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Recognition of Images Degraded by Gaussian Blur

SYSNO ASEP	0454335
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	Recognition of Images Degraded by Gaussian Blur
Author(s)	Flusser, Jan (UTIA-B)_{RID, ORCID} Farokhi, Sajad (UTIA-B) Höschl, Cyril (UTIA-B)_RID Suk, Tomáš (UTIA-B)_{RID, ORCID} Zitová, Barbara (UTIA-B)_{RID, ORCID} Pedone, M. (IT)
Number of authors	6
Source Title	IEEE Transactions on Image Processing. - : Institute of Electrical and Electronics Engineers - ISSN 1057-7149 Roč. 25, č. 2 (2016), s. 790-806
Number of pages	17 s.
Publication form	Print - P
Language	eng - English
Country	US - United States
Keywords	Blurred image ; object recognition ; blur invariant comparison ; Gaussian blur ; projection operators ; image moments ; moment invariants
Subject RIV	JD - Computer Applications, Robotics
R&D Projects	GA15-16928S GA ČR - Czech Science Foundation (CSF)
Institutional support	UTIA-B - RVO:67985556
UT WOS	000383905800023
EID SCOPUS	85016219716
DOI	10.1109/TIP.2015.2512108
Annotation	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.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2017

Number of the records: 1