Image Invariants to Anisotropic Gaussian Blur

0506779 - ÚTIA 2020 RIV CH eng C - Konferenční příspěvek (zahraniční konf.)
Kostková, Jitka - Flusser, Jan - Lébl, Matěj - Pedone, M.
Image Invariants to Anisotropic Gaussian Blur.
Image Analysis : 21st Scandinavian Conference, SCIA 2019. Cham: Springer, 2019, s. 140-151. Lecture Notes in Computer Science, 11482. ISBN 978-3-030-20204-0. ISSN 0302-9743. E-ISSN 1611-3349.
[Scandinavian Conference on Image Analysis - SCIA'19. Norkoping (SE), 11.06.2019-14.06.2019]
Grant CEP: GA ČR GA18-07247S
Institucionální podpora: RVO:67985556
Klíčová slova: Gaussian blur * Semi-group * Projection operator * Image moments * Moment invariants
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://library.utia.cas.cz/separaty/2019/ZOI/kostkova-0506779.pdf

The paper presents a new theory of invariants to Gaussian blur. Unlike earlier methods, the blur kernel may be arbitrary oriented, scaled and elongated. Such blurring is a semi-group action in the image space, where the orbits are classes of blur-equivalent images. We propose a non-linear projection operator which extracts blur-insensitive component of the image. The invariants are then formally defined as moments of this component but can be computed directly from the blurred image without an explicit construction of the projections. Image description by the new invariants does not require any prior knowledge of the particular blur kernel shape and does not include any deconvolution. Potential applications are in blur-invariant image recognition and in robust template matching.
Trvalý link: http://hdl.handle.net/11104/0297951