@InProceedings{SoaresKörtFons:2015:ImDiSe,
author = "Soares, Anderson Reis and K{\"o}rting, Thales Sehn and Fonseca,
Leila M. Garcia",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)}",
title = "Improvements of the divide and segment method for parallel image
segmentation",
booktitle = "Anais...",
year = "2015",
editor = "Fileto, Renato and Korting, Thales Sehn",
pages = "222--232",
organization = "Simp{\'o}sio Brasileiro de Geoinform{\'a}tica, 16. (GEOINFO)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "Remote Sensing is an important source of information about the
dynamics of Earth's land and oceans, but retrieve information from
this technique, is a challenge. Segmentation is a traditional
method in remote sensing, which have a high computational cost. An
alternative to suppress this problem is use parallel approaches,
which split the image into tiles, and segment each one
individually. However, the divisions among tiles are not natural,
which create inconsistent objects. In this work, we extended our
previous work, which used non-crisp borders computed based on
graph-theory. By applying this non-crisp line cut, we avoid the
post-processing of neighboring regions, and therefore speed up the
segmentation.",
conference-location = "Campos do Jord{\~a}o",
conference-year = "27 nov. a 02 dez. 2015",
issn = "2179-4820",
language = "en",
ibi = "8JMKD3MGPDW34P/3KP38AL",
url = "http://urlib.net/ibi/8JMKD3MGPDW34P/3KP38AL",
targetfile = "soares2015improvements.pdf",
urlaccessdate = "28 abr. 2024"
}