram300showing an exemplary compressed data format, according to an embodiment. Diagram300includes an exemplary QR code compressed data string302. The QR code compressed data string302can be comprised of characters encoded as ASCII, UTF-8, Unicode, or other suitable format. The QR code compressed data string302can include various markers to delimit multiple fields. In one or more embodiments, the markers can include a special character, followed by a preset number of alphanumeric characters. As an example, a delimiter can include an asterisk followed by a four-character alphanumeric code. Other combinations of characters may be used as markers in one or more embodiments. The QR code compressed data string302can include public codebook marker304, indicating that the following data pertains to a public codebook Uniform Resource Locator (URL)306. The public codebook Uniform Resource Locator (URL)306may be used to access a public codebook from public codebook library106.

The QR code compressed data string302can include private codebook marker310, indicating that the following data pertains to a private codebook Uniform Resource Locator (URL)312. The private codebook Uniform Resource Locator (URL)312may be used to access a private codebook from private codebook library108. The QR code compressed data string302can include hash marker316, indicating that the following data pertains to hash data318. The hash data318may be used to encode the public uncompressed data324and/or private uncompressed data326as a hash value, computed by hash engine116. In embodiments, the public uncompressed data324and the private uncompressed data326are concatenated into a single string prior to performing a hash on it. In one or more embodiments, the hash value can be computed using an md5 hash, SHA1 hash, SHA256 hash, or other suitable hashing technique. In one or more embodiments, the hash data318is used to confirm that the compressed data is properly decompressed. In embodiments, the QR decoding device (e.g., a laser scanner, smartphone, or the like) computes a hash value of the data that was uncompressed on the device, and compares it to the hash data318, with a match indicating correct decompression, and a mismatch indicating an error in decompressing the data. In this way, disclosed embodiments provide confirmation that the compressed data is decompressed with the correct codebook(s).

FIG.4is a diagram showing an exemplary user interface indicating successful QR decoding, according to an embodiment. Electronic device400may be a smartphone, tablet computer, laser scanner, or other suitable electronic device for scanning a QR code of disclosed embodiments. The electronic device includes an electronic display402. The electronic device400further includes a camera409, which is used to obtain an image of a QR code412in a digital format, which is loaded into a memory of the electronic device400for further processing. In the embodiment shown inFIG.4, various steps of the QR decoding process are shown, along with a corresponding status indicator. At field420, there is an indication of a successful scanning (image acquisition), and a corresponding success indicator431. At field422, there is an indication of a successful codebook access (successful retrieval of public codebook(s) and/or private codebook(s)), and a corresponding success indicator432. At field424, there is an indication of a successful data authentication (e.g., matching of computed hash and the hash included in the QR code compressed data string), and a corresponding success indicator433. At426, the uncompressed data from the QR code is rendered. Thus, embodiments can include identifying a hash within the input string; computing a concatenation of the decoded public data portion and the decoded private data portion; computing a hashed value of the concatenation; and in response to the hash within the input string matching the hashed value, setting a status of the uncompressed data string to authenticated.

FIG.5is a diagram showing an exemplary user interface indicating a failed QR decoding due to an error during codebook access, according to an embodiment. Electronic device500may be a smartphone, tablet computer, laser scanner, or other suitable electronic device for scanning a QR code of disclosed embodiments. The electronic device includes an electronic display502. The electronic device500further includes a camera509, which is used to obtain an image of a QR code512in a digital format, which is loaded into a memory of the electronic device500for further processing. In the embodiment shown inFIG.5, various steps of the QR decoding process are shown, along with a corresponding status indicator. At field520, there is an indication of a successful scanning (image acquisition), and a corresponding success indicator531. At field522, there is an indication of a failed codebook access (failure to retrieve public codebook(s) and/or private codebook(s)), and a corresponding failure indicator532. Failure causes can include network connectivity failures, and/or authentication/credential failures. At field524, there is an indication of an uncompleted data authentication (i.e., since the codebook(s) could not be retrieved, and a corresponding incomplete indicator533. At526, a corresponding error message is rendered, indicating that one or more codebooks could not be accessed (e.g., based on codebook URLs, such as shown inFIG.3at306and312).

