Publications in Scientific Journals:

A. Karimov, G. Mistelbauer, T. Auzinger, S. Bruckner:
"Guided Volume Editing based on Histogram Dissimilarity";
Computer Graphics Forum (invited), 34 (2015), 3; 91 - 100.

English abstract:
Segmentation of volumetric data is an important part of many analysis pipelines, but frequently requires manual inspection and correction. While plenty of volume editing techniques exist, it remains cumbersome and error-prone for the user to find and select appropriate regions for editing. We propose an approach to improve volume editing by detecting potential segmentation defects while considering the underlying structure of the object of interest. Our method is based on a novel histogram dissimilarity measure between individual regions, derived from structural information extracted from the initial segmentation. Based on this information, our interactive system guides the user towards potential defects, provides integrated tools for their inspection, and automatically generates suggestions for their resolution. We demonstrate that our approach can reduce interaction effort and supports the user in a comprehensive investigation for high-quality segmentations.

Edge and feature detection, Image Processing and Computer Vision, Computer Graphics, Display algorithms, Picture/Image Generation, Segmentation, Methodology and Techniques, Interaction techniques

Created from the Publication Database of the Vienna University of Technology.