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  • 中国标准连:ISSN1005-2895
  • 续出版物号: CN 33-1180/TH
  • 主管单位:轻工业杭州机电设计研究院有限公司
  • 主办单位:轻工业杭州机电设计研究院有限公司、中国轻工机械协会、中国轻工业机械总公司
  • 社  长:刘安江
  • 主  编:黄丽珍
  • 地  址:杭州市余杭区高教路970号西溪联合科技广场4-711
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汤锋, 张团善, 黄乾玮, 李乐乐.基于显著性检测和超像素分割的本色织物疵点检测系统[J].轻工机械,2021,39(6):65-69
基于显著性检测和超像素分割的本色织物疵点检测系统
Detection System for Grey Fabric Defects Based on Saliency Detection and Superpixel Segmentation
  
DOI:10.3969/j.issn.1005 2895.2021.06.010
中文关键词:  疵点检测  本色织物  显著性  超像素分割
英文关键词:defect detection  grey cloth  saliency  superpixel segmentation
基金项目:
作者单位
汤锋, 张团善, 黄乾玮, 李乐乐 西安工程大学 陕西省智能纺织装备研究院 陕西 西安710048 
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中文摘要:
      针对本色织物生产过程中出现的断经、断纬、污渍、擦伤和破洞等表面缺陷,课题组设计了一种基于显著性检测和超像素分割的本色织物疵点检测系统。课题组首先对输入的图像进行双边滤波,保持图像边缘的同时去除织物纹理;然后将图像分成n×n个大小相同的图像块,对每个图像块使用基于全局对比度的图像显著性检测生成显著图;再对整张粗定位显著图进行超像素精细分割,以及二值化和图像形态学处理剔除孤立点,定位出疵点区域。实验结果表明:与3种常见的显著性检测算法相比,新系统对本色织物疵点检测的准确率更高,时间更短且疵点轮廓的分割更精确。
英文摘要:
      In view of the surface defects such as broken warp, broken weft, stains, scratches and holes in the production process of natural fabric, a detection system of natural fabric defects based on saliency detection and super pixel segmentation was designed.First,bilateral filtering was used for the input image to keep the image edge and remove the fabric texture;then,the image was divided into n×n image block with the same size based on the global contrast of image significant testing generates significant figure; again,the entire coarse positioning significant figure was eliminated isolated point positioning the defect area, by pixel fine segmentation, and binarization and morphological image processing.The experimental results show that compared with the three common saliency detection algorithms, new system has higher accuracy, shorter time and more accurate segmentation of the defect contour of this color cloth.
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