scholarly journals Developing a portable gas imaging camera using highly tunable active-illumination and computer vision

2020 ◽  
Vol 28 (13) ◽  
pp. 18566
Author(s):  
Kyle J. Nutt ◽  
Nils Hempler ◽  
Gareth T. Maker ◽  
Graeme P. A. Malcolm ◽  
Miles J. Padgett ◽  
...  
Keyword(s):  
Computer Vision ◽  
Imaging Camera ◽  
Active Illumination

scholarly journals Improvement of EPIC/DSCOVR Image Registration by Means of Automatic Coastline Detection

2019 ◽  
Vol 11 (15) ◽  
pp. 1747 ◽  
Author(s):  
Víctor Molina García ◽  
Sruthy Sasi ◽  
Dmitry S. Efremenko ◽  
Diego Loyola
Keyword(s):  
Computer Vision ◽  
Image Registration ◽  
Lagrangian Point ◽  
Deep Space ◽  
Radial Distortion ◽  
Imaging Camera ◽  
Non Linear ◽  
Linear Optimisation

In this work, we address the image geolocation issue that is present in the imagery of EPIC/DSCOVR (Earth Polychromatic Imaging Camera/Deep Space Climate Observatory) Level 1B version 2. To solve it, we develop an algorithm that automatically computes a registration correction consisting of a motion (translation plus rotation) and a radial distortion. The correction parameters are retrieved for every image by means of a regularised non-linear optimisation process, in which the spatial distances between the theoretical and actual locations of chosen features are minimised. The actual features are found along the coastlines automatically by using computer vision techniques. The retrieved correction parameters show a behaviour that is related to the period of DSCOVR orbiting around the Lagrangian point L 1 . With this procedure, the EPIC coastlines are collocated with an accuracy of about 1.5 pixels, thus significantly improving the original registration of about 5 pixels from the imagery of EPIC/DSCOVR Level 1B version 2.

Human Vision and Computer Vision

1985 ◽  
Vol 30 (1) ◽  
pp. 47-47
Author(s):  
Herman Bouma
Keyword(s):  
Computer Vision ◽  
Human Vision

Computer vision for industrial applications

1983 ◽  
Vol 2 (5) ◽  
pp. 130
Author(s):  
J.A. Losty ◽  
P.R. Watkins
Keyword(s):  
Computer Vision ◽  
Industrial Applications

The Diverging Collimator

1970 ◽  
Vol 09 (01) ◽  
pp. 84-94
Author(s):  
G. Muehllehner
Keyword(s):  
Unit Area ◽  
Field Of View ◽  
Imaging Camera ◽  
Good Agreement ◽  
Parallel Hole

SummaryThe diverging collimator makes it possible to increase the field of view of a radioisotope imaging camera. The larger field of view is obtained by sacrificing efficiency per unit area of the field of view while preserving the resolution of the system. This situation is analogous to that of the scanner, where the efficiency per unit area is inversely proportional to the total area scanned.Efficiency and resolution of diverging collimators can be calculated quite accurately as is evidenced by the good agreement between calculated and measured values. The problem of septum penetration, however, needs to be further investigated for both parallel-hole as well as diverging collimators, so that the influence of the shape and arrangement of the holes upon septum penetration is taken into account.

The machine training in problems of satellite images’s processing

Metrologiya ◽  
2020 ◽  
pp. 15-37
Author(s):  
L. P. Bass ◽  
Yu. A. Plastinin ◽  
I. Yu. Skryabysheva
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Computer Vision ◽  
Satellite Images ◽  
Vision Systems ◽  
Earth Remote Sensing ◽  
Practical Applications ◽  
Convolution Neural Networks ◽  
Computer Vision Systems ◽  
Trained Neural Network

Use of the technical (computer) vision systems for Earth remote sensing is considered. An overview of software and hardware used in computer vision systems for processing satellite images is submitted. Algorithmic methods of the data processing with use of the trained neural network are described. Examples of the algorithmic processing of satellite images by means of artificial convolution neural networks are given. Ways of accuracy increase of satellite images recognition are defined. Practical applications of convolution neural networks onboard microsatellites for Earth remote sensing are presented.

Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

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