Abstract: A grain tailings elevator for a combine harvester includes a an elevator housing having an interior containing a conveyor arrangement configured to transport grain tailings through the elevator housing to a discharge outlet. The elevator housing has a side wall with a window to the interior of the elevator housing. A camera having a camera housing containing an image sensor is mounted to the side wall of the elevator housing over the window with the image sensor in registration with the window. The image sensor is trained on the conveyor arrangement and configured to image the grain tailings transported by the conveyor arrangement through the elevator housing.

Abstract: A method and system for controlling the quality of harvested grains include capturing, by one or more image sensors, one or more images of material at a sampling location within a grain elevator of the combine harvester. The captured images are defined by a set of image pixels represented by image data and having a classification feature indicative of grain or non-grain material. One or more controllers receive the image data associated with the one or more images captured by the image sensor(s) and select a sample image defined by a subset of image pixels of the set of image pixels. The controller(s) apply a convolutional neural network (CNN) algorithm to the image data of the subset of image pixels of the selected sample image to determine the classification feature. The controller(s) analyze the determined classification feature to adjust an operational parameter of the combine harvester.

Abstract: A method and system for controlling the quality of harvested grains include capturing, by one or more image sensors, one or more images of material at a sampling location within a grain elevator of the combine harvester. The captured images are defined by a set of image pixels represented by image data and having a classification feature indicative of grain or non-grain material. One or more controllers receive the image data associated with the one or more images captured by the image sensor(s) and select a sample image defined by a subset of image pixels of the set of image pixels. The controller(s) apply a convolutional neural network (CNN) algorithm to the image data of the subset of image pixels of the selected sample image to determine the classification feature. The controller(s) analyze the determined classification feature to adjust an operational parameter of the combine harvester.

Abstract: A grain tailings elevator for a combine harvester includes a an elevator housing having an interior containing a conveyor arrangement configured to transport grain tailings through the elevator housing to a discharge outlet. The elevator housing has a side wall with a window to the interior of the elevator housing. A camera having a camera housing containing an image sensor is mounted to the side wall of the elevator housing over the window with the image sensor in registration with the window. The image sensor is trained on the conveyor arrangement and configured to image the grain tailings transported by the conveyor arrangement through the elevator housing.

Abstract: An observation system for viewing light-sensitive tissue includes an illumination system configured to illuminate the light-sensitive tissue, an imaging system configured to image at least a portion of the light-sensitive tissue upon being illuminated by the illumination system, and an image display system in communication with the imaging system to display an image of the portion of the light-sensitive tissue. The illumination system is configured to illuminate the light-sensitive tissue with a reduced amount of light within a preselected wavelength range compared to multispectral illumination light, and the image of the portion of the light-sensitive tissue is compensated for the reduced amount of light within the preselected frequency range to approximate an image of the light-sensitive tissue under the multispectral illumination.

Abstract: An observation system for viewing light-sensitive tissue includes an illumination system configured to illuminate the light-sensitive tissue, an imaging system configured to image at least a portion of the light-sensitive tissue upon being illuminated by the illumination system, and an image display system in communication with the imaging system to display an image of the portion of the light-sensitive tissue.

Abstract: An observation system for viewing light-sensitive tissue includes an illumination system configured to illuminate the light-sensitive tissue, an imaging system configured to image at least a portion of the light-sensitive tissue upon being illuminated by the illumination system, and an image display system in communication with the imaging system to display an image of the portion of the light-sensitive tissue. The illumination system is configured to illuminate the light-sensitive tissue with a reduced amount of light within a preselected wavelength range compared to multispectral illumination light, and the image of the portion of the light-sensitive tissue is compensated for the reduced amount of light within the preselected frequency range to approximate an image of the light-sensitive tissue under the multispectral illumination.

Abstract: An observation system for viewing light-sensitive tissue includes an illumination system configured to illuminate the light-sensitive tissue, an imaging system configured to image at least a portion of the light-sensitive tissue upon being illuminated by the illumination system, and an image display system in communication with the imaging system to display an image of the portion of the light-sensitive tissue.