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Effect of orientation of workpiece and filter cut-offs in the surface roughness evaluation using machine vision
Date Issued
01-01-2014
Author(s)
Nammi, Srinagalakshmi
Uppu, Sree Lakshmi
Ramamoorthy, B.
Abstract
In this work, surface roughness of milled surfaces is quantified using digital images obtained by a machine vision system. Images captured are pre-processed for waviness profile elimination using digital filters. The influence of various filters at different cut-offs on the image based surface roughness value 'Ga' is studied in comparison with the conventional surface roughness parameter, 'Ra'. In addition, Grey Level Co-occurrence Matrix (GLCM) is used to determine the image quantification parameters namely contrast, correlation, and energy using the images of machined components arranged in varying orientations in the horizontal plane. The effect of orientation of components on vision parameters is studied. Subsequent improvement in the value of vision roughness parameters obtained before and after the application of filters on these preprocessed digital images is established. All the results are compared with Ra obtained using stylus method and analyzed for the scale, translation, rotation invariance of image based roughness.