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White leg shrimp is one of the animals that is popularly consumed and exported in Thailand. A lot of farmers cultivate white leg shrimp in many areas. To raise white leg shrimp larvae into mature white leg shrimp that can be sold in the market for further consumption or export. Before a farm sells white leg shrimp larvae to a farmer, the farm staff needs to count the number of them. The traditional counting method is naked-eye estimation which requires experience and gives a rough estimation. A traditional technique causes time- consuming and human error. Moreover, a farm usually adds some scoops to make sure that the number of white leg shrimp larvae is not less than an order. This situation affects the farm's costs. This study proposes a new system for automated counting white leg shrimp larvae by applying the simple blob detector technique with opening and closing of morphological operations. The experimental result of the proposed system shows that this proposed system gives the best accuracy (94.20%), precision (97.68%), recall (96.35%), and F1 score (96.98 % ) compared with Canny Edge Detection and Blob analysis, morphological operations (opening, dilatation and gamma correction), and the blue sense system.
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Kamthang et al. (2024) studied this question.
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