US20150009338A1 - Volume dimensioning system calibration systems and methods - Google Patents

Volume dimensioning system calibration systems and methods Download PDF

Info

Publication number
US20150009338A1
US20150009338A1 US14490989 US201414490989A US2015009338A1 US 20150009338 A1 US20150009338 A1 US 20150009338A1 US 14490989 US14490989 US 14490989 US 201414490989 A US201414490989 A US 201414490989A US 2015009338 A1 US2015009338 A1 US 2015009338A1
Authority
US
Grant status
Application
Patent type
Prior art keywords
distortion
volume dimensioning
system
dimensioning system
dimensional
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US14490989
Inventor
Franck Laffargue
Serge Thuries
H. Sprague Ackley
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Intermec IP Corp
Original Assignee
Intermec IP Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date

Links

Images

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N17/00Diagnosis, testing or measuring for television systems or their details
    • H04N17/002Diagnosis, testing or measuring for television systems or their details for television cameras
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01FMEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
    • G01F17/00Methods or apparatus for determining the capacity of containers or cavities, or the volume of solid bodies
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01FMEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
    • G01F25/00Testing or calibrating apparatus for measuring volume, volume flow or liquid level, or for metering by volume
    • G01F25/0084Testing or calibrating apparatus for measuring volume, volume flow or liquid level, or for metering by volume for measuring volume

Abstract

Various corporate, industry, and regulatory guidelines, best practices and standards are used in establishing acceptable levels of accuracy for volume dimensioning systems used in commerce. A volume dimensioning system can determine at least one distortion value that is indicative of an amount of distortion present in the system and responsive to the amount of distortion, autonomously after or adjust the units of accuracy of information reported by the system. Such alteration or adjustment of units of accuracy may be performed based on an assessment of the distortion relative to a number of distortion thresholds. Responsive to the assessment, the volume dimensioning system can adjust a unit of accuracy in a representation of volume dimensioning related information.

