![]() ![]() We illustrate the feasibility of our technique by reconstructing 3D insect models and flower models with natural color textures. We also provide techniques to combine multiple textures obtained from multiple photographs and to synthesize missing texture regions caused by occlusion. We then project the photograph onto the 3D model from the found camera position to obtain a texture. A key idea is camera position estimation given a photograph and a 3D model obtained from a CT volume, we estimate the camera position of the photograph relative to the 3D model. In this paper, we present a novel digitization technique that combines image-based and CT-based approaches we reconstruct a shape by using a CT volume of a specimen and generate a texture from photographs taken from multiple viewpoints. However, X-ray CT does not provide surface colors, and it is difficult to reconstruct surface textures. This approach reconstructs a 3D shape accurately even if a specimen has concave and/or occluded structures. The CT-based approach takes an X-ray CT scan of a specimen to get a volumetric image (volume) and reconstructs the shape by segmenting the volume. Since this approach uses images as input, it obtains both shapes and textures at the same time however, it is difficult to reconstruct concave and occluded structures. The image-based approach reconstructs 3D shapes from photographs taken from multiple viewpoints by adopting visual hull or stereo vision methods. Both approaches have advantages and disadvantages. While some researchers reconstruct a 3D shape by using multiple photographs, other researchers adopt CT devices. Many methods for the 3D digitization of plant and insect specimens have been studied. In this paper, we also present a 3D reconstruction technique for natural objects based on measurement. ![]() Various digitization methods have been developed, and they store specimens with different data formats, such as two-dimensional (2D) photographs or three-dimensional (3D) surface models. In addition, it is possible to capture and store digital information that is invisible to the naked eye by using various devices, e.g., highly detailed surface textures obtained with microscopy and internal structures captured with X-ray computed tomography (CT). Natural objects, such as insects and plants, have been important targets of digitization because digital formats have various benefits, e.g., they are deterioration-free, space-efficient, and highly accessible. ![]() There was no additional external funding received for this study.Ĭompeting interests: The authors have declared that no competing interests exist.ĭigitization is a process for converting a target specimen into a digital format. ) The same data and links are also available at the first author’s web page ( ).įunding: This work was supported in part by the Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research (15H05924) to TI, HT, and YD. Source codes are available at GitHub repository (. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All data sets, including 3D models, textures, X-ray CT volumes, and photographs used in this paper, are available at the BioStudy repository ( ). Received: DecemAccepted: MaPublished: April 12, 2018Ĭopyright: © 2018 Ijiri et al. PLoS ONE 13(4):Įditor: Li Zeng, Chongqing University, CHINA The combination of X-ray CT and a digital camera makes it possible to successfully digitize specimens with complicated 3D structures accurately and allows us to browse both surface colors and internal structures.Ĭitation: Ijiri T, Todo H, Hirabayashi A, Kohiyama K, Dobashi Y (2018) Digitization of natural objects with micro CT and photographs. We illustrate the feasibility of our 3D digitization technique by digitizing 3D textured models of insects and flowers. We also present techniques for merging multiple textures generated from multiple photographs and recovering missing texture areas caused by occlusion. To achieve this reconstruction, we introduce a technique for estimating a camera position for each photograph. We then reconstruct a 3D model by segmenting the CT volume and generate a texture by projecting the photographs onto the model. We measure a specimen by using an X-ray CT device and a digital camera to obtain a CT volumetric image (volume) and multiple photographs. The key idea is to combine X-ray computed tomography (CT) and photographs to obtain both complicated 3D shapes and surface textures of target specimens. In this paper, we present a three-dimensional (3D) digitization technique for natural objects, such as insects and plants. ![]()
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