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DKUM
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Title:
Preverjanje kvalitete izdelkov z uporabo strojnega vida
Authors:
ID
Marolt, Jakob
(Author)
ID
Klančnik, Simon
(Mentor)
More about this mentor...
Files:
MAG_Marolt_Jakob_2017.pdf
(3,64 MB)
MD5: 7435BED27F59585BE3DEB2F6B1D7A18F
PID:
20.500.12556/dkum/c381c7f1-0a0a-4848-a946-a81ce2b3ed8d
Language:
Slovenian
Work type:
Master's thesis/paper
Typology:
2.09 - Master's Thesis
Organization:
FS - Faculty of Mechanical Engineering
Abstract:
V magistrskem delu smo reševali problem preverjanja kakovosti površin rebričenih obdelovancev z uporabo strojnega vida. Na kratko smo predstavili področje računalniškega vida s tremi algoritmi primerjanja oblik (SIFT, SURF in ORB). Izdelali smo prototipni sistem za nadzor kvalitete rebričenja s pomočjo strojnega vida. Zajete slike je procesiral računalnik Raspberry Pi model 1 B+, ki ga je operiral operacijski sistem Raspbian. Obdelovanci so bili osvetljeni z dvema belima visoko svetilnima LED diodama. Sliko je zajela standardna CMOS Raspberry Pi kamera s 5 MP. Izdelali smo računalniški program v programskem jeziku Python z uporabo standardnih modulov in knjižnice OpenCV. Primerjali smo uspešnost in čas procesiranja vseh treh algoritmov primerjanja oblik. Vsi algoritmi so 100 % uspešno ločili ustrezne obdelovance od neustreznih. Najkrajši čas procesiranja je imel program z algoritmom ORB, na drugem mestu SURF in na zadnjem mestu SIFT. Ocenili smo materialne stroške prototipnega sistema, ki znašajo 87 €.
Keywords:
strojni vid
,
računalniški vid
,
preverjanje kvalitete
,
OpenCV
,
Python
,
rebričenje
,
SIFT
,
SURF
,
ORB
Place of publishing:
Maribor
Publisher:
[J. Marolt]
Year of publishing:
2017
PID:
20.500.12556/DKUM-66789
UDC:
004.923.021:004.93(043.2)
COBISS.SI-ID:
20880662
NUK URN:
URN:SI:UM:DK:OE0JWWPM
Publication date in DKUM:
07.08.2017
Views:
1599
Downloads:
319
Metadata:
Categories:
KTFMB - FS
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:
MAROLT, Jakob, 2017,
Preverjanje kvalitete izdelkov z uporabo strojnega vida
[online]. Master’s thesis. Maribor : J. Marolt. [Accessed 26 March 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=66789
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Licences
License:
CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:
The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:
10.07.2017
Secondary language
Language:
English
Title:
Quality control of products using computer vision
Abstract:
In our master thesis we inspected the quality of knurled parts with the use of machine vision. We briefly introduced the field of computer vision and explained the processes behind three popular feature matching algorithms (SIFT, SURF and ORB). We engineered a prototype system for quality control of knurled parts using machine vision. For data processing we used Raspberry Pi model 1 B+ which ran on the Raspbian debian system. We installed two white LED diodes with high brightness for lighting. Pictures were taken by a standard Raspberry Pi CMOS camera with 5 MP. The program was created in Python, using its standard modules and the OpenCV library. We analyzed success and time delay of all three feature matching algorithms. All were 100% successful in distinguishing the good parts from the bad ones. The fastest algorithm was ORB, followed by SURF and then SIFT. The material cost of the system was 87€.
Keywords:
machine vision
,
computor vision
,
quality control
,
OpenCV
,
Python
,
knurling
,
SIFT
,
SURF
,
ORB
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