Publication detail

Control of laboratory processes using modern methods of image processing

KIAC, M.

Original Title

Control of laboratory processes using modern methods of image processing

English Title

Control of laboratory processes using modern methods of image processing

Type

errata

Language

en

Original Abstract

The thesis deals with the image processing and detection of specific objects in the image. The main objective of this work is to implement a algoritm for the control of pipetting processes based on images from the camera. In this thesis is used for image processing an open source computer vision library OpenCV and for pipette detection is used convolutional neural network. The proposed solution is still in development process. The following article describes the issue and the results of the thesis solution.

English abstract

The thesis deals with the image processing and detection of specific objects in the image. The main objective of this work is to implement a algoritm for the control of pipetting processes based on images from the camera. In this thesis is used for image processing an open source computer vision library OpenCV and for pipette detection is used convolutional neural network. The proposed solution is still in development process. The following article describes the issue and the results of the thesis solution.

Keywords

image processing, OpenCV, cnn, dnn, convolutional neural network, application, object detection, pipette, microplate, wells, laboratory processes

Released

26.06.2020

Publisher

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních

Location

Brno

Pages from

335

Pages to

339

Pages count

5

URL

Documents

BibTex


@misc{BUT164352,
  author="Martin {Kiac}",
  title="Control of laboratory processes using modern methods of image processing",
  annote="The thesis deals with the image processing and detection of specific objects in the image.
The main objective of this work is to implement a algoritm for the control of pipetting processes based
on images from the camera. In this thesis is used for image processing an open source computer vision
library OpenCV and for pipette detection is used convolutional neural network. The proposed solution
is still in development process. The following article describes the issue and the results of the thesis solution.",
  address="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních",
  chapter="164352",
  howpublished="online",
  institution="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních",
  year="2020",
  month="june",
  pages="335--339",
  publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních",
  type="errata"
}