TY - GEN
T1 - Matching with quantum genetic algorithm and shape contexts
AU - Mezghiche, Khalil M.
AU - Melkemi, Kamal E.
AU - Foufou, Sebti
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014
Y1 - 2014
N2 - In this paper, we propose to combine the shape context (SC) descriptor with quantum genetic algorithms (QGA) to define a new shape matching and retrieval method. The SC matching method is based on finding the best correspondence between two point sets. The proposed method uses the QGA to find the best configuration of sample points in order to achieve the best possible matching between the two shapes. This combination of SC and QGA leads to a better retrieval results based on our tests. The SC is a very powerful discriminative descriptor which is translation and scale invariant, but weak against rotation and flipping. In our proposed quantum shape context algorithm (QSC), we use the QGA to estimate the best orientation of the target shape to ensure the best matching for rotated and flipped shapes. The experimental results showed that our proposed QSC matching method is much powerful than the classic SC method for the retrieval of shapes with orientation changes.
AB - In this paper, we propose to combine the shape context (SC) descriptor with quantum genetic algorithms (QGA) to define a new shape matching and retrieval method. The SC matching method is based on finding the best correspondence between two point sets. The proposed method uses the QGA to find the best configuration of sample points in order to achieve the best possible matching between the two shapes. This combination of SC and QGA leads to a better retrieval results based on our tests. The SC is a very powerful discriminative descriptor which is translation and scale invariant, but weak against rotation and flipping. In our proposed quantum shape context algorithm (QSC), we use the QGA to estimate the best orientation of the target shape to ensure the best matching for rotated and flipped shapes. The experimental results showed that our proposed QSC matching method is much powerful than the classic SC method for the retrieval of shapes with orientation changes.
KW - quantum genetic algorithm
KW - shape context
KW - shape matching
KW - shape retrieval
UR - http://www.scopus.com/inward/record.url?scp=84940857689&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84940857689&partnerID=8YFLogxK
U2 - 10.1109/AICCSA.2014.7073245
DO - 10.1109/AICCSA.2014.7073245
M3 - Conference contribution
AN - SCOPUS:84940857689
T3 - Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA
SP - 536
EP - 542
BT - 2014 IEEE/ACS 11th International Conference on Computer Systems and Applications, AICCSA 2014
PB - IEEE Computer Society
T2 - 2014 11th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2014
Y2 - 10 November 2014 through 13 November 2014
ER -