Thesis Details
Automatická kontrola kvality výrobku z obrazu
The goal of this thesis is to create overall, automatic and non-contact quality control of a pellet. The issue is divided into two separate parts. The first part deals with precise dimensional measuring of pellet - its length and head diameter so that it is precise and reasonably fast. Precise measuring is achieved with help of algorithms which achieve the sub-pixel precision by polynomial approximation of the edges extracted from the image gradients. The second part deals with the defects of a pellet. Detecting defects like longitudinal furrows or skirt cuts is achieved with convolutional neural networks. The measurement modules work with the resulting precision up to 0.025 mm in case of length measuring and up to 0.01 mm in case of head diameter measuring. In case of defect detections, neural network shows very high classification success rate. The contribution of this thesis is a presentation of innovative approaches in automatic quality control of pellets with use of neural networks and a demonstration of its usage in real manufacturing process.
Convolutional neural networks, dimensional measurement, surface defects detection, computer vision, machine learning.
Burget Radim, Doc. Ing., Ph.D. (UTKO FEEC BUT), člen
Černocký Jan, prof. Dr. Ing. (DCGM FIT BUT), člen
Holík Lukáš, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Hradiš Michal, Ing., Ph.D. (DCGM FIT BUT), člen
Szőke Igor, Ing., Ph.D. (DCGM FIT BUT), člen
@mastersthesis{FITMT20772,
author = "Martin Krut\'{a}k",
type = "Master's thesis",
title = "Automatick\'{a} kontrola kvality v\'{y}robku z obrazu",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2019,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/20772/"
}