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Application of artificial neural networks for feature recognition in image registration
Author(s) -
ONTMAN A.Y.M.,
SHIFLET G.J.
Publication year - 2012
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/j.1365-2818.2011.03580.x
Subject(s) - artificial intelligence , feature (linguistics) , artificial neural network , computer vision , image registration , computer science , segmentation , pattern recognition (psychology) , process (computing) , image (mathematics) , image segmentation , image processing , feature detection (computer vision) , philosophy , linguistics , operating system
Summary 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.