Lecture Abstract
The Depth from Defocus (DFD) imaging technique is used for measuring the size and number density of spherical particles in a dispersed two-phase flow. Typical application examples include the measurement of liquid sprays.
The presentation will summarize the working principles of the DFD technique and explore its limits in terms of particle size bandwidth, number density, and measurement volume. Two main approaches for processing the images will be discussed:
- The first approach utilizes not only the gray level of the blurred, out-of-focus images, but also the gradient of the gray level normal to the nominal particle contour.
- The second approach is based on a masked, regional convolutional neural network (R-CNN).
These approaches are validated and evaluated using a dedicated apparatus in which particles of known size can be systematically varied in terms of number density and degree of out-of-focus. The presentation concludes with recent developments for advancing the technique to size non-spherical particles.
Distinguished Speaker
Prof. Dr.-Ing. Cameron Tropea
Prof. Dr.-Ing. Cameron Tropea graduated in Engineering Sciences from the University of Toronto (M.A.Sc. 1977). He earned his Dr.-Ing. at TU Karlsruhe (1982) and his Habilitation at the University of Erlangen-Nürnberg (1991). In 1997, he was appointed Head of the Institute of Fluid Mechanics and Aerodynamics at Technische Universität Darmstadt.
He served as Editor-in-Chief of Experiments in Fluids (2003–2025), Director of the CSI Excellence Cluster (2007–2014), and a member of Germany's Council of Science and Humanities (Wissenschaftsrat, 2016–2022).
Prof. Tropea previously held the Henry Ford Visiting Professorship Chair at IIT Madras and a VAJRA Faculty position at IISc Bangalore (2020–2025). He is currently Visiting Faculty at IISc Bangalore, IIT Madras, and Shanghai Jiao Tong University.
Cordially Invited
All faculty members, research scholars, students, and interested colleagues are cordially invited to attend this expert lecture.