0575756 20240402214439.420230922235959.9 10.1109/ICIP49359.2023.10223161 5 s. E cav_un_epca*0575755978-1-7281-9835-41410-1414PiscatawayIEEE2023 Detection Classification Automotive cav_un_auth*0455337 Staněk R. CZ cav_un_auth*0379363 Kerepecký Tomáš UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0283562 Novozámský Adam 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*0101238 Zitová Barbara 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*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/2023/ZOI/kerepecky-0575756.pdf GA21-03921S GA ČR cav_un_auth*0412209 StrategieAV21/1 AV ČR CZ cav_un_auth*0441412 This paper proposes a novel approach to real-time automatic rim detection, classification, and inspection by combining traditional computer vision and deep learning techniques. At the end of every automotive assembly line, a quality control process is carried out to identify any potential defects in the produced cars. Common yet hazardous defects are related, for example, to incorrectly mounted rims. Routine inspections are mostly conducted by human workers that are negatively affected by factors such as fatigue or distraction. We have designed a new prototype to validate whether all four wheels on a single car match in size and type. Additionally, we present three comprehensive open-source databases, CWD1500, WHEEL22, and RB600, for wheel, rim, and bolt detection, as well as rim classification, which are free-to-use for scientific purposes. cav_un_auth*0455338 IEEE International Conference on Image Processing 2023 (ICIP 2023) 20231008 20231011 Kuala Lumpur MY JC 10000 10200 10201 2024 6 PO RVO:67985556 https://hdl.handle.net/11104/0345841 cav_un_auth*0439145 Univerzita Karlova UK CZ cav_un_auth*0377559 ČVUT v Praze, Fakulta jaderného a fyzikálního inženýrství ČVUT FJFI CZ S 2023 SCOPUS PUBMED WOS cav_un_epca*0575755 Proceedings of the 2023 IEEE International Conference on Image Processing (ICIP) 978-1-7281-9835-4 1410 1414 Piscataway IEEE 2023