Patents by Inventor Lowell D. Jacobson
Lowell D. Jacobson has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240078801Abstract: This invention provides a system and method for finding line features in an image that allows multiple lines to be efficiently and accurately identified and characterized. When lines are identified, the user can train the system to associate predetermined (e.g. text) labels with respect to such lines. These labels can be used to define neural net classifiers. The neural net operates at runtime to identify and score lines in a runtime image that are found using a line-finding process. The found lines can be displayed to the user with labels and an associated probability score map based upon the neural net results. Lines that are not labeled are generally deemed to have a low score, and are either not flagged by the interface, or identified as not relevant.Type: ApplicationFiled: July 10, 2023Publication date: March 7, 2024Inventors: Lei Wang, Vivek Anand, Lowell D. Jacobson
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Publication number: 20240005148Abstract: This invention provides a system and method for finding patterns in images that incorporates neural net classifiers. A pattern finding tool is coupled with a classifier that can be run before or after the tool to have labeled pattern results with sub-pixel accuracy. In the case of a pattern finding tool that can detect multiple templates, its performance is improved when a neural net classifier informs the pattern finding tool to work only on a subset of the originally trained templates. Similarly, in the case of a pattern finding tool that initially detects a pattern, a neural network classifier can then determine whether it has found the correct pattern. The neural network can also reconstruct/clean-up an imaged shape, and/or to eliminate pixels less relevant to the shape of interest, therefore reducing the search time, as well significantly increasing the chance of lock on the correct shapes.Type: ApplicationFiled: January 30, 2023Publication date: January 4, 2024Inventors: Lei Wang, Vivek Anand, Lowell D. Jacobson, David Y. Li
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Patent number: 11854173Abstract: This invention provides a system and method for finding multiple line features in an image. Two related steps are used to identify line features. First, the process computes x and y-components of the gradient field at each image location, projects the gradient field over a plurality subregions, and detects a plurality of gradient extrema, yielding a plurality of edge points with position and gradient. Next, the process iteratively chooses two edge points, fits a model line to them, and if edge point gradients are consistent with the model, computes the full set of inlier points whose position and gradient are consistent with that model. The candidate line with greatest inlier count is retained and the set of remaining outlier points is derived. The process then repeatedly applies the line fitting operation on this and subsequent outlier sets to find a plurality of line results. The process can be exhaustive RANSAC-based.Type: GrantFiled: December 18, 2020Date of Patent: December 26, 2023Assignee: Cognex CorporationInventors: Yu Feng Hsu, Lowell D. Jacobson, David Y. Li
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Patent number: 11699283Abstract: This invention provides a system and method for finding line features in an image that allows multiple lines to be efficiently and accurately identified and characterized. When lines are identified, the user can train the system to associate predetermined (e.g. text) labels with respect to such lines. These labels can be used to define neural net classifiers. The neural net operates at runtime to identify and score lines in a runtime image that are found using a line-finding process. The found lines can be displayed to the user with labels and an associated probability score map based upon the neural net results. Lines that are not labeled are generally deemed to have a low score, and are either not flagged by the interface, or identified as not relevant.Type: GrantFiled: December 18, 2020Date of Patent: July 11, 2023Assignee: Cognex CorporationInventors: Lei Wang, Vivek Anand, Lowell D. Jacobson
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Patent number: 11599978Abstract: This invention provides a system and method for finding multiple line features in an image. Two related steps are used to identify line features. First, the process computes x and y-components of the gradient field at each image location, projects the gradient field over a plurality subregions, and detects a plurality of gradient extrema, yielding a plurality of edge points with position and gradient. Next, the process iteratively chooses two edge points, fits a model line to them, and if edge point gradients are consistent with the model, computes the full set of inlier points whose position and gradient are consistent with that model. The candidate line with greatest inlier count is retained and the set of remaining outlier points is derived. The process then repeatedly applies the line fitting operation on this and subsequent outlier sets to find a plurality of line results. The process can be exhaustive RANSAC-based.Type: GrantFiled: December 18, 2020Date of Patent: March 7, 2023Assignee: Cognex CorporationInventors: Yu Feng Hsu, Lowell D. Jacobson, David Y. Li
