@inproceedings{abd65ce56d734f74baf5a10bf591cfe2,
title = "Handling spatial uncertainty in binary images: A rough set based approach",
abstract = "In this paper we consider the problem of detecting binary objects. We present a method for constructing a gray-scaled (or, fuzzy) template for use in correlation-based matching of Boolean images, using rough sets. First, we represent the binary images in the morphological sense-that is-as sets. Next, we assume a cause for spatial uncertainty that is quite common in machine vision applications and present a methodology for modeling it indirectly in the construction of the template. Then we show how rough sets can be used to determine the matching probabilities constructively, rather than through trial and error, as is usually the case. Our technique is computationally efficient and is superior to correlation-based techniques, which can be easily fooled and automates the hand-selection of structuring elements for the hit-or-miss transform technique, both of which are usually used to solve this problem.",
author = "D. Sinha and P. Laplante",
year = "2002",
month = jan,
day = "1",
language = "English (US)",
isbn = "9783540442745",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "610--621",
editor = "Alpigini, {James J.} and Peters, {James F.} and Ning Zhong and Andrzej Skowron",
booktitle = "Rough Sets and Current Trends in Computing - 3rd International Conference, RSCTC 2002, Proceedings",
address = "Germany",
note = "3rd International Conference on Rough Sets and Current Trends in Computing, RSCTC 2002 ; Conference date: 14-10-2002 Through 16-10-2002",
}