Publications:
All
 Iñesta, J.M., Buendía, M., Sarti, M.A.
"Reliable polygonal approximations of Imaged Real Objects through dominant point detection" Pattern Recognition, vol. 31, pp. 685699
(1998)
: bibtexAbstract: The problem of data reduction in contours via dominant points is posed, taking into account what usually happens in practice. The algorithms found in the literature often prove their performance with laboratory contours (i.e., artificial curves designed by the authors in order to test their algorithms), but the shapes in real images are quite different: noise, quantization, and high inter and intrashape variability are effects that should be taken into account. The presence of noise has already been faced
by using a gaussian smoothing. To deal with variability only an
algorithm working independently of input parameters, adjusting
itself to each curve, could give satisfactory results if an efficient
and reliable representation of the contours is desired. Here we
focus in the problem of image quantization. The addition to the
existent non parametric algorithms of a criterion for deleting
collinear points is very useful, since it increments the
compression rate, without raising the error committed by the
polygonal approximation. Thus, the number of segments
necessary to reliably represent the shape of the contours is
reduced. For evaluating it, a new measurement of the error has
been defined that assess the goodness of the approximation with
a single value, taking into account both the compression rate
and the reliability of the selected set of points.
We will also focus on the conditions for an efficient (few
points) and precise (low error) dominant point extraction that
preserves the original shape. A measurement of the committed
error (optimization error, E0) that takes into account both aspects
is defined for studying this feature. Some classic algorithms are
reviewed and compared to ours, showing that the latter fits well
to data using few points (low E0), so accurate and efficient
approximations are obtained.
@article {
author = "Iñesta, J.M., Buendía, M., Sarti, M.A.",
title = "Reliable polygonal approximations of Imaged Real Objects through dominant point detection",
journal = "Pattern Recognition",
number = "6",
pages = "685699",
volume = "31",
year = "1998"
}
