摘要:
System and method for characterizing vision systems. A multi-dimensional condition space is provided, each dimension representing a respective condition axis, where each point in the condition space specifies a set of conditions under which a vision system may operate. An image is provided. The condition space is sampled according to a pseudo-random sequence, e.g., a low-discrepancy sequence, to determine a plurality of test conditions usable to characterize the vision system, where each test condition corresponds to a respective set of conditions. A plurality of test images corresponding to the plurality of test conditions are generated based on the image, e.g., by applying image processing functions to the image that simulate the test conditions. A vision inspection is performed on each of the plurality of test images to generate respective test results, and the test results are analyzed to determine conditions under which the vision system operates correctly.
摘要:
System and method for characterizing vision systems. A multi-dimensional condition space is provided, each dimension representing a respective condition axis, where each point in the condition space specifies a set of conditions under which a vision system may operate. An image is provided. The condition space is sampled according to a pseudo-random sequence, e.g., a low-discrepancy sequence, to determine a plurality of test conditions usable to characterize the vision system, where each test condition corresponds to a respective set of conditions. A plurality of test images corresponding to the plurality of test conditions are generated based on the image, e.g., by applying image processing functions to the image that simulate the test conditions. A vision inspection is performed on each of the plurality of test images to generate respective test results, and the test results are analyzed to determine conditions under which the vision system operates correctly.
摘要:
System and method for measuring distances in an image. An image is received that includes curves corresponding to one or more objects in the image. Multiple curves in a specified region of interest (ROI) in the image are detected, where the ROI has a specified direction. Each curve includes respective curve points. A convex hull is determined based on the respective curve points. One or more candidate antipodal point pairs of the convex hull are determined. A first point pair of the one or more antipodal point pairs is selected based on one or more specified constraints. A clamp angle corresponding to the first point pair is determined. A distance between the first point pair along a direction specified by the clamp angle is determined. The first point pair, the distance, and the clamp angle are stored. Calibration information may be applied at any point during the process.
摘要:
System and method for measuring distances in an image. An image is received that includes curves corresponding to one or more objects in the image. Multiple curves in a specified region of interest (ROI) in the image are detected, where the ROI has a specified direction. Each curve includes respective curve points. A convex hull is determined based on the respective curve points. One or more candidate antipodal point pairs of the convex hull are determined. A first point pair of the one or more antipodal point pairs is selected based on one or more specified constraints. A clamp angle corresponding to the first point pair is determined. A distance between the first point pair along a direction specified by the clamp angle is determined. The first point pair, the distance, and the clamp angle are stored. Calibration information may be applied at any point during the process.
摘要:
Object detection for scene change analysis is performed by a statistical test applied to data extracted from two images taken from the same scene from identical viewpoints. It is assumed that a single change region corresponding to an object that is present in one image but absence in the other is given. In the case of TV data, the test consists of measuring the coincidence of edge pixels in each image with the boundary of the change region. In the case of IR data, the tests consist of measuring the pixel intensity variance within the change region in each image.