We propose a 500-frames-per-second high-speed vision (HSV) sensor network that acquires frames at a timing that is precisely synchronized across the network. Multiple vision sensor nodes, individually comprising a camera and a PC, are connected via Ethernet for data transmission and for clock synchronization. A network of synchronized HSV sensors provides a significantly expanded field-of-view compared with that of each individual HSV sensor. In the proposed system, the shutter of each camera is controlled based on the clock of the PC locally provided inside the node, and the shutters are globally synchronized using the Precision Time Protocol (PTP) over the network. A theoretical analysis and experiment results indicate that the shutter trigger skew among the nodes is a few tens of microseconds at most, which is significantly smaller than the frame interval of 1000-fps-class high-speed cameras. Experimental results obtained with the proposed system comprising four nodes demonstrated the ability to capture the propagation of a small displacement along a large-scale structure.
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http://dx.doi.org/10.3390/s18041276 | DOI Listing |
Sci Adv
January 2025
Department of Bio and Brain engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.
Nocturnal and crepuscular fast-eyed insects often exploit multiple optical channels and temporal summation for fast and low-light imaging. Here, we report high-speed and high-sensitive microlens array camera (HS-MAC), inspired by multiple optical channels and temporal summation for insect vision. HS-MAC features cross-talk-free offset microlens arrays on a single rolling shutter CMOS image sensor and performs high-speed and high-sensitivity imaging by using channel fragmentation, temporal summation, and compressive frame reconstruction.
View Article and Find Full Text PDFJMIR Biomed Eng
December 2024
School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, United States.
Background: Cell concentration in body fluid is an important factor for clinical diagnosis. The traditional method involves clinicians manually counting cells under microscopes, which is labor-intensive. Automated cell concentration estimation can be achieved using flow cytometers; however, their high cost limits accessibility.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Ningbo Institute of Dalian University of Technology, Ningbo 315032, China.
In the high-stakes domain of precision manufacturing, Cubic Boron Nitride (CBN) inserts are pivotal for their hardness and durability. However, post-production surface defects on these inserts can compromise product integrity and performance. This paper proposes an automated detection and classification system using machine vision to scrutinize these surface defects.
View Article and Find Full Text PDFGigascience
January 2024
Department of Health Technology, Technical University of Denmark, Kongens Lyngby 2800, Denmark.
Background: Corneocyte surface nanoscale topography (nanotexture) has recently emerged as a potential biomarker for inflammatory skin diseases, such as atopic dermatitis (AD). This assessment method involves quantifying circular nano-size objects (CNOs) in corneocyte nanotexture images, enabling noninvasive analysis via stratum corneum (SC) tape stripping. Current approaches for identifying CNOs rely on computer vision techniques with specific geometric criteria, resulting in inaccuracies due to the susceptibility of nano-imaging techniques to environmental noise and structural occlusion on the corneocyte.
View Article and Find Full Text PDFBiomicrofluidics
December 2024
Shanghai Aurefluidics Technology Co. Ltd, Shanghai 201800, China.
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