Abstract
Corrosion phenomena are usually difficult to recognize without a deep knowledge of the electrochemical properties of materials, this creates difficulties in the analysis of corrosion in practice, control measures are developed through image processing to solve these problems. This article describes a methodology for the analysis of the inner surface of steam pipelines by means of digital image processing (DIP). A classification algorithm is presented that is able to detect four levels of corrosion on the inner surface of steam pipelines. Gray-level co-occurrence matrix GLCM, which analyzes all the attributes of each image texture was employed. The performance of the classification algorithm was evaluated by using a confusion matrix, which showed very reliable classification results by comparing with experimental tests.
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