Surface Roughness Image Analysis using Quasi-Fractal Characteristics and Fuzzy Clustering Methods | Zendy

Tiberiu Vesselényi | Zendy; Ioan Dziţac | Zendy; Simona Dzițac | Zendy; Victor Vaida | Zendy

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Surface Roughness Image Analysis using Quasi-Fractal Characteristics and Fuzzy Clustering Methods

Author(s) -

Tiberiu Vesselényi,

Ioan Dziţac,

Simona Dzițac,

Victor Vaida

Publication year - 2008

Publication title -

international journal of computers communications and control

Language(s) - English

Resource type - Journals

eISSN - 1841-9844

pISSN - 1841-9836

DOI - 10.15837/ijccc.2008.3.2398

Subject(s) - fractal , cluster analysis , fractal analysis , surface roughness , fractal dimension , surface finish , computer science , fuzzy clustering , fuzzy logic , image (mathematics) , artificial intelligence , surface (topology) , image processing , computer vision , data mining , pattern recognition (psychology) , mathematics , materials science , mathematical analysis , geometry , composite material

In this paper the authors describe the results of experiments for surface roughness image acquisition and processing in order to develop an automated rough- ness control system. This implies the finding of a characteristic roughness parameter (for example Ra) on the bases of information contained in the image of the surface. To achieve this goal we use quasi-fractal characteristics and fuzzy clustering meth- ods.

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