A novel image registration scheme is proposed. In the proposed scheme, the complete isometric mapping (Isomap) is used to extract features from the image sets, and these features are input vectors of feedforward neural networks. Neural network outputs are those translation, rotation and scaling parameters with respect to reference and observed image sets. Comparative experiments for Isomap based method, the discrete cosine transform (DCT) and Zernike moment are performed. The results show that the proposed scheme is not only accurate but also remarkably robust to noise. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Xu, A., & Guo, P. (2006). Isomap and neural networks based image registration scheme. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3972 LNCS, pp. 486–491). Springer Verlag. https://doi.org/10.1007/11760023_71
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