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Combined Invariants to Gaussian Blur and Affine Transformation
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SYSNO ASEP 0541853 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Combined Invariants to Gaussian Blur and Affine Transformation Author(s) Kostková, Jitka (UTIA-B) ORCID
Flusser, Jan (UTIA-B) RID, ORCID
Pedone, M. (FI)Number of authors 3 Source Title Proceedings of the 25th International Conference on Pattern Recognition (ICPR 2020). - Piscataway : IEEE, 2021 - ISBN 978-1-7281-8808-9 Pages s. 459-464 Number of pages 6 s. Publication form Online - E Action 25th International Conference on Pattern Recognition (ICPR) Event date 10.01.2021 - 15.01.2021 VEvent location Milan, Italy Country IT - Italy Event type WRD Language eng - English Country US - United States Keywords combined moment invariants ; Gaussian blur ; Substitution Theorem Subject RIV JD - Computer Applications, Robotics OECD category Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) R&D Projects GA18-07247S GA ČR - Czech Science Foundation (CSF) Institutional support UTIA-B - RVO:67985556 Annotation The paper presents a new theory of combined moment invariants to Gaussian blur and spatial affine transformation. The blur kernel may be arbitrary oriented, scaled and elongated. No prior information about the kernel parameters and about the underlaying affine transform is required. The main idea, expressed by the Substitution Theorem, is to substitute pure blur invariants into traditional affine moment invariants. Potential applications of the new descriptors are in blur-invariant image recognition and in robust template matching. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2022
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