Počet záznamů: 1  

Recognition of Images Degraded by Gaussian Blur

  1. 1. 0454335 - UTIA-B 2017 RIV US eng J - Článek v odborném periodiku
    Flusser, Jan - Farokhi, Sajad - Höschl, Cyril - Suk, Tomáš - Zitová, Barbara - Pedone, M.
    Recognition of Images Degraded by Gaussian Blur.
    IEEE Transactions on Image Processing. Roč. 25, č. 2 (2016), s. 790-806. ISSN 1057-7149
    Grant CEP: GA ČR(CZ) GA15-16928S
    Institucionální podpora: RVO:67985556
    Klíčová slova: Blurred image * object recognition * blur invariant comparison * Gaussian blur * projection operators * image moments * moment invariants
    Kód oboru RIV: JD - Využití počítačů, robotika a její aplikace
    Impakt faktor: 4.828, rok: 2016
    http://library.utia.cas.cz/separaty/2016/ZOI/flusser-0454335.pdf

    In this paper, we propose a new theory of invariants to Gaussian blur. We introduce a notion of a primordial image as a canonical form of all Gaussian blur-equivalent images. The primordial image is defined in spectral domain by means of projection operators. We prove that the moments of the primordial image are invariant to Gaussian blur and we derive recursive formulas for their direct computation without actually constructing the primordial image itself. We show how to extend their invariance also to image rotation. The application of these invariants is in blur-invariant image comparison and recognition. In the experimental part, we perform an exhaustive comparison with two main competitors: 1) the Zhang distance and 2) the local phase quantization.
    Trvalý link: http://hdl.handle.net/11104/0257080