LISP: a laser imaging simulation package for developing and testing laser vision systems

1993 ◽  
Author(s):  
Kung C. Wu
2014 ◽  
Vol 84 (18) ◽  
pp. 1987-1994 ◽  
Author(s):  
Feng Liu ◽  
Zhenwei Su ◽  
Xiangcheng He ◽  
Chaoyong Zhang ◽  
Mouqin Chen ◽  
...  

The existing machine vision systems cannot efficiently detect white contaminants in cotton under the illumination of visible lights, because their color is the same or very close. To solve the problem, this article proposes an imaging method based on line lasers. Under the illumination of a line laser, the white contaminants and cotton showed the differences in the optical characteristic of their surface. Then, according to the features of the intensity of their reflected lights or the distribution of the fluff around their surfaces in the images, an example algorithm for identification of white contaminants from cotton was suggested. The experimental results indicated that, using our method, the mean successful detection rate of the typical white contaminants in cotton was over 87%.


2021 ◽  
Vol 9 (2) ◽  
pp. 133-141
Author(s):  
Valeriy Alexeev ◽  
Dmitry Goryachkin ◽  
Nikolay Gryaznov ◽  
Viktor Kuprenyuk ◽  
Evgeniy Sosnov

The analysis of the implementation problems of technical vision systems based on the use of time-of-flight laser lidars is carried out. It is concluded that the implementation of vision systems with acceptable parameters dictates an excessively high cost of the lidar. An alternative version of the lidar implementation is considered – a gated lidar based on a laser vision system. Replacing the broadband detector and high-speed scanning system with a gated CCD-matrix can significantly reduce the cost of the lidar while ensuring the high resolution of the lidar. The analysis of the dependence of the signal-to-noise ratio for gated lidar with and without an electron-optical converter has shown that in bad weather conditions the decrease in the gain of the useful signal when the image intensifier is excluded is compensated by the exclusion of the EOC's noise factor, so that the loss in the observation distance is less than 15%.


Nature ◽  
2002 ◽  
Author(s):  
Philip Ball
Keyword(s):  

Metrologiya ◽  
2020 ◽  
pp. 15-37
Author(s):  
L. P. Bass ◽  
Yu. A. Plastinin ◽  
I. Yu. Skryabysheva

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.


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