Title :
Breakpoint detection using covariance propagation
Author :
Ji, Qiang ; Haralick, Robert M.
Author_Institution :
Dept. of Electr. Eng., Washington Univ., Seattle, WA, USA
fDate :
8/1/1998 12:00:00 AM
Abstract :
Presents a statistical approach for detecting breakpoints from chain encoded digital arcs. An arc point is declared as a breakpoint if the estimated orientations of the two fitted lines of the two arc segments immediately to the right and left of the arc point are significantly statistically different. The major contributions of this research include developing a method for analytically estimating the covariance matrix of the fitted line parameters and proposing a perturbation model to characterize the perturbation associated with each arc point
Keywords :
computer vision; covariance matrices; edge detection; least squares approximations; statistical analysis; analytical estimation; breakpoint detection; chain encoded digital arcs; corner detection; covariance propagation; perturbation model; statistical approach; Computer errors; Computer vision; Covariance matrix; Detectors; Image edge detection; Object detection; Pattern matching; Pattern recognition; Statistical analysis; Testing;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on