Surface defect detection using adaptive image modeling

Philippe Salembier

doi:10.1117/12.24140

1 September 1990 Surface defect detection using adaptive image modeling

Philippe Salembier

Proceedings Volume 1360, Visual Communications and Image Processing '90: Fifth in a Series; (1990) https://doi.org/10.1117/12.24140
Event: Visual Communications and Image Processing '90, 1990, Lausanne, Switzerland

Abstract

This paper deals with surface defect detection. The approach investigated here attempts to detect grey level as well as texture defects. The defects are regarded as being characterized by abrupt, local and unpredictable changes in an image. On the other hand, a defect-free surface is assumed to be regular and homogeneous, possibly with smooth and slow variation in its features. The detection is based on adaptive image modeling. It is shown that a classical autoregressive model is not really suitable for this detection problem. Then, two modified models are proposed. Their advantage lies in their taking into account the grey level value as well as the texture information.The model adaptation can be stated as a joint optimization problem with constraint. Two different algorithms are defined and tested. The first algorithm performs the adaptation in a recursive way while enforcing the constraint at each step, whereas the second one imposes the constraint only at optimum. The performance of each algorithms is assessed with a statistical test using synthetic images. Finally, it is shown how this adaptive modeling technique can be applied to practical defect detection problems. Several cases are presented and discussed.

Citation Download Citation

Philippe Salembier "Surface defect detection using adaptive image modeling", Proc. SPIE 1360, Visual Communications and Image Processing '90: Fifth in a Series, (1 September 1990); https://doi.org/10.1117/12.24140

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