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master's thesis
Vizijski sustav za automatsku kontrolu kvalitete uložaka grebenaste sklopke
Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2020. urn:nbn:hr:235:068446
Rešetar, Emanuela
University of Zagreb
Faculty of Mechanical Engineering and Naval Architecture

Institutional repository: Repository of Faculty of Mechanical Engineering and Naval Architecture University of Zagreb

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Rešetar, E. (2020). Vizijski sustav za automatsku kontrolu kvalitete uložaka grebenaste sklopke (Master's thesis). Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture. Retrieved from https://urn.nsk.hr/urn:nbn:hr:235:068446

Rešetar, Emanuela. "Vizijski sustav za automatsku kontrolu kvalitete uložaka grebenaste sklopke." Master's thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2020. https://urn.nsk.hr/urn:nbn:hr:235:068446

Rešetar, Emanuela. "Vizijski sustav za automatsku kontrolu kvalitete uložaka grebenaste sklopke." Master's thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2020. https://urn.nsk.hr/urn:nbn:hr:235:068446

Rešetar, E. (2020). 'Vizijski sustav za automatsku kontrolu kvalitete uložaka grebenaste sklopke', Master's thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, accessed 03 June 2024, https://urn.nsk.hr/urn:nbn:hr:235:068446

Rešetar E. Vizijski sustav za automatsku kontrolu kvalitete uložaka grebenaste sklopke [Master's thesis]. Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture; 2020 [cited 2024 June 03] Available at: https://urn.nsk.hr/urn:nbn:hr:235:068446

E. Rešetar, "Vizijski sustav za automatsku kontrolu kvalitete uložaka grebenaste sklopke", Master's thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:235:068446

Metadata
TitleVizijski sustav za automatsku kontrolu kvalitete uložaka grebenaste sklopke
Title (english)Machine vision system for automated quality control of rotary switch inserts
AuthorEmanuela Rešetar
MentorTomislav Staroveški (mentor)
Committee memberJosip Kasać (predsjednik povjerenstva)
Committee memberZoran Kunica (član povjerenstva)
Committee memberIvica Garašić (član povjerenstva)
Committee memberTomislav Staroveški (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Mechanical Engineering and Naval Architecture
Zagreb
Defense date and country2020-03-12, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Mechanical Engineering
Abstract
Rad se bavi razvojem vizijskog sustava za prepoznavanje i lokalizaciju uložaka grebenaste sklopke. Predstavljene su dvije algoritamske metode prikladne za robusno prepoznavanje. Prva algoritamska metoda koristi Houghovu kružnu transformaciju na binarnim slikama kako bi se locirali uzorci, koji se zatim kategoriziraju analizom intenziteta obodnih piksela. Druga algoritamska metoda temelji se na segmentaciji slike i analizi bloba pri čemu se koriste momenti za lokalizaciju i analiza konture za prepoznavanje. Oba pristupa testirana su na velikom broju slika različite složenosti (u rasponu od jednostavnih slika bez preklapanja uzoraka do slika sa znatnim preklapanjem uzoraka). Rezultati pokazuju kako su obje algoritamske metode prikladne za robusno prepoznavanje i lokalizaciju uzoraka. Međutim, prvi algoritam pokazao se bolji u pogledu vremena odziva i računske intenzivnosti.
Abstract (english)
This thesis presents the development of a machine vision system for the classification and localization of rotary switch inserts. In order to achieve robust results, two approaches were investigated. In the first approach, Hough transform for circles was used on binarized edge images in order to localize inserts, which were then classified by analyzing pixel intensities across the insert perimeter. The second approach is based on the image segmentation and blob analysis in which moments were used for localization and contour analysis for classification. Both approaches were tested on a large number of images with different scene complexities (ranging from simple images with no insert overlapping to images with considerable insert overlapping). Results show that both approaches can be used for this application, however, the first approach had a lower response time and was less computationally intensive.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:235:068446
Study programmeTitle: Mechanical Engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka strojarstva (magistar/magistra inženjer/inženjerka strojarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2020-12-02 10:52:57