Binarization Method for On-Line Ferrograph Image Based on Uniform Curvelet Transformation

Through real-time acquisition of visual characteristics of wear debris in lube oil, OLVF achieves on-line monitoring of equipment wear in practice. However, since a large number of bubbles exist in lube oil, which appear as a dynamically changing interference shadow in OLVF ferrograms, the traditional algorithms may easily misidentify the interference shadow as wear debris, resulting in a large error in the extracted wear debris characteristic. Based on this, an UDCT-based method for binarization of wear debris images was proposed. Through multi-scale analysis of OLVF ferrogram using UDCT and non-linear transformation of UDCT coefficients, low frequency suppression and high-frequency denoising of wear debris images were conducted. Then, Otsu algorithm was used to realize binarization of wear debris images under strong interferences.