0508021 20241106135744.820190904235959.9 85072864730 10.1007/978-3-030-29891-3_36 12 s. P cav_un_epca*0508720978-3-030-29929-3413-424ChamSpringer2019VentoM.PercannellaG.ColantonioS.GiorgiD.MatuszewskiB. J.KerdegariH.RazaakM. Affine transformation Invariants Image normalization Gaussian-Hermite moments cav_un_auth*0101087 Flusser Jan UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101203 Suk Tomáš UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0236665 Yang B. CN http://library.utia.cas.cz/separaty/2019/ZOI/flusser-0508021.pdf cav_un_auth*0360229 GA18-07247S GA ČR We propose a new kind of moment invariants with respect to an affine transformation. The new invariants are constructed in two steps. First, the affine transformation is decomposed into scaling, stretching and two rotations. The image is partially normalized up to the second rotation, and then rotation invariants from Gaussian-Hermite moments are applied. Comparing to the existing approaches – traditional direct affine invariants and complete image normalization – the proposed method is more numerically stable. The stability is achieved thanks to the use of orthogonal Gaussian-Hermite moments and also due to the partial normalization, which is more robust to small changes of the object than the complete normalization. Both effects are documented in the paper by experiments. Better stability opens the possibility of calculating affine invariants of higher orders with better discrimination power. This might be useful namely when different classes contain similar objects and cannot be separated by low-order invariants. cav_un_auth*0380252 International Conference on Computer Analysis of Images and Patterns, CAIP 2019 /18./ 20190902 20190906 Salerno IT JD 20000 20200 20206 2020 3 4 A sml 4as 20241106135744.8 PR RVO:67985556 http://hdl.handle.net/11104/0299553 S Copyright transfer 20190528 Copyright 2019 Soubory v repozitáři: flusser-0508021-copyright transfer.pdf 85072864730 SCOPUS PUBMED WOS cav_un_epca*0508720 Computer Analysis of Images and Patterns : CAIP 2019 International Workshops, ViMaBi and DL-UAV, Salerno, Italy, September 6, 2019, Proceedings Springer 2019 Cham 413 424 978-3-030-29929-3 Communications in Computer and Information Science 1089 340 Vento M. 340 Percannella G. 340 Colantonio S. 340 Giorgi D. 340 Matuszewski B. J. 340 Kerdegari H. 340 Razaak M.