Earticle

초록

영어

In this paper, we propose an intelligent method to extract flaws from nondestructive testing(NDT) images of ceramics. Our goal is to extend the previous study[8]'s feasibility to handle images having skewed brightness distribution or darker images. Thus, we use Gaussian filtering along with anisotropic filtering and sigma fuzzy binarization instead of repetitive binarization used in [8]. These techniques enable us to enhance the brightness contrast successfully so that the usability of our method is extended and verified in experiment. Two phases of image processing - area segmentation and extraction of the defect by searching for labeled pixel to form a defected object by Grassfire algorithm - are explained in detail.

목차

Abstract
 1. Introduction
 2. Area Segmentation by Slope Analysis
  2.1. Image Transform by Ends-in Search Stretching
  2.2. Removing Minute Noise by Anisotropic Mask and Gaussian Filtering
  2.3. Extracting Boundary Line with 7 X 7 Sobel Mask
  2.4. Area Segmentation by Slope Analysis of Boundaries
 3. Extracting the Defect
  3.1. Area Segmentation by Grassfire labeling
  3.2. Extract the Defect by Sigma Fuzzy Binarization
  3.3 Removing Noise with Morphological Information
 4. Experiment and Analysis
 5. Conclusion
 References

키워드

저자

• Kwang Baek Kim [ Department of Computer Engineering, Silla University, Korea ]
• Doo Heon Song [ Department of Computer Games, Yong-in SongDam University, Korea ]
• Won Joo Lee [ Department of Computer Science, Inha Technical College, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605