Cognex Corporation

Cognex Coporation

David Y Li

Lowell D Jacobson

Lei Wang

Guruprasad Shivaram

Xiangyun Ye

Li Sun

Yu Feng Hsu

Aaron S Wallack

Cyril C Marrion

Gang Liu

Vivek Anand

Jian Yang

David J Michael

Sanjay J Nichani

Lifeng Liu

Nigel John Foster

Joseph R Scola

Xiaoguang Wang

Yukun Bian

Kirk F Goldsworthy

This invention provides a system and method for calibration of a 3D vision system using a multi-layer 3D calibration target that removes the requirement of accurate pre-calibration of the target. The system and method acquires images of the multi-layer 3D calibration target at different spatial locations and at different times, and computes the orientation difference of the 3D calibration target between the two acquisitions. The technique can be used to perform vision-based single-plane orientation repeatability inspection and monitoring. By applying this technique to an assembly working plane, vision-based assembly working plane orientation repeatability, inspection and monitoring can occur. Combined with a moving robot end effector, this technique provides vision-based robot end-effector orientation repeatability inspection and monitoring. Vision-guided adjustment of two planes to achieve parallelism can be achieved. The system and method operates to perform precise vision-guided robot setup to achieve parallelism of the robot's end-effector and the assembly working plane.

System and method for three-dimensional calibration of a vision system

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 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 runtime determination (self-diagnosis) of camera miscalibration (accuracy), typically related to camera extrinsics, based on historical statistics of runtime alignment scores for objects acquired in the scene, which are defined based on matching of observed and expected image data of trained object models. This arrangement avoids a need to cease runtime operation of the vision system and/or stop the production line that is served by the vision system to diagnose if the system's camera(s) remain calibrated. Under the assumption that objects or features inspected by the vision system over time are substantially the same, the vision system accumulates statistics of part alignment results and stores intermediate results to be used as indicator of current system accuracy. For multi-camera vision systems, cross validation is illustratively employed to identify individual problematic cameras. The system and method allows for faster, less-expensive and more-straightforward diagnosis of vision system failures related to deteriorating camera calibration.

System and method for runtime determination of camera miscalibration

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

This invention provides a system and method for aligning a first work piece with an underlying second work piece in the presence of occlusion by the first work piece of critical alignment features of the second work piece. The vision system, which guides the motion of a manipulator holding the first work piece and a motion stage holding the second work piece, learns secondary alignment features at least one of the first and second work pieces. Using these secondary features, the vision system determines alignment between the work pieces and guides the manipulator and the motion stage to achieve alignment as the first work piece engages the second work piece. The secondary features are used to define a course alignment. Deterministic movements of the manipulator and/or motion stage are used to learn the relationship between the secondary and primary features. Secondary features are used to direct alignment.

System and method for aligning two work pieces with a vision system in the presence of occlusion

Described are methods, systems, and apparatus, including computer program products for calibrating machine vision systems. A system includes: one or more cameras; a motion rendering device; and a calibration module. The calibration module is configured to acquire, from a first camera of the one or more cameras, a plurality of images of a calibration target comprising a calibration pattern that provides a plurality of calibration features; extract calibration features of the plurality of calibration features from the plurality of images, wherein physical positions of the plurality of calibration features are in a calibration target length unit associated with the calibration target; determine a ratio between the calibration target length unit and a motion rendering device length unit associated with the motion rendering device; and provide a first calibration for the first camera based on the ratio.

Machine vision system calibration using inaccurate calibration targets

This invention provides a system and method to validate the accuracy of camera calibration in a single or multiple-camera embodiment, utilizing either 2D cameras or 3D imaging sensors. It relies upon an initial calibration process that generates and stores camera calibration parameters and residual statistics based upon images of a first calibration object. A subsequent validation process (a) acquires images of the first calibration object or a second calibration object having a known pattern and dimensions; (b) extracts features of the images of the first calibration object or the second calibration object; (c) predicts positions expected of features of the first calibration object or the second calibration object using the camera calibration parameters; and (d) computes a set of discrepancies between positions of the extracted features and the predicted positions of the features. The validation process then uses the computed set of discrepancies in a decision process that determines whether at least one of the discrepancies exceeds a predetermined threshold value. If so, recalibration is required. Where multiple cameras are employed, extrinsic parameters are determined and used in conjunction with the intrinsics.

System and method for validating camera calibration in a vision system

This invention provides a system and method for determining the pose of shapes that are known to a vision system that undergo both affine transformation and deformation. The object image with fiducial is acquired. The fiducial has affine parameters, including degrees of freedom (DOFs), search ranges and search step sizes, and control points with associated DOFs and step sizes. Each 2D affine parameter's search range and the distortion control points' DOFs are sampled and all combinations are obtained. The coarsely specified fiducial is transformed for each combination and a match metric is computed for the transformed fiducial, generating a score surface. Peaks are computed on this surface, as potential candidates, which are refined until a match metric is maximized. The refined representation exceeding a predetermined score is returned as potential shapes in the scene. Alternately the candidate with the best score can be used as a training fiducial.

System and method for automatically determining pose of a shape

An apparatus for associating codes on parts with part spaces on a conveyor wherein each part has a leading edge and a trailing edge that define a part space and each part is to be marked with at least one code, the apparatus comprising an area scan camera having a two dimensional field of view (FOV), the camera supported adjacent the conveyor so that parts conveyed by the conveyor pass through the FOV, a processor linked to the area scan camera, the processor programmed to perform the steps of receiving images from the area scan camera, identifying the locations of codes on parts in at least one of the images wherein a code located is a located code, identifying the locations of leading and trailing edges of parts wherein the leading and trailing edges define part spaces and associating each located code with a part space that includes the location of the located code.

Code and part associating method and apparatus

This invention provides a system and method for determining the three-dimensional alignment of a modeled object or scene. A 3D (stereo) sensor system views the object to derive a runtime 3D representation of the scene containing the object. Rectified images from each stereo head are preprocessed to enhance their edge features. 3D points are computed for each pair of cameras to derive a 3D point cloud. The amount of 3D data from the point cloud is reduced by extracting higher-level geometric shapes (HLGS), such as line segments. Found HLGS from runtime are corresponded to HLGS on the model to produce candidate 3D poses. A coarse scoring process prunes the number of poses. The remaining candidate poses are then subjected to a further more-refined scoring process. These surviving candidate poses are then verified whereby the closest match is the best refined three-dimensional pose.

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West Roxbury, MA, United States of America

David Y Li