TY - GEN
T1 - Handling spatial uncertainty in binary images
T2 - 3rd International Conference on Rough Sets and Current Trends in Computing, RSCTC 2002
AU - Sinha, D.
AU - Laplante, P.
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2002.
PY - 2002
Y1 - 2002
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84942901988&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84942901988&partnerID=8YFLogxK
U2 - 10.1007/3-540-45813-1_81
DO - 10.1007/3-540-45813-1_81
M3 - Conference contribution
AN - SCOPUS:84942901988
SN - 9783540442745
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 610
EP - 621
BT - Rough Sets and Current Trends in Computing - 3rd International Conference, RSCTC 2002, Proceedings
A2 - Alpigini, James J.
A2 - Peters, James F.
A2 - Skowron, Andrzej
A2 - Zhong, Ning
PB - Springer Verlag
Y2 - 14 October 2002 through 16 October 2002
ER -