Abstract: A system and method of detecting trees in an image. A system and method may receive a dimension related to the trees in an input image. A two dimensional (2D) high pass filter may be applied to the input image to produce a high pass image. Objects may be marked in the high pass image based on the dimension. A processed image may be produced by associating a set of pixels in the high pass image with a respective set of grayscale values. A density operator may be applied to the processed image to identify locations with high frequency changes. Shapes may be defined to include the locations. Trees may be identified by grouping one or more shapes.

Abstract: A system and method for detecting and representing a directionality of objects in an image. A system and method may process an input image to produce a set of direction-filtered images, calculate a local gradient field based on the of direction-filtered images, calculate a magnitude of a projection of a local gradient on a predefined direction and use the projection to represent a directionality of the set of objects. A system and method may calculate a local orientation angle and associate the local orientation angle with pixels in an input digital image.

Abstract: A system and method of detecting trees in an image. A system and method may receive a dimension related to the trees in an input image. A two dimensional (2D) high pass filter may be applied to the input image to produce a high pass image. Objects may be marked in the high pass image based on the dimension. A processed image may be produced by associating a set of pixels in the high pass image with a respective set of grayscale values. A density operator may be applied to the processed image to identify locations with high frequency changes. Shapes may be defined to include the locations. Trees may be identified by grouping one or more shapes.

Abstract: A system and method for detecting and representing a directionality of objects in an image. A system and method may process an input image to produce a set of direction-filtered images, calculate a local gradient field based on the of direction-filtered images, calculate a magnitude of a projection of a local gradient on a predefined direction and use the projection to represent a directionality of the set of objects. A system and method may calculate a local orientation angle and associate the local orientation angle with pixels in an input digital image.

Abstract: A device and method for identifying plant rows in a field represented by an image is provided. The plant rows may be identified using the frequency domain. The plant rows may further be identified using information regarding plant positions. Additionally, plant rows may be obtained by any appropriate method and analyzed to differentiate between planted and non-planted rows. Further, plant rows may be segmented according to predefined classifications or attributes thereof, wherein the classification/attributes may derived from an image of the area in which the plant rows are found and/or using any other appropriate method.

Abstract: A device and method for identifying plant rows in a field represented by an image is provided. The plant rows may be identified using the frequency domain. The plant rows may further be identified using information regarding plant positions. Additionally, plant rows may be obtained by any appropriate method and analyzed to differentiate between planted and non-planted rows. Further, plant rows may be segmented according to predefined classifications or attributes thereof, wherein the classification/attributes may derived from an image of the area in which the plant rows are found and/or using any other appropriate method.