Technologies for guiding an agricultural vehicle through crop rows using a camera and signal processing to locate the crop row or centers of the crop row. The signal processing uses a filter to filter data from images captured by the camera and locates the row or the centers based on the filtered data. The filter is generated based on a signal processing transform and an initial image of the crop row captured by the camera. The filter is applied to subsequent images of the crop row captured by the camera. In some embodiments, the camera includes one lens. For example, monocular computer vision is used in some embodiments. Also, in some embodiments, a central processing unit generates the filter based on the transform and the initial image of the crop row and applies the generated filter to the subsequent images of the row.

A turbine blade or vane inspection apparatus comprising a controller, mounting for holding a turbine blade or vane, a source of illumination, and a camera. At least two of the source of illumination, the camera, and the mounting are moveable components. The controller is configured to control the moveable components to (a) position the turbine blade or vane mounted thereon relative to the illumination source so as to provide a contrast of illumination between a feature of the turbine blade or vane and an adjacent surface of the turbine blade or vane and (b), position the camera so that the optical axis of the camera is directed towards the feature. The controller is further configured to determine a dimension and/or shape of the feature based on an image obtained by the camera.

A turbine blade or vane inspection apparatus comprising a controller, mounting for holding a turbine blade or vane, a source of illumination, and a camera. At least two of the source of illumination, the camera, and the mounting are moveable components. The controller is configured to control the moveable components to (a) position the turbine blade or vane mounted thereon relative to the illumination source so as to provide a contrast of illumination between a feature of the turbine blade or vane and an adjacent surface of the turbine blade or vane and (b), position the camera so that the optical axis of the camera is directed towards the feature. The controller is further configured to determine a dimension and/or shape of the feature based on an image obtained by the camera.

The present disclosure is generally directed to systems and methods for executing optical character recognition faster than at least some traditional OCR systems, without sacrificing recognition accuracy. Towards this end, various exemplary embodiments involve the use of a bounding box and a grid-based template to identify certain unique aspects of each of various characters and/or numerals. For example, in one embodiment, the grid-based template can be used to recognize a numeral and/or a character based on a difference in centerline height between the numeral and the character when a monospaced font is used. In another exemplary embodiment, the grid-based template can be used to recognize an individual digit among a plurality of digits based on certain parts of the individual digit being uniquely located in specific portions of the grid-based template.

The present disclosure is generally directed to systems and methods for executing optical character recognition faster than at least some traditional OCR systems, without sacrificing recognition accuracy. Towards this end, various exemplary embodiments involve the use of a bounding box and a grid-based template to identify certain unique aspects of each of various characters and/or numerals. For example, in one embodiment, the grid-based template can be used to recognize a numeral and/or a character based on a difference in centerline height between the numeral and the character when a monospaced font is used. In another exemplary embodiment, the grid-based template can be used to recognize an individual digit among a plurality of digits based on certain parts of the individual digit being uniquely located in specific portions of the grid-based template.

A method for authenticating an object, comprising determining a physical dispersion pattern of a set of elements, determining a physical characteristic of the set of elements which is distinct from a physical characteristic producible by a transfer printing technology, determining a digital code associated with the object defining the physical dispersion pattern, and authenticating the object by verifying a correspondence of the digital code with the physical dispersion pattern, and verifying the physical characteristic.

A method for authenticating an object, comprising determining a physical dispersion pattern of a set of elements, determining a physical characteristic of the set of elements which is distinct from a physical characteristic producible by a transfer printing technology, determining a digital code associated with the object defining the physical dispersion pattern, and authenticating the object by verifying a correspondence of the digital code with the physical dispersion pattern, and verifying the physical characteristic.

Disclosed is an operating method of an electronic device for manufacture of a semiconductor device. The operating method includes receiving a layout image of the semiconductor device, generating an intermediate image by generating assist features based on main features of the layout image, evaluating a process result by performing simulation based on the intermediate image, and correcting the intermediate image by correcting shapes of the main features and/or the assist features of the intermediate image based on the process result.

Disclosed is an operating method of an electronic device for manufacture of a semiconductor device. The operating method includes receiving a layout image of the semiconductor device, generating an intermediate image by generating assist features based on main features of the layout image, evaluating a process result by performing simulation based on the intermediate image, and correcting the intermediate image by correcting shapes of the main features and/or the assist features of the intermediate image based on the process result.

A method of inventory management involves steps to obtain a real-time image of a scene using a sensor, filter the real-time image to delineate portions of the scene, predict objects in the filtered real-time image, identify portions of the objects, and classify the objects using a trained model and the identified portions. The method transmits the real-time image to a remote site configured to generate updates to the trained model. The trained model is sent via over-the-air updates to the trained model. A method of image detection and training involves steps to receive image information of a scene, filter the image information to specify delineated portions of the scene, label portions of the image information, train a convolutional neural network to identify features of the labeled portions, extract the features of the labeled portions, and train a model based on the extracted features to be used in connection with real-time object detection.