Vladimir Curic: Exciting world of image analysis
I am Vladimir Curic, a postdoctoral researcher at Uppsala University, Sweden. My research interests include the development of mathematical models for image analysis, morphological image processing and data analysis. The scientic problems that I have found most interesting are related to the development of mathematical models for various real world problems ranging from engineering to biology.
I finished my master degree in technomathematics from University of Novi Sad, Serbia. During my master studies, thanks to the ECMI exchange program, I had the opportunity to spend four months at Lappeeranta University of Technology, Finland, where I worked with profesor Matti Heilio. My master thesis focused on the development of a mathematical model for optimal pump scheduling in water distribution system.
I received my PhD degree from Centre for Image Analysis, Uppsala University in 2014, under the supervision of professor Gunilla Borgefors. In particular, I proposed and developed several methods for the object comparison, especially how to measure and characterize objects in images, in terms of their shape, size, and geometry. In the first project, I proposed a new distance function between sets of points, where the contribution of each point to the distance function is determined by the position of the point within the set, i.e., weighted with the respect of the complement of the considered set. The applicability of the new distance function was shown for different shape recognition and image registration, including often complicated multi-modal image registration. The second scientic problem that attracted my attention is the development of adaptive mathematical morphology, i.e., adaptive morphological operators that utilize spatially variant structuring elements, which adapt their size and shape with respect to the position in the image. I developed various mathematical models for adaptive morphological operators, where new theoretical results are proposed and usefulness of these operators was shown in several applications including image denoising and isolating text from images of historical documents.
After finishing my PhD studies, I continued working on image and data analysis as a postdoctoral researcher at Uppsala University, where my current research focus is on the development of image analysis methods for the single molecule tracking experiment. Recent technological developments have provided the tools to design and build scientific instruments of high sensitivity and precision to manipulate and visualize individual molecules (The Nobel Prize in Chemistry 2014 is awarded jointly to Eric Betzig, Stefan W. Hell and William E. Morner for the development of super-resolved fluorescent microscopy). This has enabled single-particle tracking applications for studying the dynamics of molecules and one of the crucial points of such applications is to localize single fluorophores with very high precission and accuracy.