Cognex Corporation

Cognex Technology and Investment Corporation

Lowell D Jacobson

Lei Wang

David Y Li

Gang Liu

Vivek Anand

Mikhail Akopyan

Yu Feng Hsu

Robert A Wolff

John F Filhaber

George J Costigan

Joseph R Scola

Xiaoguang Wang

Li Sun

Vladimir N Ruzhitsky

David J Michael

Ivan A Bachelder

John McGarry

Guruprasad Shivaram

Alex Zatsman

Leonid Segal

Jay Negro

Andrew Persky

Nelson Tarr

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.

System and method for finding and classifying patterns in an image with a vision system

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.

System and method for determining 3D surface features and irregularities on an object

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.

System and method for finding lines in an image with a vision system

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.

System and method for finding and classifying lines in an image with a vision system

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.

System and method for calibrating a vision system with respect to a touch probe

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.

System and method for 3D profile determination using model-based peak selection

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.

A vision system capable of performing run-time 3D calibration includes a mount configured to hold an object, the mount including a 3D calibration structure; a camera; a motion stage coupled with the mount or the camera; and a computing device configured to perform operations including: acquiring images from the camera when the mount is in respective predetermined orientations relative to the camera, each of the acquired images including a representation of at least a portion of the object and at least a portion of the 3D calibration structure that are concurrently in a field of view of the camera; performing at least an adjustment of a 3D calibration for each of the acquired images based on information relating to the 3D calibration structure as imaged in the acquired images; and determining 3D positions, dimensions or both of one or more features of the object.

Calibration for vision system

A system and method for automated determination of position and movement of a contact lens with respect to a subject wearer's eye based upon a complimentary pair of images, acquired in rapid succession, in which one image of the pair is acquired using light that allows viewing of the pupil and/or limbus through the lens and the other image is acquired using light that is absorbed by the lens to generate an opaque image with a defined edge relative to the surrounding sclera. The images of the pair are acquired in close enough temporal proximity to ensure that eye movement in the interval therebetween is insignificant and both images are in the same approximate reference frame. Thus, the location of the pupil and limbus in one image can be accurately compared with the location of the contact lens edge in the other image.

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Grafton, MA, United States of America

Lowell D Jacobson