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Progress in the Automated Identification, Measurement, and Counting of Fish in Underwater Image Sequences

机译:水下图像序列中鱼的自动识别,测量和计数的进展

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摘要

Underwater video systems are widely used for counting and measuring fish in aquaculture, fisheries, and conservation management. To determine Population counts, spatial or temporal: frequencies, and age or weight distributions, snout to tail fork length measurements are performed in video most commonly using using a point and click 'process by a human operator. Current research aims to automate the identification, measurement, and counting of fish in order to improve the efficiency of population counts or biomass estimates. A fully automated process requires the detection and isolation of candidates for measurement, followed by the snout to tail fork length measurement, species classification, as well counting and tracking of fish. This paper reviews the used for the:detection, identification, measurement :counting,, and tracking-of fish in underwater video sequences. The paper analyzes the most commonly used approaches leading to an evaluation of the techniques most likely to be a comprehensive solution to the complete process of candidate. detection, species identification, length measurement, and population counts for biomass estimation.
机译:水下视频系统广泛用于水产养殖,渔业和保护管理中的鱼类计数和测量。为了确定人口计数,空间或时间:频率以及年龄或体重分布,通常在视频中使用人工操作人员的“单击并单击”过程来执行鼻子到尾叉长度的测量。当前的研究旨在使鱼类的识别,测量和计数自动化,以提高种群计数或生物量估计的效率。全自动过程需要检测和隔离待测候选物,然后进行口鼻至尾叉长度测量,物种分类以及鱼类的计数和跟踪。本文概述了用于水下视频序列中鱼的检测,识别,测量,计数和跟踪的方法。本文分析了最常用的方法,从而对最有可能成为候选人完整过程的综合解决方案的技术进行了评估。检测,物种识别,长度测量以及用于生物量估算的种群计数。

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