Bearing surface defect detection based on context-aware saliency

Aimed at the problem of bearing surface defect detection, a method based on context-aware saliency detection is proposed. Firstly, the image of bearing surface defects was preprocessed, and homomorphic filtering method was used to weaken the influence of uneven illumination and environment. Then, the saliency of the defect area was enhanced by the context-aware visual saliency detection method, and a saliency map highlighting the defect area was generated. Finally, Otsu method was used to segment the defect of saliency map, and the defect detection results were obtained. The results showed that the context-aware saliency detection method can accurately detect all kinds of defects on the bearing surface, and has better precision and recall than other significant detection methods.