Description

    BACKGROUND
  • 1. Field
  • This disclosure generally relates to volume dimensioning systems, and particularly to systems and methods useful in the promoting compliance with governmental or industry standard calibration guidelines.
  • 2. Description of the Related Art
  • Volume dimensioning systems are useful for providing dimensional and/or volumetric information related to three-dimensional objects. The objects may, for example take the form of parcels or packages intended for transit via a carrier (e.g., courier) or other items intended for transit. Dimensional and/or volumetric information is useful for example, in providing users with accurate shipping rates based on the actual size and/or volume of the object being shipped. Dimensional and/or volumetric information may be used by the carrier in selecting and scheduling appropriately sized vehicles and/or delivery routes. The ready availability of dimensional and/or volumetric information for all objects within a carrier's network assists the carrier in ensuring optimal use of available space in the many different vehicles and containers used in local, interstate, and international shipping.
  • Such may be of particular significant in today's economy where many businesses rely on “just in time” manufacturing. Typically, every supplier in the supply chain must be able to ship necessary components or resources on demand or with very little lead time. Thus, efficient handling of cargo is required. It does a supplier no good to have the desired goods on hand, if the supplier cannot readily ship the desired goods.
  • Automating volume dimensioning can speed parcel intake, improve the overall level of billing accuracy, and increase the efficiency of cargo handling. Unfortunately, parcels are not confined to a standard size or shape, and may, in fact, have virtually any size or shape. Additionally, parcels may also have specialized shipping and/or handling instructions (e.g., fragile, this side up) that must be followed during shipping or handling to protect the objects during shipping.
  • Volume dimensioning devices are used throughout the package delivery and carriage industry to provide a rapid way of measuring the overall dimensions of an object and, in some instances, to provide shipping rates for the object based on one or more classes of service. Historically, shipping rates were principally a function of an object's weight—heavier objects were assigned higher shipping costs than lighter objects. However, such a costing system failed to appreciate that volume the volume occupied by an object also impacted shipping costs since vehicles were not just limited in gross vehicle weight, but internal volume as well. As a consequence shippers began establishing shipping rates using both volume and weight as factors considered in determining the ultimate shipping rate charged to a customer.
  • The concept of volume dimensioning factors the shipping volume of an object into the overall shipping cost of an object. Thus, objects having a relatively light weight but a relatively large physical volume may have a shipping cost that exceeds the shipping cost of a physically smaller, but heavier, object. The use of volume in determining shipping costs increased the labor associated with package intake, since objects could no longer simply be weighed and a cost assigned. Instead, to accurately obtain a volume dimension, multiple dimensional measurements were taken and used to determine the volume of the object. Once the volume is determined, a shipping cost is assigned based on the measured volume and/or weight of the object. Thus, the shipping cost charged a customer is a function of the weight of an object, the volume occupied by the object, or both the weight of and the volume occupied by the object. Automated volume dimensioning systems have replaced the laborious and error prone derivation of an object's volume by manually obtaining multiple linear dimensions (e.g., the length, width, height, girth, etc.) of an object. The accuracy of a quoted shipping rate is thus dependent upon the accuracy with which an object can be dimensioned using a volume dimensioning system.
  • There exists a need for new dimensioning systems that may accurately perform volume dimensioning of objects including parcels and packages as well as other objects.
  • BRIEF SUMMARY
  • The Applicants have developed systems and methods useful for adjusting the reported or displayed dimensional measurement accuracy and consequently the reported or displayed shipping or cartage rate obtained using dimensional or volumetric data supplied by the volume dimensioning system. The systems and methods described herein take into consideration the level of distortion (e.g., dimensional distortion, optical distortion, etc.) present in the image data provided by such automated volume dimensioning systems. In some instances, the system adjusts a dimensional accuracy of a representation of volume dimensioning information (e.g., dimensions, cost based on the measured distortion present in the volume dimensioning system). Such may ensure that the dimensional and shipping cost data generated by the system is determined using the finest units of accuracy achievable given the current system operational parameters to reliably provide the most accurate shipping or cartage costs. Such systems and methods can be used to promote or facilitate volume dimensioning system compliance with corporate, industry, or regulatory standards, best practices, or guidelines, for example National Institute of Standards (NIST) Handbook 44-2012 Chapter 5.58—“Multiple Dimension Measuring Devices”.
  • The systems and methods disclosed herein also facilitate the ongoing, operationally transparent, calibration of volume dimensioning systems. Such ongoing calibrations provide system users and consumers with a degree of confidence in the dimensional and shipping cost data provided by the volume dimensioning system and also provide an early indication that the system calibration can no longer be brought into compliance with corporate, industry, or regulatory standards, best practices, or guidelines.
  • A volume dimensioning system may be summarized as including at least one image sensor that provides image data representative of a number of images of a field of view of the at least one image sensor; and a control subsystem communicatively coupled to the at least one image sensor to receive the image data therefrom, the control subsystem including at least one nontransitory storage medium and at least one processor, the at least one nontransitory storage medium which stores at least one of information or processor executable instructions; and the at least one processor which: determines at least one distortion value indicative of an amount of distortion in the images based at least in part on at least a portion of a calibration pattern which appears in the field of view of the at least one image sensor in at least a portion of some of the images, the calibration pattern having a set of defined characteristics; assesses the at least one distortion value relative to a number of distortion threshold values; and adjusts a unit of accuracy in a representation of volume dimensioning related information based at least in part on the assessment of the at least one distortion value relative to the distortion threshold values.
  • The at least one processor may determine the at least one distortion value as at least one set of optical distortion values and at least one set of dimensional distortion values, the set of optical distortion values representative of an optical contribution to distortion in the image data and the set of dimensional distortion values representative of a dimensional contribution to distortion in the image data. The at least one processor may assess the at least one distortion value relative to a recalibration threshold value that represents distortion correctable via a self recalibration by the volume dimensioning system. The at least one processor may assess the at least one distortion value relative to a service required threshold value that represents distortion that can only be corrected via a servicing of the volume dimensioning system by a service technician. The at least one processor may adjust the unit of accuracy in the representation of volume dimensioning related information in response to an assessment that the at least one distortion value exceeds the recalibration threshold value and is below the service required threshold value. Responsive to the determination that the at least one distortion value is less than the recalibration threshold value, the at least one processor may recalibrate the volume dimensioning system to a fine unit of accuracy; and wherein responsive to the determination that the at least one distortion value exceeds the recalibration threshold value and is below the service required threshold value, the at least one processor may recalibrate the volume dimensioning system to a coarse unit of accuracy. The processor may further produce an alert in response to an assessment that the at least one distortion value exceeds the service required threshold value. The processor may further determine at least one of a set of calculated optical distortion correction factors or a set of calculated dimensional correction factors in response to an assessment that the at least one distortion value is within the recalibration threshold value and wherein the processor may further apply at least one of the set of calculated optical distortion correction factors or the set of calculated dimensional correction factors to the image data in determining the volume dimensioning related information. The processor may adjust a decimal place represented to adjust the unit of accuracy in the representation of volume dimensioning related information. The processor may adjust a dimensional unit of measurement represented to adjust the unit of accuracy in the representation of volume dimensioning related information. The processor may adjust a unit of currency represented to adjust the unit of accuracy in the representation of volume dimensioning related information. The volume dimensioning system may further include an illumination subsystem communicably coupled to the control subsystem, the illumination subsystem to at least partially illuminate the calibration pattern. The volume dimensioning system may further include a support structure to receive at least the at least one image sensor such that when the at least one image sensor is received by the support structure at least a portion of the pattern is within a field of view of the at least one image sensor. The system may be fixed or hand held. The at least one distortion value may be associated with at least one of data indicative of a date or data indicative of a time and wherein the at least one distortion value and the respective associated data indicative of a date or data indicative of a time may be stored in the non-transitory storage medium.
  • A volume dimensioning method may be summarized as including receiving by at least one dimensioning system processor image data representative of a number of images in a field of view of at least one image sensor; determining by the at least one dimensioning system processor at least one distortion value indicative of an amount of distortion in the images based at least in part on at least a portion of a calibration pattern which appears in the field of view of the at least one image sensor in at least some of the images, the calibration pattern having a set of defined characteristics; assessing by the at least one dimensioning system processor the at least one distortion value relative to a number of distortion threshold values stored in a non-transitory storage medium communicably coupled to the at least one dimensioning system processor; and adjusting by the at least one dimensioning system processor a unit of accuracy in a representation of volume dimensioning related information based at least in part on the assessment of the at least one distortion value relative to the distortion threshold values.
  • Assessing by the at least one dimensioning system processor the at least one distortion value relative to a number of distortion threshold values may include determining the at least one distortion value as at least one set of optical distortion values and at least one set of dimensional distortion values; wherein the set of optical distortion values represents an optical contribution to distortion in the image data; and wherein the set of dimensional distortion values represent a dimensional contribution to distortion in the image data. Assessing by the at least one dimensioning system processor the at least one distortion value relative to a number of distortion threshold values may include assessing the at least one distortion value relative to a recalibration threshold value representing distortion correctable via a recalibration of the volume dimensioning system. Assessing by the at least one dimensioning system processor the at least one distortion value relative to a number of distortion threshold values may include assessing the at least one distortion value relative to a service required threshold value representing distortion not correctable via recalibration of the volume dimensioning system. Assessing by the at least one dimensioning system processor the at least one distortion value relative to a number of distortion threshold values may include assessing the at least one distortion value to fall between the recalibration threshold value and the service required threshold value, representing distortion correctable via a recalibration of the volume dimensioning system. Adjusting a unit of accuracy in a representation of volume dimensioning related information based at least in part on the assessment of the at least one distortion value relative to the distortion threshold values may include recalibrating the volume dimensioning system to a fine unit of accuracy responsive to an assessment that the at least one distortion value relative to the recalibration threshold value indicates a distortion correctable via recalibration; recalibrating the volume dimensioning system to a coarse unit of accuracy responsive to an assessment that the at least one distortion value falls between the recalibration threshold value and the service required threshold value; and generating an alert responsive to an assessment that the at least one distortion value relative to the service required threshold value indicates a distortion not correctable via recalibration. The volume dimensioning method may further include, responsive to the determination that the at least one distortion value is within the recalibration threshold value, determining by the at least one dimensioning system processor at least one of a set of calculated optical distortion correction factors or a set of calculated dimensional correction factors; and applying at least one of the set of calculated optical distortion correction factors or the set of calculated dimensional correction factors to the image data in determining the volume dimensioning related information.
  • A volume dimensioning controller may be summarized as including at least one input communicably coupled to at least one processor, the at least one input to receive image data representative of a number of images of a field of view of at least one image sensor; and at least one processor communicably coupled to the at least one non-transitory storage medium, the at least one processor to: determine at least one distortion value indicative of an amount of distortion in the images based at least in part on at least a portion of a calibration pattern which appears in the field of view of the at least one image sensor in at least some of the images, the calibration pattern having a set of defined characteristics; assess the at least one distortion value relative to a number of distortion threshold values stored in the non-transitory storage medium; and adjust a unit of accuracy in a representation of volume dimensioning related information based at least in part on the assessment of the at least one distortion value relative to the distortion threshold values.
  • The at least one processor may determine the at least one distortion value as at least one set of optical distortion values and at least one set of dimensional distortion values, the set of optical distortion values representative of an optical contribution to distortion in the image data and the set of dimensional distortion values representative of a dimensional contribution to distortion in the image data. The at least one processor may assess the at least one distortion value relative to a recalibration threshold value that represents distortion correctable via a self recalibration by the volume dimensioning system. The at least one processor may assess the at least one distortion value relative to a service required threshold value that represents distortion that can only be corrected via a servicing of the volume dimensioning system by a service technician. The at least one processor may adjust the unit of accuracy in the representation of volume dimensioning related information in response to an assessment that the at least one distortion value exceeds the recalibration threshold value and is below the service required threshold value. Responsive to the determination that the at least one distortion value is less than the recalibration threshold value, the at least one processor may recalibrate the volume dimensioning system to a fine unit of accuracy; and wherein responsive to the determination that the at least one distortion value exceeds the recalibration threshold value and is below the service required threshold value, the at least one processor may recalibrate the volume dimensioning system to a coarse unit of accuracy.
  • BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)
  • In the drawings, identical reference numbers identify similar elements or acts. The sizes and relative positions of elements in the drawings are not necessarily drawn to scale. For example, the shapes of various elements and angles are not drawn to scale, and some of these elements are arbitrarily enlarged and positioned to improve drawing legibility. Further, the particular shapes of the elements as drawn, are not intended to convey any information regarding the actual shape of the particular elements, and have been solely selected for ease of recognition in the drawings.
  • FIG. 1 is a block diagram of an example volume dimensioning system, according to one illustrated embodiment.
  • FIG. 2A is a perspective view of a volume dimensioning system displaying one example of the effects of optical distortion, according to one illustrative embodiment.
  • FIG. 2B is a perspective view of a volume dimensioning system displaying one example of the effects of dimensional distortion, according to one illustrative embodiment.
  • FIG. 3 is a perspective view of an example image sensor received by a stand member and having a reference pattern disposed in at least a portion of the field of view of the image sensor, according to one illustrative embodiment.
  • FIG. 4A is a perspective view of an example volume dimensioning system reporting dimensions to a first unit of accuracy based at least in part on at least one determined distortion value, according to one illustrative embodiment.
  • FIG. 4B is a perspective view of an example volume dimensioning system reporting dimensions to a second unit of based at least in part on at least one determined distortion value, according to one illustrative embodiment.
  • FIG. 5 is a flow diagram showing a high level method of operation of a volume dimensioning system including the determination of at least one distortion value and one or more sets of distortion correction factors, according to one illustrated embodiment.
  • FIG. 6 is a flow diagram showing a low level method of operation of a volume dimensioning system including an assessment of at least one set of optical distortion values and at least one set of dimensional distortion values, according to one illustrative embodiment.
  • FIG. 7 is a flow diagram showing a high level method of operation of a volume dimensioning system incorporating the storage and reporting of historical distortion values or correction factors, according to one illustrated embodiment.
  • DETAILED DESCRIPTION
  • In the following description, certain specific details are set forth in order to provide a thorough understanding of various disclosed embodiments. However, one skilled in the relevant art will recognize that embodiments may be practiced without one or more of these specific details, or with other methods, components, materials, etc. In other instances, well-known structures associated with volume dimensioning systems, correction of optical and dimensional distortion in single and compound lens devices, wired, wireless and optical communications systems, and/or automatic data collection (ADC) readers have not been shown or described in detail to avoid unnecessarily obscuring descriptions of the embodiments.
  • Unless the context requires otherwise, throughout the specification and claims which follow, the word “comprise” and variations thereof, such as, “comprises” and “comprising” are to be construed in an open, inclusive sense, that is as “including, but not limited to.”
  • Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
  • As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the content clearly dictates otherwise. It should also be noted that the term “or” is generally employed in its broadest sense, that is as meaning “and/or” unless the content clearly dictates otherwise.
  • The headings and Abstract of the Disclosure provided herein are for convenience only and do not interpret the scope or meaning of the embodiments.
  • FIG. 1 shows a volume dimensioning system 100, according to one illustrated embodiment.
  • The volume dimensioning system 100 includes a camera subsystem 102 and control subsystem 104. The volume dimensioning system 100 optionally includes one or more of: a user interface (UI) subsystem 106; a communications subsystem 108 and/or an automatic data collection (ADC) subsystem 110.
  • The various subsystems 102-110 may be communicatively coupled by one or more couplers (e.g., electrically conductive paths, wires, optical fibers), for example via one or more buses 112 (only one shown) and/or control lines 114 (only two shown). The buses 112, or other couplers, may include power buses or lines, data buses, instruction buses, address buses, etc., which allow operation of the various subsystems 102-110 and interaction or intercommunication therebetween. The various subsystems 102-110 are each discussed in turn, below. While various individual components are generally easily categorizable into one or another of the subsystems, some components may be optionally implemented in one or two or more of the subsystems 102-110. Thus, some components may be illustrated in FIG. 1 as part of two or more subsystems 102-110. Alternatively, some of the components illustrated in FIG. 1 as discrete components in two or more subsystems 102-110 may be present as a single component within a single subsystem 102-110.
  • The camera subsystem 102 includes an optional illumination subsystem 116 to provide or emit electromagnetic illumination outward from the volume dimensioning system 100 into an environment containing a target object (not shown in FIG. 1) and a sensor subsystem 118 to receive illumination returned (e.g., reflected, fluoresced) from at least the target object.
  • The illumination subsystem 116 includes an illumination device 120. The illumination device 120 may take the form of an array of individually addressable or controllable elements, and also may have a variety of forms capable of producing electromagnetic energy having a spectral content useful for image collection by the sensor subsystem 118. The illumination subsystem 116 will typically include an illumination driver 122 which is coupled to control the individually addressable or controllable elements of the illumination device 120. Alternatively, the illumination device 120 may be controlled directly by the control subsystem 104 without the use of a dedicated illumination driver 122.
  • In particular, the illumination device 120 is controlled to produce or emit modulated electromagnetic energy in a number of wavelengths or ranges of wavelengths. For instance, illumination may include electromagnetic energy of wavelengths in an optical range or portion of the electromagnetic spectrum including wavelengths in a human-visible range or portion (e.g., approximately 390 nm-750 nm) and/or wavelengths in the near-infrared (NIR) (e.g., approximately 750 nm-1400 nm) or infrared (e.g., approximately 750 nm-1 mm) portions and/or the near-ultraviolet (NUV) (e.g., approximately 400 nm-300 nm) or ultraviolet (e.g., approximately 400 nm-122 nm) portions of the electromagnetic spectrum. The particular wavelengths are exemplary and not meant to be limiting. Other wavelengths of electromagnetic energy may be employed.
  • The sensor subsystem 118 includes an image transducer or image sensor 124, typically a two-dimensional array of photo-sensitive or photo-responsive elements, for instance a two-dimensional array of photodiodes or a two-dimensional array of charge coupled devices (CODs). The sensor subsystem 118 may optionally include a buffer 125 communicatively coupled to the image sensor 124 to receive or otherwise acquire image data measured, captured or otherwise sensed or acquired by the image sensor 124. The buffer 125 may comprise a non-transitory storage medium capable of temporarily storing image data until the image data is further processed by the volume dimensioning system 100. In at least some instances, the sensor subsystem 118 can include one or more sensors, systems, or devices for reading or scanning one or more optical machine readable symbols or radio frequency machine readable devices such as radio frequency identification (RFID) tags. Some possibly suitable systems are described in U.S. patent application Ser. No. 12/638,616, filed Dec. 15, 2009 and published as U.S. patent application publication no. US 2010-0220894, which is incorporated by reference herein in its entirety to the extent the subject matter therein does not contradict or conflict with the subject matter of the instant application.
  • The sensor subsystem may further include one or more distance determination sensors (not shown in FIG. 1) useful in measuring or otherwise determining the distance between the volume dimensioning system 100 and one or more objects within the field of view of the image sensor 124. Such distance detection sensors can include one or more time-of-flight sensors, sonar sensors, or similar. In at least some instances the image sensor 124 may advantageously include one or more distance determination features, for example parallax measured across all or a portion of the image sensor 124.
  • The control subsystem 104 includes one or more processors 126, for example one or more microprocessors (one shown) 126 a, digital signal processors (DSP—one shown) 126 b, application specific integrated circuits (ASIC), programmable gate arrays (PGA), programmable logic controllers (PLC), or the like. While the DSP 126 b may be considered or provided or packaged as part of the control subsystem 104, the DSP 126 b may in some applications be may be considered or provided or packaged as part of the camera subsystem 102.
  • The control subsystem 104 includes at least one non-transitory storage media 130. For example, the control subsystem 104 may include nonvolatile memory, for instance read only memory (ROM) or NAND Flash memory 130 a. Additionally or alternatively, all or a portion of the at least one non-transitory storage media 130 may include volatile memory, for instance dynamic random access memory (ROM) 130 b. The at least one non-transitory storage media 130 may store one or more computer- or processor-executable instructions or data, useful in causing the microprocessor, DSP or other microcontroller to perform dimensional functions, volumetric functions, volume dimensioning functions, shipping cost calculation functions, or combinations thereof, for example by executing the various methods described herein.
