Earticle

초록

영어

Biaxially oriented polyester film (BOPET) defect is an important factor affecting the quality of the film. In view of identification of defects in the conventional film production process, this mathod resulted in the identification of defects inaccurate. and low labor efficiency and machine vision recognition on identification of specific defect. This paper presents a LVQ neural network-based BOPET film of defects detection and identification methods. In this algorithm, the film images were processed and the outlines of the membrane defects were obtained. Through extracting the aspect ration, circularity, complexity and elongation , projection histogram central moment and so on, the characteristic values of membrane defects, which from the image of film images after image processing, and then input to the defects recognition system based on LVQ neural network that had been trained, in order to achieve the film defects identification, classification and localization. Through the study of features of the defects in BOPET and extracted some quantities as character input of the LVQ neural network, then input some characteristic values as training value into the LVQ neural network to achieve the learning and prediction purpose, and the LVQ neural network was designed. The experiments show that, the proposed method can meet the requirements analysis of air defects in transparent film.

목차

Abstract
 1. Introduction
 2. BOPET Film Acquisition and Image Processing
 3. BOPET Film Image Preprocessing
  3.1. Denoising
  3.2. Image Segmentation
  3.3. Edge Detection
  3.4. Binary Image Morphological Processing
 4. Defect Feature Extraction and Recognition Algorithm
  4.1. Film Defect Feature Extraction and Recognition
  4.2. LVQ Neural Network Structure Design
 5. Results
 6. Conclusion
 Acknowledgment
 References

키워드

저자

• Bao-yuan Chen [ The higher educational key laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province Harbin University of Science and Technology, Harbin 150080,China ]
• Chao Zheng [ The higher educational key laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province Harbin University of Science and Technology, Harbin 150080,China ]
• Zhong-xiang Sun [ The higher educational key laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province Harbin University of Science and Technology, Harbin 150080,China ]
• Xiao-yang Yu [ The higher educational key laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province Harbin University of Science and Technology, Harbin 150080,China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Future Generation Communication and Networking

• 간기

  격월간

• pISSN

  2233-7857

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605