Invariant feature matching by Hopfield-type neural network

被引：0
|
作者：
Li, WJ [1 ]
Lee, T [1 ]
机构：
[1] Chinese Univ Hong Kong, Dept Elect Engn, Comp Vis & Image Proc Lab, Hong Kong, Hong Kong, Peoples R China
来源：
PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3 | 2002年
关键词：
D O I：
10.1109/IJCNN.2002.1007582
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a novel Hopfield model for silhouette matching invariant to projective transformations is proposed. Although the new network has higher-order energy function, we show that it can be solved using a standard second-order Hopfield network, by taking advantage of the neighborhood information in the data. The experimental results with real data show that the proposed method can provide accurate matching results in image registration and object recognition.
引用
收藏
页码：2743 / 2748
页数：6
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