Abstract The present paper focuses on evaluation of surface roughness (Ra) in incrementally formed parts by different image processing based methods. For this, twenty-seven parts are formed as per full… Click to show full abstract
Abstract The present paper focuses on evaluation of surface roughness (Ra) in incrementally formed parts by different image processing based methods. For this, twenty-seven parts are formed as per full factorial design in incremental forming by varying three important process parameters over three levels each. The surface roughness of formed parts is measured using Taylor Hobson Talysurf and it is in the range of 0.6–3.6 µm. For image processing based evaluation of surface roughness, five images are captured from each formed part and created an image database. These images are classified in to three different classes based on the range of surface roughness using Euclidian distance method, Hamming distance method and Wavelet based method. The results reveal that the wavelet based method has yielded highest classification efficiency of 95.4%. The Hamming and Euclidian distance methods have a classification efficiency of 78.39% and 81.48% respectively.
               
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