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首页> 外文期刊>Image Processing, IET >Estimating Norway lobster abundance from deep-water videos: an automatic approach
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Estimating Norway lobster abundance from deep-water videos: an automatic approach

机译：从深水视频中估算挪威龙虾的丰度：一种自动方法

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摘要

Video technology has been playing an increasing role in marine science, both for habitat mapping and estimating commercial species abundance. However, when quantification is needed, it is usually based on manual counting, a subjective and time-consuming task. The present work proposes a methodology to automatically quantify the abundance of Norway lobsters, Nephrops norvegicus, by counting lobsters or their burrows from video sequences, as a reliable complement to the currently used operator-based approach. The methodology is validated using a set of test video sequences captured at the Portuguese continental slope, using a monochrome camera mounted on a trawl gear, being characterised by non-uniform illumination, artefacts at image border, noise and marine snow. The analysis includes, after a pre-processing stage, the segmentation of regions of interest and the corresponding classification into one of the three targeted classes: Norway lobsters, burrows and others (including trawl impact marks). The developed software prototype, named IT-IPIMAR N. norvegicus (I2N2), is able to provide an objective, detailed and comprehensive analysis to complement manual evaluation, for lobster and burrow density estimation.
机译：视频技术在海洋科学中起着越来越重要的作用，可用于栖息地测绘和估计商业物种的丰度。但是，当需要定量时，它通常基于手动计数，这是一个主观且耗时的任务。本工作提出了一种方法，可以通过对视频序列中的龙虾或它们的洞穴进行计数来自动量化挪威龙虾（Nephrops norvegicus）的数量，作为对当前使用的基于操作员的方法的可靠补充。使用在葡萄牙大陆坡上捕获的一组测试视频序列，并使用安装在拖网渔具上的单色摄像机对方法进行了验证，该摄像机的特征是照明不均匀，图像边界处的伪像，噪声和海洋积雪。在预处理阶段之后，分析包括将感兴趣的区域进行分割并将相应的分类分为三个目标类别之一：挪威龙虾，洞穴和其他（包括拖网影响标记）。名为IT-IPIMAR N. norvegicus（I2N2）的已开发软件原型能够提供客观，详细而全面的分析，以补充对龙虾和洞穴密度估算的手动评估。

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