期刊文献+

扫描电子显微镜图像中粉煤灰珠状颗粒区域的自动提取 被引量:1

Automatic extraction of bead-like particle regions of fly ash in scanning electron microscope images
下载PDF
导出
摘要 针对扫描电子显微镜图像中粉煤灰区域的提取问题,提出了基于区域生长的珠状颗粒区域提取方法。该方法自动选取种子区域,在边界约束下按灰度相似度生长,生长区域结合形状特征提取目标。提取结果比对人工提取区域,提取误差用提取面积的错分率和漏分率之和表示。实验的最小提取误差是6.8%,平均提取误差是8%,自动提取60张SEM图像的时间小于10 min。提取时间和误差均可达到估算粉煤灰含量的要求。 An unsupervised extraction method was proposed in order to extract bead-like particle regions of fly ash from scanning electron microscope image,which was based on region growing with gray similarity bounded by gradient and shape.The process was automatic,including seeds selection,regions growing and shape distinguishing.The experimental error was measured by the acreage probability of missing segmentation and false segmentation.The minimum error rate of the experimental results was 6.8 percent,and the average error rate was 8 percent.The time of extraction from 60 SEM images was within 10 minutes.The method is effective for the content estimation of fly ash in the material.
出处 《计算机应用》 CSCD 北大核心 2012年第6期1570-1573,共4页 journal of Computer Applications
基金 国家自然科学基金资助项目(61070227) 国家自然科学基金-广东联合基金重点项目(U1135003) 973计划项目子课题(2009CB62310504)
关键词 扫描电子显微镜图像 粉煤灰 梯度 区域生长 自动提取 Scanning Electron Microscope(SEM) image fly ash gradient region growing automatic extraction
  • 相关文献

参考文献14

二级参考文献110

共引文献481

同被引文献15

  • 1Xiao Y,Peng XG,Leng M,Zhu B.The research of image collection methodfor sediment online-detection[J].Journal of computes,2010,5(6):893-900.
  • 2Ying X,Bo Y,Dajun Z,et al.Morphology Based Sediment Particle Image Binarization Algorithm Research[C].Computer Science and Electronics Engineering(ICCSEE),2012 International Conference on.IEEE,2012,3:375-378.
  • 3Bayonaá,San Miguel J C,Martínez J M.Stationary foreground detection using background subtraction and temporal difference in video surveillance[C].Image Processing(ICIP),2010 17th IEEE International Conference on.IEEE,2010:4657-4660.
  • 4Hirai J,Yamaguchi T,Harada H.Extraction of moving object based on fast optical flow estimation[C].ICCAS-SICE,2009.IEEE,2009:2691-2695.
  • 5Min H,Huazhong S,Qian L,et al.A study of moving object detection based on combining background profile difference algorithm[C].Industrial and Information Systems(IIS),2010 2nd International Conference on.IEEE,2010,1:425-428.
  • 6彭宣戈,肖英,朱兵,冷明.河流泥沙图像获取系统的研究[J].井冈山大学学报(自然科学版),2010,31(1):77-81. 被引量:1
  • 7朱红求,阳春华,桂卫华,李勇刚.一种带混沌变异的粒子群优化算法[J].计算机科学,2010,37(3):215-217. 被引量:26
  • 8朱兵,周旭艳,彭宣戈,康修洪.基于小波算法的中小河流泥沙含量检测研究[J].井冈山大学学报(自然科学版),2010,31(2):50-55. 被引量:3
  • 9裴胜玉,周永权.一种基于混沌变异的多目标粒子群优化算法[J].山东大学学报(理学版),2010,45(7):18-23. 被引量:2
  • 10匡芳君,徐蔚鸿,王艳华.基于改进分水岭算法的粘连大米图像分割[J].粮食与饲料工业,2010(8):5-8. 被引量:10

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部