0508018 20240103222501.520190904235959.9 85072862685 10.1007/978-3-030-29888-3_28 12 s. P cav_un_epca*0508720978-3-030-29929-3351-362ChamSpringer2019VentoM.PercannellaG.ColantonioS.GiorgiD.MatuszewskiB. J.KerdegariH.RazaakM. Blur-invariant distance Projection operator Object recognition Blurred image cav_un_auth*0377447 Lébl Matěj 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*0101209 Šroubek Filip 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*0355333 Kautský J. AU 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. http://library.utia.cas.cz/separaty/2019/ZOI/flusser-0508018.pdf cav_un_auth*0360229 GA18-07247S GA ČR Blur is a common phenomenon in image acquisition that negatively influences recognition rate if blurred images are used as a query in template matching. Various blur-invariant features and measures were proposed in the literature, yet they are often derived under conditions that are difficult to satisfy in practise, for example, images with zero background or periodically repeating images and classes of blur that are closed under convolution.We propose a novel blur-invariant distance that puts no limitation on images and is invariant to any kind of blur as long as the blur has limited support, non-zero values and sums up to one. A template matching algorithm is then derived based on the blur-invariant distance, which projects query images on convex sets constructed around template images. The proposed method is easy to implement, it is robust to noise and blur size, and outperforms other competitors in this area. 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 4 PR RVO:67985556 http://hdl.handle.net/11104/0299778 S 2019 85072862685 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 351 362 978-3-030-29929-3 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.