Indonesian Journal of Artificial Intelligence and Data Mining
Vol 8, No 1 (2025): March 2025

Enhancing Image Quality for the Detection of Underwater Debris with Adaptive Fuzzy Filter

Halim, Apriyanto (Unknown)
Ulina, Mustika (Unknown)
Tanti, Tanti (Unknown)
Sinaga, Frans Mikael (Unknown)



Article Info

Publish Date
17 Feb 2025

Abstract

The image quality improvement process plays a very important role. This is because the process can increase the clarity and accuracy of image detection. One type of image detection that exists is the detection of garbage found under the sea. One of the image quality improvement processes is related to noise removal. Noise is a sudden increase in pixel intensity in an image. This can cause various problems that occur such as in medical photos, satellites, and photography. One method used to remove noise from images is using Adaptive Fuzzy Filter (AFF). This method is carried out by first finding the average value of the mean fuzzy set and the gray level fuzzy. After that, the value comparison process is carried out. From the results of the research conducted on 689 images from the dataset obtained, there is a decrease in the amount of noise of around 96,23% of the total noise obtained previously. This can certainly provide good results in terms of changes in noise that have been made.

Copyrights © 2025






Journal Info

Abbrev

IJAIDM

Publisher

Subject

Computer Science & IT

Description

Indonesian Journal of Artificial Intelligence and Data Mining (IJAIDM) is an electronic periodical publication published by Puzzle Research Data Technology (Predatech) Faculty of Science and Technology UIN Sultan Syarif Kasim Riau, Indonesia. IJAIDM provides online media to publish scientific ...