ITLApplied  Computational Mathematics Division
ACMD Seminar Series
Attractive Image NIST

Fast Methods to Find Optimal Shapes in Images

Gunay Dogan
Mathematical and Computational Sciences Division, NIST

Tuesday, April 21, 2009 15:00-16:00,
Building 101, Lecture Room C
Tuesday, April 21, 2009 13:00-14:00,
Room 5000

Abstract: Through the last two decades, the field of image processing has seen a significant increase in the use of energy minimization methods. An important class of such problems falls under the task of image segmentation, that is, finding distinct objects or regions in given images. Applications range from detection of people in surveillance images to 3d visualization of human organs from medical scans. These methods are usually based on partial differential equation formulations and involve iterative update of a candidate solution with respect to an assigned energy, in order to achieve a "best" solution. In this talk, we approach these problems from a shape optimization point of view and introduce a novel iterative method to find the minimum energy shapes in given images. In our method, we model the geometry explicitly, respecting the continuous structure of the problem, and discretize the resulting formulation using the finite element method. A distinct feature of our method is that it allows us to apply specially-designed gradient descent schemes tuned for improved performance. We demonstrate the power of this new method with several examples in 2d and 3d.

Speaker Bio: Gunay Dogan received his PhD degree in Applied Math and Scientific Computing from the University of Maryland, College Park in 2006. His PhD advisor was Ricardo H. Nochetto. Following his PhD, he worked as a postdoctoral researcher with George Biros at the University of Pennsylvania for two years. Currently he is a guest researcher in the Mathematical and Computational Sciences Division at NIST. Gunay Dogan's scientific contributions have been in the areas of shape optimization, image segmentation and numerical methods for inverse problems. His scientific interests are broadly in image processing, scientific computing and inverse problems, with emphasis on large-scale optimization and numerical solutions of partial differential equations."

Presentation Slides: PDF

Contact: S. Langer

Note: Visitors from outside NIST must contact Robin Bickel; (301) 975-3668; at least 24 hours in advance.

Privacy Policy | Disclaimer | FOIA
NIST is an agency of the U.S. Commerce Department.
Last updated: 2011-01-12.