  • In some instances the at least one non-transitory storage media 130 may store or otherwise retain a number of distortion values indicative of the quantitative or qualitative degree of distortion present in the image data provided by the volume dimensioning system 100. Such distortion may be present as an optical distortion, a dimensional distortion, or any other type of distortion including chromatic distortion that causes deviations between the image data and the scene within the field of view of the sensor subsystem 118. In yet other instances, the at least one non-transitory storage media 130 may store or otherwise retain a plurality of historical distortion values, such as a plurality of optical or dimensional distortion values that permit the historical trending of the optical or dimensional distortion values. Such historical data can also play a helpful role in demonstrating an ongoing compliance with one or more corporate, industry, or regulatory guidelines, best practices, or standards. In at least some instances, the at least one non-transitory storage media 130 can store or otherwise retain one or more sets of distortion correction factors useful in reducing or eliminating one or more forms of distortion present in the image data provided by the volume dimensioning system 100.
  • The optional UI subsystem 106 may include one or more user interface components which provide information to a user or allow a user to input information or control operation of the volume dimensioning system 100.
  • For example, the UI subsystem 106 may include a display 132 to visually provide information or control elements to the user. The display 132 may, for example, take the form of a liquid crystal display (LCD) panel. The display 132 may, for example, take the form of a touch sensitive display, allowing the display of user selectable icons (e.g., virtual keypad or keyboard, graphical user interface or GUI elements) in addition to the display of information. The display 132 may be coupled to the control subsystem 104 via a display driver 134 or similar component. The display driver 134 may control the presentation of information and icons on the display 132. The display driver 134 may additionally process signals indicative of user inputs made via the display 132.
  • The UI subsystem 106 may optionally include a physical keypad or keyboard 136, which allows a user to enter data and instructions or commands. The physical keypad or keyboard 136 may be integral to a housing (not shown) of the volume dimensioning system 100. Alternatively, the optional physical keypad or keyboard 136 may be separate from the housing, communicatively coupled thereto via a wireless connection or wired connection for instance a Universal Serial Bus (USB®) interface.
  • The UI subsystem 106 may optionally include a speaker 138 to provide audible information, cues and/or alerts to a user. The UI subsystem 106 may optionally include a microphone 140 to receive spoken information, instructions or commands from a user.
  • The communications subsystem 108 may include one or more wireless communications components and/or one or more wired communications components to allow communications with devices external from the volume dimensioning system 100.
  • For example the communications subsystem 108 may include one or more radios (e.g., transmitters, receivers, transceivers) 142 and associated antenna(s) 144. The radio(s) 142 may take any of a large variety of forms using any of a large variety of communications protocols, for instance IEEE 802.11, including WI-FI®, BLUETOOTH®, various cellular protocols for instance CDMA, TDMA, EDGE®, 3G, 4G, GSM.
  • Also for example, the communications subsystem 108 may include one or more communications ports 146. The communications ports 146 may take any of a large variety of forms, for example wired communications ports for instance ETHERNET® ports, USB® ports, FIREWIRE® ports, THUNDERBOLT® ports, etc. The communications ports 146 may even take the form of wireless ports, for instance an optical or radio frequency transceiver.
  • The ADC subsystem 110 may include one or more ADC readers to perform automatic data collection activities, for instance with respect to a target object.
  • For example, the ADC subsystem 110 may include a radio frequency identification (RFID) reader or interrogator 148 and associated antenna 150 to wireless read and/or write to wireless transponders (e.g., RFID tags or transponders) (not shown). Any of a large variety of RFID readers or interrogators 148 may be employed, including fixed or stationary RFID readers or portable or handheld RFID readers. RFID reader(s) 148 may be used to read information from a transponder physically or at least proximally associated with a target object (not shown in FIG. 1). Such information may, for instance, include recipient information including an address and/or telephone number, sender information including an address and/or telephone number, specific handling instructions (e.g., fragile, keep a give side up, temperature range, security information). The RFID reader 148 may also write information to the transponder, for instance information indicative of a time and/or place at which the transponder was read, creating a tracking record.
  • Also for example, the ADC subsystem 110 may include a machine-readable symbol reader 152 to wireless read machine-readable symbols (e.g., one-dimensional or barcode symbols, two-dimensional or matrix code symbols) (not shown). Any of a large variety of machine-readable symbol readers 152 may be employed. For example, such may employ scanner based machine-readable symbol readers 152 such as those that scan a point of light (e.g., laser) across a symbol and detector light returned from the symbol, and decoding information encoded in the symbol. Also for example, such may employ imager based machine-readable symbol readers 152 such as those that employ flood illumination (e.g., LEDs) of a symbol, detect or capture an image of the symbol, and decode information encoded in the symbol. The machine-readable symbol reader(s) 152 may include fixed or stationary machine-readable symbol readers or portable or handheld machine-readable symbol readers. The machine-readable symbol reader(s) 152 may be used to read information from a machine-readable symbol physically or at least proximally associated with a target object. Such information may, for instance, include recipient information including an address and/or telephone number, sender information including an address and/or telephone number, specific handling instructions (e.g., fragile, keep a give side up, temperature range, security information).
  • While not illustrated, the volume dimensioning system 100 may include a self contained, discrete source of power, for example one or more chemical battery cells, ultracapacitor cells and/or fuel cells. While also not illustrated, the volume dimensioning system 100 may include a recharging circuit, for example to recharge secondary chemical battery cells. Alternatively or additionally, the volume dimensioning system 100 may be wired to an external power source, such as mains, residential or commercial power.
  • FIGS. 2A and 2B illustrate different types of distortion visible as a deviation between the pattern image data 212, 222 within the respective systems 100 when compared the calibration or reference pattern 202. The reference pattern 202 is disposed within the field of view 210 of the at least one image sensor 124 and comprises alternating squares of white areas 204 and color areas 206.
  • The dimensions of the reference pattern 202 are defined, fixed, and known by the volume dimensioning system 100 prior to imaging. This allows the volume dimensioning system 100 to analyze pattern image data 212, 222 containing at least a portion of the reference pattern 202 to assess or quantify the distortion present in the image and to generate at least one distortion value indicative of the distortion. The distortion may be global throughout the image or may be localized with different portions of the image exhibiting different types or amounts of distortion.
  • FIG. 2A illustrates the effect of an optical distortion that renders the image with a “pincushion” distortion where the white and colored squares 204, 206 in the original pattern 202 are reproduced in the pattern image data 212 as generally diamond shaped white and colored areas 214, 216, respectively. Although the pincushion distortion illustrated in FIG. 2A is exaggerated, it can be appreciated that any such or similar optical distortion may adversely affect to some degree the volume dimensioning system's ability to accurately determine dimensional and volumetric data. Such inaccurate dimensional and volumetric data can adversely affect the system's ability to provide accurate shipping volumes and shipping rates to carriers and consumers.
  • FIG. 2B illustrates the effect of a dimensional distortion along a single (horizontal) axis where the white and colored squares 204, 206 in the reference pattern 202 are reproduced in the pattern image data 222 as generally rectangular shaped white and colored areas 224, 226, respectively. Disproportionate compression of the image data along one axis (e.g., along the x-axis 230 in FIG. 2B) causes the dimensional distortion seen in the pattern image data 222. Conversely, disproportionate extension of the image data along two or more axes may result in both dimensional and geometric distortion of the reference pattern 202. Although the dimensional distortion appearing in FIG. 2B is exaggerated, it can be appreciated that any such or similar dimensional or geometric distortion can also adversely affect the volume dimensioning system's ability to accurately determine dimensional and volumetric data. Such inaccurate dimensional and volumetric data can adversely affect the system's ability to provide accurate shipping volumes and shipping rates to carriers and consumers.
  • Although shown in two different figures for clarity and ease of discussion, optical and dimensional distortion, along with other forms of distortion such as color or chromatic aberration or distortion, may appear in image data produced by a volume dimensioning system 100. Such combinations further complicate the accurate determination of dimensional or volumetric information therefrom. Uncorrected, such optical and dimensional distortion in the image can cause the calculation or propagation of erroneous dimensional information and consequently volumetric information and volume-based shipping cost information.
  • Optical distortion may be present in the image data received from the sensor subsystem 118 in many forms. Typical forms of optical distortion present in image data can include radial distortion, chromatic or spherical aberration, linear distortion, geometric distortion, and combinations thereof. Such optical distortion may not necessarily be a consequence of a latent defect in the sensor subsystem 118 but may be inherent in the design or manufacture of the optics used to provide the sensor subsystem 118 or characteristic of the image processing hardware, firmware, or software employed by the volume dimensioning system 100. Such optical distortion may variously be referred to as pincushion distortion, barrel distortion, or mustache distortion depending on the visual appearance of the distortion present in the displayed pattern image data 212, 222. Regardless of the cause, the presence of distortion in the image data compromises the ability of the volume dimensioning system 100 to accurately determine dimensional or volumetric data for an object. Uncorrected, such optical and dimensional distortion may adversely impact the accuracy of the shipping costs provided by the volume dimensioning system 100 and also may hinder a shipper's ability to schedule and load shipping containers, trucks, railcars, or the like based on the dimensional and volumetric data.
  • In some instances, optical distortion may be present but non-uniformly distributed across an image. Such distortion may result in a portion of an image suffering little or no optical distortion while other portions of the same image suffer significant distortion. For example, little optical distortion may be present in the center portion of an image while all or a portion of the periphery of the same image may suffer a much greater degree of optical distortion. In other instances a first type of distortion may be distributed more-or-less uniformly across the image while a second type of distortion may be present in one or more localized areas. In yet other instances, an object of dimensional interest may lie within only a portion of an optically distorted image captured by the image sensor. In such instances, it may be advantageous to locally correct the distortion present in the area of the image in which the object of dimensional interest lies. In at least some instances, if the type and extent of such local distortion present in an image can be assessed or is of a known type, extent, and/or magnitude, then local dimensional correction may be possible within the image. The ability to locally correct distortion present in an image advantageously eliminates the application of such distortion correction in portions of the image having where such distortion is not present.
  • Although the reference pattern 202 is depicted as a checkerboard, any number of machine recognizable indicia including one or more machine-readable symbols, machine-readable patterns, calibration patterns, calibration targets, calibration points, or the like may be similarly employed as a tool for assessing the distortion (e.g., amount, type, location) present in the image data. Physical parameters associated with the reference pattern 202 can be provided to the volume dimensioning system 100 either as one or more factory settings (e.g., preloaded values placed into the read only portion of the non-transitory storage medium) or communicated to the volume dimensioning system (e.g., via a network, Bluetooth, or similar connection). All or a portion of such physical parameters may include color information associated with the reference pattern 202 including the overall reference pattern size, the size of the white areas 204, the size of the colored areas 206, or combinations thereof. All or a portion of such physical parameters may include the spatial or geometric relationship between the various white and colored areas 204, 206 in the reference pattern 202. All or a portion of such physical parameters may include information encoded into one or more regions or portions of the reference pattern 202 in the form of one or more machine readable indicia or symbols. Pattern image data 212, 214 is used by the at least one processor 126 to detect and quantify the distortion (e.g., optical or dimensional distortion) present in the image data using the one or more known physical parameters. The quantity of distortion present may be expressed as at least one distortion value. In at least some instances, all or a portion of the reference pattern 202 may be useful in calibrating the volume dimensioning system 100.
  • In at least some instances, the entire electromagnetic spectrum reflected or otherwise returned from the reference pattern 202 may be used by the at least one processor 126 to determine all or a portion of the at least one distortion value. In other instances, only a portion of the electromagnetic spectrum reflected or otherwise returned from the reference pattern 202 may be used by the at least one processor 126 to determine the at least one distortion value. In some instances, the reference pattern 202 may return pattern image data unique to the electromagnetic spectrum illuminating the reference pattern 202 (e.g., the pattern image data returned in a near-ultraviolet spectrum may differ from that returned in a visible spectrum). Portions of the electromagnetic spectrum used by the at least one processor 126 may include, but are not limited to, the near ultraviolet portion of the electromagnetic spectrum, the near infrared portion of the electromagnetic spectrum, one or more portions of the visible electromagnetic spectrum, or any portion of combination thereof.
  • Although the entire reference pattern 202 is shown within the field of view 210 of the image sensor 124 in both FIGS. 2A and 2B, only a portion of the reference pattern 202 need be within the field of view 210 of the image sensor 124 to permit the at least one processor 126 to determine the at least one distortion value indicative of the distortion present in the pattern image data 212, 222. Additionally, only a portion of the reference pattern 202 need be within the field of view 210 of the image sensor 124 to permit the at least one processor 126 to determine a number of sets of distortion correction factors (e.g., one or more sets of optical or dimensional distortion correction factors) that are useful in reducing or eliminating the effect of distortion on the accuracy of dimensional, volumetric, volume dimensioning or cost data provided by the volume dimensioning system 100.
  • Identification data may in some instances be created, generated or otherwise provided by the at least one processor 126 and associated with the at least one determined distortion value. Such identification data may include chronological data such as data indicative of the date or the time at which the at least one distortion value was obtained, calculated, or otherwise determined by the at least one processor 126. Such identification data may include chronological data such as data indicative of the date or the time at which one or more sets of distortion correction factors are determined by the at least one processor 126. Such identification data may include chronological data associated with system events (e.g., distortion value determination, distortion correction determination, system calibration, a change in system units of accuracy, a change in system configuration, etc.) that are recommended or required for compliance with one or more corporate, industry, or regulatory guidelines, best practices, or standards.
  • The determined at least one distortion value along with the respective associated identification data may be at least partially stored in the at least one non-transitory storage media 130. Maintaining a history of the determined at least one distortion value may advantageously provide the ability for the one or more processors 126 to predict expected future distortion values and to detect sudden or unexpected changes in the level or magnitude of the determined at least one distortion value. Sudden changes in the at least one distortion value may, for example, indicate an unexpected change in performance of the volume dimensioning system 100. The ability to predict future expected distortion values may, for example, be useful in providing a predicted replacement interval or an expected remaining service life for the volume dimensioning system 100.
  • In at least some instances, the volume dimensioning system 100 can generate an output that includes both identification data and the associated at least one distortion value either as a visible output on user interface 132 or as a data output transmitted via the communication subsystem 108 to an external device such as a non-transitory data storage location on a local network or in the cloud or an external display device such as a printer or similar data output device.
  • At least some instances, the at least one processor 126 can calculate or otherwise determine one or more sets of distortion correction factors (e.g., one or more sets of optical distortion factors or one or more sets of dimensional distortion factors) based in whole or in part on the determined at least one distortion value. When within a first set of distortion threshold values, the volume dimensioning system 100 may use the distortion correction factors to reduce or even eliminate the effects of distortion, improving the dimensional, volumetric, and resultant shipping cost calculation capabilities of the volume dimensioning system 100.
  • The at least one processor 126 may determine the distortion correction factors using one or more numerical distortion correction methods. Numerical distortion correction methods may, for example, include Brown's distortion model or other similar mathematical distortion correction methods or schemes. One or more graphical distortion correction methods may also be used alone or in cooperation with one or more numerical distortion correction methods.
  • In some instances, the at least one processor 126 may use the entire electromagnetic spectrum of the image provided by the sensor subsystem 118 to determine all or a portion of the one or more distortion correction factors. In other instances, the at least one processor may use a portion of the electromagnetic spectrum of the image provided by the sensor subsystem 118 to determine the one or more distortion correction factors. The use of sets of distortion correction factors in one or more portions of the electromagnetic spectrum may in some instances advantageously provide the ability to partially or completely correct at least a portion of the chromatic aberration present in the image data provided by the sensor subsystem 118.
  • Dimensional distortion such as that shown in FIG. 2B may cause the generally square areas of one color (e.g., white 214) and areas of a second color (e.g., black 216) within the reference pattern 202 to appear as compressed rectangular or trapezoidal areas in the pattern image data 222. Such dimensional or geometric distortion may be evenly or unevenly distributed along one or more principal axes. For example, in FIG. 2B dimensional distortion may be present along the x-axis 222, the y-axis 224, or along both axes. Some or all of the dimensional distortion may be linear or nonlinear. In addition, although illustrated along two principal axes, dimensional distortion may be present along a third axis as well. In the example shown in FIG. 2B, dimensional distortion is present only along the x-axis 230, wherein each of the respective areas of one color (e.g., white 214) and areas of the other color (e.g., black 216) have been reduced in width along the x-axis 230 by approximately 40%. Conversely, little or no dimensional distortion has occurred along the y-axis 232.
  • In at least some instances the distortion present in the image data may include both optical and dimensional distortion. In such instances the one or more processors 126 may calculate multiple distortion values including at least one optical distortion value indicative of the level of optical distortion present in the image data and at least one dimensional distortion value indicative of the level of dimensional distortion present in the image data. The at least one optical distortion value and the at least one dimensional distortion value may be stored or otherwise retained individually within the non-transitory storage media 130 or alternatively may be combined to provide at least one combined distortion value reflective of both the optical and dimensional distortion present in the image data.
  • Using one or more calibration parameters of the reference pattern 202 and based on the determined at least one distortion value, the one or more processors 126 can determine or otherwise generate one or more sets of distortion correction factors. Such sets of distortion correction factors can include one or more sets of optical distortion correction factors, one or more sets of dimensional distortion correction factors, or combinations thereof. The one or more sets of distortion correction factors can be wholly or partially stored or otherwise retained in the at least one non-transitory storage media 130. The one or more sets of distortion correction factors are used by the at least one processor 126 to reduce or eliminate the effects of distortion present in the image data on the determined dimensional, volumetric, volume dimensional, or cost data provided by the volume dimensioning system 100. Additionally, the one or more sets of distortion correction factors may be used to by the at least one processor 126 to correct the image data prior to using the image data to provide an output on the display 132.
  • The volume dimensioning system 100 can determine the at least one distortion value and one or more sets of distortion correction factors on a regular or irregular basis. For example, in some instances, the volume dimensioning system 100 can determine the at least one distortion value when the reference pattern 202 falls within the field of view of the at least one sensor 124 and the system 100 is not actively volume dimensioning an object. Such may occur when the volume dimensioning system 100 is placed in a defined location for example returned to a cradle or stand. In other instances, the routine range of motion may bring the reference pattern 202 within the field of view of the at least one sensor 124 as the volume dimensioning system is moved or displaced. For example, the reference pattern 202 may appear in the field of view of the at least one image sensor 124 when the volume dimensioning system 110 is moved from a “storage” position or location to a “ready” position or location, or from a “ready” position or location to a “storage” position or location. In yet other instances, the volume dimensioning system 100 may provide one or more human perceptible indicators or signals that prompt a user to at least partially align the volume dimensioning system 100 with the reference pattern 202 to permit the system to perform a distortion correction or calibration.
  • In other instances, determination of the at least one distortion value and optionally the determination of the at least one set of distortion correction factors may occur as a portion of the volume dimensioning system 100 calibration routine. For example, in some instances, the at least one distortion value may be determined prior to the performance of a volume dimensioning system calibration to improve or otherwise enhance the level of accuracy of the calibration. In some instances, such distortion correction or calibration routines may be time-based and conducted at regular or irregular intervals. In other instances, such distortion correction or calibration routines may be performance related and conducted based upon one or more measured system performance parameters. In yet other instances, such distortion correction or calibration routines may be time and performance based to comply with one or more corporate, industry, or regulatory standards, best practices, or guidelines.
  • Advantageously, the ability to detect the presence of distortion present in the image data, to quantify the distortion using at least one distortion value, to optionally determine one or more sets of distortion correction factors, and to optionally incorporate both into a volume dimensioning system calibration procedure reduces the likelihood of the volume dimensioning system 100 providing erroneous linear, volumetric, or shipping cost information. Such periodic detection and quantification of distortion present in the image data may be conducted on an automatic (i.e., system generated) or manual (i.e., at user discretion) basis at regular or irregular intervals.
  • FIG. 3 shows a volume dimensioning system 100 that has been received by an exemplary support member 302 such as a stand or cradle. In at least some instances, at least a portion of a reference pattern 202 appears within the field of view 210 of the image sensor 124 when the volume dimensioning system 100 is received by the support member 302. The support member 302 may include a base member 304 to increase stability of the support member. Although depicted in FIG. 3 as supporting a handheld or portable volume dimensioning system 100, in some instances the support member 302 may receive only a portion, for example the sensor subsystem 118, of a larger or even stationary volume dimensioning system 100. The reference pattern 202 may be formed as a portion of the base member 304, separate from the base member 304, or as a member that is detachably attached to the base member 304.
