This paper introduces a novel method for the quality evaluation of resistance spot welds. The evaluation is based on computer vision methods, which allow nondestructive on-line real-time processing. The input of the system is the image of a weld imprint on a metal band which covers the electrodes against wear and soiling. In order to find the position of the resistance spot welds, we describe an image registration method based on geometric pattern matching for alignment system in metal parts. Further we extract features describing the shape of localized objects in segmented images .Using these shape descriptors (geometric feature) we classify the defects by Artificial Neural Network.
목차
Abstract 1. Introduction 2. SYSTEM OVERVIEW AND RELATED WORK 3. EXPERIMENTAL METHODOLOGY 3.1 The Resistance Spot Welding Location 3.2 Segmentation of the Electrode Imprint 3.3 Image Features Extraction 4. AUTOMATIC CLASSIFICATION METHOD TO THE DEFECTS 4.1 Classification of Defects using ANN 4.2 Results 5. Conclusion and discussion ACKNOWLEDGEMENTS References
키워드
Artificial Neural Networkspot weldcomputer visionImage features extractionimage Segmentation.
저자
Yang ou [ Department of Applied Computer Engineering, Shenzhen Polytechnic, key laboratory of optoelectronic devices and system of ministry of education and Guangdong province, School of Information Engineering Changan University ]
Li yueping [ Department of Applied Computer Engineering, Shenzhen Polytechnic ]
보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Signal Processing, Image Processing and Pattern Recognition
간기
격월간
pISSN
2005-4254
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.8 No.5