Fabric complex texture defect segmentation method based on lightweight semantic segmentation network
Aiming at the problem of textile and garment complex texture surface defect segmentation,the existing automatic detection methods still need to be improved in terms of computational complexity,segmentation accuracy and real-time performance.To solve this problem,a method based on lightweight semantic segmentation network was proposed.The image enhancement technology was used to improve the clarity of the complex texture image of textile and garment,and the salient region extraction method was used to locate the candidate defect area.A lightweight semantic segmentation network was constructed to accurately segment defects by using semantic information.The experimental results show that the proposed method has obvious advantages in terms of average recall area,which proves the efficiency and accuracy of the proposed method in defect segmentation task,and helps to improve product quality and production efficiency.
lightweight semantic segmentation networktextile and clothingcomplex texturessurface defectsimage enhancement technologysalient region extraction
万方数据
维普