  • The volume dimensioning system 100 may also include one or more sensors (not visible in FIG. 3) to detect the presence of the support member 302. Example sensors may include without limitation, one or more optical sensors, one or more ultrasonic sensors, one or more proximity sensors, or similar. Such sensors may provide one or more input signals to the at least one processor 126 indicating receipt of the volume dimensioning system 100 by the support member 302. In at least some instances, upon detection of the signal indicating receipt by the support member 302 the at least one processor 126 can initiate the capture of image data by the sensor subsystem 118. Since the reference pattern 202 lies within the field of view of the at least one image sensor 124, the image data so acquired may be used to determine at least one distortion value, calibrate the system 100, calculate one or more sets of distortion correction factors, or any combination thereof. In some instances, pattern image data from the sensor subsystem 118 received by the support member 302 may be wiredly or wirelessly communicated to a remote volume dimensioning system 100.
  • In at least some instances the reference pattern 202 can be formed on the base 304 or on a rigid or flexible member that is operably coupled or otherwise attached to the base member 304. The reference pattern 202 may be formed in different colors, materials, embossings, debossings, textures, engravings, or similar. In some instances, the reference pattern 202 may include one or more inscriptions, logos, designs, trademarked images, or the like. In at least some instances all or a portion of the reference pattern 202 and the base member 304 may be detached and mounted remotely from the support member 302. For example, in at least some instances the reference pattern 202 may be mounted on a vertical surface such as a wall or similar partition.
  • In at least some situations, when the volume dimensioning system 100 is received by the support member 302 the sensor subsystem 118 may autonomously provide pattern image data including at least the portion of the reference pattern 202 to the at least one processor 126. Autonomous provision of image data by the sensor subsystem 118 to the at least one processor 126 may occur at regular or irregular intervals. Autonomous collection of pattern image data may permit a more frequent updating of the at least one distortion value or the one or more sets of distortion correction factors than a manually initiated collection of pattern image data since such autonomous collection may occur at times when the volume dimensioning system 100 is not in active use. The pattern image data so acquired allows the at least one processor 126 to determine the at least one distortion value using the known reference pattern 202 calibration parameters. Access to pattern image data also optionally permits the at least one processor 126 to determine the one or more sets of distortion correction factors. Providing the at least one processor 126 with the ability to determine the at least one distortion value and the sets of distortion correction factors while the volume dimensioning system 100 is not in active use may advantageously increase the overall accuracy of the dimensional, volumetric, and cost information provided by the system 100.
  • FIG. 4A provides a perspective view of an illustrative volume dimensioning system 100 a where the at least distortion value within a first threshold permitting the use of a fine unit of accuracy (e.g., 1 mm depicted in FIG. 4A) to determine the dimensional, volumetric, and cost data associated with object 402 a. FIG. 4B provides a perspective view of an illustrative volume dimensioning system 100 b now where the at least distortion value is not within the first threshold permitting the use of a fine unit of accuracy and, as a consequence, the at least one processor 126 has autonomously shifted to the use of a coarse unit of accuracy (e.g., 1 cm depicted in FIG. 4B) to determine the dimensional, volumetric, and cost data associated with object 402 b.
  • Although the object 402 a is depicted as a cubic solid for simplicity and ease of illustration, it should be understood that similar principles as described below will apply to any object placed within the field of view of the volume dimensioning system 100. Object 402 a is illustrated as having actual dimensions of 11.1 cm in length, 6.3 cm in width, and 15.6 cm in height. Such an object may be representative of a commonly encountered shipping container such as a cardboard box. Prior to placement of the object 402 a in the field of view 210 of the imaging sensor 124, the volume dimensioning system 100 a has determined through the use of a reference pattern 202 (not shown in FIG. 4A) that the at least one distortion value associated with the system 100 a falls within a first threshold (e.g., a recalibration threshold) permitting use of a fine unit of accuracy in dimensioning, volume, and cost determination. In the example depicted in FIG. 4A, the fine unit of accuracy is 1 mm. The volume dimensioning system 100 a is therefore able to determine the dimensions of the object 402 a to the nearest millimeter. Thus, the volume dimensioning system 100 a is able to determine the length 406 a as 11.1 cm, the width 408 a as 6.3 cm, and the height 410 a as 15.6 cm. Using these determined dimensions, the volume dimensioning system 100 a is further able to determine the volume 412 a as 1091 cm3. Finally, using the determined volume and assuming a shipping cost of $0.015/cm3, the volume dimensioning system 100 a can calculate the shipping cost 414 a for object 402 a is $16.37.
  • Object 402 b has dimensions identical to object 402 a, 11.1 cm in length, 6.3 cm in width, and 15.6 cm in height. However, prior to placement of the object 402 b in the field of view 210 of the imaging sensor 124, the volume dimensioning system 100 b has determined through the use of a reference pattern 202 (not shown in FIG. 4B) that the at least one distortion value associated with the system 100 b falls outside a first threshold (e.g., a recalibration threshold) and within a second threshold (e.g., a service required threshold) which permits the use of a coarse unit of accuracy in dimensioning, volume determination and cost determination. In the example depicted in FIG. 4B, the coarse unit of accuracy is 1 cm, an order of magnitude larger than the fine unit of accuracy used in FIG. 4A. The volume dimensioning system 100 b is therefore only able to determine the dimensions of the object 402 b to the nearest centimeter. Thus, the volume dimensioning system 100 b determines the length 406 b as 11 cm, the width 408 b as 6 cm, and the height 410 b as 16 cm. Using these determined dimensions, the volume dimensioning system 100 b is further able to determine the volume 412 b as 1056 cm3. Finally, using the determined volume and assuming a shipping cost of $0.015/cm3, the volume dimensioning system 100 b is able to calculate the shipping cost 414 b for the object 402 b is $15.84.
  • In at least some instances, the volume dimensioning system 100 can correct distortion present in only a portion of the overall image. For example, the volume dimensioning system 100 may correct only the portion of the image containing the object 402. Such local correction can proceed using one or more correction factors determined based at least in part on any distortion present in the portion of the image containing and/or proximate the object 402. Such local distortion correction factors can be used in a manner similar to image wide distortion correction factors, for example to determine the dimensional accuracy achievable with regard to the object 402 and to determine whether a fine unit of accuracy or a coarse unit of accuracy should be used in assessing dimensional and cost information for the object 402.
  • FIG. 5 is a flow diagram 500 showing a high level method of operation of a volume dimensioning system 100. The method starts at 502. At 504 the at least one processor 126 receives pattern image data from the sensor subsystem 118. In at least some instances, such pattern image data may be autonomously acquired at regular or irregular intervals by the volume dimensioning system 100. For example, pattern image data may be acquired at regular or irregular intervals when the all or a portion of the volume dimensioning system 100 is received by the support member 302. In other instances, such pattern image data may be manually acquired at regular or irregular intervals by the volume dimensioning system 100. For example, the volume dimensioning system 100 may provide one or more human perceptible indicators to a user that indicate the reference pattern 202 should be placed in the field of view of the at least one sensor 124 to permit the acquisition of pattern image data for distortion correction or calibration purposes.
  • At 506 the at least one processor 126 determines at least one distortion value using the pattern image data received from the sensor subsystem 118 at 504. The at least one processor 126 can determine any number of distortion values, including at least one of: an optical distortion value, a dimensional distortion value, a chromatic aberration or distortion value, or combinations thereof. The distortion values so determined provide a quantitative measure or assessment of the overall quality of the image data provided by the sensor subsystem 118. In some instances, all or a portion of the at least one distortion values determined by the at least one processor 126 at 506 can be stored or otherwise retained within the at least one non-transitory storage media 130.
  • At 508 the at least one processor 126 compares the determined at least one distortion value from 506 with a first distortion threshold. A determined at least one distortion value falling within the first distortion threshold indicates the distortion present in the image data provided by the sensor subsystem 118 is sufficiently small that a fine unit of accuracy may be used in determining and calculating dimensional, volumetric, and cost information. Conversely, a determined at least one distortion value exceeding the first distortion threshold may indicate the level of distortion present in the image data provided by the sensor subsystem 118 is sufficiently large that the use of the fine unit of accuracy is inappropriate and a coarse unit of accuracy should instead be used to determine and calculate dimensional, volumetric, and cost information. Such distortion thresholds may be provided as one or more factory settings or one or more periodically updated thresholds that are stored or otherwise retained in the at least one non-transitory storage media 130.
  • Advantageously, such adjustments are made autonomously by the volume dimensioning system 100 without user intervention using the determined at least one distortion value and a plurality of distortion thresholds stored or otherwise retained within the non-transitory storage media 130. For illustrative purposes, Table 1 lists one set of example values that may be associated with “fine” and “coarse” units of accuracy:
  • TABLE 1
    Example Units of Accuracy
    “Fine” Unit “Coarse” Unit
    of Accuracy of Accuracy
    Dimensional Units ½ inch 2 inches
    Volumetric Units 1 in3 8 in3
    Cost Units $0.01 $0.10
  • At 510, if the at least one processor 126 finds the distortion value determined at 506 is within or less than the first distortion threshold, the at least one processor 126 can adjust one or more volume dimensioning system parameters at 512. In at least some instances, at 512 the one or more processors 126 may calculate one or more sets of distortion correction factors to reduce or eliminate the distortion present in the image data provided by the sensor subsystem 118 using the one or more distortion values determined at 506. In some instances, adjusting the one or more volume dimensioning system parameters at 512 may also include confirming the fine units of accuracy are being used, performing one or more calibration routines, or combinations thereof.
  • At 514 the at least one processor compares the at least one distortion value determined at 506 with a second distortion threshold. If at 510 the at least one processor 126 found the at least one distortion value determined at 506 exceeded the first distortion threshold at 510, the at least one processor 126 can compare the determined at least one distortion value with a second distortion threshold at 514. In at least some instances, distortion values exceeding the second distortion threshold may indicate the presence of distortion in the image data provided by the sensor subsystem 118 that is of a magnitude or severity sufficient to render the system 100 unusable based on one or more corporate, industry, or regulatory guidelines, best practices, or standards.
  • Although FIG. 5 illustrates the use of only two distortion thresholds, any number of distortion thresholds may be similarly used. Different distortion threshold values may be indicative, for example, of varying levels or degrees of distortion in the image data provided by the sensor subsystem 118. Each of the different levels or degrees of distortion may indicate the need for the system 100 to use a corresponding unit of accuracy in displaying dimensional, volumetric or cost information. For example a first threshold value may be indicative of distortion that allows a unit of accuracy of 1 mm; a second threshold value may be indicative of distortion that allows a unit of accuracy of 2 mm; a third threshold value may be indicative of distortion that allows a unit of accuracy of 3 mm; a fourth threshold value may be indicative of distortion that allows a unit of accuracy of 4 mm; a fifth threshold value may be indicative of distortion that allows a unit of accuracy of 5 mm; and a sixth threshold value may be indicative of distortion sufficient to generate a human perceptible “service required” indicator on the system 100.
  • If at 516 the at least one processor 126 finds the at least one distortion value determined at 506 exceeds or is greater than the second distortion threshold, the at least one processor 126 can generate one or more human perceptible outputs indicative of a “service required” condition at 518. In some instances at 518, one or more functions or features of the volume dimensioning system 100, for example the costing functionality, may be inhibited if the distortion value exceeds the second distortion threshold.
  • At 520, if the at least one processor 126 found the distortion value determined at 506 fell between the first and the second distortion thresholds at 516, the at least one processor 126 can adjust the units of accuracy of the information presented by the volume dimensioning system 100. In at least some instances, at least one processor 126 can adjust dimensional, volumetric or cost information provided by the volume dimensioning system 100 to one or more coarse units of accuracy. In at least some instances, at 520 the one or more processors 126 may calculate one or more sets of distortion correction factors to reduce or eliminate the distortion present in the image data provided by the sensor subsystem 118 using the one or more distortion values determined at 506. The one or more coarse units of accuracy cause the system 100 to determine, calculate, and display dimensional, volumetric, and cost data in units of accuracy that are based at least in part on the capability of the system 100 to resolve such dimensions and volumes based on the distortion values determined at 506. In at least some instances, some or all of the units of accuracy may be based on one or more corporate, industry, or regulatory guidelines, best practices, or standards. In some instances, for example, the units of accuracy used by the volume dimensioning system may be based on the NIST Handbook 44-2012 Chapter 5.58. The method 500 terminates at 522.
  • FIG. 6 is a flow diagram 600 showing a low level method of operation of a volume dimensioning system 100. In particular, the method 600 illustrates an example method that may be used by the at least one processor 126 to assess the at least one distortion value at 506. The method 600 starts at 602. At 604 the at least one processor 126, using the pattern image data provided by the sensor subsystem 118, assesses the optical distortion present in the image data by determining at least one optical distortion value. The at least one optical distortion value determined at 604 can provide a quantitative measure of the degree or magnitude of the optical distortion present in the image data provided by the sensor subsystem 118. Such a quantitative measure of the optical distortion present in the image data may be obtained by the at least one processor 126 using one or more numerical distortion analysis techniques, graphical distortion analysis techniques, or combinations thereof.
  • At 606 the at least one processor 126 assesses the image data supplied by the sensor subsystem 118 for dimensional distortion. The assessment of the dimensional distortion by the at least one processor 126 determines at least in part at least one dimensional distortion value. The at least one dimensional distortion value determined at 606 can provide a quantitative measure of the degree or magnitude of the dimensional distortion present in the image data provided by the sensor subsystem 118. Such a quantitative measure of the dimensional distortion present in the image data may be obtained by the at least one processor 126 using one or more numerical distortion analysis techniques, graphical distortion analysis techniques, or combinations thereof. After the at least one processor 126 has determined at least one distortion value attributable to either or both optical and dimensional distortion present in the image data provided by the sensor subsystem 118, the method 600 concludes at 608.
  • FIG. 7 is a flow diagram 700 showing a low level method of operation of a volume dimensioning system 100. In particular, the method 700 illustrates an example method that may be used by the at least one processor 126 to store historical distortion data including determined distortion values and distortion correction factors in the non-transitory storage media 130. Such historical data provides a valuable resource in tracking the performance history of the volume dimensioning system 100 and in providing a tool for predicting the future performance of the system 100. In some instances, collection of such historical data may assist in compliance with one or more corporate, industry, or regulatory guidelines, best practices, or standards. Advantageously, since the determination of distortion values and distortion correction factors may be performed autonomously by the volume dimensioning system 100, the presence of such historical data in the non-transitory storage media 130 provides the system user with assurance that such distortion detection and correction routines are being performed by the system 100. The example method to store historical distortion data begins at 702.
  • At 704, the at least one processor 126 can associate one or more identifiers with the at least one distortion value determined at 506 or the one or more sets of distortion correction factors determined at 512 or 520. Any type of logical identifier, including one or more sequential or chronological identifiers, may be so associated with the at least one distortion value. The association of one or more logical identifiers with the at least one distortion value or the one or more sets of distortion correction factors permits the retrieval and presentation of such data in an organized and logical manner. Storage of such historical data may also assist in compliance with one or more corporate, industry, or regulatory guidelines, best practices, or standards.
  • At 704 the at least one processor 126 can associate one or more logical identifiers with all or a portion of the distortion values (i.e., determined at 506) or all or a portion of the calculated sets of distortion correction factors (i.e., calculated at 512 or 520). In at least some instances, the one or more logical indicators can include one or more chronological indicators such as date and time of determination of the at least one distortion value or calculation of the set of distortion correction factors by the at least one processor 126. In some instances, the one or more logical indicators can include one or more serialized indicators sequentially assigned by the at least one processor 126 upon determining the at least one distortion values or calculating the set of distortion correction factors. Any similar logical indicators that provide the ability to retrieve, sort, organize, or display the associated distortion values or distortion correction factors in a logical manner may be so assigned by the at least one processor 126.
  • At 706, the at least one distortion value or the set of distortion correction factors and the associated logical identifier are at least partially stored within a non-transitory storage media 130. In at least some instances, at least a portion of the non-transitory storage media 130 can include one or more types of removable media, for example secure digital (SD) storage media, compact flash (CF) storage media, universal serial bus (USB) storage media, memory sticks, or the like. The use of such removable storage media may advantageously permit the transfer of data such as the stored distortion values and distortion correction factors to one or more external computing devices equipped with a comparable removable storage media reader.
  • At 708, the stored distortion values or distortion correction factors are displayed sorted or otherwise arranged or organized by the associated identifier either on the internal display device 132 of the volume dimensioning system 100 or an external display device wiredly or wirelessly accessed by the system 100 via the communications subsystem 108.
  • At 710, the stored distortion values or distortion correction factors are displayed sorted by the associated identifier either on the internal display device 132 of the volume dimensioning system 100 or an external display device wiredly or wirelessly accessed by the system 100 via the communications subsystem 108. Additionally, one or more trend lines may be fitted to the displayed data to provide an indication of the overall rate of degradation or change in distortion of the image data provided by the sensor subsystem 118. Such trend data may be useful in detecting sudden or unexpected changes in the overall level of image data quality provided by the sensor subsystem 118 and may advantageously provide an indication of the overall condition of the sensor subsystem 118.
  • At 712, the stored distortion values or distortion correction factors are displayed sorted by the associated identifier either on the internal display device 132 of the volume dimensioning system 100 or an external display device wiredly or wirelessly accessed by the system 100 via the communications subsystem 108. Additionally, through the use of one or more trend lines or similar data analysis techniques, a performance forecast is provided. Such performance forecasts may identify an expected date or timeframe in which the image data provided by the sensor subsystem 118 will no longer fall within an acceptable distortion threshold. Such data may advantageously indicate or predict an expected date at which the sensor subsystem 118 or the volume dimensioning system 100 may require service or replacement. The method 700 terminates at 714
  • The above description of illustrated embodiments, including what is described in the Abstract, is not intended to be exhaustive or to limit the embodiments to the precise forms disclosed. Although specific embodiments of and examples are described herein for illustrative purposes, various equivalent modifications can be made without departing from the spirit and scope of the disclosure, as will be recognized by those skilled in the relevant art. The teachings provided herein of the various embodiments can be applied to other automated systems, not necessarily the exemplary volume dimensioning system generally described above.
  • For instance, the foregoing detailed description has set forth various embodiments of the devices and/or processes via the use of block diagrams, schematics, and examples. Insofar as such block diagrams, schematics, and examples contain one or more functions and/or operations, it will be understood by those skilled in the art that each function and/or operation within such block diagrams, flowcharts, or examples can be implemented, individually and/or collectively, by a wide range of hardware, software, firmware, or virtually any combination thereof. In one embodiment, the present subject matter may be implemented via Application Specific Integrated Circuits (ASICs). However, those skilled in the art will recognize that the embodiments disclosed herein, in whole or in part, can be equivalently implemented in standard integrated circuits, as one or more computer programs executed by one or more computers (e.g., as one or more programs running on one or more computer systems), as one or more programs executed by on one or more controllers (e.g., microcontrollers) as one or more programs executed by one or more processors (e.g., microprocessors), as firmware, or as virtually any combination thereof, and that designing the circuitry and/or writing the code for the software and or firmware would be well within the skill of one of ordinary skill in the art in light of the teachings of this disclosure.
  • When logic is implemented as software and stored in memory, logic or information can be stored on any computer-readable medium for use by or in connection with any processor-related system or method. In the context of this disclosure, a memory is a computer-readable medium that is an electronic, magnetic, optical, or other physical device or means that contains or stores a computer and/or processor program. Logic and/or the information can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions associated with logic and/or information.
  • In the context of this specification, a “computer-readable medium” can be any element that can store the program associated with logic and/or information for use by or in connection with the instruction execution system, apparatus, and/or device. The computer-readable medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device. More specific examples (a non-exhaustive list) of the computer readable medium would include the following: a portable computer diskette (magnetic, compact flash card, secure digital, or the like), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM, EEPROM, or Flash memory), a portable compact disc read-only memory (CDROM), digital tape, and other nontransitory media.
  • Many of the methods described herein can be performed with one or more variations. For example, many of the methods may include additional acts, omit some acts, and/or perform or execute acts in a different order than as illustrated or described.
  • The various embodiments described above can be combined to provide further embodiments. All of the commonly assigned US patent application publications, US patent applications, foreign patents, foreign patent applications and non-patent publications referred to in this specification and/or listed in the Application Data Sheet, including but not limited to U.S. provisional patent application Ser. No. 61/691,093, filed is incorporated herein by reference, in its entirety. Aspects of the embodiments can be modified, if necessary, to employ systems, circuits and concepts of the various patents, applications and publications to provide yet further embodiments.
  • These and other changes can be made to the embodiments in light of the above-detailed description. In general, in the following claims, the terms used should not be construed to limit the claims to the specific embodiments disclosed in the specification and the claims, but should be construed to include all possible embodiments along with the full scope of equivalents to which such claims are entitled. Accordingly, the claims are not limited by the disclosure.

