Monitoring of Irregularity on Sea Surface from Land-Taken Images

Monitoring of irregularities that will occur on the sea surface is important for environmental safety. In this study, photographs taken from the land were used to determine the irregularities on sea surface. The fact that fixed cameras placed on land and scanning the sea surface were installed in ce...

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Published in:IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference pp. 1417 - 1422
Main Authors: Sanver, Ufuk, Yesildirek, Aydin
Format: Conference Proceeding
Language:English
Published: IEEE 25.01.2022
Subjects:
Cameras
Convolutional neural networks
Image processing
irregularity on sea surface
Land surface
monitoring sea surfaces
mucilage
Safety
Sea surface
Surface treatment
ISSN:2376-6565
Online Access:Get full text
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Abstract Monitoring of irregularities that will occur on the sea surface is important for environmental safety. In this study, photographs taken from the land were used to determine the irregularities on sea surface. The fact that fixed cameras placed on land and scanning the sea surface were installed in certain regions and the possibility of installing new ones has been an incentive for this study. In the study, the images created by the mucilage experienced in the Marmara Sea at the beginning of 2021 were used as the irregularity data. The authors developed an original model for this study based on traditional image processing methods. In addition, classification was made with a convolutional neural network-based method and the results were compared.
AbstractList Monitoring of irregularities that will occur on the sea surface is important for environmental safety. In this study, photographs taken from the land were used to determine the irregularities on sea surface. The fact that fixed cameras placed on land and scanning the sea surface were installed in certain regions and the possibility of installing new ones has been an incentive for this study. In the study, the images created by the mucilage experienced in the Marmara Sea at the beginning of 2021 were used as the irregularity data. The authors developed an original model for this study based on traditional image processing methods. In addition, classification was made with a convolutional neural network-based method and the results were compared.
Author Sanver, Ufuk
Yesildirek, Aydin
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  organization: Istanbul Commerce University,Department of Computer Engineering,Istanbul,Turkey
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  givenname: Aydin
  surname: Yesildirek
  fullname: Yesildirek, Aydin
  email: aydiny@yildiz.edu.tr
  organization: Yildiz Technical University,Department of Mecahatronics Engineering,Istanbul,Turkey
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Snippet Monitoring of irregularities that will occur on the sea surface is important for environmental safety. In this study, photographs taken from the land were used...
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SubjectTerms Cameras
Convolutional neural networks
Image processing
irregularity on sea surface
Land surface
monitoring sea surfaces
mucilage
Safety
Sea surface
Surface treatment
Title Monitoring of Irregularity on Sea Surface from Land-Taken Images
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