merged

Shrimp Larvae Counting For (Penaeus Vannamei) Using Image Processing
Methods
Mas Yuhalissa binti Mat Yaziz
Supervisor: Dr. Ezmahamrul Afreen bin Awalludin
Bachelor of Applied Science (Fisheries)
School of Fisheries and Aquaculture Sciences
Larvae counting in the context of biology research is largely a manual and a labor
intensive task. In this study, we introduce a semi-automated system based on image
processing methods of edge detection and blob processing specifically for white
shrimp (Penaeus vannamei) larvae counting. The total number of 90 samples of the
shrimp larvae has been collected from Seaworld Farm Centre, Dungun, Terengganu.
The first objective in this project is to study the effectiveness of the semi-automated
and the manual approach counting for Penaeus vannamei. Secondly, to test the
performance of the proposed method system with three different of samples dataset
such as small (30), medium (30) and large (30). Based on the output results
observation, the proposed method achieved 100%, 96.75% and 98.38% accuracy for
small, medium and large, respectively. The proposed method is an alternative solution
to the manual approach to count larvae of white shrimp (Penaeus vannamei) with
more effective, high accuracy and fast time estimation.
591 | UMT UNDERGRADUATE RESEARCH DAY 2018