Method and system for providing optical distortion information for vehicle glazing

Abstract

[0006] In one example, the method includes acquiring and analyzing optical characteristics of the vehicle glazing via at least one processor of a computing device, generating digital optical distortion information for the vehicle glazing based on the analysis results, generating identification information for the vehicle glazing, and associating the digital optical distortion information with the identification information.

Description

[Technical Field]

[0001] This application claims priority to U.S. Provisional Patent Applications Nos. 62 / 900,095 and 62 / 900,119, both filed September 13, 2019, entitled "Method and System for Providing Optical Distortion Information for Vehicle Glazing," all of which are incorporated herein by reference in their entireties.

[0002] The present disclosure generally relates to methods and systems for providing optical distortion information of glass products, such as vehicle glazing. In one aspect, the present disclosure relates to determining and selecting an appropriate or compatible information acquisition system for a vehicle based on at least optical quality information of the vehicle glazing. In another aspect, the present disclosure relates to correcting distortion in images acquired by an information acquisition system through the vehicle glazing. [Background technology]

[0003] Information acquisition systems installed in vehicles are becoming increasingly common to improve safety and comfort, for example, advanced driver assistance systems (ADAS) and autonomous driving modes. These systems include imaging systems, collision prevention systems, braking assistance systems, driver assistance systems, and autonomous driving systems, and use a variety of electronic sensors and cameras.

[0004] Electronic sensors and cameras associated with the information acquisition system can be mounted directly on the interior surface of the vehicle glazing or positioned near the vehicle glazing. The sensors and cameras can collect information about conditions outside the vehicle by emitting and / or detecting visible light, infrared light, near-infrared light, and / or laser radar through vehicle glazing made from a laminated glass substrate or a single glass substrate. For example, U.S. Patent No. 10,196,005 B2 generally discloses a camera system for an ADAS.

[0005] To prevent electronic sensors and cameras from being seen from outside the vehicle, an opaque enamel layer (e.g., a dark or black enamel print) can be printed on the inner surface S2 of the outer glass (first glass) substrate and / or the outer surface S4 of the inner glass (second glass) substrate of a vehicle laminated glazing, including the front and rear windshields. The opaque enamel print can be applied in addition to the opaque enamel print area around the periphery of the vehicle laminated glazing to mask the information acquisition system and provide an opaque enamel print opening area (camera opening) through which the information acquisition system can collect information. If the vehicle glazing is composed of a single pane of glass (such as a tempered rear windshield), the opaque enamel layer, along with the opaque enamel print opening area, can be printed on the outer surface S1 and / or the inner surface S2 of the tempered single pane of glass glazing.

[0006] Optical distortions can be unavoidably present in vehicle glazing and typically result from its manufacturing processes (such as a float process to prepare a flat glass substrate, a firing process for an opaque enamel print, and / or a bending process to obtain a curved glass substrate.) Such optical distortions in vehicle glazing can be observed along the opaque enamel print, including the aperture areas, resulting in distortions in the information (e.g., images) acquired by an information acquisition system.

[0007] The image processing device of the information acquisition system may have a calibration or correction system for distorted images acquired through the vehicle glazing. For example, U.S. Patent Application Publication No. 2012 / 0206601 generally discloses using an image correction device to acquire images with reduced distortion. Such image distortion correction systems are based on the assumption that each vehicle glazing has the same or very similar optical distortion distribution. However, even if the vehicle glazings are formed using the same process, each vehicle glazing may have a different optical distortion distribution pattern.

[0008] Furthermore, vehicle glazing with reduced optical distortion is required to minimize error sources in optical sensing systems. U.S. Patent Application Publication No. 2017 / 0190151 generally discloses a vehicle windshield having a smooth surface obtained by an additional glass polishing process. However, the additional polishing process may increase the manufacturing time and cost of the vehicle glazing. Furthermore, recent advances in image resolution in information acquisition systems require further reduction in optical distortion in vehicle glazing, which may make it difficult to meet the optical distortion level requirements for high-resolution or high-performance information acquisition systems.

[0009] Therefore, it is necessary to obtain the optical quality information of vehicle glazing and accordingly select the most appropriate and compatible information acquisition system to reduce the optical distortion caused by vehicle glazing. Furthermore, especially for semi-autonomous or fully autonomous vehicles, it is necessary to obtain information (images) with reduced distortion for each windshield and to properly calibrate the information acquisition system. For example, vehicles using autonomous driving technology make extensive use of optical sensors and rely on high image quality. Summary of the Invention

[0010] Among other features, the present disclosure relates to providing optical distortion information for vehicle glazing. One example method includes acquiring and analyzing optical characteristics of the vehicle glazing via at least one processor of an optical distortion determination system, generating digital optical distortion information for the vehicle glazing based on the analysis results, generating identification information for the vehicle glazing, and associating the digital optical distortion information with the identification information. The digital optical distortion information and the identification information may be transmitted to at least one computing system via a communications network. In one example, the at least one computing system may be a cloud-based computing server system configured to store the digital optical distortion information and the identification information.

[0011] The digital optical distortion information of the vehicle glazing may include data related to the optical properties of the vehicle glazing, a warp map of the vehicle glazing, or data related to the modulation transfer function (MTF) of the vehicle glazing. The identification information of the vehicle glazing may include at least one unique machine-readable code including at least one of a number and / or letter combination, a barcode, a quick response (QR) code, a passive or active radio frequency identification (RFID) tag, a near field communication (NFC) tracker, a Bluetooth low energy (BLE) beacon, or a Global System for Mobile Communications / Short Message Service (GSM / SMS) tag.

[0012] In one embodiment, the digital optical distortion information of the vehicle glazing, in association with the identification information, is downloaded from the cloud-based computing server system and used to determine and select an appropriate or compatible information acquisition system mounted near the vehicle glazing to acquire information through the vehicle glazing. In other embodiments, the method may further include calibrating, by the other computing device, an information acquisition system mounted near the vehicle glazing to acquire information through the vehicle glazing based at least on the digital optical distortion information.

[0013] The present disclosure further discloses a system for providing optical distortion information for vehicle glazing. An example system may include at least one processor configured to acquire and analyze optical characteristics of the vehicle glazing, generate digital optical distortion information for the vehicle glazing based on the analysis results, generate identification information for the vehicle glazing, and associate the digital optical distortion information with the identification information. In one embodiment, the at least one processor may be configured to transmit the digital optical distortion information and the identification information to at least one computing system via a communications network. The digital optical distortion information for the vehicle glazing may include at least data related to the optical characteristics of the vehicle glazing, a warp map for the vehicle glazing, or data related to the MTF for the vehicle glazing. The identification information for the vehicle glazing may include at least one unique machine-readable code including at least one of a combination of numbers and / or letters, a barcode, a QR code, a passive or active RFID tag, an NFC tracker, a BLE beacon, or a GSM / SMS tag.

[0014] In one example, the at least one computing device may be a cloud-based computing server system configured to store digital optical distortion information and identification information. The digital optical distortion information of the vehicle glazing may be downloaded from the cloud-based computing server system using the identification information. The digital optical distortion information may be used to determine and select an information acquisition system to be mounted near the vehicle glazing, where the information acquisition system is configured to acquire information through the vehicle glazing. In another example, the digital optical distortion information may be used to calibrate an information acquisition system mounted near the vehicle glazing and acquiring information through the vehicle glazing.

