Handling spatial uncertainty in binary images: A rough set based approach

D. Sinha, P. Laplante

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationRough Sets and Current Trends in Computing - 3rd International Conference, RSCTC 2002, Proceedings
EditorsJames J. Alpigini, James F. Peters, Ning Zhong, Andrzej Skowron
PublisherSpringer Verlag
Pages610-621
Number of pages12
ISBN (Print)9783540442745
StatePublished - Jan 1 2002
Event3rd International Conference on Rough Sets and Current Trends in Computing, RSCTC 2002 - Malvern, United States
Duration: Oct 14 2002Oct 16 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2475
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Conference on Rough Sets and Current Trends in Computing, RSCTC 2002
CountryUnited States
CityMalvern
Period10/14/0210/16/02

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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