FIG.6is a diagram showing an exemplary user interface indicating a failed QR decoding duc to an error during data authentication, according to an embodiment. Electronic device600may be a smartphone, tablet computer, laser scanner, or other suitable electronic device for scanning a QR code of disclosed embodiments. The electronic device includes an electronic display602. The electronic device600further includes a camera609, which is used to obtain an image of a QR code612in a digital format, which is loaded into a memory of the electronic device600for further processing. In the embodiment shown inFIG.6, various steps of the QR decoding process are shown, along with a corresponding status indicator. At field620, there is an indication of a successful scanning (image acquisition), and a corresponding success indicator631. At field622, there is an indication of a successful codebook access (successful retrieval of public codebook(s) and/or private codebook(s)), and a corresponding success indicator632. At field624, there is an indication of a data authentication failure (e.g., failure to match a computed hash and a received hash), and a corresponding failure indicator633. Failure causes can include accessing an incorrect codebook, a communication error, and/or other types of errors. At626, a corresponding error message is rendered, indicating that data authentication has failed (e.g., based on computed and received hashes not matching). In one or more embodiments, the decoded data may also be rendered, such as shown at426inFIG.4. In this way, the user may be able to observe the decoded data, while also being alerted that the data authentication did not succeed. This feature can be useful for diagnosing and troubleshooting of system issues.

FIG.7is an exemplary codebook700according to one or more embodiments. As can be seen, the codebook includes a mapping of binary strings to symbols. As an example, at732, the symbol “A” is mapped to a binary string “10”, and at734, the symbol734is mapped to a binary string “1111111110.” In embodiments, the codebook mapping is based on an estimated frequency of occurrence of a given symbol, with more frequently occurring symbols mapped to shorter codes, thereby achieving a level of compression. In the example ofFIG.7, column710includes symbols that appear more frequently in the English language, while column720includes symbols that appear less frequently in the English language. Accordingly, column720has larger binary strings than column710, thereby enabling data compression. While the codebook depicted inFIG.7shows capital Roman letters, embodiments can include codebooks with more, fewer, and/or different symbols. In embodiments, the codebooks may be customized for other languages besides English, and/or customized for other types of data patterns. In one or more embodiments, the codebooks may be developed based on machine learning techniques.

Detailed Description of Exemplary Aspects

FIG.8is a flow diagram illustrating an exemplary method for encoding information into a QR code, according to an embodiment. According to the embodiment, the method800begins at step802where input data to be encoded is obtained. The data can include text data. The method800continues to step804, separating the input data into a public data portion and a private data portion. In embodiments, the determination of what data is separated into a public data portion and a private data portion may be based on user-defined settings. As an example, certain data fields within the input data may be compressed using a public codebook, while other data fields within the input data may be compressed using a private codebook. For example, in a medical records application, some data may be compressed with the public codebook to enable statistical processing and data aggregation, such as an age of a person, and the state the person resides in, while other data, such as name, address, and/or other personally identifiable data is encrypted using a private codebook. Thus, disclosed embodiments can enable anonymization of some data, while exposing other data. This can enable useful collection of statistics for a wide variety of applications, such as public health, traffic studies, consumer behavior, and so on, while maintaining privacy of individuals. A user that only has access to the public data can use a QR code reading device that has access to the public codebook, but does not have access to the private codebook, enabling access to the public data, while preventing access to the private data. Similarly, a user that only access to both the public data and the private data can use a QR code reading device that has access to both the public codebook and the private codebook, enabling access to the public data, as well as the private data.

