Abstract: A periodic task analysis system which analyzes a task conducted by an actor periodically includes a data collecting subsystem including at least one of an imaging device configured to image a state where a plurality of fundamental work operations is performed periodically, and at least one sensing means collecting data from the state; a data receiving subsystem operatively coupled to the data collecting subsystem, where the data receiving subsystem is configured to receive at least one of a video file recorded by the imaging device and a sensor data recorded by the sensing means; a task learning subsystem operatively coupled to the data receiving subsystem, where the task learning subsystem is configured to identify one or more sub-tasks from at least one of the recorded video file and the recorded sensor data; and a task analyzing subsystem. A method for analyzing a periodic task is also provided.

Abstract: A method is provided for detecting spot defects on an object when an allowable variation (called the “background”) in the appearance of the object can be modeled. Methods are also provided for measuring and classifying detected spot defects. An alignment model is used to align the image of the object, a background model is then used to estimate the (possibly different) background in each region, and each background is substantially removed from the image so as to form a foreground image on which blob analysis can be applied to detect spot defects, the blob analysis using a threshold image that accommodates different noise statistics for each region. The method facilitates robust spot defect inspection of fiber optic end faces, or of any object with different object regions. The method also allows use of blob analysis over a larger range of conditions, including conditions that make simple blob analysis infeasible.

Abstract: A method of analyzing machine vision images to identify low contrast features such as scratches or cracks on the polished ends of optical fibers. A bank of oriented filters having incremental angles of orientation are tuned to respond to the frequency characteristics of oriented scratches or cracks having an approximate width. The filters are applied to an image to generate a filter response image for each filter orientation. The set of filter response images are combined to form a single data set indicating a magnitude and angle for each pixel in the original image. Elements of the combined data set having corresponding angles and magnitudes are grouped to form contour components that can be optionally input to higher order processes.

Abstract: A method is provided for obtaining a focused image of an object in an application of machine vision in an optical inspection system. A coarse focus setting is first obtained by maximizing a coarse feature sharpness measurement performed on an image of the object of inspection. Then, a fine focus setting is obtained by maximizing a fine feature sharpness measurement performed on a portion of an image of the object of inspection. Finally, the fine focused image can be further analyzed, inspected, or otherwise processed.