Tool Wear Detection Based on Visual Saliency Mechanism

Abstract

Aiming at the characteristics of tool wear, a method is put forward for rapid detection, Firstly, extracted the tool image gray feature and formed gray feature image; Secondly, approximate sub-graph of three layers wavelet decomposition is treated by center-surround difference operations; On this basis, the significant images is formed by the fusion of feature saliency map. Finally, tool wear is detected through the segmentation method of oust variance and eliminated background texture information by region growing method. The experimental results show that the method can be effectively used in the monitoring of tool wear.