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DER VERLAG IST IN DER ZEIT VOM 12.06.2019 BIS 23.06.2019 AUSCHLIESSLICH PER EMAIL ERREICHBAR.
aktualisiert am 13. Juni 2019
978-3-8439-0496-4, Reihe Informatik
Automatic Image Analysis in Micro- and Nanorobotic Environments
163 Seiten, Dissertation Carl von Ossietzky Universität Oldenburg (2012), Softcover, B5
Micro- and nanoscale objects and structures exhibit highly interesting electrical, mechanical, optical and chemical properties. Their automated manipulation and inspection enable a multitude of industrial applications and also provide powerful tools for research. This work presents two new methods which compute sensory feedback for process automation by analyzing images. The first method uses statistical pattern recognition for classifying micro- and nanoscale objects from complex image scenes. Experimental validation has been carried out in three application scenarios using scanning electron microscopy, optical microscopy and magnetic resonance imaging. The second method allows deeper insights into specimen properties by automatically fusing different techniques of microscopy. It reconstructs the spatial interrelationship of micrographs by combining the benefits of feature- and area-based alignment. A large-scale performance analysis and also multiple extensions are presented. Both methods introduced in this work help to increase the level of automation in micro- and nanorobotic tasks significantly.