On the Evaluation of Texture and Color Features for Nondestructive Corrosion Detection

Abstract

We present a methodology for automatic corrosion detection in digital images of carbon steel storage tanks and pipelines from a petroleum refinery. The database consists of optical digital images taken from equipments exposed to marine atmosphere during their operational life. This new approach focuses on color and texture descriptors to accomplish corroded and noncorroded surface area discrimination. The performance of the proposed corrosion descriptors is evaluated by using Fisher linear discriminant analysis (FLDA). This approach presents two main advantages: No refinery stoppages are required and potential-related catastrophes can be prevented.