N
Nagaaki Ohyama
Researcher at Tokyo Institute of Technology
Publications - 258
Citations - 4721
Nagaaki Ohyama is an academic researcher from Tokyo Institute of Technology. The author has contributed to research in topics: Color image & Image processing. The author has an hindex of 32, co-authored 258 publications receiving 4480 citations. Previous affiliations of Nagaaki Ohyama include National Institute of Information and Communications Technology.
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Proceedings ArticleDOI
Development of a 16-band multispectral image archiving system
Hiroyuki Fukuda,Toshio Uchiyama,Hideaki Haneishi,Hideaki Haneishi,Masahiro Yamaguchi,Nagaaki Ohyama,Nagaaki Ohyama +6 more
TL;DR: A 16-band camera system designed to produce spectral images of ancient paintings is described and Spectral reflectance were used to analyze a degraded area on an ancient painting.
Journal ArticleDOI
Application of Blockchain to Maintaining Patient Records in Electronic Health Record for Enhanced Privacy, Scalability, and Availability
Dara Tith,Joong-Sun Lee,Hiroyuki Suzuki,W. M. A. B. Wijesundara,Naoko Taira,Takashi Obi,Nagaaki Ohyama +6 more
TL;DR: The goal is to build a system to access patient records easily among EHRs without relying on a centralized supervisory system, and to protect a patient's privacy, a proxy re-encryption scheme when the data are transferred.
Journal ArticleDOI
Three-dimensional computed tomography for optical microscopes
TL;DR: In this paper, a 3D optical imaging method based on computed tomography techniques is presented, which has a higher band spherically, since 3D reconstructed images are composed only of the in-focused information of objects.
Journal ArticleDOI
Optical implementation of the stream cipher based on the irreversible cellular automata algorithm
TL;DR: A hybrid optical scheme for efficient hardware implementation of the one-dimensional, three-neighborhood binary cellular automata rule a(i)(?) =a( i-1)XOR(a(i)OR a( i+1)) -based stream cipher is proposed.
Journal ArticleDOI
Nonlinear estimation of spectral reflectance based on Gaussian mixture distribution for color image reproduction
TL;DR: It is confirmed that the proposed nonlinear estimation method of spectral reflectance from camera responses improves the accuracy in comparison with the conventional Wiener estimation method.