Ströbel Bernhard, Schmelzle Sebastian, Blüthgen Nico, Heethoff Michael
Department of Mathematics and Natural Sciences, University of Applied Sciences Darmstadt, Schöfferstr. 3, 64295 Darmstadt, Germany.
Ecological Networks, Technische Universität Darmstadt, Schnittspahnstr. 3, 64287 Darmstadt, Germany.
Zookeys. 2018 May 17(759):1-27. doi: 10.3897/zookeys.759.24584. eCollection 2018.
Digitization of natural history collections is a major challenge in archiving biodiversity. In recent years, several approaches have emerged, allowing either automated digitization, extended depth of field (EDOF) or multi-view imaging of insects. Here, we present DISC3D: a new digitization device for pinned insects and other small objects that combines all these aspects. A PC and a microcontroller board control the device. It features a sample holder on a motorized two-axis gimbal, allowing the specimens to be imaged from virtually any view. Ambient, mostly reflection-free illumination is ascertained by two LED-stripes circularly installed in two hemispherical white-coated domes (front-light and back-light). The device is equipped with an industrial camera and a compact macro lens, mounted on a motorized macro rail. EDOF images are calculated from an image stack using a novel calibrated scaling algorithm that meets the requirements of the pinhole camera model (a unique central perspective). The images can be used to generate a calibrated and real color texturized 3Dmodel by 'structure from motion' with a visibility consistent mesh generation. Such models are ideal for obtaining morphometric measurement data in 1D, 2D and 3D, thereby opening new opportunities for trait-based research in taxonomy, phylogeny, eco-physiology, and functional ecology.
自然历史标本馆的数字化是生物多样性存档中的一项重大挑战。近年来，出现了几种方法，可实现昆虫的自动数字化、扩展景深（EDOF）或多视图成像。在此，我们介绍DISC3D：一种用于固定昆虫和其他小物体的新型数字化设备，它结合了所有这些方面。一台个人电脑和一块微控制器板控制该设备。它在一个电动双轴万向节上设有一个样品架，可让标本从几乎任何角度进行成像。通过两个圆形安装在两个半球形白色涂层圆顶（前光和背光）中的LED灯带确定环境光，这种光大多无反射。该设备配备有一台工业相机和一个紧凑型微距镜头，安装在一个电动微距导轨上。使用一种符合针孔相机模型（独特的中心视角）要求的新型校准缩放算法，从图像堆栈中计算出扩展景深图像。这些图像可通过“运动结构”生成具有一致可见性网格的校准且真实颜色的纹理化3D模型。此类模型非常适合获取一维、二维和三维的形态测量数据，从而为分类学、系统发育学、生态生理学和功能生态学中基于性状的研究带来新机遇。
