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Projection Operators and Moment Invariants to Image Blurring

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    SYSNO ASEP0434521
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleProjection 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, ORCID
    Number of authors4
    Source TitleIEEE Transactions on Pattern Analysis and Machine Intelligence. - : IEEE Computer Society - ISSN 0162-8828
    Roč. 37, č. 4 (2015), s. 786-802
    Number of pages17 s.
    Publication formPrint - P
    Languageeng - English
    CountryUS - United States
    KeywordsBlurred image ; N-fold rotation symmetry ; projection operators ; image moments ; moment invariants ; blur invariants ; object recognition
    Subject RIVJD - Computer Applications, Robotics
    R&D ProjectsGA13-29225S GA ČR - Czech Science Foundation (CSF)
    GAP103/11/1552 GA ČR - Czech Science Foundation (CSF)
    Institutional supportUTIA-B - RVO:67985556
    UT WOS000351213400007
    EID SCOPUS84924690353
    DOI10.1109/TPAMI.2014.2353644
    AnnotationIn 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.
    WorkplaceInstitute of Information Theory and Automation
    ContactMarkéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
    Year of Publishing2017
Number of the records: 1  

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