Improved image analysis based corrosion assessment using preprocessing techniques

The importance of non-destructive techniques (NDT) in structural health monitoring programmes isbeing critically felt in the recent times. The quality of the measured data, often affected by variousenvironmental conditions can be a guiding factor in terms usefulness and prediction efficiencies ofthe various detection and monitoring methods used in this regard. Often, a preprocessing of theacquired data in relation to the affecting environmental parameters can improve the informationquality and lead towards a significantly more efficient and correct prediction process. Theimprovement can be directly related to the final decision making policy about a structure or anetwork of structures and is compatible with general probabilistic frameworks of such assessmentand decision making programmes. This paper considers a preprocessing technique employed foran image analysis based structural health monitoring methodology to identify sub-marine pittingcorrosion in the presence of variable luminosity, contrast and noise affecting the quality of images.A preprocessing of the gray-level threshold of the various images is observed to bring about asignificant improvement in terms of damage detection as compared to an automatically computedgray-level threshold. The case dependent adjustments of the threshold enable to obtain the bestpossible information from an existing image. The corresponding improvements are observed in aqualitative manner in the present study