Prof. Dr. Stephan Hussmann
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Academic Career Length
20Years (2007-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications5 September 2018 in Computers and Electronics in Agriculture
Journal Article
FKFlorian J. Knoll
Florian J. KnollVCVitali Czymmek
Vitali Czymmek
SPSascha Poczihoski
Sascha Poczihoski
THTim Holtorf
Tim Holtorf
Stephan Hussmann1 May 2007
Conference Paper
Stephan HussmannTLThorsten Liepert
Thorsten Liepert
Stereo vision is widely used and well known for many 3D image applications. In this paper a 3D time-of-flight system will be introduced which is integrated into a robot vision system. The pro and cons of the system in comparison to stereo vision are discussed and the basic equations needed for acquiring the range information are derived. Moreover object segmentation algorithms working on the range data are presented and experimental results verify the function of the proposed robot vision system.
Journal Article
VCVitali Czymmek
Vitali CzymmekCKCarolin Köhn
Carolin KöhnLHLeif Ole Harders
Leif Ole HardersStephan HussmannThe sustainable cultivation of organic vegetables and the associated problem of weed control has been a current research topic for some time. Despite this, the use of chemical and synthetic pesticides increases every year. This is to be solved with the help of an automated robot system. The current version of the weeding robot uses GPUs to execute the inference phase. This requires a lot of energy for an 8-track robot. To enable autonomous solar operation, the system must be made more energy efficient. This work aims to evaluate possible approaches and the current state of research on implementing convolution neural networks on low power embedded systems. In the course of the work, the technical feasibility for the implementation of CNNs in FPGAs was examined, in particular, following the example of a feasibility analysis. This paper shows that the acceleration of convolution neural networks using FPGAs is technically feasible for use as detection hardware in the weeding robot. With the help of the current state of research and the existing literature, the optimization possibilities of the hardware and software have been evaluated. The trials of different networks on different hardware accelerators with diverse approaches were investigated and compared.
Journal Article
Manual weed control is becoming increasingly costly, necessitating the development of alternative methods. This work investigates the feasibility of using laser technology for autonomous weed regulation. We developed a system utilizing a laser scanner to target and eliminate weeds, which was first tested using a pilot laser for accuracy and performance. Subsequently, the system was upgraded with a high-power fiber laser. Experimental results demonstrated a high weed destruction accuracy with real-time capabilities. The system achieved efficient weed control with minimal environmental impact, providing a potential alternative for sustainable agriculture.
26 February 2016 in IEEE Transactions on Instrumentation and Measurement
Journal Article
FKFlorian Johannes Knoll
Florian Johannes Knoll
THTim Holtorf
Tim Holtorf
Stephan HussmannAutomatic weed control is always an important issue in organic farming. To remove the weed, it is important to find the root exit point vector of the plants. This paper focuses on the use of different sensor technologies for agricultural applications in organic farming and benchmarks them to each other. Furthermore, this paper proposes different algorithms for the search of the plant root exit point. Moreover, the plant root exit point vector is determined by the algorithms. The plant root exit point vector of weed must be known to allow a proper elimination. The performance of the derived algorithm is illustrated by the experimental results.
1 May 2015
Conference Paper
In machine vision applications, Time-of-Flight (TOF) sensors like the Photonic Mixer Devices (PMD) became considerable alternatives to common 3D sensing devices. Because of the enormous progress in TOF-vision systems, nowadays 3D matrix cameras can be used for many applications such as robotic, automotive, industrial, medical and multimedia applications. This paper focuses on the range data resolution for machine vision applications in the close-up range. For many applications the 3D information of objects are required in Cartesian coordinates. However TOF cameras normally deliver polar coordinates. In this paper different polar to Cartesian coordinate system conversion methods and their influence of the range resolution in the close-up range of TOF cameras are investigated.
About Me
Stephan Hussmann (IEEE SM’11) received his M.E. and Ph.D. degrees from the University of Siegen, Siegen, Germany, in 1995 and 2000, respectively. From 1996 to 2000, he was a Research Associate with the Center for Sensor Systems, University of Siegen, and a Development Engineer with Aicoss GmbH, Siegen. From 2001 to 2003, he was a Lecturer with the Department of Electrical and Computer Engineering, University of Auckland, Auckland, New Zealand. Since the end of 2004, he has been a Professor with the Faculty of Engineering, West Coast University of Applied Sciences (FHW), Heide, Germany, in the area of microprocessor technology and electronic systems. In 2011 he founded the registered association Initiative Bildverarbeitung e.V. where he is still the acting chairman. The Initiative Bildverarbeitung e.V. organizes regular lectures where industry partners and University members come together to discuss potential joint working groups or joint projects. Since 2014 he is leading the research group "Digitalization in the Agricultural, Forestry, and Maritime Sectors". He has widely consulted with the industry and has more than 100 publications, which include books, book chapters, international patents, and refereed journal and conference proceedings papers. His research interests include machine vision applications, low-cost multi-sensor system design, real-time image processing, embedded systems design and automation in agriculture, forestry and maritime applications.