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Projection Operators and Moment Invariants to Image Blurring
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SYSNO ASEP 0434521 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Projection Operators and Moment Invariants to Image Blurring Author(s) Flusser, Jan (UTIA-B) RID, ORCID
Suk, Tomáš (UTIA-B) RID, ORCID
Boldyš, Jiří (UTIA-B) RID
Zitová, Barbara (UTIA-B) RID, ORCIDNumber of authors 4 Source Title IEEE Transactions on Pattern Analysis and Machine Intelligence. - : IEEE Computer Society - ISSN 0162-8828
Roč. 37, č. 4 (2015), s. 786-802Number of pages 17 s. Publication form Print - P Language eng - English Country US - United States Keywords Blurred image ; N-fold rotation symmetry ; projection operators ; image moments ; moment invariants ; blur invariants ; object recognition Subject RIV JD - Computer Applications, Robotics R&D Projects GA13-29225S GA ČR - Czech Science Foundation (CSF) GAP103/11/1552 GA ČR - Czech Science Foundation (CSF) Institutional support UTIA-B - RVO:67985556 UT WOS 000351213400007 EID SCOPUS 84924690353 DOI 10.1109/TPAMI.2014.2353644 Annotation In this paper we introduce a new theory of blur invariants. Blur invariants are image features which preserve their values if the image is convolved by a point-spread function (PSF) of a certain class. We present the invariants to convolution with an arbitrary N-fold symmetric PSF, both in Fourier and image domain. We introduce a notion of a primordial image as a canonical form of all blur-equivalent images. It is defined in spectral domain by means of projection operators. We prove that the moments of the primordial image are invariant to blur and we derive recursive formulae for their direct computation without actually constructing the primordial image. We further prove they form a complete set of invariants and show how to extent their invariance also to translation, rotation and scaling. We illustrate by simulated and real-data experiments their invariance and recognition power. Potential applications of this method are wherever one wants to recognize objects on blurred images. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2017
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