Abstract: A computing device includes: a housing having a plurality of sides defining a housing interior; a first outer lens disposed on a first side of the housing; a second outer lens disposed on a second side of the housing; an image sensor in the housing interior, the image sensor having first and second capture regions; an optical divider in the housing interior, the optical divider configured to (i) direct light from the first outer lens along a first optical path, and (ii) direct light from the second outer lens along a second optical path; and a lens assembly between the optical divider and the image sensor, the lens assembly configured to (i) focus light received along the first optical path onto the first capture region of the image sensor, and (ii) focus light received along the second optical path onto the second capture region of the image sensor.

Abstract: A method includes: monitoring sensor data including one or more representations of a treaded surface captured by a device; detecting, based on the sensor data, that the device has traversed a boundary of the treaded surface; in response to detecting that the device has traversed the boundary, determining a scan trigger point within the one or more representations; and generating a profile of the treaded surface from the one or more representations based on the scan trigger point.

Abstract: A computing device includes: a housing having a plurality of sides defining a housing interior; a first outer lens disposed on a first side of the housing; a second outer lens disposed on a second side of the housing; an image sensor in the housing interior, the image sensor having first and second capture regions; an optical divider in the housing interior, the optical divider configured to (i) direct light from the first outer lens along a first optical path, and (ii) direct light from the second outer lens along a second optical path; and a lens assembly between the optical divider and the image sensor, the lens assembly configured to (i) focus light received along the first optical path onto the first capture region of the image sensor, and (ii) focus light received along the second optical path onto the second capture region of the image sensor.

Abstract: A method includes: responsive to a scan command, controlling a sensor assembly to scan a machine-readable indicium within a sensor field of view; obtaining an image corresponding to the sensor field of view; determining, from the machine-readable indicium, a decoded item identifier and a scan confidence level associated with the decoded item identifier; determining, from the image, a classified item identifier corresponding to the machine-readable indicium, and a classification confidence level associated with the classified item identifier; selecting, based on the scan confidence level and the classification confidence level, one of the decoded item identifier and the classified item identifier; and generating output data based on the selected one of the decoded item identifier and the classified item identifier.

Abstract: A computing device for extracting target data from a source document includes: a memory storing target data extraction rules; a processor connected with the memory, the processor configured to: obtain text recognition data extracted from an image of the source document, the text recognition data indicating locations of text structures in the source document; define text lines based on the text recognition data; identify a reference string from the text recognition data; select a subset of the text lines based on a location of the reference string and the target data extraction rules; and output the subset of the text lines as the target data.

Abstract: A computing device for extracting target data from a source document includes: a memory storing target data extraction rules; a processor connected with the memory, the processor configured to: obtain text recognition data extracted from an image of the source document, the text recognition data indicating locations of text structures in the source document; define text lines based on the text recognition data; identify a reference string from the text recognition data; select a subset of the text lines based on a location of the reference string and the target data extraction rules; and output the subset of the text lines as the target data.

Abstract: A method for classifying depth scan data at a computing device includes: obtaining, at the computing device, a set of depth measurements and a graphical representation of the depth measurements; automatically selecting, at the computing device, a subset of the depth measurements indicating a region of interest; rendering, on a display of the computing device, an image including (i) the graphical representation of the depth measurements and (ii) a graphical indication of the region of interest overlaid on the graphical representation of the depth measurements; receiving, via an input device, a selection associated with the image; and generating a region of interest indicator based on the subset of the depth measurements and the selection.

Abstract: A computing device includes: a memory storing an audio sequence and a reference attribute associated with playback of the audio sequence; a speaker; a microphone; an audio enclosure supporting the speaker and the microphone; a processor configured to: simultaneously (i) control the speaker to play the audio sequence, and (ii) control the microphone to capture a test recording corresponding to playback of the audio sequence; based on a comparison of the reference attribute to a test attribute associated with the test recording, detect occlusion of the audio enclosure; and in response to detecting occlusion of the audio enclosure, generate a notification message.

Abstract: A method of detecting sensor obstructions in a computing device includes: at an emitter, emitting a beam of light through a scan window toward a treaded surface; at an image sensor, for a sequence of positions of the computing device along the treaded surface: capturing a sequence of images corresponding to the sequence of positions, each image in the sequence having a first region and a second region; wherein the first regions depict a first subset of reflections of the beam of light originating from a first depth range; and wherein the second regions depict a second subset of the reflections originating from a second depth range; at a controller: receiving the sequence of images; determining, based on the second regions, whether an intensity of the second subset of the reflections exceeds a occlusion threshold; and when the determination is affirmative, generating an alert indicating obstruction of the scan window.

Abstract: A device for measuring tread depth includes: an image sensor; first and second depth sensing modules spaced apart along a separation axis, each including (i) an emitter configured to emit a beam of light, and (ii) an optical assembly configured to direct reflections of the beam of light onto a respective region of the image sensor; a controller connected to the image sensor and configured, responsive to the device traversing a treaded surface, to: receive, from the image sensor, a sequence of images corresponding to sequential positions of the device traversing the treaded surface in a travel direction substantially perpendicular to the separation axis, the sequence of images depicting successive reflections of the beams from the treaded surface; determine, for each image in the sequence of images, a first depth measurement and a second depth measurement; and store, in a memory, the first and second depth measurements.

