As of August 1 I'm no longer working for UPPMAX. I was an Application Expert in Visualisation for about 10 years. Now I will instead focus on research and then gradualy take more responsibilities in education, first as deputy director of studies and later director of studies for our division.
Handwritten Text Recognition
As of first January 2017 I have left the position as director of Swedish eScience Education to work 40% with research in handwritten text recognition. A call for PhD students is now out and a call for postdoc will follow (see Upcoming Events on this page).
Feature point descriptors for image stitching
When microscopy images are to be put together to form a larger image than one field of view, images are stitched together based on key point features in the images. Several methods for matching these images exist, but are often general in the sense that they can handle scale and rotation, which are not present in this particular case. Therefore, these methods are like cracking a nut with a sledge hammer, and we have investigated how simpler and therefore more efficient and also faster methods can be developed and applied for solving this task. Several key point descriptors have been investigated that are based on new sampling strategies and also new ways of combining these samples, using for instance elements of the Fourier transform, instead of histograms of gradients etc. A paper describing two versions of fast and simple feature point descriptor with or without rotation invariance was presented at the WSCG conference.
The whole pipeline of matching has been investigated and several improvements have been suggested. We have shown that for instance RANSAC can be substituted by a fast clustering method, which makes computation of the transformation between images and false positives removal not only faster, but also deterministic, which otherwise is a problem with RANSAC as it is based on a random sampling approach. This alternative to RANSAC was presented at the second workshop on Features and Structures (FEAST), co-located with the International Conference on Machine Learning, Lille, France, in July.