The method800continues to step806, where a hash of the public data portion and private data portion are computed. The method800continues to step808, where the public data portion is compressed using a public codebook. The method800continues to step810, where the private data portion is compressed using a private codebook. The method800continues to step812, where the public compressed data portion, private compressed data portion, and hash, are included in a combined data string, such as depicted at302inFIG.3.

FIG.9is a flow diagram illustrating an exemplary method for decoding a QR code, according to an embodiment. According to the embodiment, the method900begins at step902where a QR code image is obtained. In embodiments, the image may be obtained via an onboard camera of an electronic device, such as a smartphone, tablet computer, and/or dedicated QR code reading device. The method900continues to step904, where the obtained QR code image is decoded into an input string (e.g., such as depicted at302inFIG.3). The method900continues to step906, where a compressed public data portion and a compressed private data portion of the input string are identified. In one or more embodiments, the identification of compressed public data portion(s) and compressed private data portion(s) can include parsing the input string to identify the location of corresponding markers (e.g., such as304,310, and/or316ofFIG.3). The method900continues to step908, where the compressed public data is decoded using a public codebook. In one or more embodiments, the decompression process can include using a public codebook Uniform Resource Locator (URL) (306ofFIG.3) to access a public codebook (e.g.106ofFIG.3).

The method900continues to step910, where the compressed private data is decoded using a private codebook. In one or more embodiments, the decompression process can include using a private codebook Uniform Resource Locator (URL) (312ofFIG.3) to access a private codebook (e.g.108ofFIG.3). The method900continues to step912, where the decoded public data portion and decoded private data portion are combined into a combined uncompressed data string. The combined uncompressed data string can then be sent to one or more output device(s), such as an electronic display, printer, and/or other suitable output device.

In one or more embodiments, the codebooks may be stored in memory of an electronic device that is decoding a QR code. Thus, embodiments can include identifying a public codebook Uniform Resource Locator (URL) within the input string; storing the public codebook in the memory; identifying a public codebook Uniform Resource Locator (URL) within the input string; and storing the private codebook in the memory. In some embodiments, the codebooks may be stored in memory until a resident QR code reading application is closed. In this way, performance can be increased by not needing to retrieve a codebook that is already stored in memory, enabling faster reading of QR codes. In one or more embodiments, the codebooks may be cleared from memory (and contents overwritten with a data pattern) immediately after decoding a QR code. By clearing the codebooks from memory after each QR decode, security is improved, although there is a performance tradeoff. In one or more embodiments, a user setting can enable a user to select an option to cache the codebooks while using the QR code reading application, or to clear the codebooks after every QR decode. In one or more embodiments, the codebook clearing can be based on a network health status of the electronic device that is decoding a QR code. In embodiments, with a robust network status (e.g., high signal strength, and high bandwidth), the codebooks are cleared after each QR decode. Conversely, during conditions of a non-robust network status (e.g., low signal strength, and/or low bandwidth), the codebooks are preserved until a resident QR code reading application is closed or the network status improves. In this way, disclosed embodiments can provide a feature that provides both performance and security in decoding QR codes that provide increased data capacity. Thus, embodiments can include determining a network connectivity status of the system; and in response to determining a robust network connectivity status, clearing the private codebook from the memory after setting the status of the uncompressed data string to authenticated. Additionally, embodiments can include, in response to determining a non-robust network connectivity status, clearing the private codebook from the memory after a QR decoding application executing on the processor terminates.

Exemplary Computing Environment

FIG.10illustrates an exemplary computing environment on which an embodiment described herein may be implemented, in full or in part. This exemplary computing environment describes computer-related components and processes supporting enabling disclosure of computer-implemented embodiments. Inclusion in this exemplary computing environment of well-known processes and computer components, if any, is not a suggestion or admission that any embodiment is no more than an aggregation of such processes or components. Rather, implementation of an embodiment using processes and components described in this exemplary computing environment will involve programming or configuration of such processes and components resulting in a machine specially programmed or configured for such implementation. The exemplary computing environment described herein is only one example of such an environment and other configurations of the components and processes are possible, including other relationships between and among components, and/or absence of some processes or components described. Further, the exemplary computing environment described herein is not intended to suggest any limitation as to the scope of use or functionality of any embodiment implemented, in whole or in part, on components or processes described herein.