[0015] The present disclosure further discloses a non-transitory computer-readable medium including code that, when executed by a processor of a computing device, causes the processor to obtain and analyze optical characteristics of the vehicle glazing, generate digital optical distortion information for the vehicle glazing based on the analysis results, generate identification information for the vehicle glazing, and associate the digital optical distortion information with the identification information.

[0016] In one example, the non-transitory computer-readable medium may include code that causes a processor to transmit the digital optical distortion information and the identification information to at least one computing system over a communications network. The digital optical distortion information of the vehicle glazing may include at least data related to optical properties of the vehicle glazing, a warp map of the vehicle glazing, or data related to the MTF of the vehicle glazing. The identification information of the vehicle glazing may include at least one unique machine-readable code including at least one of a combination of numbers and / or letters, a barcode, a QR code, a passive or active RFID tag, an NFC tracker, a BLE beacon, or a GSM / SMS tag.

[0017] In one embodiment, the at least one computing system may be a cloud-based computing server system configured to store the digital optical distortion information and the identification information, and other computing devices may download the digital optical distortion information of the vehicle glazing from the cloud-based computing server system using the identification information.

[0018] In other examples, the non-transitory computer-readable medium may include code for selecting, by the other computing device, an information acquisition system mounted near the vehicle glazing to acquire information through the vehicle glazing based at least on the digital optical distortion information. In yet other examples, the non-transitory computer-readable medium may include code for calibrating, by the other computing device, an information acquisition system mounted near the vehicle glazing to acquire information through the vehicle glazing based at least on the digital optical distortion information.

[0019] The present disclosure further discloses a method for providing optical distortion information for vehicle glazing. The method may include, by a first computing device, acquiring and analyzing optical characteristics of the vehicle glazing, generating, by the first computing device, digital optical distortion information for the vehicle glazing based on results of the analysis, generating, by the first computing device, identification information for the vehicle glazing, and associating, by the first computing device, the digital optical distortion information with the identification information. The method may further include, by the first computing device, transmitting the digital optical distortion information and the identification information to a second computing device via a communications network, storing, by the second computing device, the digital optical distortion information and the identification information, downloading, by a third computing device, the digital optical distortion information from the second computing device using the identification information, and determining and selecting, by the third computing device, an information acquisition system mounted near the vehicle glazing to acquire information through the vehicle glazing based on at least the digital optical distortion information.

[0020] The present disclosure further discloses a system for providing optical distortion information for vehicle glazing. The system may include an optical distortion determination system including at least one processor configured to acquire and analyze optical characteristics of the vehicle glazing, generate digital optical distortion information for the vehicle glazing based on the analysis results, generate identification information for the vehicle glazing, associate the digital optical distortion information with the identification information, and transmit the digital optical distortion information and the identification information to at least one computing system via a communications network. The at least one computing system may be configured to store the digital optical distortion information and the identification information. The system may include a computing device configured to download the digital optical distortion information from the at least one computing system using the identification information, and determine and select, based on at least the digital optical distortion information, an information acquisition system mounted near the vehicle glazing to acquire information through the vehicle glazing.

[0021] In another example, the present disclosure discloses a method for providing optical distortion information for vehicle glazing. The method may include, by a first computing device, acquiring and analyzing optical characteristics of the vehicle glazing; generating, by the first computing device, digital optical distortion information for the vehicle glazing based on results of the analysis; generating, by the first computing device, identification information for the vehicle glazing; and associating, by the first computing device, the digital optical distortion information with the identification information. The method may further include, by the first computing device, transmitting the digital optical distortion information and the identification information to a second computing device via a communications network; storing, by the second computing device, the digital optical distortion information and the identification information; installing an information acquisition system near the vehicle glazing to acquire information through the vehicle glazing; downloading, by a third computing device, the digital optical distortion information from the second computing device using the identification information; and calibrating, by the third computing device, the information acquisition system based on at least the digital optical distortion information.

[0022] In another embodiment, the present disclosure discloses a system for providing optical distortion information for vehicle glazing. The system may include an optical distortion determination system including at least one processor configured to acquire and analyze optical characteristics of the vehicle glazing, generate digital optical distortion information for the vehicle glazing based on the analysis results, generate identification information for the vehicle glazing, associate the digital optical distortion information with the identification information, and transmit the digital optical distortion information and the identification information to at least one computing system via a communications network. The at least one computing system may be configured to store the digital optical distortion information and the identification information. An information acquisition system may be mounted near the vehicle glazing to acquire information through the vehicle glazing. A computing device of the system may be configured to download the digital optical distortion information from the at least one computing system using the identification information and calibrate the information acquisition system based at least on the digital optical distortion information.

[0023] In yet another embodiment, the present disclosure discloses a method for calibrating an information acquisition system. The method may include installing an information acquisition system near vehicle glazing to acquire information through the vehicle glazing, downloading, by a first computing device, digital optical distortion information of the vehicle glazing from a second computing device via a communications network using identification information of the vehicle glazing, and calibrating, by the first computing device, the information acquisition system based on at least the digital optical distortion information. The identification information of the vehicle glazing may include at least one unique machine-readable code associated with the digital optical distortion information.

[0024] The present disclosure further discloses a system for calibrating an information acquisition system. The system may include an information acquisition system mounted near the vehicle glazing to acquire information through the vehicle glazing, and a computing device configured to download digital optical distortion information of the vehicle glazing from at least one computing system via a communications network using identification information of the vehicle glazing, and calibrate the information acquisition system based on at least the digital optical distortion information. The identification information of the vehicle glazing may include at least one unique machine-readable code associated with the digital optical distortion information.

[0025] The present disclosure further discloses a method for determining and selecting an information acquisition system, the method including obtaining, by a computing device, identification information that uniquely identifies the vehicle glazing, receiving, by the computing device using the identification information, digital optical distortion information of the vehicle glazing, and determining and selecting, by the computing device based on at least the digital optical distortion information, an information acquisition system mounted near the vehicle glazing to acquire information through the vehicle glazing.

[0026] The vehicle glazing identification information may include at least one unique machine-readable code including at least one of a combination of numbers and / or letters, a barcode, a QR code, a passive or active RFID tag, an NFC tracker, a BLE beacon, or a GSM / SMS tag. In one embodiment, receiving the digital optical distortion information includes downloading, by the computing device, the vehicle glazing digital optical distortion information from another computing device over a communications network using the vehicle glazing identification information.

[0027] The present disclosure further provides a system for determining and selecting an information acquisition system. The system may include a computing device including a processor configured to acquire identification information uniquely identifying the vehicle glazing, use the identification information to receive digital optical distortion information of the vehicle glazing, and determine and select, based at least on the digital optical distortion information, an information acquisition system mounted near the vehicle glazing to acquire information through the vehicle glazing. The identification information of the vehicle glazing may include at least one unique machine-readable code including at least one of a combination of numbers and / or letters, a barcode, a QR code, a passive or active RFID tag, an NFC tracker, a BLE beacon, or a GSM / SMS tag. In one embodiment, the computing device may be configured to download the digital optical distortion information of the vehicle glazing from another computing device via a communication network using the identification information of the vehicle glazing.

