期刊
APPLIED SOFT COMPUTING
卷 52, 期 -, 页码 348-358出版社
ELSEVIER
DOI: 10.1016/j.asoc.2016.10.030
关键词
Mobile phone screen glass; Defect detection; Contour-based registration; Image subtraction; Fuzzy c-means cluster
资金
- National Natural Science Foundation of China [51275093, 51675106]
- Guangdong Provincial Natural Science Foundation [2015A030312008]
- Guangdong Provincial RD Key Projects [2015B010104008, 2016A030308016]
Defect detection using machine vision technology plays an important role in the manufacturing process of mobile phone screen glass (MPSG). This study proposes an improved detection algorithm for MPSG defect recognition and segmentation. Considering the problem of MPSG image misalignment caused by vibrations in the mobile stages, a contour-based registration (CR) method is used to generate the template image used to align the MPSG images. Based on this registration result, the combination of subtraction and projection (CSP) is used to identify defects on the MPSG image, which can eliminate the influence of fluctuation in ambient illumination. To segment the defects with a fuzzy grey boundary from a noisy MPSG image, an improved fuzzy c-means cluster (IFCM) algorithm is developed in this study. A defect detection system is developed, and the proposed algorithms are validated using a number of experimental tests on MPSG images. The testing results demonstrate that the approach proposed in this study can effectively detect various defects on MPSG and that it has better performance than other methods. (C) 2016 Elsevier B.V. All rights reserved.
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