The exemplary computing environment described herein comprises a computing device10(further comprising a system bus11, one or more processors20, a system memory30, one or more interfaces40, one or more non-volatile data storage devices50), external peripherals and accessories60, external communication devices70, remote computing devices80, and cloud-based services90.

System bus11couples the various system components, coordinating operation of and data transmission between those various system components. System bus11represents one or more of any type or combination of types of wired or wireless bus structures including, but not limited to, memory busses or memory controllers, point-to-point connections, switching fabrics, peripheral busses, accelerated graphics ports, and local busses using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) busses, Micro Channel Architecture (MCA) busses, Enhanced ISA (EISA) busses, Video Electronics Standards Association (VESA) local busses, a Peripheral Component Interconnects (PCI) busses also known as a Mezzanine busses, or any selection of, or combination of, such busses. Depending on the specific physical implementation, one or more of the processors20, system memory30and other components of the computing device10can be physically co-located or integrated into a single physical component, such as on a single chip. In such a case, some or all of system bus11can be electrical pathways within a single chip structure.

Computing device may further comprise externally-accessible data input and storage devices12such as compact disc read-only memory (CD-ROM) drives, digital versatile discs (DVD), or other optical disc storage for reading and/or writing optical discs62; magnetic cassettes, magnetic tape, magnetic disk storage, or other magnetic storage devices; or any other medium which can be used to store the desired content and which can be accessed by the computing device10. Computing device may further comprise externally-accessible data ports or connections12such as serial ports, parallel ports, universal serial bus (USB) ports, and infrared ports and/or transmitter/receivers. Computing device may further comprise hardware for wireless communication with external devices such as IEEE 1394 (“Firewire”) interfaces, IEEE 802.11 wireless interfaces, BLUETOOTH® wireless interfaces, and so forth. Such ports and interfaces may be used to connect any number of external peripherals and accessories60such as visual displays, monitors, and touch-sensitive screens61, USB solid state memory data storage drives (commonly known as “flash drives” or “thumb drives”)63, printers64, pointers and manipulators such as mice65, keyboards66, and other devices67such as joysticks and gaming pads, touchpads, additional displays and monitors, and external hard drives (whether solid state or disc-based), microphones, speakers, cameras, and optical scanners.

Processors20are logic circuitry capable of receiving programming instructions and processing (or executing) those instructions to perform computer operations such as retrieving data, storing data, and performing mathematical calculations. Processors20are not limited by the materials from which they are formed or the processing mechanisms employed therein, but are typically comprised of semiconductor materials into which many transistors are formed together into logic gates on a chip (i.e., an integrated circuit or IC). The term processor includes any device capable of receiving and processing instructions including, but not limited to, processors operating on the basis of quantum computing, optical computing, mechanical computing (e.g., using nanotechnology entities to transfer data), and so forth. Depending on configuration, computing device10may comprise more than one processor. For example, computing device10may comprise one or more central processing units (CPUs)21, each of which itself has multiple processors or multiple processing cores, each capable of independently or semi-independently processing programming instructions. Further, computing device10may comprise one or more specialized processors such as a graphics processing unit (GPU)22configured to accelerate processing of computer graphics and images via a large array of specialized processing cores arranged in parallel.