[0028] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate one or more exemplary aspects of the present disclosure and, together with the detailed description, serve to explain the principles and implementations of the present disclosure. [Brief explanation of the drawings]

[0029] [Figure 1] 1 is a schematic diagram of a system for providing optical distortion information associated with glass products, such as laminated glazing for vehicles, according to an exemplary embodiment of the present disclosure. [Figure 2] 2 is a cross-sectional view of a laminated glazing for a vehicle taken along line AA' of FIG. 1 according to an exemplary embodiment of the present disclosure. [Figure 3] 1 is a schematic diagram of an optical distortion determination system for correcting distortion in an image acquired by an information acquisition system through vehicle glazing, according to an exemplary aspect of the present disclosure. [Figure 4] FIG. 1 illustrates an exemplary system for measuring optical distortion in vehicle glazing, according to an exemplary aspect of the present disclosure. [Figure 5]1 illustrates an exemplary method according to an exemplary aspect of the present disclosure. [Figure 6] 1 illustrates an exemplary method for providing optical distortion information for vehicle glazing, according to an exemplary aspect of the present disclosure. [Figure 7] 1 illustrates an exemplary method for correcting distortion in an image obtained by an information acquisition system through vehicle glazing, according to an exemplary aspect of the present disclosure. [Figure 8] 1 illustrates an exemplary method for calibrating an information acquisition system, according to an exemplary aspect of the present disclosure. [Figure 9] FIG. 1 illustrates an exemplary method for determining and selecting an information acquisition system to be installed in a vehicle, according to an exemplary aspect of the present disclosure. [Figure 10] 1 illustrates a light beam path through vehicle glazing. DETAILED DESCRIPTION OF THE INVENTION

[0030] In the following description, for purposes of explanation, specific details are set forth in order to facilitate an understanding of one or more aspects of the present disclosure. It may be apparent that many of the aspects described below can be practiced without the application of the specific design details described below in some or all instances.

[0031] 1 shows a schematic diagram of a system 100 for providing optical distortion information associated with a glass product 102 according to an embodiment of the present disclosure. The glass product 102 may generally include various types of glass substrates or films (e.g., annealed glass, heat-treated glass, heat-strengthened glass, and chemically strengthened glass) for automotive, residential, commercial, and architectural applications. The glass product 102 may have any applicable structure, such as monolithic glass, laminated glass, insulated glass, or wired, textured, or patterned glass structures.

[0032] When applied to an automobile, the system 100 may be used to provide optical quality information of the vehicle glazing 104 so that distortions caused by the vehicle glazing 104 in information (e.g., images) acquired by the vehicle information acquisition system 106 can be corrected. The vehicle information acquisition system 106 may include various electronic sensors and cameras mounted within the vehicle 108 near the vehicle glazing 104 and configured to monitor and detect a number of vehicle parameters and acquire images of objects outside the vehicle 108 through the vehicle glazing 104. Examples of sensors / cameras for the vehicle information acquisition system may include, but are not limited to, monocular and stereo cameras, rear cameras, ultrasonic, lidar, radar, infrared, passive infrared, thermal, time-of-flight (TOF), speed sensors, ambient light sensors, ultrasonic sensors, automotive microelectromechanical systems (MEMS) sensors, and global positioning systems (GPS). These sensors and cameras may be used in ADAS such as lane departure warning (LDW), forward collision warning (FCA), and traffic sign monitoring (TSM) sensor systems. Other vehicle information acquisition sensor systems may also be included, such as sensors for telematics and infotainment. The sensors and cameras 106 of these vehicle information acquisition systems may be located in various locations on the vehicle 108.

[0033] FIG. 2 shows a cross-sectional view of the vehicle laminated glazing 104 of FIG. 1 equipped with a vehicle information acquisition system 106 (e.g., a high-resolution camera or stereo camera 202) along line AA′. In this example, the camera 202 is positioned in a bracket 204 near the vehicle's rearview mirror and may be masked by an opaque enamel layer 206 printed on the inside surface of the vehicle glazing 104, which may be the vehicle's front windshield. An open area 208 (e.g., open space without opaque enamel print) is provided in the opaque enamel print 206 through which the camera 202 can detect conditions outside the vehicle 108. Optical distortions 210 in the glass substrate of the vehicle glazing 104 may be observed along the opaque enamel print 206 and / or within the open area 208, which may result in distortion of the information (image distortion) acquired by the information acquisition system 106 / 202.

[0034] Optical distortion can occur when a light beam from a point on an object passes through the vehicle glazing 104 and the light beam path is refracted, resulting in an angular deviation. The angular deviation is the difference between the angle of the incident ray and the angle of the exiting ray. FIG. 10 shows the light beam path where an incident ray 1002 enters the glazing 104 and exits the glazing 104 as an exiting ray 1004. The angle theta (θ) between the exiting ray 1004 and the incident ray 1002 is the angular deviation. The change in angular deviation can be related to the optical power or refractive power of the vehicle glazing 104. The angular deviation and refractive power can serve as measures of the optical distortion of the vehicle glazing 104.

[0035] To correct the optical distortion 210 or select an appropriate information acquisition system 106 affected by the optical distortion 210, the optical distortion determination system 110 may be configured to acquire and analyze the optical characteristics of each vehicle glazing 104, generate digital optical distortion information for each vehicle glazing 104 based on the analysis results, generate identification information for uniquely identifying each vehicle glazing 104, and associate the digital optical distortion information with the identification information. The digital optical distortion information and the identification information may be transmitted via the communications network 112 to at least one computing device (e.g., the computing server system 116 of FIG. 1 ) for storage and / or further analysis. This digital optical distortion information for each vehicle glazing 104 can be accessed and downloaded at any time and from anywhere by other computing systems or devices 118 located on the same or different communications network. In one example, when the vehicle laminate glazing 104 (e.g., windshield) is assembled to the vehicle body along with the optical sensors (e.g., digital camera 202), the identification information 316 of the vehicle glazing 104 shown in FIG. 3 is scanned by a calibration device (e.g., one of the computing systems or devices 118), and digital optical distortion information of the vehicle glazing 104 is retrieved from the computing server system 116 for calibration of the various optical sensors and correction of distortions caused by the vehicle glazing 104. In other examples, the identification information 316 may be scanned (by one of the computing systems or devices 118), and digital optical distortion information of the vehicle glazing 104 may be retrieved from the computing server system 116, in order to determine and select a suitable compatible camera system to be installed on the vehicle 108.

[0036] System 100 may include appropriate or necessary interface components (not shown) that provide various adapters, connectors, channels, and communication paths to facilitate the exchange of signals and data between the various hardware and software components of optical distortion determination system 110. It may also include any applications, peer devices, remote or local server systems / service providers, and additional database systems that may be available on the system or connected via a communications network and associated communications channels and protocols. A communications network (e.g., communications network 112) may refer to a geographically distributed collection of computing devices or data points interconnected by communications links and segments for exchanging signals and data. A protocol (e.g., protocols 114a, 114b, and 114c) may refer to a set of rules that define how computing devices and networks interact with each other, such as Frame Relay, Internet Protocol (IP), Transmission Control Protocol (TCP), User Datagram Protocol (UDP), and Hypertext Transfer Protocol (HTTP).Various types of communication networks may be used, including local area networks (LANs), wide area networks (WANs), cellular networks, overlay networks, software-defined networks (SDNs), packet data networks (such as the Internet), mobile phone networks (e.g., cellular networks such as 4G and 5G), plain old telephone (POTS) networks, wireless data networks (e.g., the Institute of Electrical and Electronics Engineers (IEEE) 802.11 family of standards known as Wi-Fi®, WiGig®, the IEEE 802.16 family of standards known as WiMax®), the IEEE 802.15.4 family of standards, the Long Term Evolution (LTE) family of standards, the Universal Mobile Telecommunications System (UMTS) family of standards, peer-to-peer (P2P) networks, virtual private networks (VPNs), Bluetooth, near field communications (NFC), or other suitable networks.

