Surface Defect Recognition of Automobile Subframe Based on Level Set and FLICM
A method the combined with image processing technology is proposed,to meet the bottleneck problems of low detection efficiency and high error rate in automobile mechanical parts.It is due to the characteristics of complex surface structure and differ-ent defects shape to automobile subframe.Firstly,the method of the wavelet neighborhood shrinking and denoising is used to pre-treated the surface image of the vehicle subframe.Secondly,the defect area is located roughly by based on the level set function.Subsequently,the surface defect recognition will be defected further accurately by the spatial fuzzy C-means clustering.The sur-face scratch,indentation and air hole of the workpiece were detected.The experimental results show that the detection rate of this algorithm is 93.3%,86%and 90%respectively compared with the other two algorithms,and it has a high detection success rate.The purpose is to lay a good foundation for subsequent defect classification and meet the requirements of industrial inspection.
Aluminum Alloy CastingDefect DetectionImage ProcessingLevel Set
NETL
NSTL
万方数据