System memory30is processor-accessible data storage in the form of volatile and/or nonvolatile memory. System memory30may be either or both of two types: non-volatile memory and volatile memory. Non-volatile memory30ais not erased when power to the memory is removed, and includes memory types such as read only memory (ROM), electronically-erasable programmable memory (EEPROM), and rewritable solid-state memory (commonly known as “flash memory”). Non-volatile memory30ais typically used for long-term storage of a basic input/output system (BIOS)31, containing the basic instructions, typically loaded during computer startup, for transfer of information between components within computing device, or a unified extensible firmware interface (UEFI), which is a modern replacement for BIOS that supports larger hard drives, faster boot times, more security features, and provides native support for graphics and mouse cursors. Non-volatile memory30amay also be used to store firmware comprising a complete operating system35and applications36for operating computer-controlled devices. The firmware approach is often used for purpose-specific computer-controlled devices such as appliances and Internet-of-Things (IoT) devices where processing power and data storage space is limited. Volatile memory30bis erased when power to the memory is removed and is typically used for short-term storage of data for processing. Volatile memory30bincludes memory types such as random-access memory (RAM), and is normally the primary operating memory into which the operating system35, applications36, program modules37, and application data38are loaded for execution by processors20. Volatile memory30bis generally faster than non-volatile memory30adue to its electrical characteristics and is directly accessible to processors20for processing of instructions and data storage and retrieval. Volatile memory30bmay comprise one or more smaller cache memories which operate at a higher clock speed and are typically placed on the same IC as the processors to improve performance.

Interfaces40may include, but are not limited to, storage media interfaces41, network interfaces42, display interfaces43, and input/output interfaces44. Storage media interface41provides the necessary hardware interface for loading data from non-volatile data storage devices50into system memory30and storage data from system memory30to non-volatile data storage device50. Network interface42provides the necessary hardware interface for computing device10to communicate with remote computing devices80and cloud-based services90via one or more external communication devices70. Display interface43allows for connection of displays61, monitors, touchscreens, and other visual input/output devices. Display interface43may include a graphics card for processing graphics-intensive calculations and for handling demanding display requirements. Typically, a graphics card includes a graphics processing unit (GPU) and video RAM (VRAM) to accelerate display of graphics. One or more input/output (I/O) interfaces44provide the necessary support for communications between computing device10and any external peripherals and accessories60. For wireless communications, the necessary radio-frequency hardware and firmware may be connected to I/O interface44or may be integrated into I/O interface44.

Non-volatile data storage devices50are typically used for long-term storage of data. Data on non-volatile data storage devices50is not erased when power to the non-volatile data storage devices50is removed. Non-volatile data storage devices50may be implemented using any technology for non-volatile storage of content including, but not limited to, CD-ROM drives, digital versatile discs (DVD), or other optical disc storage; magnetic cassettes, magnetic tape, magnetic disc storage, or other magnetic storage devices; solid state memory technologies such as EEPROM or flash memory; or other memory technology or any other medium which can be used to store data without requiring power to retain the data after it is written. Non-volatile data storage devices50may be non-removable from computing device10as in the case of internal hard drives, removable from computing device10as in the case of external USB hard drives, or a combination thereof, but computing device will typically comprise one or more internal, non-removable hard drives using either magnetic disc or solid-state memory technology. Non-volatile data storage devices50may store any type of data including, but not limited to, an operating system51for providing low-level and mid-level functionality of computing device10, applications52for providing high-level functionality of computing device10, program modules53such as containerized programs or applications, or other modular content or modular programming, application data54, and databases55such as relational databases, non-relational databases, object oriented databases, BOSQL databases, and graph databases.

Applications (also known as computer software or software applications) are sets of programming instructions designed to perform specific tasks or provide specific functionality on a computer or other computing devices. Applications are typically written in high-level programming languages such as C++, Java, and Python, which are then either interpreted at runtime or compiled into low-level, binary, processor-executable instructions operable on processors20. Applications may be containerized so that they can be run on any computer hardware running any known operating system. Containerization of computer software is a method of packaging and deploying applications along with their operating system dependencies into self-contained, isolated units known as containers. Containers provide a lightweight and consistent runtime environment that allows applications to run reliably across different computing environments, such as development, testing, and production systems.

