Abstract: A camera on a railroad vehicle captures image data depicting a surrounding environment. An on-board computing system of the railroad vehicle uses image processing operations to identify railroad assets and/or railroad asset subcomponents depicted in the image data. The on-board computing system may evaluate the image data to identify, substantially in real time, defects in the railroad assets and/or subcomponents depicted in the image data. The on-board computing system may also, or alternately, generate compact asset data, such as vectors, splines, and/or polygons, that represents the types, shapes, orientations, and locations of railroad assets and/or subcomponents identified based on the captured image data. Comparison of compact asset data associated with different points in time may identify changes to the shapes, orientations, and locations of the railroad assets and/or subcomponents over time that may be indicative of defects.

Abstract: A system, method, and computer program product for registering two or more patient images for change assessment over time. An example aspect is configured to: obtain a new image of an area with an image capture system; obtain a reference image of a similar area; perform pre-processing of the new image and the reference image; perform a coarse alignment of the new image and the reference image; perform a high-resolution estimate; perform a high-resolution alignment; cross-check the at least one-point match to eliminate false matches and confirm correct matches of the high-resolution new image and the high-resolution reference image; perform segmentation of the high-resolution new image and the high-resolution reference image; perform analysis on at least one lesion in the high-resolution new image and the high-resolution reference image; and display a result of the analysis on a validator.

Abstract: A system, method, and computer program product for registering two or more patient images for change assessment over time. An example aspect is configured to: obtain a new image of an area with an image capture system; obtain a reference image of a similar area; perform pre-processing of the new image and the reference image; perform a coarse alignment of the new image and the reference image; perform a high-resolution estimate; perform a high-resolution alignment; cross-check the at least one-point match to eliminate false matches and confirm correct matches of the high-resolution new image and the high-resolution reference image; perform segmentation of the high-resolution new image and the high-resolution reference image; perform analysis on at least one lesion in the high-resolution new image and the high-resolution reference image; and display a result of the analysis on a validator.

Abstract: A system, method, and computer program product for quantification of severity of a lung disease. An example aspect is configured to: provide an image file of a chest x-ray from a patient to a first artificial intelligence system to perform pre-processing of the image, wherein the lung is divided into at least four sections; provide each section to a second artificial intelligence system to generate a first density score and a first extent score of each section to calculate a first RALE score, wherein the second artificial intelligence system generates a density segmentation map of each section to calculate a second density score and a second extent score to calculate a second RALE score; analyze the first RALE score and the second RALE score; and display a result to a user.

Abstract: A system, method, and computer program product for registering two or more patient images for change assessment over time. An example aspect is configured to: obtain a new image of an area with an image capture system; obtain a reference image of a similar area; perform pre-processing of the new image and the reference image; perform a coarse alignment of the new image and the reference image; perform a high-resolution estimate; perform a high-resolution alignment; cross-check the at least one-point match to eliminate false matches and confirm correct matches of the high-resolution new image and the high-resolution reference image; perform segmentation of the high-resolution new image and the high-resolution reference image; perform analysis on at least one lesion in the high-resolution new image and the high-resolution reference image; and display a result of the analysis on a validator.

Abstract: A vision system for assisting an operator of a machine is provided. An image capturing device, mounted on the machine, is configured to capture an image of an environment of the machine. The vision system includes a controller configured to apply an object detection process to detect an object in the image. The controller determines a bounding box comprising one or more pixels associated with the object. The controller determines a height and a range associated with the object based on the bounding box. The controller extracts the one or more pixels within the bounding box. The controller is further configured to generate a three-dimensional (3D) view comprising the object based on the image captured by the image capturing device. The controller reinserts the one or more pixels as a vertical pop-up element with respect to a ground plane in the 3D view. A display is provided to display the 3D view to the operator of the machine.

Abstract: A method for monitoring the movement of a work tool of a machine using a work tool vision a comprises sensing data related to the image of a work tool, selecting a template of an image of a work tool, and displaying the sensed image of the work tool after modifying the sensed image of the work tool by at least zooming on a portion of the sensed data of the image if the sensed data of the image of a work tool matches the template of an image of a work tool.

Abstract: A vision system for assisting an operator of a machine is provided. An image capturing device, mounted on the machine, is configured to capture an image of an environment of the machine. The vision system includes a controller configured to apply an object detection process to detect an object in the image. The controller determines a bounding box comprising one or more pixels associated with the object. The controller determines a height and a range associated with the object based on the bounding box. The controller extracts the one or more pixels within the bounding box. The controller is further configured to generate a three-dimensional (3D) view comprising the object based on the image captured by the image capturing device. The controller reinserts the one or more pixels as a vertical pop-up element with respect to a ground plane in the 3D view. A display is provided to display the 3D view to the operator of the machine.

Abstract: A method for detecting an object in an environment of a machine is provided. The method includes determining a first height of the object by applying sliding window detection process on an image. The method determines a score indicating a probability that the object detected in the image matches a predefined set of characteristics. The method further includes determining a minimum and a maximum vertical pixel associated with the object. The method includes determining a second height of the object based on a range of the object, the minimum vertical pixel, the maximum vertical pixel, intrinsic and extrinsic calibration parameters of the image capturing device. The method includes comparing the first height with the second height and accordingly, modifying the score regarding the detection of the object in the image based on whether a difference between the first height and the second height meets a predetermined criterion.

Abstract: A method for monitoring the movement of a work tool of a machine using a work tool vision a comprises sensing data related to the image of a work tool, selecting a template of an image of a work tool, and displaying the sensed image of the work tool after modifying the sensed image of the work tool by at least zooming on a portion of the sensed data of the image if the sensed data of the image of a work tool matches the template of an image of a work tool.