Detekcija vlitih navojev s pomočjo termovizije

ŠVIGELJ, ANŽE (author), Batagelj, Borut (mentor)

Cilj diplomske naloge je bil razvoj spletne aplikacije za detekcijo vlitih navojev segrevane snežne deske s pomočjo termografske kamere v okolju SICK AppStudio, ki omogoča razvoj v programskem jeziku Lua na računalniku SICK SIM4000. V začetku sta predstavljeni področji računalniškega vida in termografskih kamer. V naslednjem koraku je predstavljena oprema in pripadajoče tehnologije, ki smo jih uporabili. V nadaljevanju pa je prikazana implementacija dveh algoritmov za detekcijo navojev: zaznavanje področij in Houghova transformacija kroga ter njuna primerjava. Kot dodatek smo izdelali podatkovno bazo, ki temelji na arhitekturi REST z uporabo tehnologij Node.js in MongoDB, kamor se shranjujejo podatki vseh meritev. Delo smo zaključili s sklepnimi ugotovitvami, ki izpostavljajo tudi možne izboljšave in podlago za nadaljnji razvoj.

• Language: Slovenian
• Keywords: računalniški vid, termovizija, Lua, SICK AppStudio, termografska kamera, Houghova transformacija
• Work type: Bachelor thesis/paper
• Typology: 2.11 - Undergraduate Thesis
• Organization: FRI - Faculty of Computer and Information Science
• Year: 2022
• PID: 20.500.12556/RUL-135164
• COBISS.SI-ID: 98900995
• Publication date in RUL: 25.02.2022

ŠVIGELJ, ANŽE, 2022, Detekcija vlitih navojev s pomočjo termovizije [online]. Bachelor’s thesis. [Accessed 30 March 2025]. Retrieved from: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=eng&id=135164

Secondary language

• Language: English
• Title: Molded thread detection using thermal imaging

Abstract

The aim of this thesis was to develop a web application for detecting molded threads of a heated snowboard using a thermographic camera in the SICK AppStudio environment, which uses the Lua programming language on the SICK SIM4000 industrial computer. In the beginning, the areas of computer vision and thermographic cameras are described and presented. In the following chapter we presented the equipment we worked on and the associated technologies we used. We continued with the description of the implementation of two algorithms we used for detecting threads: blob detection and Circle Hough Transform then compared the results. In addition, we created a database based on the REST architecture using Node.js and MongoDB technologies, where data from all measurements are stored. We concluded our work with concluding remarks, which also highlight possible improvements and the basis for further development.

• Keywords: computer vision, thermal imaging, Lua, SICK AppStudio, thermal camera, Hough transform