POSTER Session 2

ANTI-BIOFOULING LENS-LESS CAMERA WITH DEEP LEARNING BASED IMAGE RECONSTRUCTION

In recent years, there has been an increasing demand for underwater cameras that monitor the condition of offshore structures and check the number of individuals in aquaculture environments with long-period observation. One of the significant issues with this observation is that biofouling sticks to the aperture and lens densely and prevents cameras from capturing clear images. This study examines an underwater camera that applies material technologies with high inherent resistance to biofouling and computer vision technologies based on image reconstruction by deep learning to lens-less cameras. For this purpose, our prototype camera uses a lens-less aperture with 1k pinholes in a thin metal plate, such as copper, which hinder the growth of biofouling and keep the surface clean. Although images taken by lens-less cameras are usually not well formed due to lack of the lens, a deep learning approach using ViT has recently demonstrated reconstructing original photo images well and our study shows that using gated MLP also yields good results. On the other hand, a certain degree of thickness for bio-repellence materials is required to exhibit their effect the thickness of aperture is necessary to use apertures sufficiently thinner than the size of the pinholes to avoid unintentional reflection and absorption on the sidewalls. Therefore, we prepared a sufficiently thin plate for image reconstruction and now currently we conduct tests of the lens-less camera of the bio-repellence aperture with actual seawater environments to determine whether it can sufficiently demonstrate the biofouling effect compared with usual camera with only waterproof.

Naoki Ide, Sony Group Corporation, Japan

Tomohiro Kawahara, Sony Group Corporation, Japan, https://orcid.org/0000-0003-0983-1452

Hiroshi Ueno, Sony Group Corporation, Japan

Daiki Yanagidaira, Sony Group Corporation, Japan

Susumu Takatsuka, Sony Group Corporation and Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Japan, https://orcid.org/0000-0002-1229-1963

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