Claims (1)

  1. 1. A method of calibrating position and orientation parameters of an imaging system in an automated data reading system, the method comprising:
    obtaining, from the imaging system, image data representing an imaged portion of a planar calibration target that is superimposed on a surface of the automated data reading system, the imaged portion of the planar calibration target including spaced-apart optical codes disposed at predetermined positions on a surface of the automated data reading system to define known locations of calibration-control points on the surface;
    identifying the optical codes from the image data to obtain observed locations of the calibration-control points represented by the image data; and
    calibrating position and orientation parameters of the imaging system based on differences between the known and observed locations.
US14490989 2012-08-20 2014-09-19 Volume dimensioning system calibration systems and methods Abandoned US20150009338A1 (en)

Priority Applications (3)

Application Number Priority Date Filing Date Title
US201261691093 true 2012-08-20 2012-08-20
US13786131 US20140049635A1 (en) 2012-08-20 2013-03-05 Volume dimensioning system calibration systems and methods
US14490989 US20150009338A1 (en) 2012-08-20 2014-09-19 Volume dimensioning system calibration systems and methods

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
US14490989 US20150009338A1 (en) 2012-08-20 2014-09-19 Volume dimensioning system calibration systems and methods

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
US13786131 Continuation US20140049635A1 (en) 2012-08-20 2013-03-05 Volume dimensioning system calibration systems and methods

Publications (1)

Publication Number Publication Date
US20150009338A1 true true US20150009338A1 (en) 2015-01-08

Family

ID=50099789

Family Applications (2)

Application Number Title Priority Date Filing Date
US13786131 Pending US20140049635A1 (en) 2012-08-20 2013-03-05 Volume dimensioning system calibration systems and methods
US14490989 Abandoned US20150009338A1 (en) 2012-08-20 2014-09-19 Volume dimensioning system calibration systems and methods

Family Applications Before (1)

Application Number Title Priority Date Filing Date
US13786131 Pending US20140049635A1 (en) 2012-08-20 2013-03-05 Volume dimensioning system calibration systems and methods

Country Status (1)

Country Link
US (2) US20140049635A1 (en)

Cited By (170)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140034731A1 (en) * 2012-07-31 2014-02-06 Datalogic ADC, Inc. Calibration and self-test in automated data reading systems
US9235737B2 (en) 2013-06-28 2016-01-12 Hand Held Products, Inc. System having an improved user interface for reading code symbols
EP2990911A1 (en) 2014-08-29 2016-03-02 Hand Held Products, Inc. Gesture-controlled computer system
US9292969B2 (en) 2012-05-07 2016-03-22 Intermec Ip Corp. Dimensioning system calibration systems and methods
EP3001368A1 (en) 2014-09-26 2016-03-30 Honeywell International Inc. System and method for workflow management
EP3007096A1 (en) 2014-10-10 2016-04-13 Hand Held Products, Inc. Depth sensor based auto-focus system for an indicia scanner
EP3006893A1 (en) 2014-10-10 2016-04-13 Hand Held Products, Inc. Methods for improving the accuracy of dimensioning-system measurements
EP3009968A1 (en) 2014-10-15 2016-04-20 Vocollect, Inc. Systems and methods for worker resource management
EP3016023A1 (en) 2014-10-31 2016-05-04 Honeywell International Inc. Scanner with illumination system
EP3035151A1 (en) 2014-12-18 2016-06-22 Hand Held Products, Inc. Wearable sled system for a mobile computer device
EP3035074A1 (en) 2014-12-18 2016-06-22 Hand Held Products, Inc. Collision-avoidance system and method
EP3038010A1 (en) 2014-12-23 2016-06-29 Hand Held Products, Inc. Mini-barcode reading module with flash memory management
EP3037924A1 (en) 2014-12-22 2016-06-29 Hand Held Products, Inc. Augmented display and glove with markers as us user input device
EP3038029A1 (en) 2014-12-26 2016-06-29 Hand Held Products, Inc. Product and location management via voice recognition
EP3038030A1 (en) 2014-12-28 2016-06-29 Hand Held Products, Inc. Dynamic check digit utilization via electronic tag
EP3037912A1 (en) 2014-12-23 2016-06-29 Hand Held Products, Inc. Tablet computer with interface channels
EP3038009A1 (en) 2014-12-23 2016-06-29 Hand Held Products, Inc. Method of barcode templating for enhanced decoding performance
EP3037951A1 (en) 2014-12-22 2016-06-29 Hand Held Products, Inc. Delayed trim of managed nand flash memory in computing devices
EP3040921A1 (en) 2014-12-29 2016-07-06 Hand Held Products, Inc. Confirming product location using a subset of a product identifier
EP3040954A1 (en) 2014-12-30 2016-07-06 Hand Held Products, Inc. Point of sale (pos) code sensing apparatus
EP3040906A1 (en) 2014-12-30 2016-07-06 Hand Held Products, Inc. Visual feedback for code readers
EP3040907A2 (en) 2014-12-27 2016-07-06 Hand Held Products, Inc. Acceleration-based motion tolerance and predictive coding
EP3040908A1 (en) 2014-12-30 2016-07-06 Hand Held Products, Inc. Real-time adjustable window feature for barcode scanning and process of scanning barcode with adjustable window feature
US9390596B1 (en) 2015-02-23 2016-07-12 Hand Held Products, Inc. Device, system, and method for determining the status of checkout lanes
EP3043300A1 (en) 2015-01-09 2016-07-13 Honeywell International Inc. Restocking workflow prioritization
EP3043443A1 (en) 2015-01-08 2016-07-13 Hand Held Products, Inc. Charge limit selection for variable power supply configuration
EP3046032A2 (en) 2014-12-28 2016-07-20 Hand Held Products, Inc. Remote monitoring of vehicle diagnostic information
EP3045953A1 (en) 2014-12-30 2016-07-20 Hand Held Products, Inc. Augmented reality vision barcode scanning system and method
US9412242B2 (en) 2014-04-04 2016-08-09 Hand Held Products, Inc. Multifunction point of sale system
US9464885B2 (en) 2013-08-30 2016-10-11 Hand Held Products, Inc. System and method for package dimensioning
US9478113B2 (en) 2014-06-27 2016-10-25 Hand Held Products, Inc. Cordless indicia reader with a multifunction coil for wireless charging and EAS deactivation
EP3086281A1 (en) 2015-04-21 2016-10-26 Hand Held Products, Inc. Systems and methods for imaging
US9488986B1 (en) 2015-07-31 2016-11-08 Hand Held Products, Inc. System and method for tracking an item on a pallet in a warehouse
US9490540B1 (en) 2015-09-02 2016-11-08 Hand Held Products, Inc. Patch antenna
US9510140B2 (en) 2014-04-21 2016-11-29 Hand Held Products, Inc. Docking system and method using near field communication
US9507974B1 (en) 2015-06-10 2016-11-29 Hand Held Products, Inc. Indicia-reading systems having an interface with a user's nervous system
US9521331B2 (en) 2015-04-21 2016-12-13 Hand Held Products, Inc. Capturing a graphic information presentation
US9557166B2 (en) 2014-10-21 2017-01-31 Hand Held Products, Inc. Dimensioning system with multipath interference mitigation
US9564035B2 (en) 2014-12-22 2017-02-07 Hand Held Products, Inc. Safety system and method
WO2017024347A1 (en) * 2015-08-10 2017-02-16 Wisetech Global Limited Volumetric estimation methods, devices, & systems
US9582698B2 (en) 2013-06-26 2017-02-28 Hand Held Products, Inc. Code symbol reading system having adaptive autofocus
US9581809B2 (en) 2014-04-29 2017-02-28 Hand Held Products, Inc. Autofocus lens system
EP3136219A1 (en) 2015-08-27 2017-03-01 Hand Held Products, Inc. Interactive display
EP3147151A1 (en) 2015-09-25 2017-03-29 Hand Held Products, Inc. A system and process for displaying information from a mobile computer in a vehicle
EP3151553A1 (en) 2015-09-30 2017-04-05 Hand Held Products, Inc. A self-calibrating projection apparatus and process
US9616749B2 (en) 2013-05-24 2017-04-11 Hand Held Products, Inc. System and method for display of information using a vehicle-mount computer
EP3159770A1 (en) 2015-10-19 2017-04-26 Hand Held Products, Inc. Quick release dock system and method
US9646189B2 (en) 2014-10-31 2017-05-09 Honeywell International, Inc. Scanner with illumination system
US9646191B2 (en) 2015-09-23 2017-05-09 Intermec Technologies Corporation Evaluating images
EP3165939A1 (en) 2015-10-29 2017-05-10 Hand Held Products, Inc. Dynamically created and updated indoor positioning map
US9652648B2 (en) 2015-09-11 2017-05-16 Hand Held Products, Inc. Positioning an object with respect to a target location
US9656487B2 (en) 2015-10-13 2017-05-23 Intermec Technologies Corporation Magnetic media holder for printer
US9659198B2 (en) 2015-09-10 2017-05-23 Hand Held Products, Inc. System and method of determining if a surface is printed or a mobile device screen
US9662900B1 (en) 2016-07-14 2017-05-30 Datamax-O'neil Corporation Wireless thermal printhead system and method
EP3173980A1 (en) 2015-11-24 2017-05-31 Intermec Technologies Corporation Automatic print speed control for indicia printer
US9674430B1 (en) 2016-03-09 2017-06-06 Hand Held Products, Inc. Imaging device for producing high resolution images using subpixel shifts and method of using same
US9672398B2 (en) 2013-08-26 2017-06-06 Intermec Ip Corporation Aiming imagers
US9678536B2 (en) 2014-12-18 2017-06-13 Hand Held Products, Inc. Flip-open wearable computer
US9679178B2 (en) 2014-12-26 2017-06-13 Hand Held Products, Inc. Scanning improvements for saturated signals using automatic and fixed gain control methods
US9680282B2 (en) 2015-11-17 2017-06-13 Hand Held Products, Inc. Laser aiming for mobile devices
US9685049B2 (en) 2014-12-30 2017-06-20 Hand Held Products, Inc. Method and system for improving barcode scanner performance
US9684809B2 (en) 2015-10-29 2017-06-20 Hand Held Products, Inc. Scanner assembly with removable shock mount
US9682625B2 (en) 2013-05-24 2017-06-20 Hand Held Products, Inc. System and method for display of information using a vehicle-mount computer
US9697401B2 (en) 2015-11-24 2017-07-04 Hand Held Products, Inc. Add-on device with configurable optics for an image scanner for scanning barcodes
US9701140B1 (en) 2016-09-20 2017-07-11 Datamax-O'neil Corporation Method and system to calculate line feed error in labels on a printer
USD792407S1 (en) 2015-06-02 2017-07-18 Hand Held Products, Inc. Mobile computer housing
EP3193188A1 (en) 2016-01-12 2017-07-19 Hand Held Products, Inc. Programmable reference beacons
EP3193146A1 (en) 2016-01-14 2017-07-19 Hand Held Products, Inc. Multi-spectral imaging using longitudinal chromatic aberrations
US9721132B2 (en) 2014-12-31 2017-08-01 Hand Held Products, Inc. Reconfigurable sled for a mobile device
EP3200120A1 (en) 2016-01-26 2017-08-02 Hand Held Products, Inc. Enhanced matrix symbol error correction method
US9727841B1 (en) 2016-05-20 2017-08-08 Vocollect, Inc. Systems and methods for reducing picking operation errors
US9729744B2 (en) 2015-12-21 2017-08-08 Hand Held Products, Inc. System and method of border detection on a document and for producing an image of the document
US9727769B2 (en) 2014-12-22 2017-08-08 Hand Held Products, Inc. Conformable hand mount for a mobile scanner
US9727840B2 (en) 2016-01-04 2017-08-08 Hand Held Products, Inc. Package physical characteristic identification system and method in supply chain management
US9734639B2 (en) 2014-12-31 2017-08-15 Hand Held Products, Inc. System and method for monitoring an industrial vehicle
US9752864B2 (en) 2014-10-21 2017-09-05 Hand Held Products, Inc. Handheld dimensioning system with feedback
US9762793B2 (en) 2014-10-21 2017-09-12 Hand Held Products, Inc. System and method for dimensioning
US9761096B2 (en) 2014-12-18 2017-09-12 Hand Held Products, Inc. Active emergency exit systems for buildings
US9767337B2 (en) 2015-09-30 2017-09-19 Hand Held Products, Inc. Indicia reader safety
US9767581B2 (en) 2014-12-12 2017-09-19 Hand Held Products, Inc. Auto-contrast viewfinder for an indicia reader
EP3220369A1 (en) 2016-09-29 2017-09-20 Hand Held Products, Inc. Monitoring user biometric parameters with nanotechnology in personal locator beacon
US9774940B2 (en) 2014-12-27 2017-09-26 Hand Held Products, Inc. Power configurable headband system and method
US9779546B2 (en) 2012-05-04 2017-10-03 Intermec Ip Corp. Volume dimensioning systems and methods
US9781502B2 (en) 2015-09-09 2017-10-03 Hand Held Products, Inc. Process and system for sending headset control information from a mobile device to a wireless headset
US9781681B2 (en) 2015-08-26 2017-10-03 Hand Held Products, Inc. Fleet power management through information storage sharing
US9786101B2 (en) 2015-05-19 2017-10-10 Hand Held Products, Inc. Evaluating image values
US9785814B1 (en) 2016-09-23 2017-10-10 Hand Held Products, Inc. Three dimensional aimer for barcode scanning
US9784566B2 (en) 2013-03-13 2017-10-10 Intermec Ip Corp. Systems and methods for enhancing dimensioning
US9792582B2 (en) 2014-10-14 2017-10-17 Hand Held Products, Inc. Identifying inventory items in a storage facility
EP3232367A1 (en) 2016-04-15 2017-10-18 Hand Held Products, Inc. Imaging barcode reader with color separated aimer and illuminator
US9805343B2 (en) 2016-01-05 2017-10-31 Intermec Technologies Corporation System and method for guided printer servicing
US9805237B2 (en) 2015-09-18 2017-10-31 Hand Held Products, Inc. Cancelling noise caused by the flicker of ambient lights
US9805257B1 (en) 2016-09-07 2017-10-31 Datamax-O'neil Corporation Printer method and apparatus
US9802427B1 (en) 2017-01-18 2017-10-31 Datamax-O'neil Corporation Printers and methods for detecting print media thickness therein
EP3239892A1 (en) 2016-04-26 2017-11-01 Hand Held Products, Inc. Indicia reading device and methods for decoding decodable indicia employing stereoscopic imaging
EP3239891A1 (en) 2016-04-14 2017-11-01 Hand Held Products, Inc. Customizable aimer system for indicia reading terminal
US9811650B2 (en) 2014-12-31 2017-11-07 Hand Held Products, Inc. User authentication system and method
US9823059B2 (en) 2014-08-06 2017-11-21 Hand Held Products, Inc. Dimensioning system with guided alignment
US9826106B2 (en) 2014-12-30 2017-11-21 Hand Held Products, Inc. System and method for detecting barcode printing errors
US9827796B1 (en) 2017-01-03 2017-11-28 Datamax-O'neil Corporation Automatic thermal printhead cleaning system
US9835486B2 (en) 2015-07-07 2017-12-05 Hand Held Products, Inc. Mobile dimensioner apparatus for use in commerce
EP3252703A1 (en) 2016-06-03 2017-12-06 Hand Held Products, Inc. Wearable metrological apparatus
US9843660B2 (en) 2014-12-29 2017-12-12 Hand Held Products, Inc. Tag mounted distributed headset with electronics module
US9844158B2 (en) 2015-12-18 2017-12-12 Honeywell International, Inc. Battery cover locking mechanism of a mobile terminal and method of manufacturing the same
US9841311B2 (en) 2012-10-16 2017-12-12 Hand Held Products, Inc. Dimensioning system
EP3255376A1 (en) 2016-06-10 2017-12-13 Hand Held Products, Inc. Scene change detection in a dimensioner
US9844956B2 (en) 2015-10-07 2017-12-19 Intermec Technologies Corporation Print position correction
EP3258210A1 (en) 2016-06-15 2017-12-20 Hand Held Products, Inc. Automatic mode switching in a volume dimensioner
US9853575B2 (en) 2015-08-12 2017-12-26 Hand Held Products, Inc. Angular motor shaft with rotational attenuation
US9849691B1 (en) 2017-01-26 2017-12-26 Datamax-O'neil Corporation Detecting printing ribbon orientation
US9852102B2 (en) 2015-04-15 2017-12-26 Hand Held Products, Inc. System for exchanging information between wireless peripherals and back-end systems via a peripheral hub
US9857167B2 (en) 2015-06-23 2018-01-02 Hand Held Products, Inc. Dual-projector three-dimensional scanner
US9861182B2 (en) 2015-02-05 2018-01-09 Hand Held Products, Inc. Device for supporting an electronic tool on a user's hand
US9864887B1 (en) 2016-07-07 2018-01-09 Hand Held Products, Inc. Energizing scanners
US9876923B2 (en) 2015-10-27 2018-01-23 Intermec Technologies Corporation Media width sensing
US9876957B2 (en) 2016-06-21 2018-01-23 Hand Held Products, Inc. Dual mode image sensor and method of using same
US9881194B1 (en) 2016-09-19 2018-01-30 Hand Held Products, Inc. Dot peen mark image acquisition
US9879823B2 (en) 2014-12-31 2018-01-30 Hand Held Products, Inc. Reclosable strap assembly
US9892356B1 (en) 2016-10-27 2018-02-13 Hand Held Products, Inc. Backlit display detection and radio signature recognition
US9892876B2 (en) 2015-06-16 2018-02-13 Hand Held Products, Inc. Tactile switch for a mobile electronic device
US9891612B2 (en) 2015-05-05 2018-02-13 Hand Held Products, Inc. Intermediate linear positioning
US9897434B2 (en) 2014-10-21 2018-02-20 Hand Held Products, Inc. Handheld dimensioning system with measurement-conformance feedback
US9902175B1 (en) 2016-08-02 2018-02-27 Datamax-O'neil Corporation Thermal printer having real-time force feedback on printhead pressure and method of using same
US9911023B2 (en) 2015-08-17 2018-03-06 Hand Held Products, Inc. Indicia reader having a filtered multifunction image sensor
US9908351B1 (en) 2017-02-27 2018-03-06 Datamax-O'neil Corporation Segmented enclosure
US9919547B2 (en) 2016-08-04 2018-03-20 Datamax-O'neil Corporation System and method for active printing consistency control and damage protection
US9924006B2 (en) 2014-10-31 2018-03-20 Hand Held Products, Inc. Adaptable interface for a mobile computing device
US9930050B2 (en) 2015-04-01 2018-03-27 Hand Held Products, Inc. Device management proxy for secure devices
US9936278B1 (en) 2016-10-03 2018-04-03 Vocollect, Inc. Communication headsets and systems for mobile application control and power savings
US9931867B1 (en) 2016-09-23 2018-04-03 Datamax-O'neil Corporation Method and system of determining a width of a printer ribbon
US9935946B2 (en) 2015-12-16 2018-04-03 Hand Held Products, Inc. Method and system for tracking an electronic device at an electronic device docking station
US9937735B1 (en) 2017-04-20 2018-04-10 Datamax—O'Neil Corporation Self-strip media module
US9939259B2 (en) 2012-10-04 2018-04-10 Hand Held Products, Inc. Measuring object dimensions using mobile computer
US9940497B2 (en) 2016-08-16 2018-04-10 Hand Held Products, Inc. Minimizing laser persistence on two-dimensional image sensors
US9949005B2 (en) 2015-06-18 2018-04-17 Hand Held Products, Inc. Customizable headset
US9946962B2 (en) 2016-09-13 2018-04-17 Datamax-O'neil Corporation Print precision improvement over long print jobs
US9953296B2 (en) 2013-01-11 2018-04-24 Hand Held Products, Inc. System, method, and computer-readable medium for managing edge devices
US9955522B2 (en) 2015-07-07 2018-04-24 Hand Held Products, Inc. WiFi enable based on cell signals
US9954871B2 (en) 2015-05-06 2018-04-24 Hand Held Products, Inc. Method and system to protect software-based network-connected devices from advanced persistent threat
US9955099B2 (en) 2016-06-21 2018-04-24 Hand Held Products, Inc. Minimum height CMOS image sensor
US9978088B2 (en) 2015-05-08 2018-05-22 Hand Held Products, Inc. Application independent DEX/UCS interface
US9984267B2 (en) 2014-01-08 2018-05-29 Hand Held Products, Inc. Indicia reader having unitary-construction
US9984685B2 (en) 2014-11-07 2018-05-29 Hand Held Products, Inc. Concatenated expected responses for speech recognition using expected response boundaries to determine corresponding hypothesis boundaries
US9984366B1 (en) 2017-06-09 2018-05-29 Hand Held Products, Inc. Secure paper-free bills in workflow applications
US9990784B2 (en) 2016-02-05 2018-06-05 Hand Held Products, Inc. Dynamic identification badge
US9990524B2 (en) 2016-06-16 2018-06-05 Hand Held Products, Inc. Eye gaze detection controlled indicia scanning system and method
US9997935B2 (en) 2015-01-08 2018-06-12 Hand Held Products, Inc. System and method for charging a barcode scanner
US10002274B2 (en) 2013-09-11 2018-06-19 Hand Held Products, Inc. Handheld indicia reader having locking endcap
US10007112B2 (en) 2015-05-06 2018-06-26 Hand Held Products, Inc. Hands-free human machine interface responsive to a driver of a vehicle
US10007858B2 (en) 2012-05-15 2018-06-26 Honeywell International Inc. Terminals and methods for dimensioning objects
US10026187B2 (en) 2016-01-12 2018-07-17 Hand Held Products, Inc. Using image data to calculate an object's weight
US10022993B2 (en) 2016-12-02 2018-07-17 Datamax-O'neil Corporation Media guides for use in printers and methods for using the same
US10026377B2 (en) 2015-11-12 2018-07-17 Hand Held Products, Inc. IRDA converter tag
US10025314B2 (en) 2016-01-27 2018-07-17 Hand Held Products, Inc. Vehicle positioning and object avoidance
US10035367B1 (en) 2017-06-21 2018-07-31 Datamax-O'neil Corporation Single motor dynamic ribbon feedback system for a printer
US10038716B2 (en) 2015-05-01 2018-07-31 Hand Held Products, Inc. System and method for regulating barcode data injection into a running application on a smart device
US10044880B2 (en) 2016-12-16 2018-08-07 Datamax-O'neil Corporation Comparing printer models
US10042593B2 (en) 2016-09-02 2018-08-07 Datamax-O'neil Corporation Printer smart folders using USB mass storage profile
US10049290B2 (en) 2014-12-31 2018-08-14 Hand Held Products, Inc. Industrial vehicle positioning system and method
US10051446B2 (en) 2015-03-06 2018-08-14 Hand Held Products, Inc. Power reports in wireless scanner systems
US10049245B2 (en) 2012-06-20 2018-08-14 Metrologic Instruments, Inc. Laser scanning code symbol reading system providing control over length of laser scan line projected onto a scanned object using dynamic range-dependent scan angle control
US10055625B2 (en) 2016-04-15 2018-08-21 Hand Held Products, Inc. Imaging barcode reader with color-separated aimer and illuminator
US10060729B2 (en) 2014-10-21 2018-08-28 Hand Held Products, Inc. Handheld dimensioner with data-quality indication
US10061565B2 (en) 2015-01-08 2018-08-28 Hand Held Products, Inc. Application development using mutliple primary user interfaces
US10061118B2 (en) 2016-02-04 2018-08-28 Hand Held Products, Inc. Beam shaping system and scanner
US10064005B2 (en) 2015-12-09 2018-08-28 Hand Held Products, Inc. Mobile device with configurable communication technology modes and geofences
US10066982B2 (en) 2015-06-16 2018-09-04 Hand Held Products, Inc. Calibrating a volume dimensioner
US10084556B1 (en) 2017-10-20 2018-09-25 Hand Held Products, Inc. Identifying and transmitting invisible fence signals with a mobile data terminal
US10085101B2 (en) 2016-07-13 2018-09-25 Hand Held Products, Inc. Systems and methods for determining microphone position
US10097681B2 (en) 2017-06-05 2018-10-09 Hand Held Products, Inc. Managing energy usage in mobile devices

