Cognex Corporation

Other

Nathaniel R Bogan

Andrew Hoelscher

Zihan Hans Liu

David J Michael

Eric Moore

Benjamin Braker

Jason Davis

Xiaoguang Wang

Aaron S Wallack

Hongwei Zhu

Toshimitsu Motoyama

The disclosure provides various components for a fishing lure. These components include a Hard Bodied Ballast Oscillator ('HBBO') which oscillates around various axes, an HBB with positive lift that rises during retrieval, and a hook for use in a rigid body which, while being fished, remains at least partially inside the body and reliably pointing upwards, and which, when the fish bites, is at least partially exposed. In some cases multiple components may be connected to each other via a stiff wire and designed to maintain, in the water, a particular orientation of the components relative to each other.

Fishing lure

The techniques described herein relate to methods, apparatus, and computer readable media configured to identify a surface feature of a portion of a three-dimensional (3D) point cloud. Data indicative of a path along a 3D point cloud is received, wherein the 3D point cloud comprises a plurality of 3D data points. A plurality of lists of 3D data points are generated, wherein: each list of 3D data points extends across the 3D point cloud at a location that intersects the received path; and each list of 3D data points intersects the received path at different locations. A characteristic associated with a surface feature is identified in at least some of the plurality of lists of 3D data points. The identified characteristics are grouped based on one or more properties of the identified characteristics. The surface feature is identified based on the grouped characteristics.

Methods and apparatus for identifying surface features in three-dimensional images

The techniques described herein relate to methods, apparatus, and computer readable media configured to determining a two-dimensional (2D) profile of a portion of a three-dimensional (3D) point cloud. A 3D region of interest is determined that includes a width along a first axis, a height along a second axis, and a depth along a third axis. The 3D points within the 3D region of interest are represented as a set of 2D points based on coordinate values of the first and second axes. The 2D points are grouped into a plurality of 2D bins arranged along the first axis. For each 2D bin, a representative 2D position is determined based on the associated set of 2D points. Each of the representative 2D positions are connected to neighboring representative 2D positions to generate the 2D profile.

Methods and apparatus for extracting profiles from three-dimensional images

A system and method for scoring trained probes for use in analyzing one or more candidate poses of a runtime image is provided. A set of probes with location and gradient direction based on a trained model are applied to one or more candidate poses based upon a runtime image. The applied probes each respectively include a discrete set of position offsets with respect to the gradient direction thereof. A match score is computed for each of the probes, which includes estimating a best match position for each of the probes respectively relative to one of the offsets thereof, and generating a set of individual probe scores for each of the probes, respectively at the estimated best match position.

System and method for efficiently scoring probes in an image with a vision system

The techniques described herein relate to methods, apparatus, and computer readable media configured to test a pose of a three-dimensional model. A three-dimensional model is stored, the three dimensional model comprising a set of probes. Three-dimensional data of an object is received, the three-dimensional data comprising a set of data entries. The three-dimensional data is converted into a set of fields, comprising generating a first field comprising a first set of values, where each value of the first set of values is indicative of a first characteristic of an associated one or more data entries from the set of data entries, and generating a second field comprising a second set of values, where each second value of the second set of values is indicative of a second characteristic of an associated one or more data entries from the set of data entries, wherein the second characteristic is different than the first characteristic. A pose of the three-dimensional model is tested with the set of fields, comprising testing the set of probes to the set of fields, to determine a score for the pose.

Methods and apparatus for testing multiple fields for machine vision

This invention provides a system and method for displaying color match information on an acquired image of an object. A model/pattern having a plurality of color test points at locations of stable color is provided. A display process generates visible geometric shapes with respect to the color test points in a predetermined color. An alignment process aligns features of the object with respect to features on the model so that the geometric shapes appear in locations on the object that correspond to locations on the model. The geometric shapes can comprise closed shapes that surround a region expected to be stable color on the object. Such shapes can define circles, squares, diamonds or any other acceptable closed or open shape that is visible to the user on the display.

System and method for representing and displaying color accuracy in pattern matching by a vision system

The techniques described herein relate to methods, apparatus, and computer readable media configured to test a pose of a model to image data. Image data of an object is received, the image data comprising a set of data entries. A set of regions of the image data are determined, wherein each region in the set of regions comprises an associated set of neighboring data entries in the set of data entries. Processed image data is generated, wherein the processed image data comprises a set of cells that each have an associated value, and generating the processed image data comprises, for each region in the set of regions, determining a maximum possible score of each data entry in the associated set of neighboring data entries from the image data, setting one or more values of the set of values based on the determined maximum possible score, and testing the pose of the model using the processed image data.

Methods and apparatus for processing image data for machine vision

Methods, systems, and devices for 3D measurement and/or pattern generation are provided in accordance with various embodiments. Some embodiments include a method of pattern projection that may include projecting one or more patterns. Each pattern from the one or more patterns may include an arrangement of three or more symbols that are arranged such that for each symbol in the arrangement, a degree of similarity between said symbol and a most proximal of the remaining symbols in the arrangement is less than a degree of similarity between said symbol and a most distal of the remaining symbols in the arrangement. Some embodiments further include: illuminating an object using the one or more projected patterns; collecting one or more images of the illuminated object; and/or computing one or more 3D locations of the illuminated object based on the one or more projected patterns and the one or more collected images.

Coding distance topologies for structured light patterns for 3D reconstruction

The techniques described herein relate to methods, apparatus, and computer readable media configured to test a pose of a model in three-dimensional data. Three-dimensional data of an object is received, the three-dimensional data comprising a set of data entries. The three-dimensional data is converted to a field comprising a set of cells that each have an associated value, comprising determining, for each cell value, representative data based on one or more data entries from the set of data entries of the three-dimensional data. A pose of the model is tested with the field to determine a score for the pose.

Methods and apparatus for generating a dense field of three dimensional data for machine vision

The present disclosure provides a multi-stage image mapping mechanism for mapping a distorted image to a rectified image. For example, the multi-stage image mapping mechanism can remove homography from a distorted image to reconstruct a rectified image in two-stages: (1) a first stage in which distortion is partially removed from a distorted image to generate an intermediate image, and (2) a second stage in which residual distortion is removed from the intermediate image to recover the rectified image.

Homography rectification

This invention provides a system and method for determining the level of clutter in an image in a manner that is rapid, and that allows a scoring process to quickly determine whether an image is above or below an acceptable level of clutter&#x2014;for example to determine if the underlying imaged runtime object surface is defective without need to perform a more in-depth analysis of the features of the image. The system and method employs clutter test points that are associated with regions on the image that should contain a low gradient magnitude, indicative of emptiness. This enables the runtime image to be analyzed quickly by mapping trained clutter test points at locations in the coordinate space in which lack of emptiness indicates clutter, and if detected, can rapidly indicate differences and/or defects that allow for the subject of the image to be accepted or rejected without further image analysis.

Growing community of inventors

Natlick, MA, United States of America

Nathaniel R Bogan