Abstract

We present a coverage segmentation method for extracting thin structures in two-dimensional images. These thin structures can be, for example, retinal vessels, or microtubules in cytoskeleton, which are often 1-2 pixels thick. There exist several methods for coverage segmentation, but when it comes to thin and long structures, the segmentation is often unreliable.We propose a method that does not shrink the structures inappropriately and creates a trustworthy segmentation. In addition, as a by-product a high-resolution crisp reconstruction is provided. The method needs a reliable crisp segmentation as an input and uses information from linear unmixing and the crisp segmentation to create a high-resolution crisp reconstruction of the object. After a procedure where holes and protrusions are removed, the high-resolution crisp image is optionally down-sampled back to its original size, creating a coverage segmentation that preserves thin structures.

Published in

Image And Signal Processing And Analysis
2013, pages: 83-+
Title: 2013 8th International Symposium on Image and Signal Processing and Analysis
ISBN: 978-953-184-187-0, eISBN: 978-953-184-194-8
Publisher: IEEE

Conference

8th International Symposium on Image and Signal Processing and Analysis (ISPA), SEP 04-06, 2013, Trieste, ITALY

SLU Authors

• Lindblad, Joakim

  • Centre for Image Analysis, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Computer Vision and Robotics (Autonomous Systems)


Permanent link to this page (URI)

https://res.slu.se/id/publ/117951