Real-time thermographic image acquisition and segmentation algorithms for continuous material

2004 ◽  
Author(s):  
Ruben Usamentiaga ◽  
Daniel F. Garcia ◽  
Alberto Mijares ◽  
Juan A. Gonzalez
Keyword(s):  
Real Time ◽  
Image Acquisition ◽  
Segmentation Algorithms ◽  
Thermographic Image ◽  
Continuous Material

scholarly journals Real-time 2D–3D door detection and state classification on a low-power device

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
João Gaspar Ramôa ◽  
Vasco Lopes ◽  
Luís A. Alexandre ◽  
S. Mogo
Keyword(s):  
Low Power ◽  
Real Time ◽  
Object Classification ◽  
Semantic Segmentation ◽  
Detection Algorithm ◽  
Power Device ◽  
Indoor Environments ◽  
State Classification ◽  
Segmentation Algorithms ◽  
Indoor Spaces

AbstractIn this paper, we propose three methods for door state classification with the goal to improve robot navigation in indoor spaces. These methods were also developed to be used in other areas and applications since they are not limited to door detection as other related works are. Our methods work offline, in low-powered computers as the Jetson Nano, in real-time with the ability to differentiate between open, closed and semi-open doors. We use the 3D object classification, PointNet, real-time semantic segmentation algorithms such as, FastFCN, FC-HarDNet, SegNet and BiSeNet, the object detection algorithm, DetectNet and 2D object classification networks, AlexNet and GoogleNet. We built a 3D and RGB door dataset with images from several indoor environments using a 3D Realsense camera D435. This dataset is freely available online. All methods are analysed taking into account their accuracy and the speed of the algorithm in a low powered computer. We conclude that it is possible to have a door classification algorithm running in real-time on a low-power device.

scholarly journals Module to Support Real-Time Microscopic Imaging of Living Organisms on Ground-Based Microgravity Analogs

2021 ◽  
Vol 11 (7) ◽  
pp. 3122
Author(s):  
Srujana Neelam ◽  
Audrey Lee ◽  
Michael A. Lane ◽  
Ceasar Udave ◽  
Howard G. Levine ◽  
...  
Keyword(s):  
Real Time ◽  
High Speed ◽  
Simulated Microgravity ◽  
Image Acquisition ◽  
Time Lapse ◽  
Moving Frames ◽  
Cell Functions ◽  
Microgravity Simulation ◽  
Division Cell ◽  
Over Time

Since opportunities for spaceflight experiments are scarce, ground-based microgravity simulation devices (MSDs) offer accessible and economical alternatives for gravitational biology studies. Among the MSDs, the random positioning machine (RPM) provides simulated microgravity conditions on the ground by randomizing rotating biological samples in two axes to distribute the Earth’s gravity vector in all directions over time. Real-time microscopy and image acquisition during microgravity simulation are of particular interest to enable the study of how basic cell functions, such as division, migration, and proliferation, progress under altered gravity conditions. However, these capabilities have been difficult to implement due to the constantly moving frames of the RPM as well as mechanical noise. Therefore, we developed an image acquisition module that can be mounted on an RPM to capture live images over time while the specimen is in the simulated microgravity (SMG) environment. This module integrates a digital microscope with a magnification range of 20× to 700×, a high-speed data transmission adaptor for the wireless streaming of time-lapse images, and a backlight illuminator to view the sample under brightfield and darkfield modes. With this module, we successfully demonstrated the real-time imaging of human cells cultured on an RPM in brightfield, lasting up to 80 h, and also visualized them in green fluorescent channel. This module was successful in monitoring cell morphology and in quantifying the rate of cell division, cell migration, and wound healing in SMG. It can be easily modified to study the response of other biological specimens to SMG.

Research on Real-Time Low Air Image Intelligence Image Acquisition and Processing Methods

2019 ◽  
pp. 23-34
Author(s):  
Pin Wang ◽  
Guocheng Zheng ◽  
Shen Zhang ◽  
Peng Xu ◽  
Zhumei Zhao ◽  
...  
Keyword(s):  
Real Time ◽  
Image Acquisition ◽  
Processing Methods

Verification Real-Time Image Acquisition System (VERITAS)

2014 ◽  
Vol 90 (1) ◽  
pp. S892-S893
Author(s):  
J. Rottmann ◽  
D. Kozono ◽  
R. Mak ◽  
A. Chen ◽  
F.L. Hacker ◽  
...  
Keyword(s):  
Real Time ◽  
Image Acquisition ◽  
Acquisition System ◽  
Real Time Image ◽  
Image Acquisition System ◽  
Time Image

Catching the Right Bus, Part VI: Some Options for Real-Time Image Acquisition

1995 ◽  
Vol 9 (5) ◽  
pp. 496
Author(s):  
Gary Forrest ◽  
Scott McKinney ◽  
James R. Matey
Keyword(s):  
Real Time ◽  
Image Acquisition ◽  
Real Time Image ◽  
The Right ◽  
Time Image
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