A evaluation of surface roughness classes by computer vision using wavelet transform in the frequency domain View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2012-03

AUTHORS

Patricia Morala-Argüello, Joaquín Barreiro, Enrique Alegre

ABSTRACT

This paper presents a multiresolution method based on the processing of surface images for unmanned visual quality inspection and surface roughness discrimination in turning. Sixteen machining tests were carried out using a constant depth of cut at 1.5 mm and different values for feed rate, in particular 0.15, 0.25, 0.4, and 0.5 mm/rev; cutting speed values were 250, 280, 320, and 350 m/min. With these cutting parameters, the roughness average values achieved covered a significant range between 0.8–14 μm. The methodology proposed is based on the extraction of texture features from part surface images in the frequency domain using wavelet transform. In particular, one-level Haar wavelet transform is applied to the original surface images obtaining four sub-images: a smooth sub-image, a horizontal detail sub-image, a vertical detail sub-image, and a diagonal detail sub-image. These images are used for the extraction of features. Surface evaluation was accomplished by means of the analysis of gray levels in the vertical detail sub-image. Finally, a texture classification was performed by a multilayer Perceptron artificial neural network. Experimental results show that the proposed approach achieves error rates between 2.59% and 4.17%. More... »

PAGES

213-220

References to SciGraph publications

  • 2010-04. Prediction of surface roughness and dimensional deviation of workpiece in turning: a machine vision approach in THE INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • 2010-12. Prediction of surface roughness in turning operations by computer vision using neural network trained by differential evolution algorithm in THE INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • 2010-01. Noncontact roughness measurement of turned parts using machine vision in THE INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • 2002-02. A Study of Computer Vision for Measuring Surface Roughness in the Turning Process in THE INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
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    URI

    http://scigraph.springernature.com/pub.10.1007/s00170-011-3480-6

    DOI

    http://dx.doi.org/10.1007/s00170-011-3480-6

    DIMENSIONS

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