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Patent number: 11568629Abstract: This invention provides a system and method for finding patterns in images that incorporates neural net classifiers. A pattern finding tool is coupled with a classifier that can be run before or after the tool to have labeled pattern results with sub-pixel accuracy. In the case of a pattern finding tool that can detect multiple templates, its performance is improved when a neural net classifier informs the pattern finding tool to work only on a subset of the originally trained templates. Similarly, in the case of a pattern finding tool that initially detects a pattern, a neural network classifier can then determine whether it has found the correct pattern. The neural network can also reconstruct/clean-up an imaged shape, and/or to eliminate pixels less relevant to the shape of interest, therefore reducing the search time, as well significantly increasing the chance of lock on the correct shapes.Type: GrantFiled: June 6, 2019Date of Patent: January 31, 2023Assignee: Cognex CorporationInventors: Lei Wang, Vivek Anand, Lowell D. Jacobson, David Y. Li
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Patent number: 11563931Abstract: A calibration fixture that enables more accurate calibration of a touch probe on, for example, a CMM, with respect to the camera. The camera is mounted so that its optical axis is approximately or substantially parallel with the z-axis of the probe. The probe and workpiece are in relative motion, along a plane defined by orthogonal x and y axes, and optionally the z-axis and/or and rotation R about the z-axis. The calibration fixture is arranged to image from beneath the touch surface of the probe and, via a 180-degree prism structure, to transmit light from the probe touch point along the optical axis to the camera. Alternatively, two cameras respectively view the fiducial location relative to the CMM arm and the probe location when aligned on the fiducial. The fixture can define an integrated assembly with an optics block and a camera assembly.Type: GrantFiled: November 23, 2020Date of Patent: January 24, 2023Assignee: Cognex CorporationInventors: John F. Filhaber, Lowell D. Jacobson, George J. Costigan
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Patent number: 11415408Abstract: This invention provides a system and method for selecting the correct profile from a range of peaks generated by analyzing a surface with multiple exposure levels applied at discrete intervals. The cloud of peak information is resolved by comparison to a model profile into a best candidate to represent an accurate representation of the object profile. Illustratively, a displacement sensor projects a line of illumination on the surface and receives reflected light at a sensor assembly at a set exposure level. A processor varies the exposure level setting in a plurality of discrete increments, and stores an image of the reflected light for each of the increments. A determination process combines the stored images and aligns the combined images with respect to a model image. Points from the combined images are selected based upon closeness to the model image to provide a candidate profile of the surface.Type: GrantFiled: August 24, 2020Date of Patent: August 16, 2022Assignee: Cognex CorporationInventors: David Y. Li, Li Sun, Lowell D. Jacobson, Lei Wang
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Publication number: 20220180499Abstract: This invention provides a system and method for determining the location and characteristics of certain surface features that comprises elevated or depressed regions with respect to a smooth surrounding surface on an object. A filter acts on a range image of the scene. A filter defines an annulus or other perimeter shape around each pixel in which a best-fit surface is established. A normal to the pixel allows derivation of local displacement height. The displacement height is used to establish a height deviation image of the object, with which bumps, dents or other height-displacement features can be determined. The bump filter can be used to locate regions on a surface with minimal irregularities by mapping such irregularities to a grid and then thresholding the grid to generate a cost function. Regions with a minimal cost are acceptable candidates for application of labels and other items in which a smooth surface is desirable.Type: ApplicationFiled: November 15, 2021Publication date: June 9, 2022Inventors: Mikhail Akopyan, Lowell D. Jacobson, Robert A. Wolff
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Patent number: 11176655Abstract: This invention provides a system and method for determining the location and characteristics of certain surface features that comprises elevated or depressed regions with respect to a smooth surrounding surface on an object. A filter acts on a range image of the scene. A filter defines an annulus or other perimeter shape around each pixel in which a best-fit surface is established. A normal to the pixel allows derivation of local displacement height. The displacement height is used to establish a height deviation image of the object, with which bumps, dents or other height-displacement features can be determined. The bump filter can be used to locate regions on a surface with minimal irregularities by mapping such irregularities to a grid and then thresholding the grid to generate a cost function. Regions with a minimal cost are acceptable candidates for application of labels and other items in which a smooth surface is desirable.Type: GrantFiled: July 11, 2014Date of Patent: November 16, 2021Assignee: Cognex CorporationInventors: Mikhail Akopyan, Lowell D. Jacobson, Robert A. Wolff
