Computer vision enhances the potential of ultrabroadband imaging in non-destructive testing

Led by Assistant Prof. Kou Li, a research group in Chuo University (President: KAWAI Hisashi, Hachioji-shi, Tokyo, Japan), under a collaboration with National Institute of Informatics (Director-General: KUROHASHI Sadao, Chiyoda-ku, Tokyo, Japan), has developed a synergetic strategy among millimeter-wave–terahertz–infrared photo-monitoring and computer vision three-dimensional modelling toward ubiquitous non-destructive inspections, with a recent paper publication in Advanced Materials Technologies .

While non-destructive inspections of daily necessities and industrial products require material composition identifications and structural reconstructions of composite multi-layered three-dimensional (3D) objects, the development of analyzing systems that fully satisfy those performances is still insufficient. Particularly, synergetic combinations are urgently indispensable among non-destructive permeable inner material identifications with millimeter-wave (MMW)–terahertz (THz)–infrared (IR) photo-monitoring and computer-vision (CV)-driven 3D modelling. However, respective approaches on the above individual concept crucially regulate their use as planar image acquisition operations for the former (missing cross-sectional information) and visual light (Vis)-based outer views for the latter (lacking non-destructive permeability to inner structures).

To this end, this manuscript made the following significant contributions.

The paper was published online in the international scientific journal, Advanced Materials Technologies (February 15, 2025).

<Researcher>

Kou Li, Assistant Professor, Department of Electrical, Electronic, and Communication Engineering of the Faculty of Science and Engineering, Chuo University

Daiki Shikichi, Master course student, Department of Electrical, Electronic, and Communication Engineering, Graduate School of Science and Engineering, Chuo University

Miki Kubota, Master course student, Department of Electrical, Electronic, and Communication Engineering, Graduate School of Science and Engineering, Chuo University

Yukio Kawano, Professor, Department of Electrical, Electronic, and Communication Engineering of the Faculty of Science and Engineering, Chuo University

Raito Ota, Bachelor student (at the time of research), Department of Electrical, Electronic, and Communication Engineering of the Faculty of Science and Engineering, Chuo University

Takeru Q. Suyama, Ph.D. student, National Institute of Informatics, SOKENDAI

Satoshi Ikehata, Associate Professor, Digital Content and Media Sciences Research Division, National Institute of Informatics

Imari Sato, Professor, Digital Content and Media Sciences Research Division, National Institute of Informatics

<Authors>

^† Co-first author, ^* Corresponding author

Daiki Shikichi ^†,1 , Raito Ota ^†,1 , Miki Kubota ^†,1 , Yuya Kinoshita ¹ , Noa Izumi ¹ , Mitsuki Kosaka ¹ , Tomoki Nishi ¹ , Daiki Sakai ¹ , Yuto Matsuzaki ¹ , Leo Takai ¹ , Minami Yamamoto ¹ , Yuto Aoshima ¹ , Ryoga Odawara ¹ , Takeru Q. Suyama ^2,3 , Hiroki Okawa ⁴ , Zhenyu Zhou ³ , Tomoya Furukawa ^5,6 , Shota Wada ^5,6 , Satoshi Ikehata ³ , Imari Sato ³ , Yukio Kawano* ^,1,3,4 , and Kou Li* ^,1

<Affiliation>

¹ Department of Electrical, Electronic, and Communication Engineering, Faculty of Science and Engineering, Chuo University

² The Graduate University for Advanced Studies, SOKENDAI

³ National Institute of Informatics

⁴ Kanagawa Industrial Institute of Science and Technology

⁵ Laboratory for Future Interdisciplinary Research of Science and Technology, Tokyo Institute of Technology

⁶ Department of Electrical and Electronic Engineering, School of Engineering, Tokyo Institute of Technology

Advanced Materials Technologies

10.1002/admt.202401724

Experimental study

Not applicable

Multi computer vision-driven testing platform: structural reconstruction and material identification with ultrabroadband carbon nanotube imagers

19-Feb-2025

The authors acknowledge Zeon Co. for providing CNT solution. The authors also thank Musashi Engineering Inc. for their technical support. This work was partially supported by many Funders. For detailed funding information, please refer to the "Funders" section.