Zebra Technologies Corporation

Christopher M West

James Matthew Witherspoon

Matthew Lawrence Horner

Abhilash Gururaja

Usha Prasad

David D Landron

Thomas Conticello

Anthony P DeLuca

Ankan Basak

Matthew M Degen

Techniques for optimizing one or more imaging settings for a machine vision job are provided. An example method includes configuring a machine vision job by setting a plurality of banks of imaging parameters, with each of the plurality of banks of imaging parameters being different from each other; transmitting the machine vision job to an imaging device; and executing the machine vision job on the imaging device to: (a) capture an image with the imaging device operating pursuant to one of the plurality of banks of imaging parameters; (b) attempt to decode a barcode within the image; (c) responsive to successfully decoding the barcode within the image, successfully ending the barcode reader tool; and (d) responsive to unsuccessfully decoding the barcode within the image, repeating (a)-(d) with another one of the one of the plurality of banks of imaging parameters.

Systems and methods to optimize imaging settings and image capture for a machine vision job

Methods and systems for facilitating selection of tools for one or more machine vision jobs are disclosed herein. An example method may be performed by one or more processors and includes displaying, via a display screen, an interactive graphical user interface (GUI) of an application, the application configured to generate job scripts for imaging devices to execute and the application operating in a job construction mode. The method also includes displaying an image within the GUI and detecting a selection of a portion of the image. The method further includes analyzing the portion of the image to determine a corresponding tool for processing the portion of the image and displaying, within the interactive GUI, a user-selectable option to add the corresponding tool to a machine vision job.

Systems and methods for facilitating selection of tools for machine vision jobs

Example systems and methods for interacting with overlapping regions of interest (ROIs) in machine vision applications are disclosed. An example system includes a machine vision camera, and a client computing device coupled to the machine vision camera. The client computing device configured to: receive an image from the machine vision camera; present the image on a canvas, wherein the canvas is part of a first user interface of a machine vision application displayed on the client computing device; present a first ROI associated with a first machine vision tool on the canvas; present a second ROI associated with a second machine vision tool on the canvas; and target the first ROI or the second ROI as a targeted ROI for interaction based upon distances from a pointer displayed on the canvas to features of the first ROI and the second ROI.

Systems and methods for interacting with overlapping regions of interest in machine vision applications

Systems and methods for enhancing image content captured by a machine vision camera are disclosed herein. An example method includes receiving an image captured by a machine vision camera that includes a plurality of visual features, determining bounds of a bounding region for each respective visual feature, and displaying a plurality of entries corresponding to the respective visual feature. The example method further includes receiving a selection of an entry, and determining coordinate limits of the bounding region and a secondary region of the entry. The example method further includes displaying the image such that a center-point of the secondary box is positioned near a center-point of a display region, and scaling the image such that at least one of a vertical pixel count or a horizontal pixel count of the secondary region is within a ratio threshold of a vertical pixel count or a horizontal pixel count of the display region.

Systems and methods for enhancing image content captured by a machine vision camera

Methods and systems for optimizing one or more imaging settings for a machine vision job are disclosed herein. An example method includes detecting, by one or more processors, an initiation trigger that initiates the machine vision job. The example method further includes, responsive to detecting the initiation trigger, capturing, by an imaging device, a first image of a target object in accordance with a first configuration of the one or more imaging settings. The example method further includes, responsive to capturing the first image of the target object, automatically adjusting, by the one or more processors, the one or more imaging settings to a second configuration that includes at least one different imaging setting from the first configuration; and capturing, by the imaging device, a second image of the target object in accordance with the second configuration of the one or more imaging settings.

Systems and methods to optimize imaging settings for a machine vision job

Systems and methods for enhancing image content captured by a machine vision camera are disclosed herein. An example method includes receiving an image captured by a machine vision camera that includes a plurality of indicia, determining bounds of a bounding box for each respective indicia, and displaying a plurality of entries corresponding to the respective indicia. The example method further includes receiving a selection of an entry, and determining coordinate limits of the bounding box and a secondary box of the entry. The example method further includes displaying the image such that a center-point of the secondary box is positioned near a center-point of a display region, and scaling the image such that at least one of a vertical pixel count or a horizontal pixel count of the secondary box is within a ratio threshold of a vertical pixel count or a horizontal pixel count of the display region.

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South Setauket, NY, United States of America

Christopher M West