An Improved Fabric Defect Detection Method Based on SSD

The fabric defect detection algorithm based on object detection has become a research hotspot. The method based on the Single Shot MultiBox Detector (SSD) model has a fast detection speed, but the detection accuracy is insufficient. To balance the detection speed and accuracy of the model and meet the actual needs of the industry, an improved fabric defect detection algorithm based on SSD is proposed in this study. The Fully Convolutional Squeeze-and-Excitation (FCSE) block is added into the traditional SSD to improve the detection accuracy of the model. The number of default boxes was adjusted to accommodate the detection of long strip defects on fabric surface. Experimental results on the TILDA and Xuelang dataset confirm that our detection method based on SSD efficiently detected various fabric defects.

Automated summary

This study proposes an improved fabric defect detection algorithm based on SSD, which enhances detection accuracy by adding FCSE blocks and adjusting the number of default boxes. Experimental results confirm the effectiveness of this method in detecting various fabric defects.