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Using Directional Variance to Extract Curvees in Images, thus Improving Object Recognition in Clutter |
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@TechReport{Selinger:TR99b,
author = {Andrea Selinger and Randal C. Nelson},
title = {Using Directional Variance to Extract Curvees in Images, thus Improving Object Recognition in Clutter },
institution = {Comp. Sci. Dept. University of Rochester},
year = {1999},
number = {712},
address = {Rochester NY},
month = {April},
abstract = {
In this report we describe a method for extracting curves from an image using directional pixel variances instead
of gradient measures as low-level boundary evidence. The advantage of the variance over the image gradient is that
we can accurately compute the direction of a local edge even if a sudden contrast change occurs in the background.
This allows curves belonging to object contours to be followed more easily. We compared our method to a similar
method based on the image gradient and we found that it obtains better results when run on synthetic and natural
images. Our method also improved the performance of a contour-based 3D object recognition system in cluttered images.
}
}