The memories and non-volatile data storage devices described herein do not include communication media. Communication media are means of transmission of information such as modulated electromagnetic waves or modulated data signals configured to transmit, not store, information. By way of example, and not limitation, communication media includes wired communications such as sound signals transmitted to a speaker via a speaker wire, and wireless communications such as acoustic waves, radio frequency (RF) transmissions, infrared emissions, and other wireless media.

External communication devices70are devices that facilitate communications between computing device and either remote computing devices80, or cloud-based services90, or both. External communication devices70include, but are not limited to, data modems71which facilitate data transmission between computing device and the Internet75via a common carrier such as a telephone company or internet service provider (ISP), routers72which facilitate data transmission between computing device and other devices, and switches73which provide direct data communications between devices on a network. Here, modem71is shown connecting computing device10to both remote computing devices80and cloud-based services90via the Internet75. While modem71, router72, and switch73are shown here as being connected to network interface42, many different network configurations using external communication devices70are possible. Using external communication devices70, networks may be configured as local area networks (LANs) for a single location, building, or campus, wide area networks (WANs) comprising data networks that extend over a larger geographical area, and virtual private networks (VPNs) which can be of any size but connect computers via encrypted communications over public networks such as the Internet75. As just one exemplary network configuration, network interface42may be connected to switch73which is connected to router72which is connected to modem71which provides access for computing device10to the Internet75. Further, any combination of wired77or wireless76communications between and among computing device10, external communication devices70, remote computing devices80, and cloud-based services90may be used. Remote computing devices80, for example, may communicate with computing device through a variety of communication channels74such as through switch73via a wired77connection, through router72via a wireless connection76, or through modem71via the Internet75. Furthermore, while not shown here, other hardware that is specifically designed for servers may be employed. For example, secure socket layer (SSL) acceleration cards can be used to offload SSL encryption computations, and transmission control protocol/internet protocol (TCP/IP) offload hardware and/or packet classifiers on network interfaces42may be installed and used at server devices.

In a networked environment, certain components of computing device10may be fully or partially implemented on remote computing devices80or cloud-based services90. Data stored in non-volatile data storage device50may be received from, shared with, duplicated on, or offloaded to a non-volatile data storage device on one or more remote computing devices80or in a cloud computing service92. Processing by processors20may be received from, shared with, duplicated on, or offloaded to processors of one or more remote computing devices80or in a distributed computing service93. By way of example, data may reside on a cloud computing service92, but may be usable or otherwise accessible for use by computing device10. Also, certain processing subtasks may be sent to a microservice91for processing with the result being transmitted to computing device10for incorporation into a larger processing task. Also, while components and processes of the exemplary computing environment are illustrated herein as discrete units (e.g., OS51being stored on non-volatile data storage device51and loaded into system memory35for usc) such processes and components may reside or be processed at various times in different components of computing device10, remote computing devices80, and/or cloud-based services90.

In an implementation, the disclosed systems and methods may utilize, at least in part, containerization techniques to execute one or more processes and/or steps disclosed herein. Containerization is a lightweight and efficient virtualization technique that allows you to package and run applications and their dependencies in isolated environments called containers. One of the most popular containerization platforms is Docker, which is widely used in software development and deployment. Containerization, particularly with open-source technologies like Docker and container orchestration systems like Kubernetes, is a common approach for deploying and managing applications. Containers are created from images, which are lightweight, standalone, and executable packages that include application code, libraries, dependencies, and runtime. Images are often built from a Dockerfile or similar, which contains instructions for assembling the image. Dockerfiles are configuration files that specify how to build a Docker image. Systems like Kubernetes also support containers or CRI-O. They include commands for installing dependencies, copying files, setting environment variables, and defining runtime configurations. Docker images are stored in repositories, which can be public or private. Docker Hub is an exemplary public registry, and organizations often set up private registries for security and version control using tools such as Hub, JFrog Artifactory and Bintray, Github Packages or Container registries. Containers can communicate with each other and the external world through networking. Docker provides a bridge network by default, but can be used with custom networks. Containers within the same network can communicate using container names or IP addresses.

