Image Invariants to Anisotropic Gaussian Blur
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F19%3A00506779" target="_blank" >RIV/67985556:_____/19:00506779 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-20205-7_12" target="_blank" >http://dx.doi.org/10.1007/978-3-030-20205-7_12</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-20205-7_12" target="_blank" >10.1007/978-3-030-20205-7_12</a>
Alternative languages
Result language
angličtina
Original language name
Image Invariants to Anisotropic Gaussian Blur
Original language description
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.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA18-07247S" target="_blank" >GA18-07247S: Methods and Algorithms for Vector and Tensor Field Image Analysis</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Image Analysis : 21st Scandinavian Conference, SCIA 2019
ISBN
978-3-030-20204-0
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
12
Pages from-to
140-151
Publisher name
Springer
Place of publication
Cham
Event location
Norkoping
Event date
Jun 11, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—