Families Citing this family (37)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103780847A (en) 2012-10-24 2014-05-07 霍尼韦尔国际公司 Chip on board-based highly-integrated imager
US9070032B2 (en) 2013-04-10 2015-06-30 Hand Held Products, Inc. Method of programming a symbol reading system
US9930142B2 (en) 2013-05-24 2018-03-27 Hand Held Products, Inc. System for providing a continuous communication link with a symbol reading device
US9141839B2 (en) 2013-06-07 2015-09-22 Hand Held Products, Inc. System and method for reading code symbols at long range using source power control
US9239950B2 (en) 2013-07-01 2016-01-19 Hand Held Products, Inc. Dimensioning system
US9250652B2 (en) 2013-07-02 2016-02-02 Hand Held Products, Inc. Electronic device case
US9773142B2 (en) 2013-07-22 2017-09-26 Hand Held Products, Inc. System and method for selectively reading code symbols
US9297900B2 (en) 2013-07-25 2016-03-29 Hand Held Products, Inc. Code symbol reading system having adjustable object detection
US9082023B2 (en) 2013-09-05 2015-07-14 Hand Held Products, Inc. Method for operating a laser scanner
US9572901B2 (en) 2013-09-06 2017-02-21 Hand Held Products, Inc. Device having light source to reduce surface pathogens
US9251411B2 (en) 2013-09-24 2016-02-02 Hand Held Products, Inc. Augmented-reality signature capture
US9165174B2 (en) 2013-10-14 2015-10-20 Hand Held Products, Inc. Indicia reader
US9800293B2 (en) 2013-11-08 2017-10-24 Hand Held Products, Inc. System for configuring indicia readers using NFC technology
US9530038B2 (en) 2013-11-25 2016-12-27 Hand Held Products, Inc. Indicia-reading system
CN204009928U (en) 2013-12-12 2014-12-10 手持产品公司 Laser scanner
US9665757B2 (en) 2014-03-07 2017-05-30 Hand Held Products, Inc. Indicia reader for size-limited applications
US9224027B2 (en) 2014-04-01 2015-12-29 Hand Held Products, Inc. Hand-mounted indicia-reading device with finger motion triggering
US9301427B2 (en) 2014-05-13 2016-03-29 Hand Held Products, Inc. Heat-dissipation structure for an indicia reading module
US9277668B2 (en) 2014-05-13 2016-03-01 Hand Held Products, Inc. Indicia-reading module with an integrated flexible circuit
US9280693B2 (en) 2014-05-13 2016-03-08 Hand Held Products, Inc. Indicia-reader housing with an integrated optical structure
US9542746B2 (en) * 2014-06-13 2017-01-10 Xerox Corporation Method and system for spatial characterization of an imaging system
US9794392B2 (en) 2014-07-10 2017-10-17 Hand Held Products, Inc. Mobile-phone adapter for electronic transactions
CN104089684B (en) * 2014-07-11 2017-02-15 重庆长安汽车股份有限公司 Calibration of the fuel gauge car
US9443123B2 (en) 2014-07-18 2016-09-13 Hand Held Products, Inc. System and method for indicia verification
US9310609B2 (en) 2014-07-25 2016-04-12 Hand Held Products, Inc. Axially reinforced flexible scan element
US20160057230A1 (en) 2014-08-19 2016-02-25 Hand Held Products, Inc. Mobile computing device with data cognition software
US20160125873A1 (en) 2014-10-29 2016-05-05 Hand Held Products, Inc. Method and system for recognizing speech using wildcards in an expected response
US20160125342A1 (en) 2014-11-03 2016-05-05 Hand Held Products, Inc. Directing an inspector through an inspection
US20160125217A1 (en) 2014-11-05 2016-05-05 Hand Held Products, Inc. Barcode scanning system using wearable device with embedded camera
EP3043235B1 (en) 2014-12-31 2018-06-20 Hand Held Products, Inc. Reconfigurable sled for a mobile device
US20160232891A1 (en) 2015-02-11 2016-08-11 Hand Held Products, Inc. Methods for training a speech recognition system
US9250712B1 (en) 2015-03-20 2016-02-02 Hand Held Products, Inc. Method and application for scanning a barcode with a smart device while continuously running and displaying an application on the smart device display
US20160292477A1 (en) 2015-03-31 2016-10-06 Hand Held Products, Inc. Aimer for barcode scanning
US20160377414A1 (en) * 2015-06-23 2016-12-29 Hand Held Products, Inc. Optical pattern projector
EP3118576B1 (en) * 2015-07-15 2018-09-12 Hand Held Products, Inc. Mobile dimensioning device with dynamic accuracy compatible with nist standard
EP3285042A1 (en) 2015-07-16 2018-02-21 Hand Held Products, Inc. Method and system for dimensioning and imaging items
EP3156825B1 (en) 2015-10-16 2018-08-29 Hand Held Products, Inc. Dimensioning system with multipath interference mitigation

