TY - JOUR
T1 - A genetic algorithm for affine invariant object shape recognition
AU - Tsang, P. W M
PY - 1997
Y1 - 1997
N2 - Abstract: In this paper, a novel technique for matching images of object shapes which have been subject to affine transformation caused by variations in the camera position is reported. The method is based on the genetic algorithm, and is more efficient and reliable than conventional approaches that rely on corresponding dominant point pairs to determine the best alignment between object boundaries. Experimental results are presented to demonstrate the feasibility of the approach and its capability in identifying object shapes that had been distorted with heavy noise contamination. © IMechE 1997.
AB - Abstract: In this paper, a novel technique for matching images of object shapes which have been subject to affine transformation caused by variations in the camera position is reported. The method is based on the genetic algorithm, and is more efficient and reliable than conventional approaches that rely on corresponding dominant point pairs to determine the best alignment between object boundaries. Experimental results are presented to demonstrate the feasibility of the approach and its capability in identifying object shapes that had been distorted with heavy noise contamination. © IMechE 1997.
KW - Affine invariant shape matching
KW - Curvature guided split and merge
KW - Genetic algorithm
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0031338796&origin=recordpage
M3 - RGC 21 - Publication in refereed journal
SN - 0959-6518
VL - 211
SP - 385
EP - 392
JO - Proceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering
JF - Proceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering
IS - 5
ER -