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Detection of fish disease for grouper using image processing techniques
Nor Azma Azlina Binti Mohd Rosli
Supervisor: Dr Ezmahamrul Afreen Bin Awalludin
Bachelor of Science in Agrotechnology (Aquaculture)
School of Fisheries and Aquaculture Sciences
Disease is one of the real reasons for fish mortality. It is hard to monitor the fish
infections manually. It requires a large scope of worker, and requires more preparation
time to get results. Hence, image processing is used to detect the fish diseases in this
study. There are several techniques; image acquisition, image pre-processing, image
segmentation and blob processing. The MATLAB software is used as the graphical user
interface (GUI) to detect the status area of fish disease whether its health or unhealth.
Total number of 20 samples dataset was used to estimate distribution of the fish
disease area. In the study, the t-test statistics based on paired-samples was used to
measure the health and unhealthy area on grouper bodies. Based on the output
results, there was a significant difference in the scores for health (M=18.22, SD=4.96)
and unhealthy (M=2.04, SD=1.34) conditions; t(2)=13.88, p=0.05. The proposed
method is promising to estimate the fish body area with more reliable and more
efficient with less time consuming.
510 | UMT UNDERGRADUATE RESEARCH DAY 2018