Recognition of Images Degraded by Gaussian Blur

0454335 - ÚTIA 2017 RIV US eng J - Journal Article
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. E-ISSN 1941-0042
R&D Projects: GA ČR(CZ) GA15-16928S
Institutional support: RVO:67985556
Keywords : Blurred image * object recognition * blur invariant comparison * Gaussian blur * projection operators * image moments * moment invariants
Subject RIV: JD - Computer Applications, Robotics
Impact factor: 4.828, year: 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.
Permanent Link: http://hdl.handle.net/11104/0257080