Journal ArticleDOI
Evaluation of three-dimensional surface roughness parameters based on digital image processing.
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TLDR
A three-dimensional measuring technique is proposed, which is used to survey components surface roughness, based on the digital image processing technology, and an athree-dimensional surface Roughness evaluation system is established consisting of both hardware and software architecture.Abstract:
With the development and application of optoelectric technology, laser technology and computer technology in mind, we have developed a method to evaluate three-dimensional surface roughness using surface profile information. This article proposes a three-dimensional measuring technique, which is used to survey components surface roughness, based on the digital image processing technology, and establishes athree-dimensional surface roughness evaluation system consisting of both hardware and software architecture. The hardware used in the present experiment is listed as follows: a stereomicroscope, a digital camera with special interface, a parallel light (by halogen lamp), an X, Y bidirectional laboratory bench and a computer. A computer-aided system (CAS), developed with Visual C++ , is used in the image pretreatment and data processing analysis. In the experiment, image information gathered from the digital camera is pre-processed by median filtering, grayscale equalization and histogram conversion amplification. Then the data are analyzed by normalized cross-correlation and surface fitting techniques. Lastly, the correlation between m, σ,
Sq, S
ku
and Ra is discussed for different surface roughness specimens.read more
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References
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Comprehensive study of parameters for characterising three- dimensional surface topography: III: Parameters for characterising amplitude and some functional properties
TL;DR: In this paper, a primary 3D parameter set is proposed based on an understanding of intrinsic properties of surface topographic features and parameters, and the feasibility in terms of sampling conditions and the application scope of the parameters is discussed.
Journal ArticleDOI
Comprehensive study of parameters for characterising three-dimensional surface topography: IV: Parameters for characterising spatial and hybrid properties
TL;DR: In this article, the authors described a comprehensive study of parameters used to characterize 3D surface topography in 3D. The feasibility and significance of the parameters in characterising surface topology in 3d are addressed by conducting experiments on a wide range of engineered surfaces.
Journal ArticleDOI
Application of digital image magnification for surface roughness evaluation using machine vision
TL;DR: Based on the surface image features, a parameter called G a has been estimated using regression analysis, for the original images and for the magnified quality improved images and a comparison has been carried to establish correlation between magnification index, G a and surface roughness.
Journal ArticleDOI
An evaluation of surface roughness parameters measurement using vision-based data
TL;DR: The overall acquired results indicate that vision systems are a valid source of data to obtain both amplitude and spacing roughness parameters with confidence using the proposed methodology.
Journal ArticleDOI
A vision system for surface roughness assessment using neural networks
TL;DR: Experimental results have shown that the proposed roughness features and neural networks are efficient and effective for automated classification of surface roughness.