Abstract: A method for visual recognition of an object in an electronic image includes extracting unique points of an object to be learned and/or a target object. The unique points are obtained by cross-correlating the image with a structure. Generally, the structure and/or the size of the structure may vary to detect extremum information associated with the learned object and/or target object. An icon corresponding to each of the unique points is extracted. The size of the icon corresponds to the scale of the unique point. After extraction of the various icons, an object becomes a collection of icons. Each of these icons is un-rotated and normalized or resized to a constant size so it can be compared with other icons.

Abstract: An industrial robot system includes an end effector connectable to a robot arm, a drive assembly, and a controller. The end effector includes a distal housing, a spindle assembly rotatable about a rotational axis, a drill bit rotatable about the rotational axis, and a sensor assembly. The sensor assembly includes a first light source, a second light source, and a photosensitive array. The first light source produces a first fan of light which is projected as a first line of light on the object surface. The second light source produces a second fan of light, which is projected as a second line of light on the object surface. The photosensitive array detects a first reflection line corresponding to the first line of light and a second reflection line corresponding to the second line of light.

Abstract: A method for measuring wheel alignment of a test wheel rotating about a z-axis using at least one camera and a processor includes obtaining a calibration point from a calibration image of a zero-offset wheel that is the same size as the test wheel and that rotates about the z-axis, obtaining at least one test image of the test wheel with the camera and a non-structured light source, and locating a measurement point in the test image. The measurement point coincides with a radius that the calibration point is offset from the z-axis and the angular displacement of the calibration point from the vertical diameter of the zero-offset wheel. The measurement point is further located based on a change of reflectivity between other points in the test image adjacent the measurement point.

Abstract: A method for delivering an electronic coupon to a mobile device includes receiving via a wireless network a target image or icons extracted from the target image, comparing the target image to a plurality of learned images using a processor in communication with the wireless network, determining whether the target image matches at least one learned image, and when the target image matches at least one learned image, delivering to the mobile device over the wireless network an electronic coupon associated with the at least one learned image. The target image can represent at least a portion of a front surface of a consumer packaged good located in a retail outlet. The target image can be generated using a mobile device configured to communicate with the wireless network.

Abstract: A method for visual recognition of an object in an electronic image includes extracting unique points of an object to be learned and/or a target object. The unique points are obtained by cross-correlating the image with a structure. Generally, the structure and/or the size of the structure may vary to detect extremum information associated with the learned object and/or target object. An icon corresponding to each of the unique points is extracted. The size of the icon corresponds to the scale of the unique point. After extraction of the various icons, an object becomes a collection of icons. Each of these icons is un-rotated and normalized or resized to a constant size so it can be compared with other icons.

Abstract: A method for visual recognition of an object in an electronic image includes extracting unique points of an object to be learned and/or a target object. The unique points are obtained by cross-correlating the image with a structure. Generally, the structure and/or the size of the structure may vary to detect extremum information associated with the learned object and/or target object. An icon corresponding to each of the unique points is extracted. The size of the icon corresponds to the scale of the unique point. After extraction of the various icons, an object becomes a collection of icons. Each of these icons is un-rotated and normalized or resized to a constant size so it can be compared with other icons. One of the unique properties of these icons is their stability over scale and angle. Thus, this invention allows the recognition of an image(s) or object(s) from large number of trained images or objects very quickly.

Abstract: A system and method of visual monitoring of a work implement (e.g., a welding torch) while a task is being performed (e.g., forming a welding joint) to train workers (e.g., apprentices, inexperienced workers) in proper welding technique, for example) and/or to evaluate the worker's use of a particular work implement (e.g., to determine if the welding torch was held in a desired relationship to the items being welded together, determine if the welding torch formed the joint at the current speed, etc.). In general, one or more cameras may acquire images of a target secured to and/or formed on the work implement. The images may be analyzed to provide feedback to the user, to be evaluated for weld integrity purposes; and/or may be used to compare the performance of a task (e.g., forming a welding joint) with a database of one or more profiles made by experienced and/or expert craftsmen.

