Image invariants to anisotropic Gaussian blur |
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Author: | Kostková, Jitka1; Flusser, Jan1; Lébl, Matěj1; |
Organizations: |
1The Czech Academy of Sciences, Institute of Information Theory and Automation, Prague 8, Czech Republic 2The Center for Machine Vision Research, Department of Computer Science and Engineering, University of Oulu, Oulu, Finland |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 2.9 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe202001101746 |
Language: | English |
Published: |
Springer Nature,
2019
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Publish Date: | 2020-05-12 |
Description: |
AbstractThe paper presents a new theory of invariants to Gaussian blur. Unlike earlier methods, the blur kernel may be arbitrary oriented, scaled and elongated. Such blurring is a semi-group action in the image space, where the orbits are classes of blur-equivalent images. We propose a non-linear projection operator which extracts blur-insensitive component of the image. The invariants are then formally defined as moments of this component but can be computed directly from the blurred image without an explicit construction of the projections. Image description by the new invariants does not require any prior knowledge of the particular blur kernel shape and does not include any deconvolution. Potential applications are in blur-invariant image recognition and in robust template matching. see all
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Series: |
Lecture notes in computer science |
ISSN: | 0302-9743 |
ISSN-E: | 1611-3349 |
ISSN-L: | 0302-9743 |
ISBN: | 978-3-030-20205-7 |
ISBN Print: | 978-3-030-20204-0 |
Pages: | 140 - 151 |
DOI: | 10.1007/978-3-030-20205-7_12 |
OADOI: | https://oadoi.org/10.1007/978-3-030-20205-7_12 |
Host publication: |
21st Scandinavian Conference, SCIA 2019, Norrköping, Sweden, June 11–13, 2019, Proceedings |
Host publication editor: |
Felsberg, Michael Forssén, Per-Erik Sintorn, Ida-Maria Unger, Jonas |
Conference: |
Scandinavian Conference on Image Analysis |
Type of Publication: |
A4 Article in conference proceedings |
Field of Science: |
113 Computer and information sciences |
Subjects: | |
Copyright information: |
© Springer Nature Switzerland AG 2019. This is a post-peer-review, pre-copyedit version of an article published in Scandinavian Conference on Image Analysis. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-20205-7_12. |