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060122497A1 (en) * 2004-11-12 2006-06-08 Glossop Neil D Device and method for ensuring the accuracy of a tracking device in a volume
US20070229665A1 (en) * 2006-03-31 2007-10-04 Tobiason Joseph D Robust field of view distortion calibration
US20100290665A1 (en) * 2009-05-13 2010-11-18 Applied Vision Company, Llc System and method for dimensioning objects using stereoscopic imaging
US20110188741A1 (en) * 2009-05-13 2011-08-04 Applied Vision Corporation System and method for dimensioning objects using stereoscopic imaging

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7715656B2 (en) * 2004-09-28 2010-05-11 Qualcomm Incorporated Magnification and pinching of two-dimensional images
US7451002B2 (en) * 2006-01-06 2008-11-11 Ge Medical Systems Global Technology Company, Llc Automated generation of transfer functions based upon machine data
US8958118B2 (en) * 2007-06-26 2015-02-17 Samsung Electronics Co., Ltd. Method and apparatus for adjusting size of object included in printing target to be printed at predetermined reduction ratio
US8405865B2 (en) * 2009-05-07 2013-03-26 Eastman Kodak Company Geometric correction of a recording apparatus

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060122497A1 (en) * 2004-11-12 2006-06-08 Glossop Neil D Device and method for ensuring the accuracy of a tracking device in a volume
US20070229665A1 (en) * 2006-03-31 2007-10-04 Tobiason Joseph D Robust field of view distortion calibration
US20100290665A1 (en) * 2009-05-13 2010-11-18 Applied Vision Company, Llc System and method for dimensioning objects using stereoscopic imaging
US20110188741A1 (en) * 2009-05-13 2011-08-04 Applied Vision Corporation System and method for dimensioning objects using stereoscopic imaging

Cited By (202)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9779546B2 (en) 2012-05-04 2017-10-03 Intermec Ip Corp. Volume dimensioning systems and methods
US9292969B2 (en) 2012-05-07 2016-03-22 Intermec Ip Corp. Dimensioning system calibration systems and methods
US10007858B2 (en) 2012-05-15 2018-06-26 Honeywell International Inc. Terminals and methods for dimensioning objects
US10049245B2 (en) 2012-06-20 2018-08-14 Metrologic Instruments, Inc. Laser scanning code symbol reading system providing control over length of laser scan line projected onto a scanned object using dynamic range-dependent scan angle control
US20140034731A1 (en) * 2012-07-31 2014-02-06 Datalogic ADC, Inc. Calibration and self-test in automated data reading systems
US9519810B2 (en) * 2012-07-31 2016-12-13 Datalogic ADC, Inc. Calibration and self-test in automated data reading systems
US9939259B2 (en) 2012-10-04 2018-04-10 Hand Held Products, Inc. Measuring object dimensions using mobile computer
US9841311B2 (en) 2012-10-16 2017-12-12 Hand Held Products, Inc. Dimensioning system
US9953296B2 (en) 2013-01-11 2018-04-24 Hand Held Products, Inc. System, method, and computer-readable medium for managing edge devices
US9784566B2 (en) 2013-03-13 2017-10-10 Intermec Ip Corp. Systems and methods for enhancing dimensioning
US9682625B2 (en) 2013-05-24 2017-06-20 Hand Held Products, Inc. System and method for display of information using a vehicle-mount computer
US9616749B2 (en) 2013-05-24 2017-04-11 Hand Held Products, Inc. System and method for display of information using a vehicle-mount computer
US10013591B2 (en) 2013-06-26 2018-07-03 Hand Held Products, Inc. Code symbol reading system having adaptive autofocus
US9582698B2 (en) 2013-06-26 2017-02-28 Hand Held Products, Inc. Code symbol reading system having adaptive autofocus
US9235737B2 (en) 2013-06-28 2016-01-12 Hand Held Products, Inc. System having an improved user interface for reading code symbols
US9672398B2 (en) 2013-08-26 2017-06-06 Intermec Ip Corporation Aiming imagers
US9464885B2 (en) 2013-08-30 2016-10-11 Hand Held Products, Inc. System and method for package dimensioning
US10002274B2 (en) 2013-09-11 2018-06-19 Hand Held Products, Inc. Handheld indicia reader having locking endcap
US9984267B2 (en) 2014-01-08 2018-05-29 Hand Held Products, Inc. Indicia reader having unitary-construction
US9672507B2 (en) 2014-04-04 2017-06-06 Hand Held Products, Inc. Multifunction point of sale system
US9412242B2 (en) 2014-04-04 2016-08-09 Hand Held Products, Inc. Multifunction point of sale system
US9510140B2 (en) 2014-04-21 2016-11-29 Hand Held Products, Inc. Docking system and method using near field communication
US10073197B2 (en) 2014-04-29 2018-09-11 Hand Held Products, Inc. Autofocus lens system
US9581809B2 (en) 2014-04-29 2017-02-28 Hand Held Products, Inc. Autofocus lens system
US9478113B2 (en) 2014-06-27 2016-10-25 Hand Held Products, Inc. Cordless indicia reader with a multifunction coil for wireless charging and EAS deactivation
US9911295B2 (en) 2014-06-27 2018-03-06 Hand Held Products, Inc. Cordless indicia reader with a multifunction coil for wireless charging and EAS deactivation
US9976848B2 (en) 2014-08-06 2018-05-22 Hand Held Products, Inc. Dimensioning system with guided alignment
US9823059B2 (en) 2014-08-06 2017-11-21 Hand Held Products, Inc. Dimensioning system with guided alignment
EP2990911A1 (en) 2014-08-29 2016-03-02 Hand Held Products, Inc. Gesture-controlled computer system
EP3001368A1 (en) 2014-09-26 2016-03-30 Honeywell International Inc. System and method for workflow management
US9779276B2 (en) 2014-10-10 2017-10-03 Hand Held Products, Inc. Depth sensor based auto-focus system for an indicia scanner
EP3006893A1 (en) 2014-10-10 2016-04-13 Hand Held Products, Inc. Methods for improving the accuracy of dimensioning-system measurements
EP3007096A1 (en) 2014-10-10 2016-04-13 Hand Held Products, Inc. Depth sensor based auto-focus system for an indicia scanner
US9792582B2 (en) 2014-10-14 2017-10-17 Hand Held Products, Inc. Identifying inventory items in a storage facility
EP3009968A1 (en) 2014-10-15 2016-04-20 Vocollect, Inc. Systems and methods for worker resource management
US9557166B2 (en) 2014-10-21 2017-01-31 Hand Held Products, Inc. Dimensioning system with multipath interference mitigation
US9752864B2 (en) 2014-10-21 2017-09-05 Hand Held Products, Inc. Handheld dimensioning system with feedback
US9826220B2 (en) 2014-10-21 2017-11-21 Hand Held Products, Inc. Dimensioning system with feedback
US9762793B2 (en) 2014-10-21 2017-09-12 Hand Held Products, Inc. System and method for dimensioning
US10060729B2 (en) 2014-10-21 2018-08-28 Hand Held Products, Inc. Handheld dimensioner with data-quality indication
US9897434B2 (en) 2014-10-21 2018-02-20 Hand Held Products, Inc. Handheld dimensioning system with measurement-conformance feedback
EP3016023A1 (en) 2014-10-31 2016-05-04 Honeywell International Inc. Scanner with illumination system
US9924006B2 (en) 2014-10-31 2018-03-20 Hand Held Products, Inc. Adaptable interface for a mobile computing device
US9646189B2 (en) 2014-10-31 2017-05-09 Honeywell International, Inc. Scanner with illumination system
US9984685B2 (en) 2014-11-07 2018-05-29 Hand Held Products, Inc. Concatenated expected responses for speech recognition using expected response boundaries to determine corresponding hypothesis boundaries
US9767581B2 (en) 2014-12-12 2017-09-19 Hand Held Products, Inc. Auto-contrast viewfinder for an indicia reader
EP3035074A1 (en) 2014-12-18 2016-06-22 Hand Held Products, Inc. Collision-avoidance system and method
US9743731B2 (en) 2014-12-18 2017-08-29 Hand Held Products, Inc. Wearable sled system for a mobile computer device
US9761096B2 (en) 2014-12-18 2017-09-12 Hand Held Products, Inc. Active emergency exit systems for buildings
US9678536B2 (en) 2014-12-18 2017-06-13 Hand Held Products, Inc. Flip-open wearable computer
EP3035151A1 (en) 2014-12-18 2016-06-22 Hand Held Products, Inc. Wearable sled system for a mobile computer device
US9727769B2 (en) 2014-12-22 2017-08-08 Hand Held Products, Inc. Conformable hand mount for a mobile scanner
EP3037924A1 (en) 2014-12-22 2016-06-29 Hand Held Products, Inc. Augmented display and glove with markers as us user input device
US9564035B2 (en) 2014-12-22 2017-02-07 Hand Held Products, Inc. Safety system and method
EP3037951A1 (en) 2014-12-22 2016-06-29 Hand Held Products, Inc. Delayed trim of managed nand flash memory in computing devices
US10049246B2 (en) 2014-12-23 2018-08-14 Hand Held Products, Inc. Mini-barcode reading module with flash memory management
EP3037912A1 (en) 2014-12-23 2016-06-29 Hand Held Products, Inc. Tablet computer with interface channels
EP3038009A1 (en) 2014-12-23 2016-06-29 Hand Held Products, Inc. Method of barcode templating for enhanced decoding performance
EP3038010A1 (en) 2014-12-23 2016-06-29 Hand Held Products, Inc. Mini-barcode reading module with flash memory management
EP3038029A1 (en) 2014-12-26 2016-06-29 Hand Held Products, Inc. Product and location management via voice recognition
US9679178B2 (en) 2014-12-26 2017-06-13 Hand Held Products, Inc. Scanning improvements for saturated signals using automatic and fixed gain control methods
US9774940B2 (en) 2014-12-27 2017-09-26 Hand Held Products, Inc. Power configurable headband system and method
EP3040907A2 (en) 2014-12-27 2016-07-06 Hand Held Products, Inc. Acceleration-based motion tolerance and predictive coding
US9652653B2 (en) 2014-12-27 2017-05-16 Hand Held Products, Inc. Acceleration-based motion tolerance and predictive coding
EP3038030A1 (en) 2014-12-28 2016-06-29 Hand Held Products, Inc. Dynamic check digit utilization via electronic tag
EP3046032A2 (en) 2014-12-28 2016-07-20 Hand Held Products, Inc. Remote monitoring of vehicle diagnostic information
US9843660B2 (en) 2014-12-29 2017-12-12 Hand Held Products, Inc. Tag mounted distributed headset with electronics module
EP3040921A1 (en) 2014-12-29 2016-07-06 Hand Held Products, Inc. Confirming product location using a subset of a product identifier
EP3040908A1 (en) 2014-12-30 2016-07-06 Hand Held Products, Inc. Real-time adjustable window feature for barcode scanning and process of scanning barcode with adjustable window feature
EP3045953A1 (en) 2014-12-30 2016-07-20 Hand Held Products, Inc. Augmented reality vision barcode scanning system and method
US9830488B2 (en) 2014-12-30 2017-11-28 Hand Held Products, Inc. Real-time adjustable window feature for barcode scanning and process of scanning barcode with adjustable window feature
US9826106B2 (en) 2014-12-30 2017-11-21 Hand Held Products, Inc. System and method for detecting barcode printing errors
EP3040954A1 (en) 2014-12-30 2016-07-06 Hand Held Products, Inc. Point of sale (pos) code sensing apparatus
US9685049B2 (en) 2014-12-30 2017-06-20 Hand Held Products, Inc. Method and system for improving barcode scanner performance
US9898635B2 (en) 2014-12-30 2018-02-20 Hand Held Products, Inc. Point-of-sale (POS) code sensing apparatus
EP3040906A1 (en) 2014-12-30 2016-07-06 Hand Held Products, Inc. Visual feedback for code readers
US9879823B2 (en) 2014-12-31 2018-01-30 Hand Held Products, Inc. Reclosable strap assembly
US9721132B2 (en) 2014-12-31 2017-08-01 Hand Held Products, Inc. Reconfigurable sled for a mobile device
US9734639B2 (en) 2014-12-31 2017-08-15 Hand Held Products, Inc. System and method for monitoring an industrial vehicle
US10049290B2 (en) 2014-12-31 2018-08-14 Hand Held Products, Inc. Industrial vehicle positioning system and method
US9811650B2 (en) 2014-12-31 2017-11-07 Hand Held Products, Inc. User authentication system and method
EP3043443A1 (en) 2015-01-08 2016-07-13 Hand Held Products, Inc. Charge limit selection for variable power supply configuration
US9997935B2 (en) 2015-01-08 2018-06-12 Hand Held Products, Inc. System and method for charging a barcode scanner
US10061565B2 (en) 2015-01-08 2018-08-28 Hand Held Products, Inc. Application development using mutliple primary user interfaces
EP3043300A1 (en) 2015-01-09 2016-07-13 Honeywell International Inc. Restocking workflow prioritization
US9861182B2 (en) 2015-02-05 2018-01-09 Hand Held Products, Inc. Device for supporting an electronic tool on a user's hand
US9390596B1 (en) 2015-02-23 2016-07-12 Hand Held Products, Inc. Device, system, and method for determining the status of checkout lanes
US10051446B2 (en) 2015-03-06 2018-08-14 Hand Held Products, Inc. Power reports in wireless scanner systems
US9930050B2 (en) 2015-04-01 2018-03-27 Hand Held Products, Inc. Device management proxy for secure devices
US9852102B2 (en) 2015-04-15 2017-12-26 Hand Held Products, Inc. System for exchanging information between wireless peripherals and back-end systems via a peripheral hub
US9521331B2 (en) 2015-04-21 2016-12-13 Hand Held Products, Inc. Capturing a graphic information presentation
US9693038B2 (en) 2015-04-21 2017-06-27 Hand Held Products, Inc. Systems and methods for imaging
EP3086281A1 (en) 2015-04-21 2016-10-26 Hand Held Products, Inc. Systems and methods for imaging
US10038716B2 (en) 2015-05-01 2018-07-31 Hand Held Products, Inc. System and method for regulating barcode data injection into a running application on a smart device
US9891612B2 (en) 2015-05-05 2018-02-13 Hand Held Products, Inc. Intermediate linear positioning
US9954871B2 (en) 2015-05-06 2018-04-24 Hand Held Products, Inc. Method and system to protect software-based network-connected devices from advanced persistent threat
US10007112B2 (en) 2015-05-06 2018-06-26 Hand Held Products, Inc. Hands-free human machine interface responsive to a driver of a vehicle
US9978088B2 (en) 2015-05-08 2018-05-22 Hand Held Products, Inc. Application independent DEX/UCS interface
US9786101B2 (en) 2015-05-19 2017-10-10 Hand Held Products, Inc. Evaluating image values
USD792407S1 (en) 2015-06-02 2017-07-18 Hand Held Products, Inc. Mobile computer housing
US9507974B1 (en) 2015-06-10 2016-11-29 Hand Held Products, Inc. Indicia-reading systems having an interface with a user's nervous system
US10066982B2 (en) 2015-06-16 2018-09-04 Hand Held Products, Inc. Calibrating a volume dimensioner
US9892876B2 (en) 2015-06-16 2018-02-13 Hand Held Products, Inc. Tactile switch for a mobile electronic device
US9949005B2 (en) 2015-06-18 2018-04-17 Hand Held Products, Inc. Customizable headset
US9857167B2 (en) 2015-06-23 2018-01-02 Hand Held Products, Inc. Dual-projector three-dimensional scanner
US9955522B2 (en) 2015-07-07 2018-04-24 Hand Held Products, Inc. WiFi enable based on cell signals
US9835486B2 (en) 2015-07-07 2017-12-05 Hand Held Products, Inc. Mobile dimensioner apparatus for use in commerce
US10094650B2 (en) 2015-07-16 2018-10-09 Hand Held Products, Inc. Dimensioning and imaging items
US9488986B1 (en) 2015-07-31 2016-11-08 Hand Held Products, Inc. System and method for tracking an item on a pallet in a warehouse
WO2017024347A1 (en) * 2015-08-10 2017-02-16 Wisetech Global Limited Volumetric estimation methods, devices, & systems
US9853575B2 (en) 2015-08-12 2017-12-26 Hand Held Products, Inc. Angular motor shaft with rotational attenuation
US9911023B2 (en) 2015-08-17 2018-03-06 Hand Held Products, Inc. Indicia reader having a filtered multifunction image sensor
US9781681B2 (en) 2015-08-26 2017-10-03 Hand Held Products, Inc. Fleet power management through information storage sharing
EP3136219A1 (en) 2015-08-27 2017-03-01 Hand Held Products, Inc. Interactive display
US9798413B2 (en) 2015-08-27 2017-10-24 Hand Held Products, Inc. Interactive display
US9490540B1 (en) 2015-09-02 2016-11-08 Hand Held Products, Inc. Patch antenna
US9781502B2 (en) 2015-09-09 2017-10-03 Hand Held Products, Inc. Process and system for sending headset control information from a mobile device to a wireless headset
US9659198B2 (en) 2015-09-10 2017-05-23 Hand Held Products, Inc. System and method of determining if a surface is printed or a mobile device screen
US10083331B2 (en) 2015-09-11 2018-09-25 Hand Held Products, Inc. Positioning an object with respect to a target location
US9652648B2 (en) 2015-09-11 2017-05-16 Hand Held Products, Inc. Positioning an object with respect to a target location
US9805237B2 (en) 2015-09-18 2017-10-31 Hand Held Products, Inc. Cancelling noise caused by the flicker of ambient lights
US9646191B2 (en) 2015-09-23 2017-05-09 Intermec Technologies Corporation Evaluating images
US9916488B2 (en) 2015-09-23 2018-03-13 Intermec Technologies Corporation Evaluating images
EP3147151A1 (en) 2015-09-25 2017-03-29 Hand Held Products, Inc. A system and process for displaying information from a mobile computer in a vehicle
US10096099B2 (en) 2015-09-30 2018-10-09 Hand Held Products, Inc. Image-stitching for dimensioning
EP3151553A1 (en) 2015-09-30 2017-04-05 Hand Held Products, Inc. A self-calibrating projection apparatus and process
US10049249B2 (en) 2015-09-30 2018-08-14 Hand Held Products, Inc. Indicia reader safety
US9767337B2 (en) 2015-09-30 2017-09-19 Hand Held Products, Inc. Indicia reader safety
US9844956B2 (en) 2015-10-07 2017-12-19 Intermec Technologies Corporation Print position correction
US9656487B2 (en) 2015-10-13 2017-05-23 Intermec Technologies Corporation Magnetic media holder for printer
US9975324B2 (en) 2015-10-13 2018-05-22 Intermec Technologies Corporation Magnetic media holder for printer
EP3159770A1 (en) 2015-10-19 2017-04-26 Hand Held Products, Inc. Quick release dock system and method
US9727083B2 (en) 2015-10-19 2017-08-08 Hand Held Products, Inc. Quick release dock system and method
US10057442B2 (en) 2015-10-27 2018-08-21 Intermec Technologies Corporation Media width sensing
US9876923B2 (en) 2015-10-27 2018-01-23 Intermec Technologies Corporation Media width sensing
US9883063B2 (en) 2015-10-27 2018-01-30 Intermec Technologies Corporation Media width sensing
US9684809B2 (en) 2015-10-29 2017-06-20 Hand Held Products, Inc. Scanner assembly with removable shock mount
EP3165939A1 (en) 2015-10-29 2017-05-10 Hand Held Products, Inc. Dynamically created and updated indoor positioning map
US10026377B2 (en) 2015-11-12 2018-07-17 Hand Held Products, Inc. IRDA converter tag
US9680282B2 (en) 2015-11-17 2017-06-13 Hand Held Products, Inc. Laser aiming for mobile devices
US9697401B2 (en) 2015-11-24 2017-07-04 Hand Held Products, Inc. Add-on device with configurable optics for an image scanner for scanning barcodes
EP3173980A1 (en) 2015-11-24 2017-05-31 Intermec Technologies Corporation Automatic print speed control for indicia printer
US9864891B2 (en) 2015-11-24 2018-01-09 Intermec Technologies Corporation Automatic print speed control for indicia printer
US10064005B2 (en) 2015-12-09 2018-08-28 Hand Held Products, Inc. Mobile device with configurable communication technology modes and geofences
US9935946B2 (en) 2015-12-16 2018-04-03 Hand Held Products, Inc. Method and system for tracking an electronic device at an electronic device docking station
US9844158B2 (en) 2015-12-18 2017-12-12 Honeywell International, Inc. Battery cover locking mechanism of a mobile terminal and method of manufacturing the same
US9729744B2 (en) 2015-12-21 2017-08-08 Hand Held Products, Inc. System and method of border detection on a document and for producing an image of the document
US9727840B2 (en) 2016-01-04 2017-08-08 Hand Held Products, Inc. Package physical characteristic identification system and method in supply chain management
US9805343B2 (en) 2016-01-05 2017-10-31 Intermec Technologies Corporation System and method for guided printer servicing
EP3193188A1 (en) 2016-01-12 2017-07-19 Hand Held Products, Inc. Programmable reference beacons
US10026187B2 (en) 2016-01-12 2018-07-17 Hand Held Products, Inc. Using image data to calculate an object's weight
EP3193146A1 (en) 2016-01-14 2017-07-19 Hand Held Products, Inc. Multi-spectral imaging using longitudinal chromatic aberrations
US9945777B2 (en) 2016-01-14 2018-04-17 Hand Held Products, Inc. Multi-spectral imaging using longitudinal chromatic aberrations
EP3200120A1 (en) 2016-01-26 2017-08-02 Hand Held Products, Inc. Enhanced matrix symbol error correction method
US10025314B2 (en) 2016-01-27 2018-07-17 Hand Held Products, Inc. Vehicle positioning and object avoidance
US10061118B2 (en) 2016-02-04 2018-08-28 Hand Held Products, Inc. Beam shaping system and scanner
US9990784B2 (en) 2016-02-05 2018-06-05 Hand Held Products, Inc. Dynamic identification badge
US9955072B2 (en) 2016-03-09 2018-04-24 Hand Held Products, Inc. Imaging device for producing high resolution images using subpixel shifts and method of using same
US9674430B1 (en) 2016-03-09 2017-06-06 Hand Held Products, Inc. Imaging device for producing high resolution images using subpixel shifts and method of using same
EP3217353A1 (en) 2016-03-09 2017-09-13 Hand Held Products, Inc. An imaging device for producing high resolution images using subpixel shifts and method of using same
EP3239891A1 (en) 2016-04-14 2017-11-01 Hand Held Products, Inc. Customizable aimer system for indicia reading terminal
US10055625B2 (en) 2016-04-15 2018-08-21 Hand Held Products, Inc. Imaging barcode reader with color-separated aimer and illuminator
EP3232367A1 (en) 2016-04-15 2017-10-18 Hand Held Products, Inc. Imaging barcode reader with color separated aimer and illuminator
EP3239892A1 (en) 2016-04-26 2017-11-01 Hand Held Products, Inc. Indicia reading device and methods for decoding decodable indicia employing stereoscopic imaging
US9727841B1 (en) 2016-05-20 2017-08-08 Vocollect, Inc. Systems and methods for reducing picking operation errors
EP3246863A1 (en) 2016-05-20 2017-11-22 Vocollect, Inc. Systems and methods for reducing picking operation errors
EP3252703A1 (en) 2016-06-03 2017-12-06 Hand Held Products, Inc. Wearable metrological apparatus
US9940721B2 (en) 2016-06-10 2018-04-10 Hand Held Products, Inc. Scene change detection in a dimensioner
EP3255376A1 (en) 2016-06-10 2017-12-13 Hand Held Products, Inc. Scene change detection in a dimensioner
EP3258210A1 (en) 2016-06-15 2017-12-20 Hand Held Products, Inc. Automatic mode switching in a volume dimensioner
US9990524B2 (en) 2016-06-16 2018-06-05 Hand Held Products, Inc. Eye gaze detection controlled indicia scanning system and method
US9955099B2 (en) 2016-06-21 2018-04-24 Hand Held Products, Inc. Minimum height CMOS image sensor
US9876957B2 (en) 2016-06-21 2018-01-23 Hand Held Products, Inc. Dual mode image sensor and method of using same
US9864887B1 (en) 2016-07-07 2018-01-09 Hand Held Products, Inc. Energizing scanners
US10097949B2 (en) 2016-07-08 2018-10-09 Hand Held Products, Inc. Device, system, and method for determining the status of lanes
US10085101B2 (en) 2016-07-13 2018-09-25 Hand Held Products, Inc. Systems and methods for determining microphone position
US9662900B1 (en) 2016-07-14 2017-05-30 Datamax-O'neil Corporation Wireless thermal printhead system and method
US9902175B1 (en) 2016-08-02 2018-02-27 Datamax-O'neil Corporation Thermal printer having real-time force feedback on printhead pressure and method of using same
US9919547B2 (en) 2016-08-04 2018-03-20 Datamax-O'neil Corporation System and method for active printing consistency control and damage protection
US9940497B2 (en) 2016-08-16 2018-04-10 Hand Held Products, Inc. Minimizing laser persistence on two-dimensional image sensors
US10042593B2 (en) 2016-09-02 2018-08-07 Datamax-O'neil Corporation Printer smart folders using USB mass storage profile
US9805257B1 (en) 2016-09-07 2017-10-31 Datamax-O'neil Corporation Printer method and apparatus
US9946962B2 (en) 2016-09-13 2018-04-17 Datamax-O'neil Corporation Print precision improvement over long print jobs
US9881194B1 (en) 2016-09-19 2018-01-30 Hand Held Products, Inc. Dot peen mark image acquisition
US9701140B1 (en) 2016-09-20 2017-07-11 Datamax-O'neil Corporation Method and system to calculate line feed error in labels on a printer
US9931867B1 (en) 2016-09-23 2018-04-03 Datamax-O'neil Corporation Method and system of determining a width of a printer ribbon
US9785814B1 (en) 2016-09-23 2017-10-10 Hand Held Products, Inc. Three dimensional aimer for barcode scanning
EP3220369A1 (en) 2016-09-29 2017-09-20 Hand Held Products, Inc. Monitoring user biometric parameters with nanotechnology in personal locator beacon
US9936278B1 (en) 2016-10-03 2018-04-03 Vocollect, Inc. Communication headsets and systems for mobile application control and power savings
US9892356B1 (en) 2016-10-27 2018-02-13 Hand Held Products, Inc. Backlit display detection and radio signature recognition
US10022993B2 (en) 2016-12-02 2018-07-17 Datamax-O'neil Corporation Media guides for use in printers and methods for using the same
US10044880B2 (en) 2016-12-16 2018-08-07 Datamax-O'neil Corporation Comparing printer models
US9827796B1 (en) 2017-01-03 2017-11-28 Datamax-O'neil Corporation Automatic thermal printhead cleaning system
US10071575B2 (en) 2017-01-18 2018-09-11 Datamax-O'neil Corporation Printers and methods for detecting print media thickness therein
US9802427B1 (en) 2017-01-18 2017-10-31 Datamax-O'neil Corporation Printers and methods for detecting print media thickness therein
US9849691B1 (en) 2017-01-26 2017-12-26 Datamax-O'neil Corporation Detecting printing ribbon orientation
US9908351B1 (en) 2017-02-27 2018-03-06 Datamax-O'neil Corporation Segmented enclosure
US9937735B1 (en) 2017-04-20 2018-04-10 Datamax—O'Neil Corporation Self-strip media module
US10097681B2 (en) 2017-06-05 2018-10-09 Hand Held Products, Inc. Managing energy usage in mobile devices
US9984366B1 (en) 2017-06-09 2018-05-29 Hand Held Products, Inc. Secure paper-free bills in workflow applications
US10035367B1 (en) 2017-06-21 2018-07-31 Datamax-O'neil Corporation Single motor dynamic ribbon feedback system for a printer
US10084556B1 (en) 2017-10-20 2018-09-25 Hand Held Products, Inc. Identifying and transmitting invisible fence signals with a mobile data terminal

