• 中文核心期刊要目总览
  • 中国科技核心期刊
  • 中国科学引文数据库(CSCD)
  • 中国科技论文与引文数据库(CSTPCD)
  • 中国学术期刊文摘数据库(CSAD)
  • 中国学术期刊(网络版)(CNKI)
  • 中文科技期刊数据库
  • 万方数据知识服务平台
  • 中国超星期刊域出版平台
  • 国家科技学术期刊开放平台
  • 荷兰文摘与引文数据库(SCOPUS)
  • 日本科学技术振兴机构数据库(JST)

Comprehensive defect detection of bamboo strips with new feature extraction machine vision methods

Comprehensive defect detection of bamboo strips with new feature extraction machine vision methods

  • 摘要: Bamboo strips, as assembling parts of sleeping mats, cushions and other decorative components, play an important role in humans’ everyday life and social economy now. Therefore, quality control for bamboo strips production is very critical. Traditional manual sorting technology owns many disadvantages such as high production cost and low sorting accuracy. This work deals with an automatic sorting system for comprehensive defect detection of bamboo strips based on machine vision. Differing from the present feature extraction methods of the bamboo strip in image processing, contour features considering area and geometrical symmetry and texture feature considering average gradient are newly introduced. An experimental automatic sorting system is designed to verify the feasibility and superiority of the proposed comprehensive defect detection method. Experimental results show that total defect detection accuracy, contour defect detection accuracy, surface texture defect detection accuracy and sorting accuracy reach 99.1%, 98.33%, 95.2% and 95.125%, respectively. The designed sorting system finishes one time sorting in 197 ms with a comparable low-speed computation processor in laboratory and it can be utilized instead of three skilled workers in practice.

     

    Abstract: Bamboo strips, as assembling parts of sleeping mats, cushions and other decorative components, play an important role in humans’ everyday life and social economy now. Therefore, quality control for bamboo strips production is very critical. Traditional manual sorting technology owns many disadvantages such as high production cost and low sorting accuracy. This work deals with an automatic sorting system for comprehensive defect detection of bamboo strips based on machine vision. Differing from the present feature extraction methods of the bamboo strip in image processing, contour features considering area and geometrical symmetry and texture feature considering average gradient are newly introduced. An experimental automatic sorting system is designed to verify the feasibility and superiority of the proposed comprehensive defect detection method. Experimental results show that total defect detection accuracy, contour defect detection accuracy, surface texture defect detection accuracy and sorting accuracy reach 99.1%, 98.33%, 95.2% and 95.125%, respectively. The designed sorting system finishes one time sorting in 197 ms with a comparable low-speed computation processor in laboratory and it can be utilized instead of three skilled workers in practice.

     

/

返回文章
返回