Abstract
In this publication, we describe an automatic vision based system for the reliable detection and recognition of green asparagus in variable daylight conditions. The focus is on an algorithm for the estimation and tracking of the 3D-position of green asparagus based on using of Kalman and Particle filters and a combination of both filters.
Zusammenfassung
In diesem Artikel beschreiben wir ein bildbasiertes automatisches System zur zuverlässigen Erfassung und Erkennung von grünen Spargelstangen unter variablen Tageslichtbedingungen. Der Schwerpunkt liegt auf einem Algorithmus zur Schätzung und Verfolgung der 3D-Fußpunktposition von grünem Spargel mit einem Kalman-Filter und einem Partikelfilter sowie einer Kombination der beiden Filter.
Funding statement: Seventh Framework Programme,http://dx.doi.org/10.13039/501100004963
About the authors
Jelena Ivanova received the diploma degree in Electrical Engineering from Technical University Hamburg-Harburg, Germany, in 2009. She is currently a Ph.D. student at Institute of Automation, University of Bremen. Her main areas of interest are digital image processing and probabilistic filters.
Institute of Automation, University of Bremen, Otto-Hahn-Allee, NW1, 28359 Bremen, Germany
Henning Kampe received the diploma degree in Electrical Engineering and Information Technology from University of Bremen, Germany, in 2009. He received his Ph.D. degree in the field of software-architecture design from the University of Bremen in 2016. His main areas of interest are software development and system design.
Institute of Automation, University of Bremen, Otto-Hahn-Allee, NW1, 28359 Bremen, Germany
Xiangpeng Liu received the B.Eng. degree in Electronic Information Engineering from Shandong University, China, in 2009 and M.Sc. degree in Information and Automation Engineering from University of Bremen, Germany in 2011 respectively. He is currently a Ph.D. student at the Institute of Automation, University of Bremen. His research interest is digital image processing for driver assistance systems.
Institute of Automation, University of Bremen, Otto-Hahn-Allee, NW1, 28359 Bremen, Germany
Axel Gräser received the diploma in electrical engineering from the University of Karlsruhe, Germany, in 1976 and the Ph.D. degree in control theory from the TH Darmstadt, Germany, in 1982. Since 1994, he has been the Director of the Institute of Automation, University of Bremen, and the Head of the Department of Robotics and Process Automation. His research interests include service robotics, brain robot interface, digital image processing and augmented reality.
Institute of Automation, University of Bremen, Otto-Hahn-Allee, NW1, 28359 Bremen, Germany
©2017 Walter de Gruyter Berlin/Boston
