@InProceedings{VaqueroBarrHira:2005:MaApMu,
author = "Vaquero, Daniel Andr{\'e} and Barrera, Junior and Hirata Jr.,
Roberto",
affiliation = "{Universidade de S{\~a}o Paulo}",
title = "A maximum-likelihood approach for multiresolution W-operator
design",
booktitle = "Proceedings...",
year = "2005",
editor = "Rodrigues, Maria Andr{\'e}ia Formico and Frery, Alejandro
C{\'e}sar",
organization = "Brazilian Symposium on Computer Graphics and Image Processing, 18.
(SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "design of image operators, mathematical morphology,
multiresolution, entropy, handwritten digits recognition.",
abstract = "The design of W-operators from a set of input/output examples for
large windows is a hard problem. From the statistical standpoint,
it is hard because of the large number of examples necessary to
obtain a good estimate of the joint distribution. From the
computational standpoint, as the number of examples grows memory
and time requirements can reach a point where it is not feasible
to design the operator. This paper introduces a technique for
joint distribution estimation in W-operator design. The
distribution is represented by a multiresolution pyramidal
structure and the mean conditional entropy is proposed as a
criterion to choose between distributions induced by different
pyramids. Experimental results are presented for
maximum-likelihood classifiers designed for the problem of
handwritten digits classification. The analysis shows that the
technique is interesting from the theoretical point of view and
has potential to be applied in computer vision and image
processing problems.",
conference-location = "Natal",
conference-year = "9-12 Oct. 2005",
language = "en",
targetfile = "vaquerod_multiresolution.pdf",
urlaccessdate = "2020, Nov. 27"
}