Carbon nanotube Eye: reconstruction of inner hidden composition & structure of inspection targets

Joint Press Release by Chuo University and National Institute of Informatics.

【Table of Contents】

○ Development of non-destructive imaging with a multi-functional photo-sensor into better understandings of hidden compositional identification and structural reconstruction via computer vision^{term 1} technique.
○ Effective use of computer vision in ultrabroad and multi-wavelength bands. Frontier-“invisible photo irradiation-based analysis” leads to breakthroughs in quality assessment techniques.
○ Carbon nanotube-based soft thin-films, a constituent of the photo-sensing eye, facilitate frontier computer vision monitoring by collectively detecting both visible and invisible irradiation in high sensitivities.
○ The presenting device and system allow identifications and reconstructions of composite complicated multi-layer structures concealed by opaque configurations in a non-destructive and non-contact manner.

【Abstract】
A research group at Chuo University, Japan, organized by Assistant Professor Kou Li (Faculty of Science and Engineering), developed a novel non-destructive inspection technique by effectively combining their own multi-functional photo monitoring device and system with image data-driven three-dimensional (3D) restoration methods, in collaboration with National Institute of Informatics. The presenting technique precisely evaluates target objects by compositional identifications and structural reconstructions (Fig. 1).

Since the dawn of the IoT (Internet of Things) society, non-destructive inspection techniques have garnered attention to assure the fundamental safety in cyber and physical interactions by detecting concealed defects of daily and industrial components. In particular, photo-imaging methods play core roles in non-destructive inspections for their non-contact and large-area (i.e., informative) data acquisition. Meanwhile, representative inspecting points include compositional identifications (what materials target objects and their concealed defects comprise) and structural reconstructions (how and which shapes the above materials form). Although efforts, collectively satisfying the compositional identifications and structural reconstructions, potentially facilitate precise and reliable social quality testing, studies demonstrating the above concepts are still insufficient.

To tackle such crucial technical limitations, this work developed an unconventional non-destructive inspection platform that would provide a breakthrough in the study field of safety and quality testing. In this work, Assis. Prof. Li, the leader of the collaborative research group, effectively combined the sensing device and system for compositional identifications uniquely developed in Chuo Univ. by employing cutting-edge nanomaterials: Japan-origin carbon nanotubes (CNT), with 3D structural reconstruction schemes in NII: simply based on superposition of silhouette images from target objects.

Their original research paper regarding the above topic is available in the international scientific journal “Advanced Optical Materials”, published on December 25^th, 2023. 
 

【Term】

1）CV: Computer vision
CV is a study filed in which information engineering techniques and numerical analyses handle image data for synergetic functionalities.