A fuzzy approach to identify fish red spot disease
Grey Systems: Theory and Application
ISSN: 2043-9377
Article publication date: 7 April 2020
Issue publication date: 18 June 2020
Abstract
Purpose
Fish are considered as one of the important aquatic animals in the planet. They play a vital role in the nutrient cycle. They can be considered as one of the healthy food for human beings. They can also act as a solution for some of the human health problems. If fish are affected by several diseases, they in turn provide an adverse effect on human health. Therefore, it is very much essential to protect fish from being affected by any diseases.
Design/methodology/approach
This paper is mainly focused on the identification of the red spot diseased area in fish. In this work, a fuzzy rule based method (FRBAM) and triangular membership function (TMFN) is used to identify the red spot disease (RSD) in the fish by analyzing several red spot diseased fish (RSDF) images. The canny edge detector is used for intermediate processing of RSDF images.
Findings
The proposed method is able to identify the red pixels over the fish by marking the affected area with red color by using a standard RGB model.
Originality/value
The proposed method follows FRBAM and TMFN in order to detect the RSD and canny edge detector for processing of RSDF images. Finally, it is tested using ten different image sizes and the results show its better performance in terms of detection of RSD affected regions of fish and execution time.
Keywords
Citation
Bhoi, S.K., Panda, S.K., Jena, K.K., Mallick, C. and Khan, A. (2020), "A fuzzy approach to identify fish red spot disease", Grey Systems: Theory and Application, Vol. 10 No. 3, pp. 249-263. https://doi.org/10.1108/GS-11-2019-0051
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited