Visual Sensing System for Thin Plate Welding Based on Rotund Facular Laser

2012 ◽  
Vol 538-541 ◽  
pp. 1498-1501
Author(s):  
Wang Ping Gu ◽  
Zhen Yu Xiong ◽  
Pin Liu
Keyword(s):  
Thin Plate ◽  
Visual Image ◽  
Sensor System ◽  
Vision Sensor ◽  
Butt Welding ◽  
Vision Sensing ◽  
Sensing System ◽  
Visual Sensing ◽  
Processing Software ◽  
Image Processing Software

In order to solve the problem of thin plate butt-welded tracking, a welding vision sensing system with a rotund facular laser has been designed. In the vision sense system, each parameter of the interior part has been designed by a variety of experiments. The designed image processing software can precisely identify the position of the joint, based on the optimal designed vision sensor system. The thin plate butt welding experiments have been taken with the designed sensing device. The experimental results show that the vision sensor system with a suitable auxiliary illuminant can obtain satisfying visual image information in stainless thin plate butt-welded.

Analysis of the 9th November 1990 flare

2000 ◽  
Vol 179 ◽  
pp. 229-232
Author(s):  
Anita Joshi ◽  
Wahab Uddin
Keyword(s):  
Image Processing ◽  
Two Dimensional ◽  
Temporal Behaviour ◽  
Contour Maps ◽  
Dimensional Measurements ◽  
Processing Software ◽  
Image Processing Software

AbstractIn this paper we present complete two-dimensional measurements of the observed brightness of the 9th November 1990Hαflare, using a PDS microdensitometer scanner and image processing software MIDAS. The resulting isophotal contour maps, were used to describe morphological-cum-temporal behaviour of the flare and also the kernels of the flare. Correlation of theHαflare with SXR and MW radiations were also studied.

scholarly journals Demineralization Depth Using QLF and a Novel Image Processing Software

2010 ◽  
Vol 2010 ◽  
pp. 1-7 ◽  
Author(s):  
Jun Wu ◽  
Zachary R. Donly ◽  
Kevin J. Donly ◽  
Steven Hackmyer
Keyword(s):  
Image Processing ◽  
Linear Regression ◽  
Polarized Light ◽  
Region Of Interest ◽  
Linear Regression Method ◽  
Percent Loss ◽  
Significant Linear Correlation ◽  
Processing Software ◽  
Image Processing Software ◽  
Imagej Software

Quantitative Light-Induced fluorescence (QLF) has been widely used to detect tooth demineralization indicated by fluorescence loss with respect to surrounding sound enamel. The correlation between fluorescence loss and demineralization depth is not fully understood. The purpose of this project was to study this correlation to estimate demineralization depth. Extracted teeth were collected. Artificial caries-like lesions were created and imaged with QLF. Novel image processing software was developed to measure the largest percent of fluorescence loss in the region of interest. All teeth were then sectioned and imaged by polarized light microscopy. The largest depth of demineralization was measured by NIH ImageJ software. The statistical linear regression method was applied to analyze these data. The linear regression model wasY=0.32X+0.17, whereXwas the percent loss of fluorescence andYwas the depth of demineralization. The correlation coefficient was 0.9696. The two-tailed t-test for coefficient was 7.93, indicating theP-value=.0014. TheFtest for the entire model was 62.86, which shows theP-value=.0013. The results indicated statistically significant linear correlation between the percent loss of fluorescence and depth of the enamel demineralization.

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