20.500.12556/DKUM-55117 Nadzor kakovosti pšeničnih zrn z naprednimi postopki računalniške obdelave slik in razpoznavanja vzorcev Wheat grains quality control with advanced methods for image processing and pattern recognition Pšenica je ena izmed najbolj priljubljenih žitaric v prehrambni industriji, zato je nadzor kakovosti pšenice ključnega pomena. V okviru magistrske naloge smo pokazali, da je mogoče proces nadzora kakovosti pšenice avtomatizirati in izboljšati v primerjavi z današnjim pristopom. Reševanja problema smo se lotili z računalniško analizo digitalnih slik in spektralnih odzivov zrn ter uporabo algoritmov strojnega učenja. Posebno pozornost smo posvetili združevanju obeh tipov podatkov. Prišli smo do zaključka, da lahko z natančnostjo 90 % ali več razvrstimo zrna zdrave pšenice in ostalih 8 razredov, ki predstavljajo poškodovana zrna in druga žita. Za potrditev rezultatov in izboljšanje robustnosti algoritma predlagamo še dodatne eksperimente. Wheat is one of the most produced cereals for food industry worldwide. Therefore quality control of wheat is an essential part of the supply chain. In the thesis, it has been shown that it is possible to automatize and improve the wheat quality inspection procedures used today. To solve the problem digital images and spectral responses of the grains have been analysed in combination with the machine learning algorithms. Additional effort has been spent on combining the two types of data. Conclusion has been made that it is possible to distinguish between the healthy wheat and the other 8 classes, which represent damaged grains and other cereals, with the accuracy of 90% or more. In order to confirm the results and improve the robustness of the developed algorithm further experiments shall be made. nadzor kakovosti pšenica strojno učenje razvrščanje obdelava slik quality inspection wheat machine learning classification image processing true true false B. Krpan Slovenski jezik Angleški jezik Magistrsko delo/naloga 2015-09-28 20:58:28 2015-10-15 12:31:19 2022-06-08 03:10:35 2021-05-13 03:34:13 2015 0 [Maribor 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.93'1:633.11(043.2) 19317014 URN:SI:UM:DK:EJVBLIFJ MAG_Krpan_Blaz_2015.pdf MAG_Krpan_Blaz_2015.pdf 1 2CD510414BAA30144DCB339B07F800E8 d35d15b55714b4a2043593a84d6436df7e35379b4f1b0c037ebe43c6ac81ffcd 358aebcf-7c07-11eb-bb7a-00155d0001ca https://dk.um.si/Dokument.php?lang=slv&id=82365 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0