Study on the Length Identification System of Steel Tape Based on LabVIEW Image Processing

2013 ◽  
Vol 718-720 ◽  
pp. 2021-2025
Author(s):  
Min An Tang ◽  
Xiao Ming Wang ◽  
Hui Feng Kang
Keyword(s):  
Image Processing ◽  
Image Recognition ◽  
Experimental Results ◽  
Identification System ◽  
Processing Software ◽  
Image Processing Software ◽  
Industrial Cameras ◽  
Measured Length ◽  
Standard Steel ◽  
Identification Procedures

The error of the steel tape itself is an important factor to affect the measured length. According to the identification system of the improved identification procedures of steel tape, the industrial cameras are adopted to take photos for the steel tape and the standard steel tape which will be measured. At the same time, the LabVIEW image processing software is employed to process the photographs. Through comparing the errors of each point in the steel tape calculated by the image recognition, the identification results are finally obtained. The experimental results show that the proposed method is effective.

scholarly journals SPRAY CONE ANGLES GENERATED BY A DUAL CENTRIFUGAL INJECTOR

2014 ◽  
Vol 13 (1) ◽  
pp. 36
Author(s):  
R. A. Vásquez ◽  
F. S. Costa
Keyword(s):  
Experimental Data ◽  
Image Processing ◽  
Experimental Results ◽  
Spray Cone ◽  
Centrifugal Injector ◽  
Swirl Injector ◽  
Processing Software ◽  
Image Processing Software ◽  
Pressure Swirl ◽  
Semi Empirical

A dual pressure swirl injector is characterized by two independent concentric chambers which can provide independent rotational levels to a single liquid or two different liquids. This paper compares theoretical, semi-empirical and experimental results concerning the spray cone angles formed by injection of water, ethanol and biodiesel through a dual pressure swirl injector. Data are obtained for injection of the same liquid through the primary and secondary chambers and for injection of ethanol in the primary chamber and biodiesel through the secondary chamber of the injector. Experimental data are obtained using photographic techniques and are analyzed by an image processing software developed in Matlab language.

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.

Sign in / Sign up

Export Citation Format

Share Document