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Application of digital image magnification for surface roughness evaluation using machine vision
B. Dhanasekar, B. Ramamoorthy
Published in
2005
Volume: 45
   
Issue: 2
Pages: 228 - 234
Abstract
In this work, a machine vision system has been utilized to capture the images and then the quantification of the surface roughness of machined surfaces (ground, milled and shaped) is done by the application of regression analysis, Subsequently, original images have been magnified using Cubic Convolution interpolation technique and improved (edge enhancement) through Linear Edge Crispening algorithm. Based on the surface image features, a parameter called Ga has been estimated using regression analysis, for the original images and for the magnified quality improved images. Finally, a comparison has been carried to establish correlation between magnification index, Ga and surface roughness. © 2004 Elsevier Ltd. All rights reserved.
About the journal
JournalInternational Journal of Machine Tools and Manufacture
ISSN08906955
Open AccessNo
Concepts (15)
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    Algorithms
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    Computer vision
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    Correlation methods
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    Fiber optics
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    Fourier transforms
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    Interpolation
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    Quality control
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    Regression analysis
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    Sensors
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    Surface roughness
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    CUBIC CONVOLUTION
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    GREY LEVEL AVERAGE
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    Magnification factors
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    Process monitoring
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    Image processing