Object

Title: A Comparative Study of Various Edge Detection Techniques for Underwater Images, Journal of Telecommunications and Information Technology, 2022, nr 1

Description:

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 tech niques 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 fil tering 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 evalu ated 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 re sults of the experiment showed that the Canny edge detection technique outperformed other approaches used in the course of the project.

Publisher:

Instytut Łączności - Państwowy Instytut Badawczy

Format:

application/pdf

Resource Identifier:

ISSN 1509-4553, on-line: ISSN 1899-8852 ; oai:bc.itl.waw.pl:2212

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Object collections:

Last modified:

Mar 11, 2024

In our library since:

Apr 21, 2022

Number of object content hits:

34

All available object's versions:

https://bc.itl.waw.pl/publication/2518

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