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Monitoring of Plankton Spatial and Temporal Characteristics With the Use of a Submersible Digital Holographic Camera
Frontiers in Marine Science ( IF 2.8 ) Pub Date : 2020-08-28 , DOI: 10.3389/fmars.2020.00653
Victor Dyomin , Alexandra Davydova , Sergey Morgalev , Nikolay Kirillov , Alexey Olshukov , Igor Polovtsev , Sergey Davydov

This study shows that the use of a submersible digital holographic camera as part of a multifunctional hardware and software complex allows carrying out in situ measurements of plankton, automating the process of obtaining data on plankton, as well as classifying plankton species up to an order within the specified taxonomic groups. Such automation ensures monitoring expeditionary or stationary research of species diversity and spatial and temporal organization of zooplankton in conjunction with the hydrophysical parameters of the medium. This paper presents the full-scale results of vertical profiles and daily measurements of plankton made with the use of the submersible digital holographic camera as well as the classification of plankton in laboratory and field conditions in the automatic mode. It is shown that, within the accomplished version, the classification algorithm using the morphological parameter makes it possible to solve the problem quickly (the time required to obtain the result is less than 1 s and depends on the number of plankton particles and the frame size of a restored image); however, the classification accuracy by orders varies within 50–60%.

中文翻译:

使用潜水式数字全息相机监测浮游生物时空特征

这项研究表明,使用潜水式数字全息相机作为多功能硬件和软件复合体的一部分,可以对浮游生物进行原位测量,使获取浮游生物数据的过程自动化,以及对浮游生物物种进行分类。指定的分类群。这种自动化确保监测物种多样性和浮游动物空间和时间组织的远征或静止研究,并结合介质的水文参数。本文介绍了使用潜水式数字全息相机制作的浮游生物垂直剖面和日常测量的全尺寸结果,以及在实验室和野外条件下自动模式下的浮游生物分类。结果表明,在完成的版本中,使用形态学参数的分类算法可以快速解决问题(获得结果所需的时间小于1s,取决于浮游生物颗粒的数量和恢复图像的帧大小);然而,按订单分类的准确率在 50-60% 之间变化。
更新日期:2020-08-28
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