Abstract: A method of detecting sensor obstructions in a computing device includes: at an emitter, emitting a beam of light through a scan window toward a treaded surface; at an image sensor, for a sequence of positions of the computing device along the treaded surface: capturing a sequence of images corresponding to the sequence of positions, each image in the sequence having a first region and a second region; wherein the first regions depict a first subset of reflections of the beam of light originating from a first depth range; and wherein the second regions depict a second subset of the reflections originating from a second depth range; at a controller: receiving the sequence of images; determining, based on the second regions, whether an intensity of the second subset of the reflections exceeds a occlusion threshold; and when the determination is affirmative, generating an alert indicating obstruction of the scan window.

Abstract: A method for classifying depth scan data at a computing device includes: obtaining, at the computing device, a set of depth measurements and a graphical representation of the depth measurements; automatically selecting, at the computing device, a subset of the depth measurements indicating a region of interest; rendering, on a display of the computing device, an image including (i) the graphical representation of the depth measurements and (ii) a graphical indication of the region of interest overlaid on the graphical representation of the depth measurements; receiving, via an input device, a selection associated with the image; and generating a region of interest indicator based on the subset of the depth measurements and the selection.

Abstract: A device for measuring tread depth includes: an image sensor; first and second depth sensing modules spaced apart along a separation axis, each including (i) an emitter configured to emit a beam of light, and (ii) an optical assembly configured to direct reflections of the beam of light onto a respective region of the image sensor; a controller connected to the image sensor and configured, responsive to the device traversing a treaded surface, to: receive, from the image sensor, a sequence of images corresponding to sequential positions of the device traversing the treaded surface in a travel direction substantially perpendicular to the separation axis, the sequence of images depicting successive reflections of the beams from the treaded surface; determine, for each image in the sequence of images, a first depth measurement and a second depth measurement; and store, in a memory, the first and second depth measurements.

Abstract: Embodiments of the present invention generally relate to the field of inventory management. In an embodiment, the present application is a method of reading barcodes. The method includes capturing, by an imaging assembly, an image of a target, the target including: (i) a symbol encoding a payload data, and (ii) a set of one or more alphanumeric characters containing a payload descriptor associated with the symbol; decoding, by a first processor, the symbol to extract the payload data; performing, by a second processor, an optical character recognition analysis on the set of one or more alphanumeric characters to identify the payload descriptor associated with the symbol; associating the payload data with the payload descriptor, resulting in an associated pair; and forwarding the associated pair to a third processor for further processing of the payload data based on the payload descriptor.

Abstract: A method of decoding spatially related indicia includes: at an imaging controller, controlling an image sensor to capture an image containing a plurality of indicia; at the imaging controller, detecting image positions of each of the indicia; at the imaging controller, for each of a plurality of indicia pairs: determining whether the image positions of the indicia in the pair have a predefined spatial relationship; and responsive to determining that the indicia in the pair have the predefined spatial relationship, presenting (i) values decoded from the indicia in the pair, and (ii) an indicator that the decoded values are related.

Abstract: A method in a data capture device of dynamically capturing indicia includes: responsive to initiation of a capture session, receiving a quantity indicator defining an expected number of the indicia to be captured during the capture session; capturing an indicium from a set of indicia and storing a string decoded from the indicium in a capture session buffer; responsive to storing the string, determining whether a number of strings in the capture session buffer matches the expected number defined by the quantity indicator; when the number of strings in the capture session buffer does not match the expected number, repeating (i) the capturing and the storing for a further indicium from the set of indicia, and (ii) the determining; and when the number of strings in the capture session buffer matches the expected number, generating a session termination signal to terminate the capture session.

Abstract: Implementations relate to a device and method for barcode scanning and dimensioning. In some implementations, the method includes acquiring a two-dimensional (2D) preview image of an object, and processing the 2D preview image to determine one or more dark areas and to determine a location of a code on the object. The method also includes acquiring a three-dimensional (3D) image of the object based on the one or more dark areas, and processing the 3D image to determine depth data and to determine dimensions of the object. The method also includes acquiring a 2D data capture image of the object based on the depth data in the processed 3D image, where the 2D data capture image captures the code. The method also includes reading the code based on the 2D data capture image.

Abstract: Disclosed herein are methods and systems for highlighting box surfaces and edges in mobile box dimensioning. An embodiment takes the form of a method that includes obtaining a three-dimensional (3D) point cloud from a depth sensor when the depth sensor is positioned such that an aiming indicator appears on a first surface of an object; processing the 3D point cloud to identify an extent of the first surface; further processing the 3D point cloud to identify a second surface that is adjacent and normal to the first surface, and to identify an extent of the second surface; and displaying at least part of the 3D point cloud via a user interface, including displaying the identified first surface in a first color and the identified second surface in a second color different from the first color.

Abstract: Implementations relate to a device and method for barcode scanning and dimensioning. In some implementations, the method includes acquiring a two-dimensional (2D) preview image of an object, and processing the 2D preview image to determine one or more dark areas and to determine a location of a code on the object. The method also includes acquiring a three-dimensional (3D) image of the object based on the one or more dark areas, and processing the 3D image to determine depth data and to determine dimensions of the object. The method also includes acquiring a 2D data capture image of the object based on the depth data in the processed 3D image, where the 2D data capture image captures the code. The method also includes reading the code based on the 2D data capture image.

Abstract: A method and apparatus with predictive triggering includes a housing including electronics operable to perform a process that can be activated by a user depressing a trigger with a finger. A trigger is operable to activate the electronics to perform the process. A proximity sensor is operable to detect a user's finger in proximity to the trigger. A processor coupled to the electronics, trigger, and proximity sensor, wherein when the proximity sensor detects a user's finger in proximity to the trigger, before the user's finger actually depresses the trigger, the processor initiates activation of the electronics to perform a portion of the process, and when the user's finger depresses the trigger, the processor directs the electronics to complete the process.