Remote computing devices80are any computing devices not part of computing device10. Remote computing devices80include, but are not limited to, personal computers, server computers, thin clients, thick clients, personal digital assistants (PDAs), mobile telephones, watches, tablet computers, laptop computers, multiprocessor systems, microprocessor based systems, set-top boxes, programmable consumer electronics, video game machines, game consoles, portable or handheld gaming units, network terminals, desktop personal computers (PCs), minicomputers, main frame computers, network nodes, virtual reality or augmented reality devices and wearables, and distributed or multi-processing computing environments. While remote computing devices80are shown for clarity as being separate from cloud-based services90, cloud-based services90are implemented on collections of networked remote computing devices80.

Cloud-based services90are Internet-accessible services implemented on collections of networked remote computing devices80. Cloud-based services are typically accessed via application programming interfaces (APIs) which are software interfaces which provide access to computing services within the cloud-based service via API calls, which are pre-defined protocols for requesting a computing service and receiving the results of that computing service. While cloud-based services may comprise any type of computer processing or storage, three common categories of cloud-based services90are microservices91, cloud computing services92, and distributed computing services93.

Microservices91are collections of small, loosely coupled, and independently deployable computing services. Each microservice represents a specific computing functionality and runs as a separate process or container. Microservices promote the decomposition of complex applications into smaller, manageable services that can be developed, deployed, and scaled independently. These services communicate with each other through well-defined application programming interfaces (APIs), typically using lightweight protocols like HTTP, gRPC, or message queues such as Kafka. Microservices91can be combined to perform more complex processing tasks.

Cloud computing services92are delivery of computing resources and services over the Internet75from a remote location. Cloud computing services92provide additional computer hardware and storage on as-needed or subscription basis. Cloud computing services92can provide large amounts of scalable data storage, access to sophisticated software and powerful server-based processing, or entire computing infrastructures and platforms. For example, cloud computing services can provide virtualized computing resources such as virtual machines, storage, and networks, platforms for developing, running, and managing applications without the complexity of infrastructure management, and complete software applications over the Internet on a subscription basis.

Distributed computing services93provide large-scale processing using multiple interconnected computers or nodes to solve computational problems or perform tasks collectively. In distributed computing, the processing and storage capabilities of multiple machines are leveraged to work together as a unified system. Distributed computing services are designed to address problems that cannot be efficiently solved by a single computer or that require large-scale computational power. These services enable parallel processing, fault tolerance, and scalability by distributing tasks across multiple nodes.

Although described above as a physical device, computing device10can be a virtual computing device, in which case the functionality of the physical components herein described, such as processors20, system memory30, network interfaces40, and other like components can be provided by computer-executable instructions. Such computer-executable instructions can execute on a single physical computing device, or can be distributed across multiple physical computing devices, including being distributed across multiple physical computing devices in a dynamic manner such that the specific, physical computing devices hosting such computer-executable instructions can dynamically change over time depending upon need and availability. In the situation where computing device10is a virtualized device, the underlying physical computing devices hosting such a virtualized computing device can, themselves, comprise physical components analogous to those described above, and operating in a like manner. Furthermore, virtual computing devices can be utilized in multiple layers with one virtual computing device executing within the construct of another virtual computing device. Thus, computing device10may be either a physical computing device or a virtualized computing device within which computer-executable instructions can be executed in a manner consistent with their execution by a physical computing device. Similarly, terms referring to physical components of the computing device, as utilized herein, mean either those physical components or virtualizations thereof performing the same or equivalent functions.

As can now be appreciated, disclosed embodiments enable improved QR code generation and decoding by using multiple compression codebooks, including a proprietary codebook, to both increase capacity and provide security in an integrated solution. While examples of disclosed embodiment utilized QR codes, disclosed embodiments can be utilized with barcodes, and/or other types of optical codes.

The skilled person will be aware of a range of possible modifications of the various aspects described above. Accordingly, the present invention is defined by the claims and their equivalents.