Also Published As

Publication number Publication date Type
US20140049635A1 (en) 2014-02-20 application

Similar Documents

Publication Publication Date Title
US7219841B2 (en) Device and system for verifying quality of bar codes
US9007368B2 (en) Dimensioning system calibration systems and methods
US6606579B1 (en) Method of combining spectral data with non-spectral data in a produce recognition system
US20130293539A1 (en) Volume dimensioning systems and methods
US20100070209A1 (en) Method and apparatus for adaptively handling level measurements under unstable conditions
US20150019391A1 (en) Detecting item interaction and movement
US5878379A (en) Coarse volume measurement with interlock
US20110077909A1 (en) Portable computing device and method for asset management in a logistics system
US7271719B2 (en) RFID system for monitoring food hygiene
US20130342653A1 (en) Cargo sensing
US20130329013A1 (en) Hand held dimension capture apparatus, system and method
US20140071430A1 (en) Method for estimating volume
US20140104414A1 (en) Dimensioning system
US8643717B2 (en) System and method for measuring irregular objects with a single camera
EP3007096A1 (en) Depth sensor based auto-focus system for an indicia scanner
US20140379613A1 (en) Information processing device, information processing system, information processing method, and computer-readable non-transitory storage medium
US20140379588A1 (en) System and method for waste managment
US6373579B1 (en) Portable measurement apparatus for determinging the dimensions of an object and associated method
US20150210199A1 (en) Shelving and package locating systems for delivery vehicles
US20160109219A1 (en) Handheld dimensioning system with measurement-conformance feedback
US20080061937A1 (en) Rfid reader and range indicating method for the rfid reader
US20090207024A1 (en) Utilization of motion and spatial identification in mobile rfid interrogator
US8224576B2 (en) Environmental sensing and communication
US20130278386A1 (en) Portable encoded information reading terminal configured to adjust transmit power level
US20160040982A1 (en) Dimensioning system with guided alignment

Legal Events

Date Code Title Description
AS Assignment

Owner name: INTERMEC IP CORP., SOUTH CAROLINA

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:LAFFARGUE, FRANCK;THURIES, SERGE;ACKLEY, H. SPRAGUE;SIGNING DATES FROM 20130318 TO 20130424;REEL/FRAME:033836/0462