Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: This invention provides a system and method for determining the three-dimensional alignment of a modeledobject or scene. After calibration, 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. A stereo matching process is then performed on at least two (a pair) of the rectified preprocessed images at a time by locating a predetermined feature on a first image and then locating the same feature in the other image. 3D points are computed for each pair of cameras to derive a 3D point cloud. The 3D point cloud is generated by transforming the 3D points of each camera pair into the world 3D space from the world calibration. 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.

Abstract: A methods and apparatuses are disclosed for determining the state of elements in an image. The elements can be arranged in any regular pattern, such as a matrix of LCD display elements. The state of the elements is determined by extracting a characteristic of the elements, such as intensity, and processing the characteristic to provide comparison criteria, such as a difference value. The comparison criteria are then used to determine the state of the element alone or in combination with other comparisons, such as average intensity comparisons. Several comparisons and variations thereof are disclosed, as well as the preferred ordering and configuration of comparisons for LCD displays. Also disclosed is an embodiment where a model of the elements is generated and used to inspect the elements.

Abstract: A methods and apparatuses are disclosed for determining the state of elements in an image. The elements can be arranged in any regular pattern, such as a matrix of LCD display elements. The state of the elements is determined by extracting a characteristic of the elements, such as intensity, and processing the characteristic to provide comparison criteria, such as a difference value. The comparison criteria are then used to determine the state of the element alone or in combination with other comparisons, such as average intensity comparisons. Several comparisons and variations thereof are disclosed, as well as the preferred ordering and configuration of comparisons for LCD displays. Also disclosed is an embodiment where a model of the elements is generated and used to inspect the elements.

Abstract: A method and apparatus for identifying an object having an identifying feature includes a two step process for detecting the identifying feature. The process involves locating the feature based upon a first characteristic of the feature and then verifying that feature is the identifying feature based upon a second characteristic of the feature. Preferably, the first step of the process is less discriminating and substantially faster than the second step. This permits the process to be performed rapidly without reducing accuracy.