Abstract: The empty vs. non-empty status of a cargo container is detected based on boundary analysis of a wide-angle image obtained by a monocular vision system. The wide-angle image is warped to remove distortion created by the vision system optics, and the resulting image is edge-processed to identify the boundaries of the container floor. If package boundaries are detected within the floor space, or a large foreground package is blocking the floor boundaries, the cargo status is set to non-empty. If floor boundaries are detected and no package boundaries are detected within the floor space, the cargo status is set to empty.

Abstract: A method for identifying objects in an electronic image is provided. The method includes the steps of providing an electronic source image and processing the electronic source image to identify edge pixels. The method further includes the steps of providing an electronic representation of the edge pixels and processing the electronic representation of the edge pixels to identify valid edge center pixels. The method still further includes the step of proving an electronic representation of the valid edge center pixels. Each valid edge center pixel represents the approximate center of a horizontal edge segment of a target width. The horizontal edge segment is made up of essentially contiguous edge pixels. The method also includes the steps of determining symmetry values of test regions associated with valid edge center pixels, and classifying the test regions based on factors including symmetry.

Abstract: A method for identifying objects in an electronic image is provided. The method includes the steps of providing an electronic source image and processing the electronic source image to identify edge pixels. The method further includes the steps of providing an electronic representation of the edge pixels and processing the electronic representation of the edge pixels to identify valid edge center pixels. The method still further includes the step of proving an electronic representation of the valid edge center pixels. Each valid edge center pixel represents the approximate center of a horizontal edge segment of a target width. The horizontal edge segment is made up of essentially contiguous edge pixels. The method also includes the steps of determining symmetry values of test regions associated with valid edge center pixels, and classifying the test regions based on factors including symmetry.

Abstract: The empty vs. non-empty status of a cargo container is detected based on boundary analysis of a wide-angle image obtained by a monocular vision system. The wide-angle image is warped to remove distortion created by the vision system optics, and the resulting image is edge-processed to identify the boundaries of the container floor. If package boundaries are detected within the floor space, or a large foreground package is blocking the floor boundaries, the cargo status is set to non-empty. If floor boundaries are detected and no package boundaries are detected within the floor space, the cargo status is set to empty.

Abstract: A technique for identifying beam images of a beam matrix includes a number of steps. Initially, a plurality of light beams of a beam matrix, which are arranged in rows and columns, are received after reflection from a surface of a target. Next, a reference light beam is located in the beam matrix. Then, a row pivot beam is located in the beam matrix based on the reference beam. Next, remaining reference row beams of a reference row that includes the row pivot beam and the reference beam are located. Then, a column pivot beam in the beam matrix is located based on the reference beam. Next, remaining reference column beams of a reference column that includes the column pivot beam and the reference beam are located. Finally, remaining ones of the light beams in the beam matrix are located.

Abstract: A pattern recognition system is utilized in a supplementary inflatable restraint (SIR) system to distinguish between deployment and non-deployment events. The pattern recognition system preferably includes dedicated hardware or a microprocessor programmed to perform a neural network simulation utilizing crash data in the form of vehicle acceleration data. Training and trial vectors are generated from the data to train and, subsequently, test the neural network.