Institute of Information Theory and Automation

Publication details

Recognition of Images Degraded by Gaussian Blur

Journal Article

Flusser Jan, Farokhi Sajad, Höschl Cyril, Suk Tomáš, Zitová Barbara, Pedone M.

serial: IEEE Transactions on Image Processing vol.25, 2 (2016), p. 790-806

project(s): GA15-16928S, GA ČR

keywords: Blurred image, object recognition, blur invariant comparison, Gaussian blur, projection operators, image moments, moment invariants

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abstract (eng):

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.


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Last modification: 21.12.2012
Institute of Information Theory and Automation