[0037] For example, system 100 may employ a cloud-based communications network 112 to provide computing services using shared resources. Cloud computing is Internet-based and involves computing resources being dynamically provisioned and allocated on demand to each connected computing device or other devices from a collection of resources available via a network or cloud. Cloud computing resources may include any type of resource, such as computing, storage, or networking. For example, cloud computing resources may include service devices (firewalls, deep packet inspectors, traffic monitors, load balancers, etc.), compute / processing devices (servers, central processing units (CPUs), graphics processing units (GPUs), random access memory, caches), and storage devices (network-attached storage, storage area network devices, hard disk drives, solid-state devices, etc.). Furthermore, these computing resources may be used to support virtual networks, virtual machines, databases, applications, etc.

[0038] Cloud computing resources accessible via communications network 112 may include private clouds, public clouds, and / or hybrid clouds. For example, a private cloud may be a cloud infrastructure operated by a company for its use, while a public cloud may refer to a cloud infrastructure that provides services and resources over a network for public use. In a hybrid cloud computing environment that uses a combination of on-premises private clouds and third-party public cloud services, with orchestration between the two platforms, data and applications may move between the private cloud and the public cloud for increased flexibility and deployment options.

[0039] According to one aspect of the present disclosure, the computing server system 116 and the devices 118 may be cloud-based and may include at least one of a personal computer, server, server farm, laptop, tablet, mobile device, smartphone, cellular device, media player, network-enabled printer, router, wireless access point, network appliance, storage system, gateway device, virtual or augmented reality device, or other suitable device deployed on the same or a different communication network as the optical distortion determination system 110. The computing server system 116 may be configured to provide functionality to the connected devices, such as storing information, sharing data or provisioning resources among multiple client devices, or performing computations for each connected client device.

[0040] Referring to FIG. 3 , the optical distortion determination system 110 of the system 100 may include at least one processor 302 configured to control and execute multiple modules, including a measurement module 304, an analysis module 306, an optical distortion information generation module 308, an identification generation module 310, and a transceiver module 312. As used herein, the terms “component” and “module” refer to an actual device, apparatus, or arrangement of components or modules configured using an application-specific integrated circuit (ASIC) or field-programmable gate array (FPGA), or a combination of hardware and software, such as a microprocessor system and a set of instructions for implementing the functionality of the component or module, where the set of instructions (when executed) transforms the microprocessor system into a dedicated device. A component or module may also be configured as a combination of the two, with certain functions facilitated solely by hardware and other functions facilitated by a combination of hardware and software. Each component or module may be implemented in a variety of suitable configurations and is not limited to the specific configurations illustrated herein.

[0041] The memory 314 associated with the processor 302 may be configured to store at least a portion of the information obtained by the optical distortion determination system 110. In one embodiment, the memory 314 may be a non-transitory machine-readable medium configured to store at least one set of data structures or instructions (e.g., software) embodying or utilized in at least one of the techniques or functions described herein. It should be understood that the term "non-transitory machine-readable medium" may include a single medium or multiple media (e.g., a centralized or distributed database and / or associated cache) configured to store at least one instruction. The term "machine-readable medium" may include any medium capable of storing, encoding, or carrying instructions for execution by all modules of the optical distortion determination system 110, causing those modules to perform at least one of the techniques of the present disclosure, or capable of storing, encoding, or carrying data structures used by or associated with such instructions. Non-limiting examples of machine-readable media may include solid-state memory, optical, and magnetic media. Specific examples of machine-readable media may include non-volatile memory such as semiconductor memory devices (e.g., Electrically Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM)), flash memory devices, magnetic disks such as internal hard disks and removable disks, magneto-optical disks, random access memory (RAM), solid-state drives (SSD), CD-ROMs, and DVD-ROM disks.

[0042] According to an aspect of the present application, the measurement module 304 is configured by the processor 302 of the optical distortion determination system 110 to measure parameters and / or characteristics related to the optical distortion 210 at a predetermined location on the vehicle glazing 104, such as the opaque print aperture area 208. In another example, the predetermined location is a central area of the vehicle windshield 104, where head-up display information is projected. An exemplary vehicle laminate glazing or windshield 104 may include at least two curved panes of glass laminated together with a polymer interlayer. The polymer interlayer may include any suitable material, such as polyvinyl butyral (PVB). When the laminate glazing is used with a head-up display device, the polymer interlayer in some examples may be a PVB interlayer having a wedge angle.

[0043] Specifically, the measurement module 304 may include multiple components and equipment configured to measure several parameters such as the optical (angular) deviation and optical power (also called dioptric power, refractive power, focusing power, or convergence power) of the vehicle glazing 104.

[0044] Referring to FIG. 4 , initially, the camera 408 may include a lens, an image chip, and a display screen 402 positioned at a distance within the focal point of the camera 408. The display screen 402 may include a calibration pattern 404, such as a slope or horizon line. The calibration pattern 404 may be permanently formed on the display screen 402, or may be projected onto the display screen 402, generated on the display screen 402 if the display screen 402 is an LCD monitor, or otherwise provided on the display screen. An image 410 of the calibration pattern 404 may be captured by the camera 408. The vehicle glazing 104 is then inserted between the camera 408 and the display screen 402, and the camera 408 captures a second image 412 with the vehicle glazing 104 in front of the camera 408, and changes in this second image 412 are compared to the image 410 formed before the insertion of the vehicle glazing 104 to determine optical deviations caused by the vehicle glazing 104. The display screen 402 displays the same calibration pattern 404 as the camera 408 captures each image 410, 412. The vehicle glazing 104 may be inserted at a predetermined insertion angle (i.e., a predetermined mounting angle relative to the vehicle body, such as 60.6 degrees). The change in the lateral displacement of the projected diagonal line from a similar line shown on the screen 402 may be a measure of the angular deviation. The change in the width of the projected horizontal line, particularly in the vertical direction, may be a measure of the optical power of the vehicle glazing 104. A line may be projected and measured in any desired direction, providing the optical power of the vehicle glazing 104 in a direction perpendicular to the measured line. Optical power is the degree to which a lens, mirror, or other optical system converges or diverges light. It can be defined as the reciprocal of the focal length of the convex / concave lens of the optical system being measured, usually expressed in millidiopters (mdpt), and can be positive or negative. Higher optical power corresponds to shorter focal lengths. When two or more thin lenses are placed together, the optical power of the combined lens is approximately equal to the sum of the optical powers of the individual lenses.Similarly, the optical power of a single lens is approximately equal to the sum of the optical powers of each of its surfaces.

[0045] FIG. 4 illustrates examples of distortions that may occur when the vehicle glazing 104 is presented before a calibration pattern 404. The calibration pattern 404 may include any type of pattern suitable for performing spatial or chromatic calibration (e.g., a checkerboard pattern including multiple checkerboard squares or a dot pattern including multiple open or closed circles). The calibration pattern 404 may include any type of test or calibration pattern, such as a geometric pattern or a random stochastic pattern. The calibration pattern 404 may be captured by a camera 408 to obtain an image 412 after the vehicle glazing 104 is inserted between the camera 408 and a display screen 402. Distortions present in such an image 412 may include spatial distortions (e.g., when visible pixels are not in expected locations within the field of view) and color distortions (e.g., when color values of visible pixels differ from expected values). For example, the checkerboard squares of the pattern 404 may shift and / or distort from their expected positions in the image 412 (e.g., spatial error). Furthermore, rather than the checkerboard squares appearing in black and white, some checkerboard squares in image 412 may appear in other colors, such as purple (eg, color error).

