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Coverage segmentation of thin structures by linear unmixing and local centre of gravity attraction
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- Lindblad, Joakim (author)
- Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Centre for Image Analysis
- ISBN 9789531841870
- 2013
- 2013
- English.
- In: Image And Signal Processing And Analysis. - 1845-5921. ; , s. 83-
- Conference paper (peer-reviewed)
Abstract
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- 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.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
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