Earticle

초록

영어

Nondestructive Testing (NDT) is appropriate for ceramic materials but the image may contain cracks, spiracles, and other foreign substances to form various defects on the surface. Such subtle defects are often neglected on manual visual inspection and it also causes inspector subjectivity problem thus we need am automated computational method to solve the problem. In this paper, we propose a fuzzy logic based method to detect such various defects from the surface of ceramic material. In our method, we first apply fuzzy stretching to enhance the brightness contrast from the input image. Then the fuzzy binarization and upper/lower level search algorithm finds the interval range of defects' existence. Finally ART2 learning algorithm determines different types of defects. The novelty of this paper is avoiding segmentation-identification paradigm and apply simpler image processing technique with fuzzy logic and neural learning in defect identification. In experiment, the proposed method successfully detects poor fusing and tungsten defects.

목차

Abstract
 1. Introduction
 2. Fuzzy Stretching for Enhancing Image Brightness Contrast
 3. Finding Defective Area
 4. Defect Detection
 5. Experiment and Analysis
 6. Conclusion
 References

키워드

저자

• Kwang Baek Kim [ Dept. of Computer Engineering, Silla University, 140 Baegyang-daero(Blvd) 700 beon-gil(Rd), Sasang-gu, Busan 617-736, Korea, Dept. of Computer Games, Yong-In SongDam College, Yongin 449-040, Korea ]
• Doo Heon Song [ Dept. of Computer Engineering, Silla University, 140 Baegyang-daero(Blvd) 700 beon-gil(Rd), Sasang-gu, Busan 617-736, Korea, Dept. of Computer Games, Yong-In SongDam College, Yongin 449-040, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605