[0046] It should be noted that because the camera 202 is positioned at an angle and displacement within the vehicle, the camera 408 may be fully calibrated to ensure that any distortion in the image captured by the camera 408 is due to the vehicle glazing 104 and not errors associated with the camera itself. For example, camera calibration may include performing at least one of flat-field correction (e.g., ensuring that the intensity response of the camera is uniform across its field of view (FOV)), lens distortion correction (e.g., identifying and correcting for lens distortion), and pixel scaling (e.g., determining the relationship between pixel size on the camera image and pixel size in the source image).

[0047] The analysis module 306 may then be configured by the processor 302 of the optical distortion determination system 110 to analyze at least one image captured by the camera 408 to determine the deviation between the correct (physical) position of each position mark and its actual displayed position. In one aspect, at least some of the position marks may correspond to features of the calibration image (e.g., the center and corners of a calibration checkerboard square). The distortion information generation module 308 may be configured to generate a warp map, or vector field (Δx, Δy)(x, y), based on the analysis results of the module 306. Each vector in the vector field may represent the distortion effect caused by both the lens of the camera 408 and the vehicle glazing 104. By knowing the effect of the camera lens, a warp map related only to the vehicle glazing 104 may be calculated by the distortion information generation module 308.

[0048] Using the warp map of the vehicle glazing 104, local or global distortion information may be further determined by module 308. For example, an optical distortion map may be generated based on at least the warp map. The optical distortion map may be used to analyze the distribution of pixel position error values (e.g., vector magnitudes) throughout the generated vector field. The optical distortion map may be a histogram showing the frequency of pixel position errors (e.g., plotting the magnitude of the pixel position error against the frequency with which the error magnitude appears in the vector field). The optical distortion map may be used to analyze other attributes of the vector field (e.g., the direction of distortion).

[0049] In some embodiments, the optical distortion map may be represented as a contour optical power distribution map (measured in millidiopters mdpt) of a transmissive optical system in a predetermined region of the vehicle glazing 104. In particular embodiments, the optical power of horizontal optical distortion in the vehicle glazing 104 may be measured. The optical power distribution map may be determined using, without limitation, an ISRA Labscan-Screen 2D inspection device with optical filter setting parameters 3 / 2 / 0, corresponding to a physical length of 2 mm, and masking filter settings 6 / 5 / 5 / R, corresponding to a physical masking length of approximately 9 mm around the opaque black print at a predetermined installation angle of the vehicle glazing 104. Because inspection algorithms exhibit mathematical artifacts when calculating optical power values near opaque regions, the application of masking may be preferable. These artifacts may be hidden by a mask so as not to be confused with the optical power of the glass, rather than the physical properties of the glass. Furthermore, the optical power distribution map may be measured without the calibration pattern 404 if two line measurement cameras are used.

[0050] According to other aspects of the present disclosure, the optical distortion determination system 110 may be configured to calculate the modulation transfer function (MTF) of the vehicle glazing 104 using any suitable method, such as ISO 15529:2010, "Optics and photonics—Optical transfer function—Measurement principles for the modulation transfer function (MTF) of sampled imaging systems," (incorporated herein by reference). The MTF is a measure of the ability of an optical system to transfer various levels of detail from an object to an image (i.e., the sharpness of the optical system). The amount of detail in an image is defined by the resolution of the optical system, specified in line pairs per millimeter (lp / mm). A line pair contains one cycle of light and dark bars of the same width and has unity contrast. The MTF is a plot of contrast, measured in percent, against spatial frequency, measured in lp / mm. The MTF may be normalized to a value of 1 at zero spatial frequency (all white or black). Applications that depend on image integrity or resolution may utilize MTF as a measure of performance in important dimensions such as linewidth, pixel resolution, and retinal-sensor spacing. MTF is analogous to electrical frequency response, allowing for modeling of optical systems using linear systems theory. For example, an optical system containing multiple stages (i.e., lenses, film, and the human eye) may have a system MTF equal to the product of the MTFs of the individual stages, allowing characterization of the subsystems to measure overall optical system performance.

[0051] In one example, the measurement module 304, the analysis module 306, and the distortion information generation module 308 may use a slanted edge method to measure the MTF of the vehicle glazing 104. In one example, the optical resolution across a series of images of a slanted edge target captured by the camera 408 in a mounted position with and without the vehicle glazing 104 inserted in front of the camera 408 may be analyzed. An example of a slanted edge target may include a checkerboard with a title in the background and five low-contrast slanted edges in the foreground with surrounding gray patches. These images may be acquired across a range of slanted edge angles, contrasts, and noise levels (e.g., at five different positions on the edge and in the center) within the field of view of the camera 408. The optical resolution of these images may be used by the analysis module 306 and the distortion information generation module 308 to calculate the MTF of the vehicle glazing 104.

[0052] Additionally, the strain information generation module 308 may be configured to transform (e.g., filter, prune, reformat, aggregate, summarize, or compress) the digitized strain information of the vehicle glazing 104 into a format suitable for storage and / or further analysis on the cloud platform. The module 308 may alter at least a portion of the digitized strain information of the vehicle glazing 104 based on explicit or inferred requirements of the cloud computing device, user-defined transformation profiles that dictate how various categories of raw data pushed to the cloud are transformed, and / or contextual metadata that provides context for the raw data.

[0053] For example, module 308 may include one or more of a formatting component, a context component, an encryption component, a filter component, an aggregation component, and a compression component (not shown). The formatting component may be configured to convert any specified subset of the digitized distortion information of the vehicle glazing 104 from a first format to a second format according to the requirements of the cloud-based devices or systems 116, 118, thereby normalizing the digital distortion for collective analysis with data acquired from other, different data sources. For example, a cloud-based vehicle information acquisition and calibration system may require measured optical distortion data in a specific, common format so that dependencies and correlations between different data sets from different industry sources can be identified and analyzed. Thus, the formatting component of module 308 may convert a selected subset of the digital distortion information of the vehicle glazing 104 from an initial format to a required common format before uploading the digital distortion information to the cloud-based system 100. Alternatively, the digital distortion information of the vehicle glazing 104 may be reformatted by the computing systems 116, 118 using various cloud computing resources.

[0054] The context component of module 308 associates contextual metadata with the raw data acquired by the measurement module 304, such as a time / date stamp, a quality value, a location (e.g., geographic location) associated with the data, machine status at the time the data was generated, and other contextual information that may be used by the cloud-based systems 116, 118 in connection with cloud-side analysis.

[0055] Additionally, module 308 may include an encryption component configured to encrypt confidential or proprietary information contained in the digital distortion information of the vehicle glazing 104 before uploading to the computing server system 116. An aggregation component of module 308 may be configured to combine related data from multiple sources. For example, data obtained from multiple sensors of measurement module 304 may be identified and aggregated by the aggregation component into a single cloud upload packet. A compression component of module 308 may compress the data being uploaded to the cloud using any suitable data compression algorithm. This may include detecting and removing redundant data bits, truncating high precision bits, or other suitable compression operations.

[0056] According to some aspects of the present disclosure, the optical distortion determination system 110 may include an identification generation module 310 configured by the processor 302 to generate identification information 316 for data associated with each of the vehicle glazing 104. For example, at least one unique machine-readable code may be generated for each vehicle glazing 104 and associated with the vehicle glazing's 104 digital optical distortion information. Examples of machine-readable codes may include at least one of a number and / or letter combination, a barcode, a quick response (QR) code, a passive or active radio frequency identification (RFID) tag, a near field communication (NFC) tracker, a Bluetooth low energy (BLE) beacon, and / or a Global System for Mobile Communications / Short Message Service (GSM / SMS) tag. As shown in FIG. 3 , the identification information 316 may be provided on the opaque print area 206 or at least one primary viewing surface of the vehicle glazing. The identification information 316 may be created by any suitable printing (e.g., screen printing or laser printing) or by any suitable etching method (e.g., sandblasting or laser etching). In some embodiments, the identification information 316 may be a sticker on the exterior or interior surface of the vehicle glazing 104.

