TY - GEN
T1 - Shape classifier based on Hopfield-Amari network
AU - Fu, Alan M N
AU - Yan, Hong
PY - 1996
Y1 - 1996
N2 - The representation and recognition of a planar shape based on contour information is an important issue in computer vision. In this paper, we propose a method for extracting the main features of a contour using the Curve Bend Function (CBF), which can be used to characterize the contour completely. A Hopfield-Amari network is built based on the CBF description to perform classification of planar shapes. The experimental results demonstrate that the proposed system is powerful and reliable for solving shape recognition problems.
AB - The representation and recognition of a planar shape based on contour information is an important issue in computer vision. In this paper, we propose a method for extracting the main features of a contour using the Curve Bend Function (CBF), which can be used to characterize the contour completely. A Hopfield-Amari network is built based on the CBF description to perform classification of planar shapes. The experimental results demonstrate that the proposed system is powerful and reliable for solving shape recognition problems.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0029770192&origin=recordpage
M3 - RGC 32 - Refereed conference paper (with host publication)
VL - 1
SP - 588
EP - 593
BT - IEEE International Conference on Neural Networks - Conference Proceedings
T2 - Proceedings of the 1996 IEEE International Conference on Neural Networks, ICNN. Part 1 (of 4)
Y2 - 3 June 1996 through 6 June 1996
ER -