Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/3490
Title: Image Enhancement on Underwater Images for Protozoan White Spot Fish Disease Detection
Authors: Azhar A.S.B.M. 
Harun N.H.B. 
Yusoff, N. 
Hassan M.G.B. 
Chu K.B. 
Keywords: Image Enhancement;Image Processing;Mariculture
Issue Date: 2022
Publisher: Institute of Electrical and Electronics Engineers Inc.
Conference: 2022 International Conference on Intelligent Systems and Computer Vision, ISCV 2022 
Abstract: 
White spot disease in mariculture fish could lead to major economic losses if the disease could not be contained in early stage. With the advent of current technology, image processing is believed could be a key contributor to early prevention of fish disease specifically protozoan white spot disease in early stage via the use of image enhancement technique on underwater images. This alternative could contribute to aquaculture sector by preventing the disease worst-case scenarios. Hence, this paper demonstrates the comparison between variety image enhancement techniques to find the best method in addressing the issues related to underwater images. The image enhancement techniques include auto-level colour correction and contrast limited adaptive histogram equalization (CLAHE) have been tested. The techniques alone and the combination of both has been compared and successfully improved underwater image quality. Hence, the idea of explore a combination of multiple techniques in order to create a superior underwater image quality could be done to ease the process of detecting protozoan white spot disease.
Description: 
Scopus
URI: http://hdl.handle.net/123456789/3490
ISBN: 978-166549558-5
DOI: 10.1109/ISCV54655.2022.9806095
Appears in Collections:Faculty of Data Science and Computing - Proceedings

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