Inselect: Automating the Digitization of Natural History Collections.
Inselect: Automating the Digitization of Natural History Collections.
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DOI：
10.1371/journal.pone.0143402
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Smith VS
中科院分区：
文献类型：
--
作者：
Hudson LN;Blagoderov V;Heaton A;Holtzhausen P;Livermore L;Price BW;van der Walt S;Smith VS
世界自然历史收藏品构成了对自然界进行科学研究的巨大证据基础。为了促进这些研究和改善对藏品的获取，许多组织正在开展重大的数字化方案。这需要大规模数字化的自动化方法，以支持标本的快速成像和相关的数据捕获，以便处理大多数自然历史收藏中常见的数千万件标本。在本文中，我们介绍了InSELECT-一种模块化的、易于使用的、跨平台的开源软件工具套件，它支持对自然历史数字化程序生成的标本图像进行半自动处理。该软件由Windows、Mac OS X和Linux桌面应用程序以及命令行工具组成，这些工具旨在对批量图像进行无人值守操作。将自动识别标本的图像可视化算法与支持条形码读取、标签转录和元数据捕获等后处理任务的工作流结合在一起，INSELECT填补了提高标本数字化速度的关键空白。
The world’s natural history collections constitute an enormous evidence base for scientific research on the natural world. To facilitate these studies and improve access to collections, many organisations are embarking on major programmes of digitization. This requires automated approaches to mass-digitization that support rapid imaging of specimens and associated data capture, in order to process the tens of millions of specimens common to most natural history collections. In this paper we present Inselect—a modular, easy-to-use, cross-platform suite of open-source software tools that supports the semi-automated processing of specimen images generated by natural history digitization programmes. The software is made up of a Windows, Mac OS X, and Linux desktop application, together with command-line tools that are designed for unattended operation on batches of images. Blending image visualisation algorithms that automatically recognise specimens together with workflows to support post-processing tasks such as barcode reading, label transcription and metadata capture, Inselect fills a critical gap to increase the rate of specimen digitization.