IBG-2: Plant Sciences - Plant Enabling Technologies
Quantitative Image Processing group
Quantitative Image Processing
The Quantitative Image Processing group develops automated imaging systems and analyses, as well as theoretical foundations of novel image processing algorithms
Image processing addresses pattern recognition and machine learning. This includes parameter and error estimation in partial differential equations, energy- and diffusion-based data reconstruction, and automatic parametrization based on image statistics. Modeling focuses on 3D plant growth, i.e. 3D dynamic scenes including deformable objects with varying surface properties.
For imaging machines the focus of the group lies on automated high-throughput plant screening machines and lab-scale imaging setups for leaf and root growth measurement. Lab-scale imaging includes an innovative force-feedback robot arm for measuring plant shape. All aspects of system development are addressed, e.g. hardware design and selection, data storage, automatic work-flow, user interfaces, and establishing the machines as routine measurement tools. This is done in close cooperation with scientists performing biological experiments.
Leader: Dr. Hanno Scharr
last change 27.04.2010 | ICG3 Admin | Print