A Comparative Study of Various Edge Detection Techniques for Underwater Images

• Autorzy: Awalludin Ezmahamrul Afreen , Arsad Tengku Noorfarahana T. , Yussof Wan Nural Jawahir Hj Wan , Bachok Zainudin , Hitam Muhammad Suzuri

Identyfikatory

DOI

10.26636/jtit.2022.155921

• Języki publikacji: EN

Abstrakty

EN

Nowadays, underwater image identification is a challenging task for many researchers focusing on various ap plications, such as tracking fish species, monitoring coral reef species, and counting marine species. Because underwater im ages frequently suffer from distortion and light attenuation, pre-processing steps are required in order to enhance their quality. In this paper, we used multiple edge detection techniques to determine the edges of the underwater images. The pictures were pre-processed with the use of specific techniques, such as enhancement processing, Wiener filtering, median filtering and thresholding. Coral reef pictures were used as a dataset of underwater images to test the efficiency of each edge detection method used in the experiment. All coral reef image datasets were captured using an underwater GoPro camera. The performance of each edge detection technique was evaluated using mean square error (MSE) and peak signal to noise ratio (PSNR). The lowest MSE value and the highest PSNR value represent the best quality of underwater images. The results of the experiment showed that the Canny edge detection technique outperformed other approaches used in the course of the project.

Słowa kluczowe

EN

edge detection; mean square error; median filtering; peak signal to noise; wiener filtering

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2022
• Tom: nr 1
• Strony: 23--33
• Opis fizyczny: Bibliogr. 23 poz., rys., tab.

Twórcy

autor

Awalludin Ezmahamrul Afreen

• Faculty of Fisheries and Food Science, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia

• https://orcid.org/0000-0003-4470-0052

autor

Arsad Tengku Noorfarahana T.

• Faculty of Fisheries and Food Science, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia

autor

Yussof Wan Nural Jawahir Hj Wan

• Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu 21030 Kuala Nerus Terengganu, Malaysia

• https://orcid.org/0000-0002-3618-1638

autor

Bachok Zainudin

• Institute of Oceanography and Environment, Universiti Malaysia Terengganu, 21030 Kuala Nerus Terengganu, Malaysia

• https://orcid.org/0000-0002-3221-3540

autor

Hitam Muhammad Suzuri

• Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu 21030 Kuala Nerus Terengganu, Malaysia

• https://orcid.org/0000-0002-0545-4437

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).