Accuracy Improvement of the Shrimp-size Estimation Method for an Automatic Feeding-tray Lifting System Used in Shrimp Farming

Chanon Nontarit, T. Kondo, Masahiro Yamaguchi, Warakorn Khamkaew, Jaroenmit Woradet, Jessada Karnjana
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Abstract

Two shrimp-size estimation methods were previously proposed in the shrimp-growth estimation based on ResNeXt for an automatic feeding-tray lifting system. The first one is based on the size of the smallest rectangle in which a shrimp is inscribed. The second is based on the shrimp’s skeleton. Both methods have their strength and weakness. The former works better in the case of straight-body shrimp, but the latter works well in the case of curved-body shrimp. This study proposes a combination method of box-based and skeleton-based measurements by using a box ratio or eigenvalue ratio as a method-selection parameter to improve the performance of the shrimp-size estimation. Experimental results showed that the combination method using the box ratio can reduce the error by 63.56% and 9.24% compared with those of the previous box-based and skeleton-based methods, respectively. The combination method with the eigenvalue ratio can reduce the error by 63.10% and 8.08%, respectively. This study shows that combining the box-based and the skeleton-based measurements can reduce the error of the shrimp-size estimation method and improve its performance considerably.
对虾养殖中自动投料盘提升系统对虾尺寸估算方法精度的提高
在基于ResNeXt的自动喂料盘提升系统对虾生长估计中,提出了两种对虾大小估计方法。第一个是根据一个小虾的最小矩形的大小。第二种是基于虾的骨架。两种方法各有优缺点。前者在直体虾中效果更好,而后者在弯曲体虾中效果更好。本研究提出了一种基于箱形比或特征值比作为方法选择参数的基于箱形比和基于骨架的测量相结合的方法,以提高对虾尺寸估计的性能。实验结果表明,基于盒比的组合方法与之前基于盒比和基于骨架比的组合方法相比,误差分别降低了63.56%和9.24%。该方法与特征值比值相结合,误差分别降低63.10%和8.08%。本研究表明,将基于盒子和基于骨骼的测量相结合,可以大大降低虾的尺寸估计方法的误差,提高其性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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