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Patent number: 11159784Abstract: A calibration fixture is provided that enables more accurate calibration of a touch probe on, for example, a coordinate measuring machine (CMM), with respect to the camera. The camera is mounted so that its optical axis is approximately or substantially parallel with the z-axis of the probe. The probe and workpiece are in relative motion, along a plane defined by orthogonal x and y axes, and optionally the z-axis and/or and rotation R about the z-axis. The calibration fixture is arranged to image from beneath the touch surface of the probe and, via a 180-degree prism structure, to transmit light from the probe touch point along the optical axis to the camera. Alternatively, two cameras respectively view the fiducial location relative to the CMM arm and the probe location when aligned on the fiducial. The fixture can define an integrated assembly with an optics block and a camera assembly.Type: GrantFiled: October 16, 2015Date of Patent: October 26, 2021Assignee: Cognex CorporationInventors: John F. Filhaber, Lowell D. Jacobson, George J. Costigan
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Publication number: 20210233250Abstract: This invention provides a system and method for finding line features in an image that allows multiple lines to be efficiently and accurately identified and characterized. When lines are identified, the user can train the system to associate predetermined (e.g. text) labels with respect to such lines. These labels can be used to define neural net classifiers. The neural net operates at runtime to identify and score lines in a runtime image that are found using a line-finding process. The found lines can be displayed to the user with labels and an associated probability score map based upon the neural net results. Lines that are not labeled are generally deemed to have a low score, and are either not flagged by the interface, or identified as not relevant.Type: ApplicationFiled: December 18, 2020Publication date: July 29, 2021Inventors: Lei Wang, Vivek Anand, Lowell D. Jacobson
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Publication number: 20210183032Abstract: This invention provides a system and method for finding multiple line features in an image. Two related steps are used to identify line features. First, the process computes x and y-components of the gradient field at each image location, projects the gradient field over a plurality subregions, and detects a plurality of gradient extrema, yielding a plurality of edge points with position and gradient. Next, the process iteratively chooses two edge points, fits a model line to them, and if edge point gradients are consistent with the model, computes the full set of inlier points whose position and gradient are consistent with that model. The candidate line with greatest inlier count is retained and the set of remaining outlier points is derived. The process then repeatedly applies the line fitting operation on this and subsequent outlier sets to find a plurality of line results. The process can be exhaustive RANSAC-based.Type: ApplicationFiled: December 18, 2020Publication date: June 17, 2021Inventors: Yu Feng Hsu, Lowell D. Jacobson, David Y. Li
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Publication number: 20210176456Abstract: This invention provides a calibration fixture that enables more accurate calibration of a touch probe on, for example, a CMM, with respect to the camera. The camera is mounted so that its optical axis is approximately or substantially parallel with the z-axis of the probe. The probe and workpiece are in relative motion, along a plane defined by orthogonal x and y axes, and optionally the z-axis and/or and rotation R about the z-axis. The calibration fixture is arranged to image from beneath the touch surface of the probe and, via a 180-degree prism structure, to transmit light from the probe touch point along the optical axis to the camera. Alternatively, two cameras respectively view the fiducial location relative to the CMM arm and the probe location when aligned on the fiducial. The fixture can define an integrated assembly with an optics block and a camera assembly.Type: ApplicationFiled: November 23, 2020Publication date: June 10, 2021Inventors: John F. Filhaber, Lowell D. Jacobson, George J. Costigan
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Publication number: 20210148694Abstract: This invention provides a system and method for selecting the correct profile from a range of peaks generated by analyzing a surface with multiple exposure levels applied at discrete intervals. The cloud of peak information is resolved by comparison to a model profile into a best candidate to represent an accurate representation of the object profile. Illustratively, a displacement sensor projects a line of illumination on the surface and receives reflected light at a sensor assembly at a set exposure level. A processor varies the exposure level setting in a plurality of discrete increments, and stores an image of the reflected light for each of the increments. A determination process combines the stored images and aligns the combined images with respect to a model image. Points from the combined images are selected based upon closeness to the model image to provide a candidate profile of the surface.Type: ApplicationFiled: August 24, 2020Publication date: May 20, 2021Inventors: David Y. Li, Li Sun, Lowell D. Jacobson, Lei Wang
