Labor shortage and an aging population are driving automation in the aqua and agricultural industries. In a flatfish farm, it is important to sort flatfishes according to their sizes for effective and stable growth. This sorting is often done by human eye-estimation, thereby making it difficult to carry out total inspection of the fishes on the farm. Most fish graders in the industries sort round fishes (fishes with high length to height ratios) but they are inadequate to sort flatfishes. Thus, in this study, an automatic grader for flatfish using machine vision is developed. The grader has three main parts: conveyor belt, machine vision, and sorter. The conveyor belt transfers the fishes to the measurement and sorter parts. When the fish is detected and its length is calculated by image processing, the position of the sorter is controlled by length classification. A low-cost commercial webcam is used, and the sorter of the grader has a simple structure that consists of a single actuator. After several experiments, it was verified that length measurement using machine vision is accurate to within 10 mm, and the grader can sort 30 fishes in a minute. The developed grader minimizes the out-of-water exposure of the fishes compared to the conventional eye-measurement. Hence, it is effective to maintain the quality and freshness of the fishes.

中文翻译：

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使用机器视觉的比目鱼自动分级机

劳动力短缺和人口老龄化正在推动水产和农业行业的自动化。在比目鱼养殖场，重要的是根据比目鱼的大小进行分类，以实现有效和稳定的生长。这种分类通常是通过人眼估计来完成的，因此很难对养殖场的鱼类进行全面检查。行业中的大多数鱼类分级师对圆鱼（长高比高的鱼）进行分选，但不足以分选比目鱼。因此，在本研究中，开发了一种使用机器视觉的比目鱼自动分级机。分级机由三个主要部分组成：传送带、机器视觉和分拣机。传送带将鱼传送到测量和分拣机部件。当检测到鱼并通过图像处理计算其长度时，分拣机的位置由长度分类控制。使用低成本的商用网络摄像头，分级机的分拣机结构简单，由单个执行器组成。经过多次实验验证，机器视觉测长精度在10mm以内，分级机一分钟可分选30条鱼。与传统的眼睛测量相比，开发的分级器最大限度地减少了鱼类的水外暴露​​。因此，保持鱼的质量和新鲜度是有效的。与传统的眼睛测量相比，开发的分级器最大限度地减少了鱼类的水外暴露​​。因此，保持鱼的质量和新鲜度是有效的。与传统的眼睛测量相比，开发的分级器最大限度地减少了鱼类的水外暴露​​。因此，保持鱼的质量和新鲜度是有效的。