Abstract: A method for generating a signal based on a visual image includes photographing a target object with a digital camera to obtain a target image; receiving the target image into a processor that is in communication with the camera; cross-correlating the target image with a structure having a variety of scales across the target image; and based on cross-correlating the target image, generating a signal for output on a device associated with the camera. A visual recognition system is also disclosed.

Abstract: A method for delivering an electronic coupon to a mobile device includes receiving via a wireless network a target image or icons extracted from the target image, comparing the target image to a plurality of learned images using a processor in communication with the wireless network, determining whether the target image matches at least one learned image, and when the target image matches at least one learned image, delivering to the mobile device over the wireless network an electronic coupon associated with the at least one learned image. The target image can represent at least a portion of a front surface of a consumer packaged good located in a retail outlet. The target image can be generated using a mobile device configured to communicate with the wireless network.

Abstract: Disclosed is method of visual search for objects that include straight lines. A two-step process is used, which includes detecting straight line segments in an image. The lines are generally characterized by their length, midpoint location, and orientation. Hypotheses that a particular straight line segment belongs to a known object are generated and tested. The set of hypotheses is constrained by spatial relationships in the known objects. The speed and robustness of the method and apparatus disclosed makes it immediately applicable to many computer vision applications.

Abstract: Disclosed is method of visual search for objects that include straight lines. A two-step process is used, which includes detecting straight line segments in an image. The lines are generally characterized by their length, midpoint location, and orientation. Hypotheses that a particular straight line segment belongs to a known object are generated and tested. The set of hypotheses is constrained by spatial relationships in the known objects. The speed and robustness of the method and apparatus disclosed makes it immediately applicable to many computer vision applications.

Abstract: A system and method of visual monitoring of a work implement (e.g., a welding torch) while a task is being performed (e.g., forming a welding joint) to train workers (e.g., apprentices, inexperienced workers) in proper welding technique, for example) and/or to evaluate the worker's use of a particular work implement (e.g., to determine if the welding torch was held in a desired relationship to the items being welded together, determine if the welding torch formed the joint at the current speed, etc.). In general, one or more cameras may acquire images of a target secured to and/or formed on the work implement. The images may be analyzed to provide feedback to the user, to be evaluated for weld integrity purposes; and/or may be used to compare the performance of a task (e.g., forming a welding joint) with a database of one or more profiles made by experienced and/or expert craftsmen.

Abstract: Disclosed herein are embodiments and methods of a visual guidance and recognition system requiring no calibration. One embodiment of the system comprises a servo actuated manipulator configured to perform a function, a camera mounted on the face plate of the manipulator, and a recognition controller configured to acquire a two dimensional image of the work piece. The manipulator controller is configured to receive and store the face plate position at a distance “A” between the reference work piece and the manipulator along an axis of the reference work piece when the reference work piece is in the camera's region of interest. The recognition controller is configured to learn the work piece from the image and the distance “A”. During operation, a work piece is recognized with the system, and the manipulator is accurately positioned with respect to the work piece so that the manipulator can accurately perform its function.

Abstract: A method for visual recognition of an object in an electronic image includes extracting unique points of an object to be learned and/or a target object. The unique points are obtained by cross-correlating the image with a structure. Generally, the structure and/or the size of the structure may vary to detect extremum information associated with the learned object and/or target object. An icon corresponding to each of the unique points is extracted. The size of the icon corresponds to the scale of the unique point. After extraction of the various icons, an object becomes a collection of icons. Each of these icons is un-rotated and normalized or resized to a constant size so it can be compared with other icons. One of the unique properties of these icons is their stability over scale and angle. Thus, this invention allows the recognition of an image(s) or object(s) from large number of trained images or objects very quickly.

Abstract: Disclosed is method of visual search for objects that include straight lines. A two-step process is used, which includes detecting straight line segments in an image. The lines are generally characterized by their length, midpoint location, and orientation. Hypotheses that a particular straight line segment belongs to a known object are generated and tested. The set of hypotheses is constrained by spatial relationships in the known objects. The speed and robustness of the method and apparatus disclosed makes it immediately applicable to many computer vision applications.