Application of artificial neural networks for feature recognition in image registration

被引:1
|
作者
Ontman, A. Y. M. [1 ]
Shiflet, G. J. [1 ]
机构
[1] Univ Virginia, Dept Mat Sci & Engn, Charlottesville, VA 22904 USA
关键词
Microindentation; microstructure; modelling; neural network; self-organization and patterning; simulation;
D O I
10.1111/j.1365-2818.2011.03580.x
中图分类号
TH742 [显微镜];
学科分类号
摘要
Image registration is a process of aligning two or more images taken at different times or using different sensors by transforming the same area into one coordinate system. Imaging conditions, image and area deteriorations from repeated sectioning, are serious impediments to successful image registration. The application of artificial neural networks for feature recognition is introduced to the field of metallurgy to assist in an automated approach to image registration of metallurgical microstructures. Low susceptibility to feature deterioration, often occurring during serial sectioning, is demonstrated and assessed. The process of image registration using an artificial neural network to aid in feature segmentation is performed using computer generated shapes and a metallurgical microstructure.
引用
收藏
页码:20 / 32
页数:13
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