[0057] The transceiver module 312 may be configured by the processor 302 of the optical distortion determination system 110 to communicate various information and data with other computing systems and devices. For example, the transceiver module 312 may transmit the digital optical distortion information of the vehicle glazing 104 and its identification information 316 via the communications network 112 to the cloud-based computing server system 116 for storage or further analysis.

[0058] According to aspects of the present disclosure, the computing server system 116 may include multiple databases configured to perform various data storage operations, including content indexing, data deduplication, policy-driven data storage, data retrieval, data classification, data mining or search, data encryption and compression, and data migration within a cloud environment. The digital optical distortion information of the vehicle glazing 104 can be accessed and downloaded from anywhere, at any time, by another computing system 118 deployed in a cloud environment, for example. For example, the identification information 316 can be scanned by an end-user's computing device 118 to determine the most suitable / compatible camera system to install on the vehicle 108 with the vehicle glazing 104 from among many camera systems available on the market. In another example, the identification information 316 can be scanned by a standalone device or a device associated with the computing device 118 functioning as a calibration device / system when the vehicle laminate glazing 104 (e.g., windshield) is assembled to the vehicle body with the information acquisition system 106 (e.g., camera 202 in FIG. 2 ). The information acquisition system 106 itself may have calibration capabilities. A search query may then be generated by a scanning device and sent to the computing server system 116 for searching the database content index. Examples of scanners may include a wand scanner, a laser scanner, a charge-coupled device (CCD) scanner, a camera-based scanner, a video camera reader, a wide-field reader, and an omnidirectional barcode scanner. As a result, digital optical distortion information of the vehicle glazing 104 matching the identification information 316 may be accessed and downloaded from the computing server system 116. In one embodiment, such information may be used to calibrate the camera 202.In another embodiment, the computing device 118 evaluates the optical quality information of the vehicle glazing 104 based on the downloaded digital optical distortion information in order to determine and select an appropriate or compatible camera system to install on the vehicle 108 so that optical distortion in images captured by the camera system is minimized or eliminated.

[0059] Each information acquisition system 106 can be calibrated and corrected based on the digitized optical distortion information of the vehicle glazing 104 assembled to the vehicle body. The calibration and analysis methods can depend on the mechanisms of each specific information acquisition system 106 and on the digital optical distortion information of the vehicle glazing 104. Any suitable calibration and analysis method capable of processing at least the digital optical distortion information can be used to calibrate the information acquisition system and correct distorted images. For example, a warp correction process can be performed by shifting the coordinates of the camera images and interpolating subpixels of each image. Warp correction refers to the process of correcting images to undo the effects of geometric distortion caused by camera lenses found in fisheye and 360° devices. It is known that cameras with wide-angle lenses can have a field of view (horizontal or vertical) of up to approximately 180 degrees. When a camera captures an image through a wide-angle lens, such as a fisheye lens camera, the image is often rounded or distorted. Therefore, such images can be converted to flat images through a warp correction process. For example, but not by way of limitation, the non-patent document, "Computational Optical Distortion Correction Using Radial Basis Function-Based Mapping Methods," by Aaron Bauer et al., Optics Express, Vol. 20, No. 14, pp. 14906-20, which is incorporated herein by reference, generally discloses image warp correction methods.

[0060] As a result of the warp correction process performed based on the digital optical distortion information of the vehicle glazing 104, each information acquisition system 106 of the assembled vehicle may acquire corrected, undistorted information.

[0061] Additionally, the downloaded digital optical distortion information of the vehicle glazing 104 may be used to provide end users, including vehicle repairers or vehicle manufacturers, with information to understand the optical quality of the vehicle glazing 104 when selecting a vehicle camera system. Additionally, the computing server system 116 may include one or more databases that store digital optical distortion information of various vehicle glazing and / or glass products.

[0062] In one embodiment, the computing server system 116 may include multiple components configured to maintain (e.g., update, filter, prune, reformat, aggregate, summarize, or compress) uploaded digital distortion information for glass products (e.g., vehicle glazing 104) in a format suitable for storage and / or further analysis on a cloud platform. For example, the computing server system 116 may be configured to receive updated information or dates related to the optical quality of glass products from various data sources on the cloud platform. Upon receiving a request from a connected cloud device to retrieve corrected digital distortion information for a glass product, the computing server system 116 modifies at least a portion of the stored digital distortion information based on the explicit or inferred requirements of the requesting device or user, or based on user-defined transformation profiles that dictate how to transform various categories of raw data and / or contextual metadata that provides context for the raw data.

[0063] For example, the computing server system 116 may include one or more formatting components, context components, encryption components, filter components, aggregation components, and compression components (not shown). The formatting component may be configured to convert any specified subset of the stored digital strain information of the glass product from a first format to a second format, thereby normalizing the digital strain information for collective analysis with data obtained from other, different data sources. For example, an end user's computing device may require the measured optical strain data of the glass product in a specific, common format so that dependencies and correlations between different data sets from different industry sources can be identified and analyzed. Thus, the formatting component of the computing server system 116 may convert a selected subset of the digital strain information of the glass product from its native format to the required common format before transmitting it to the end user. Alternatively, the digital strain information may be reformatted by the computing server system 116 using various cloud computing resources.

[0064] The context component of the computing server system 116 may associate contextual metadata with the stored digital distortion information, such as time / date stamps, quality values, locations (e.g., geographic locations) associated with the data, machine status at the time of data generation, information related to updates or modifications to the stored information, and other contextual information, which may be used by the cloud-based systems 116, 118 in connection with cloud-side analysis.

[0065] Additionally, the computing server system 116 may include an encryption component configured to encrypt any confidential or proprietary information contained in all stored digital distortion information before transmitting it to other cloud-based devices. The aggregation component of the computing server system 116 may be configured to combine relevant data from multiple sources. For example, the computing server system 116 may retrieve, aggregate, and update data reflecting changes to the stored digital distortion information of glass products from trusted data sources. The compression component of the computing server system 116 may compress data relative to a selected data structure using any suitable data compression algorithm. This may include detecting and removing redundant data bits, truncating high precision bits, or other suitable compression operations.

[0066] The optical distortion information of various glass products stored by the computing server system 116 can serve as a data source for audits. For example, in the event of an exception or accident (e.g., in a self-driving car), this information can be a valuable source of information for documenting the liability of parties in a compensation claim.

[0067] Referring to FIG. 5 , a flowchart of a method 500 is shown according to an aspect of the present disclosure. Method 500 may be performed to provide optical distortion information of the vehicle glazing or to correct distortion of an image acquired by an information acquisition system through the vehicle glazing. Method 500 may include acquiring and analyzing optical characteristics of the vehicle glazing (502) via at least one processor of a computing device (e.g., optical distortion determination system 110 of FIG. 1 ) and generating digital optical distortion information of the vehicle glazing based on the analysis results (504). Method 500 may further include generating identification information for the vehicle glazing (506) and associating the digital optical distortion information with the identification information (508). In some examples, the identification information may be generated prior to acquiring and analyzing the optical characteristics of the vehicle glazing, and the digital optical distortion may be associated with identification information previously provided for the vehicle glazing. The digital optical distortion information and the identification information may be transmitted to at least one computing system via a communications network. In one embodiment, the at least one computing system may be a cloud-based computing server system configured to store digital optical distortion information and identification information for the vehicle glazing.

