Abstract: Example systems and methods for auto-configuring a tool for one or more imaging device jobs are disclosed. An example system includes a machine vision camera, and a client computing device coupled thereto. The client computing device, operating in a build mode, is configured to: receive an image; present the image on a canvas, wherein the canvas is part of a user interface of a machine vision application; display targets of interest in the canvas based on a machine vision tool; upon selection of a target, determine corresponding metadata elements for the target and automatically reconfigure the tool to identify targets corresponding to those metadata elements or to a range thereof. The reconfigured tool is then deployed for runtime operation.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Methods and systems for optimizing performance of a machine vision system are disclosed herein. An example method includes obtaining one or more first and second images of a target object, where each of the one or more first and second images include a pass indication and a fail indication, respectively. The example method further includes conducting, by a feasibility setup tool, a feasibility setup analysis by (i) performing machine vision techniques on each of the one or more first and second images and (ii) generating a respective updated result indication for each of the one or more first and second images. The example method further includes comparing the respective updated result indication to the respective pass indications and fail indications for the one or more first and second images, respectively; and based on the comparing, generating one or more suggestions to optimize the performance of the machine vision system.

Abstract: 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.

Abstract: 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.

Abstract: Methods and systems for optimizing a performance of a machine vision system are disclosed herein. An example method includes capturing, by an imaging device, an image of a target object in accordance with a set of imaging device settings. The example method further includes analyzing, by one or more processors, the image in accordance with a machine vision job. The example method further includes comparing, by the one or more processors, each of (i) the image to a baseline image, (ii) the machine vision job to a baseline machine vision job, and (iii) the set of imaging device settings to a baseline set of imaging device settings. The example method further includes, based on the comparing, generating, by the one or more processors, one or more suggestions to optimize the performance of the machine vision system.

Abstract: Methods and systems for optimizing performance of a machine vision system are disclosed herein. An example method includes obtaining one or more first and second images of a target object, where each of the one or more first and second images include a pass indication and a fail indication, respectively. The example method further includes conducting, by a feasibility setup tool, a feasibility setup analysis by (i) performing machine vision techniques on each of the one or more first and second images and (ii) generating a respective updated result indication for each of the one or more first and second images. The example method further includes comparing the respective updated result indication to the respective pass indications and fail indications for the one or more first and second images, respectively; and based on the comparing, generating one or more suggestions to optimize the performance of the machine vision system.