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Patent number: 10937168Abstract: This invention provides a system and method for finding line features in an image that allows multiple lines to be efficiently and accurately identified and characterized. When lines are identified, the user can train the system to associate predetermined (e.g. text) labels with respect to such lines. These labels can be used to define neural net classifiers. The neural net operates at runtime to identify and score lines in a runtime image that are found using a line-finding process. The found lines can be displayed to the user with labels and an associated probability score map based upon the neural net results. Lines that are not labeled are generally deemed to have a low score, and are either not flagged by the interface, or identified as not relevant.Type: GrantFiled: June 6, 2018Date of Patent: March 2, 2021Assignee: Cognex CorporationInventors: Lei Wang, Vivek Anand, Lowell D. Jacobson
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Patent number: 10902568Abstract: This invention provides a system and method for finding multiple line features in an image. Two related steps are used to identify line features. First, the process computes x and y-components of the gradient field at each image location, projects the gradient field over a plurality subregions, and detects a plurality of gradient extrema, yielding a plurality of edge points with position and gradient. Next, the process iteratively chooses two edge points, fits a model line to them, and if edge point gradients are consistent with the model, computes the full set of inlier points whose position and gradient are consistent with that model. The candidate line with greatest inlier count is retained and the set of remaining outlier points is derived. The process then repeatedly applies the line fitting operation on this and subsequent outlier sets to find a plurality of line results. The process can be exhaustive RANSAC-based.Type: GrantFiled: December 10, 2018Date of Patent: January 26, 2021Assignee: Cognex CorporationInventors: Yu Feng Hsu, Lowell D. Jacobson, David Y. Li
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Patent number: 10753726Abstract: This invention provides a system and method for selecting the correct profile from a range of peaks generated by analyzing a surface with multiple exposure levels applied at discrete intervals. The cloud of peak information is resolved by comparison to a model profile into a best candidate to represent an accurate representation of the object profile. Illustratively, a displacement sensor projects a line of illumination on the surface and receives reflected light at a sensor assembly at a set exposure level. A processor varies the exposure level setting in a plurality of discrete increments, and stores an image of the reflected light for each of the increments. A determination process combines the stored images and aligns the combined images with respect to a model image. Points from the combined images are selected based upon closeness to the model image to provide a candidate profile of the surface.Type: GrantFiled: March 23, 2018Date of Patent: August 25, 2020Assignee: Cognex CorporationInventors: David Y. Li, Li Sun, Lowell D. Jacobson, Lei Wang
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Patent number: 10657650Abstract: This invention provides a system and method for finding line features in an image that allows multiple lines to be efficiently and accurately identified and characterized. When lines are identified, the user can train the system to associate predetermined (e.g. text) labels with respect to such lines. These labels can be used to define neural net classifiers. The neural net operates at runtime to identify and score lines in a runtime image that are found using a line-finding process. The found lines can be displayed to the user with labels and an associated probability score map based upon the neural net results. Lines that are not labeled are generally deemed to have a low score, and are either not flagged by the interface, or identified as not relevant.Type: GrantFiled: June 6, 2018Date of Patent: May 19, 2020Assignee: Cognex CorporationInventors: Lei Wang, Vivek Anand, Lowell D. Jacobson
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Publication number: 20200005069Abstract: This invention provides a system and method for finding patterns in images that incorporates neural net classifiers. A pattern finding tool is coupled with a classifier that can be run before or after the tool to have labeled pattern results with sub-pixel accuracy. In the case of a pattern finding tool that can detect multiple templates, its performance is improved when a neural net classifier informs the pattern finding tool to work only on a subset of the originally trained templates. Similarly, in the case of a pattern finding tool that initially detects a pattern, a neural network classifier can then determine whether it has found the correct pattern. The neural network can also reconstruct/clean-up an imaged shape, and/or to eliminate pixels less relevant to the shape of interest, therefore reducing the search time, as well significantly increasing the chance of lock on the correct shapes.Type: ApplicationFiled: June 6, 2019Publication date: January 2, 2020Inventors: Lei Wang, Vivek Anand, Lowell D. Jacobson, David Y. Li