An innovative image-processing model for rust detection using Perlin Noise to simulate oxide textures

作者：Gamarra Acosta Margarita R; Velez Diaz Juan C; Schettini Castro Norelli

来源：Corrosion Science, 2014, 88: 141-151.

DOI：10.1016/j.corsci.2014.07.027

• Modeling studies
• Rust

This article presents an image-processing model for detection of rust zones using digital images of metals. The input image, containing a wide range of possible rusted textures, is simulated with Perlin Noise, which allows simulating extreme corrosion conditions, without waiting for these conditions to occur. Probabilistic descriptors are determined by means of discriminant analysis using Fisher indexes. A Bayesian classifier is used to identify rusted regions. Additionally, performance tests under different noise conditions and texture variations, generated with Perlin Noise, are presented.

• 出版日期2014-11