Authors: Ioannis G. Mariolis, Evangelos S. Dermatas
Addresses: Department of Electrical Engineering and Computer Technology, University of Patras, 26500, Patras, Greece. ' Department of Electrical Engineering and Computer Technology, University of Patras, 26500, Patras, Greece
Abstract: A novel method performing automatic seam quality control based on visual information is introduced. More specifically, oblique illumination is applied and greyscale images of seam specimens are acquired. The amount of shadowing present in each image is being estimated through dynamic thresholding and first order statistics and is used by a simple linear classifier to estimate the seam quality by means of ordinary least squares (OLS) regression. The proposed method has been evaluated in the case of 112 seam specimens classified by human experts into five discrete quality grades and a correct classification rate of 84.82% has been produced exceeding the experts| average performance. Moreover, in case one grade disagreement is acceptable, the classification results become error free.
Keywords: seam quality; seam puckering; machine vision; shadow detection; regression; quality control; clothing industry; apparel industry; garment industry.
International Journal of Computer Aided Engineering and Technology, 2009 Vol.1 No.2, pp.225 - 238
Published online: 26 Jan 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article