지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2020.4
- 수록면
- 3 - 11 (9page)
- DOI
- 10.7584/JKTAPPI.2020.04.52.2.3
이용수
초록· 키워드
오류제보하기
In the printing process, the surface of the outer package printed matter is prone to defects such as chromatic aberration and misting, leading to a defective product. It is necessary to take an effective method to identify and detect surface defects in printed matter. In this paper, the application of machine vision technology in the detection of defects in outer package was studied. Firstly, a machine vision image acquisition device based on charge coupled device (CCD) camera was designed; secondly, the obtained image was processed by graying the average method, then OTSU binarization was performed after denoising by median filtering, and finally an improved differential matching method was designed for defect detection. The example analysis showed that the clear defect image of the outer package could be obtained by using the method proposed in this paper. The detection rate of the method in detecting 2,000 images reached 99.4%, and the average detection time was 103 ms. In the detection of 5,000 images, the detection rate of the manual detection method was 81%, but the detection rate of the method proposed in this paper was 99.1%. The experimental results proved the reliability of the method and provided some theoretical basis for the further application of defect detection technology based on machine vision in the print industry, which was conducive to the good development of the print industry.
목차
ABSTRACT
1. Introduction
2. Materials and Methods
3. Results and Discussion
4. Conclusions
Literature Cited
참고문헌 (13)
참고문헌 신청
Xing, S. Y / 2015 / Research on the inspection and mark on the defects of printed matter based on template matching algorithm / Appl. Mech. Mater. 713-715:377~380
Yuan, X. C / 2015 / An improved Otsu method using the weighted object variance for defect detection / Appl. Surface Sci. 349:472~484
Meng, F / 2018 / Rubber hose surface defect detection system based on machine vision / IOP Conf. Ser.:Earth Environ. Sci. 108:022057
Wang, Y / 2018 / Design of gear defect detection system based on machine vision / IOP Conf. Ser.: Earth Environ. Sci :022025
Min, Y / 2018 / Real time detection system for rail surface defects based on machine vision / EURASIP J. Image and Video Process 2018(1):3
Yuan, X. C / 2015 / An improved Otsu method using the weighted object variance for defect detection / Appl. Surface Sci. 349:472~484
Meng, F / 2018 / Rubber hose surface defect detection system based on machine vision / IOP Conf. Ser.:Earth Environ. Sci. 108:022057
Wang, Y / 2018 / Design of gear defect detection system based on machine vision / IOP Conf. Ser.: Earth Environ. Sci :022025
Min, Y / 2018 / Real time detection system for rail surface defects based on machine vision / EURASIP J. Image and Video Process 2018(1):3
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UCI(KEPA) : I410-ECN-0101-2020-586-000604781