Use of Hopfield neural network for complex image registration
Zhebin Qian, Jie-Gu Li · 2002
The paper presents an image registration method based on a two-dimensional Hopfield neural network, where the problem of image matching is treated with the minimization of the energy function of the Hopfield neural network. The input data used for registration are the locations of the corner points extracted from the images. In order to improve and expedite the matching process, a fast block-based algorithm is put forward, together with the laboratory results obtained, which show the effectiveness of the algorithm.