[0068] The digital optical distortion information of the vehicle glazing may include data related to the optical properties of the vehicle glazing, a warp map of the vehicle glazing, or data related to the MTF of the vehicle glazing. The identification information of the vehicle glazing may include at least one unique machine-readable code including at least one of a number and / or letter combination, a barcode, a QR code, a passive or active RFID tag, an NFC tracker, a BLE beacon, or a GSM / SMS tag. In one embodiment, the digital optical distortion information of the vehicle glazing may be downloaded from a cloud-based computing server system using the identification information and used to determine and select an acquisition system mounted near the vehicle glazing to acquire information through the vehicle glazing. Alternatively, the digital optical distortion information may be used to calibrate an acquisition system mounted near the vehicle glazing to acquire information through the vehicle glazing.

[0069] Referring to Figure 6, a flowchart of a method 600 for providing optical distortion information for vehicle glazing is shown according to an aspect of the present disclosure. Method 600 may include acquiring and analyzing (602) optical characteristics of the vehicle glazing by a first computing device (e.g., optical distortion determination system 110 of Figure 1), generating (604) digital optical distortion information for the vehicle glazing based on the analysis results by the first computing device. Method 600 may further include generating (606) identification information for the vehicle glazing by the first computing device, associating (608) the digital optical distortion information with the identification information by the first computing device, and transmitting (610) the digital optical distortion information and the identification information to a second computing device (e.g., computer server system 116 of Figure 1) via a communications network (e.g., communications network 112 of Figure 1). In some examples, the identification information may be generated prior to acquiring and analyzing the optical properties of the vehicle glazing, and the digital optical distortion may be associated with the identification information previously provided on the vehicle glazing. Alternatively, the digital optical distortion information and the identification information of the vehicle glazing may be stored in any suitable data storage device or system.

[0070] Further, method 600 may include storing (612) the digital optical distortion information and the identification information by the second computing device; downloading (614) the digital optical distortion information from the second computing device by a third computing device (e.g., computing system or device 118 of FIG. 1) using the identification information; and determining and selecting (616) by the third computing device, based at least on the digital optical distortion information, an information acquisition system to be mounted near the vehicle glazing and to acquire information through the vehicle glazing.

[0071] 7, a flowchart of a method 700 for correcting distortion in an image acquired by an information acquisition system through vehicle glazing is shown in accordance with an aspect of the present disclosure. Method 700 may include acquiring and analyzing (702) optical characteristics of the vehicle glazing by a first computing device (e.g., optical distortion determination system 110 of FIG. 1 ), generating (704) digital optical distortion information for the vehicle glazing based on the analysis results by the first computing device. Method 700 may further include generating (706) identification information for the vehicle glazing by the first computing device, associating (708) the digital optical distortion information with the identification information by the first computing device, and transmitting (710) the digital optical distortion information and the identification information to a second computing device (e.g., computer server system 116 of FIG. 1 ) via a communications network (e.g., communications network 112 of FIG. 1 ). In some examples, the identification information may be generated prior to acquiring and analyzing the optical properties of the vehicle glazing, and the digital optical distortion may be associated with the identification information previously provided on the vehicle glazing. Alternatively, the digital optical distortion information and the identification information of the vehicle glazing may be stored in any suitable data storage device or system.

[0072] Further, method 700 may include storing (712) the digital optical distortion information and identification information by the second computing device, installing (714) an information acquisition system near the vehicle glazing that acquires information through the vehicle glazing, downloading (716) the digital optical distortion information from the second computing device by a third computing device (e.g., computing system or device 118 of FIG. 1) using the identification information, and calibrating (718) the information acquisition system based at least on the digital optical distortion information by the third computing device.

[0073] Referring to FIG. 8 , a flowchart of a method 800 for calibrating an information acquisition system according to an aspect of the present disclosure is shown. Method 800 may include installing (802) an information acquisition system near the vehicle glazing to acquire information through the vehicle glazing. Method 800 may also include downloading (804), by a first computing device, digital optical distortion information from a second computing device over a communications network using identification information for the vehicle glazing. In one embodiment, the identification information for the vehicle glazing includes at least one unique machine-readable code associated with the digital optical distortion information. Method 800 may also include calibrating (806), by the first computing device, the information acquisition system based on at least the digital optical distortion information.

[0074] 9, a flowchart of a method 900 for determining and selecting an information acquisition system to be installed in a vehicle is shown according to an aspect of the present disclosure. Method 900 may include: acquiring, by a computing device, identification information that uniquely identifies the vehicle glazing (902); receiving, by the computing device, digital optical distortion information of the vehicle glazing using the identification information (904); and determining and selecting, by the computing device, based on at least the digital optical distortion information (906), an information acquisition system to be mounted near the vehicle glazing and to acquire information through the vehicle glazing.

[0075] The above description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the common principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Furthermore, the above description in connection with the drawings illustrates examples and does not represent the only examples within the scope of the appended claims that may be implemented.

[0076] Additionally, although elements of the described aspects and / or embodiments may be described or claimed in the singular, the plural is included unless limitation to the singular is explicitly stated. Moreover, all or a portion of any aspect and / or embodiment may be utilized with all or a portion of any other aspect and / or embodiment unless otherwise stated. Thus, the present disclosure is not limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. 1. A method for providing optical distortion information for an individual vehicle glazing installed on a vehicle, comprising: acquiring and analyzing optical properties of the vehicle glazing via at least one processor of the computing device; generating digital optical distortion information of the vehicle glazing based on the analysis results; generating identification information for the vehicle glazing, wherein the identification information uniquely identifies the vehicle glazing; Associating the digital optical distortion information with the identification information; providing identification information on the exterior and / or interior surfaces of each individual vehicle glazing; A method comprising:

2. The method of claim 1 , further comprising transmitting the digital optical distortion information and the identification information to at least one computing system over a communications network.

3. 2. The method of claim 1, wherein the digital optical distortion information of the vehicle glazing includes at least data related to optical properties of the vehicle glazing, a warp map of the vehicle glazing, or data related to a modulation transfer function (MTF) of the vehicle glazing.

4. 10. The method of claim 1, wherein the vehicle glazing identification information comprises at least one unique machine-readable code comprising at least one of a combination of numbers and / or letters, a barcode, a quick response (QR) code, a passive or active radio frequency identification (RFID) tag, a near field communication (NFC) tracker, a Bluetooth low energy (BLE) beacon, or a Global System for Mobile Communications / Short Message Service (GSM / SMS) tag.

5. the at least one computing system comprises a cloud-based computing server system; The method of claim 2 , further comprising storing the digital optical distortion information and the identification information by a cloud-based computing server system.

6. The method of claim 5 , further comprising downloading, by another computing device, the digital optical distortion information of the vehicle glazing from a cloud-based computing server system using the identification information.

7. The method of claim 1 , further comprising determining and selecting, by another computing device based on at least the digital optical distortion information, an information acquisition system to be mounted near the vehicle glazing and to acquire information through the vehicle glazing.

8. The method of claim 1 , further comprising calibrating, by another computing device, an information acquisition system mounted near the vehicle glazing and acquiring information through the vehicle glazing, based at least on the digital optical distortion information.

