On-line seam detection in rolling processes using snake projection and discrete wavelet transform

This paper proposes an on-line quality inspection method to detect seam, a major type of surface defect generated in rolling processes. A feature-preserving snake-projection procedure is first adopted to convert the images of suspect seams to one-dimensional sequences. Discrete Wavelet Transform is then performed on the derived sequences with features extracted from wavelet coefficients. Finally, T ² control chart is established to discriminate between real seams and false positives. Minimization of the discrimination error based on training data is also presented with illustrations. On-line implementation of the proposed method shows that it satisfies the requirements of both detection accuracy and detection speed.