Abstract
In-situ crevice corrosion images of U75V high-speed rail steel samples before and after heat treatment for microstructure refinement were obtained by a self-developed monitoring device, and facile image processing techniques have been developed. Gray value and entropy have been demonstrated to be the significant parameters able to describe the process of crevice corrosion. Gray value has been found to have good correlation with corrosion depth, and distribution of column average gray value can be applied to obtain corrosion depth profiles along crevice depth. Gray histogram is a good indicator to distinguish local preferential dissolution and uniform dissolution via deviation from original peak position and valley height. Entropy means uncertainty of how corrosion patterns develop. Its increase indicates high activity for change of corrosion patterns, while low activity leads to cease of increase. When metal surface has been corroded extensively, entropy will decrease, indicating less potential routes for development of corrosion patterns. This work has provided new ideas on the application of image processing on corrosion study.
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