9. 1. A method for providing optical distortion information for an individual vehicle glazing installed on a vehicle, comprising: acquiring and analyzing optical properties of the vehicle glazing with a first computing device; generating, by the first computing device, digital optical distortion information of the vehicle glazing based on the analysis; generating, by a first computing device, identification information for the vehicle glazing, wherein the identification information uniquely identifies the vehicle glazing; associating, by the first computing device, the digital optical distortion information with identification information; transmitting, by a first computing device, the digital optical distortion information and the identification information to a second computing device over a communications network; storing, by a second computing device, the digital optical distortion information and the identification information; providing identification information on the exterior and / or interior surfaces of each individual vehicle glazing; scanning, with a third computing device, the identification information provided on the exterior or interior surface of each individual vehicle glazing and downloading the digital optical distortion information from the second computing device; determining and selecting, with a third computing device, an information acquisition system mounted near the vehicle glazing to acquire information through the vehicle glazing based on at least the digital optical distortion information; A method comprising:

10. 1. A method for providing optical distortion information for an individual vehicle glazing installed on a vehicle, comprising: acquiring and analyzing optical properties of the vehicle glazing with a first computing device; generating, by the first computing device, digital optical distortion information of the vehicle glazing based on the analysis; generating, by a first computing device, identification information for the vehicle glazing, wherein the identification information uniquely identifies the vehicle glazing; associating, by the first computing device, the digital optical distortion information with identification information; transmitting, by a first computing device, the digital optical distortion information and the identification information to a second computing device over a communications network; storing, by a second computing device, the digital optical distortion information and the identification information; providing identification information on the exterior and / or interior surfaces of each individual vehicle glazing; locating an information acquisition system near the vehicle glazing to acquire information through the vehicle glazing; scanning, with a third computing device, the identification information provided on the exterior or interior surface of each individual vehicle glazing and downloading the digital optical distortion information from the second computing device; calibrating, by a third computing device, the information acquisition system based on at least the digital optical distortion information; A method comprising:

11. 1. A system for providing optical distortion information for an individual vehicle glazing installed on a vehicle, comprising: an optical distortion determination system including at least one processor configured to acquire and analyze optical characteristics of the vehicle glazing, generate digital optical distortion information for the vehicle glazing based on the analysis results, generate identification information for the vehicle glazing provided on an exterior surface or an interior surface of each individual vehicle glazing, associate the digital optical distortion information with the identification information, and transmit the digital optical distortion information and the identification information to at least one computing system via a communications network, wherein the identification information uniquely identifies the vehicle glazing; wherein the at least one computing system is configured to store the digital optical distortion information and the identification information; an information acquisition system mounted near the vehicle glazing to acquire information through the vehicle glazing; a computing device configured to download digital optical distortion information from the at least one computing system by scanning identification information provided on an exterior surface or an interior surface of each individual vehicle glazing, and to calibrate an information acquisition system based on at least the digital optical distortion information; A system including:

12. 1. A method for calibrating an information acquisition system, comprising: locating an information acquisition system near the vehicle glazing to acquire information through each vehicle glazing attached to the vehicle; scanning, by a first computing device, vehicle glazing identification information provided on an exterior surface or an interior surface of each individual vehicle glazing, and downloading digital optical distortion information of the vehicle glazing from a second computing device via a communications network, wherein the identification information uniquely identifies the vehicle glazing; calibrating, by the first computing device, an information acquisition system based on at least the digital optical distortion information; A method comprising:

13. The method of claim 12 , wherein the vehicle glazing identification information comprises at least one unique machine-readable code associated with the digital optical distortion information.

14. 13. The method of claim 12, wherein the digital optical distortion information of the vehicle glazing includes at least data related to optical properties of the vehicle glazing, a warp map of the vehicle glazing, or data related to a modulation transfer function (MTF) of the vehicle glazing.

15. 14. The method of claim 13, wherein the vehicle glazing identification information comprises at least one unique machine-readable code comprising at least one of a combination of numbers and / or letters, a barcode, a quick response (QR) code, a passive or active radio frequency identification (RFID) tag, a near field communication (NFC) tracker, a Bluetooth low energy (BLE) beacon, or a Global System for Mobile communications / Short Message Service (GSM / SMS) tag.

16. The method of claim 12 , wherein the second computing device comprises at least one cloud-based computing server system configured to store the digital optical distortion information and the identification information.

17. 1. A method for determining and selecting an information acquisition system, comprising: obtaining, with a computing device, identification information that uniquely identifies each individual vehicle glazing to be installed on the vehicle, wherein the identification information is provided on an exterior surface or an interior surface of each of the individual vehicle glazing; scanning identification information provided on an exterior or interior surface of each individual vehicle glazing to receive, with said computing device, digital optical distortion information of the vehicle glazing; determining and selecting, by the computing device based on at least the digital optical distortion information, an information acquisition system to be mounted near the vehicle glazing and to acquire information through the vehicle glazing; A method comprising:

18. 20. The method of claim 17, wherein the vehicle glazing identification information comprises at least one unique machine-readable code comprising at least one of a combination of numbers and / or letters, a barcode, a quick response (QR) code, a passive or active radio frequency identification (RFID) tag, a near field communication (NFC) tracker, a Bluetooth low energy (BLE) beacon, or a Global System for Mobile communications / Short Message Service (GSM / SMS) tag.

19. 20. The method of claim 17, wherein the digital optical distortion information of the vehicle glazing includes at least data related to optical properties of the vehicle glazing, a warp map of the vehicle glazing, or data related to a modulation transfer function (MTF) of the vehicle glazing.

20. 20. The method of claim 17, wherein receiving the digital optical distortion information includes downloading, by the computing device, the digital optical distortion information of the vehicle glazing from another computing device via a communications network using identification information of the vehicle glazing.

21. 21. The method of claim 20, wherein the other computing device comprises a cloud-based computing server system configured to store the digital optical distortion information and the identification information.

22. An individual vehicle glazing to be attached to a vehicle, comprising: A glass substrate; at least one unique machine-readable code configured to associate with the digital optical distortion information of the vehicle glazing and provided on an exterior surface or an interior surface of each individual vehicle glazing, wherein the at least one unique machine-readable code uniquely identifies the vehicle glazing; Equipped with wherein the digital optical distortion information is stored in at least one computing system. Vehicle glazing.

23. 23. The vehicle glazing of claim 22, wherein the digital optical distortion information of the vehicle glazing includes at least data related to the optical properties of the vehicle glazing, a warp map of the vehicle glazing, or data related to a modulation transfer function (MTF) of the vehicle glazing.

24. 23. The vehicle glazing of claim 22, wherein the identification information of the vehicle glazing comprises at least one unique machine-readable code comprising at least one of a combination of numbers and / or letters, a barcode, a quick response (QR) code, a passive or active radio frequency identification (RFID) tag, a near field communication (NFC) tracker, a Bluetooth low energy (BLE) beacon, or a Global System for Mobile communications / Short Message Service (GSM / SMS) tag.

25. 23. The vehicle glazing of claim 22, wherein the digital optical distortion information is used to calibrate an information acquisition system mounted near the vehicle glazing and acquiring information through the vehicle glazing based at least on the digital optical distortion information.

26. 23. The vehicle glazing of claim 22, wherein the digital optical distortion information is used to determine and select an information acquisition system to be mounted near the vehicle glazing and acquire information through the vehicle glazing based at least on the digital optical distortion information.

27. 23. The vehicle glazing of claim 22, wherein the at least one computing system comprises at least one cloud-based computing server system configured to store the digital optical distortion information and the identification information.

Images