Defect Detection of Workpiece Surface Based on Improved SSD
The surface defects of the workpiece not only affect the appearance,but also affect the quality,life and performance of the product directly.Therefore it is necessary to carry out real-time surface defects detection of the workpiece.Aiming at the problems that current SSD algorithm was not suitable for small target detection,which was easy to result and error,an improved SSD automatic detection method based on single-stage multi-layer detector was proposed.The original VGGNet was replaced by ResNet in SSD.The question about small target detection was researched.By using the method of deconvolution of deep features and combine of deep features and shallow features,the problem that the semantic information which was insufficient and easy to be misdetected was studied.The results show that the mAP value of surface defect detection can be improved by the proposed method about 4.6%compared with the original SSD model.The method proposed can be used for real-time automatic detection of surface defect of the workpiece.
NETL
NSTL
万方数据
