Surface Defect Detection on Optical Devices Based on Microscopic Dark-Field Scattering Imaging
文献类型：期刊论文
| 作者 | Yin, Yingjie ; Xu, De; Zhang, Zhengtao; Bai, Mingran; Zhang, Feng; Tao, Xian; Wang, Xingang
|
| 刊名 | STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING
 |
| 出版日期 | 2015 |
| 卷号 | 61期号:1页码:24-32 |
| 关键词 | scale invariance feature transform linear discriminant function cluster algorithm image segmentation image mosaic dark-field imaging optical devices |
| 英文摘要 | Methods of surface defect detection on optical devices are proposed in this paper. First, a series of microscopic dark-field scattering images were collected with a line-scan camera. Translation transformation between overlaps of adjacent microscopic dark-field scattering images resulted from the line-scan camera's imaging feature. An image mosaic algorithm based on scale invariance feature transform (SIFT) is proposed to stitch dark-field images collected by the line-scan camera. SIFT feature matching point-pairs were extracted from regions of interest in the adjacent microscopic dark-field scattering images. The best set of SIFT feature matching point-pairs was obtained via a parallel clustering algorithm: The transformation matrix of the two images was calculated by the best matching point-pair set, and then image stitching was completed through transformation matrix. Secondly, a sample threshold segmentation method was used to segment dark-field images that were previously stitched together because the image background was very dark. Finally, four different supervised learning classifiers are used to classify the defect represented by a six-dimensional feature vector by shape (point or line), and the performance of linear discriminant function (LDF) classifier is demonstrated to be the best. The experimental results showed that defects on optical devices could be detected efficiently by the proposed methods. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Engineering, Mechanical |
| 研究领域[WOS] | Engineering |
| 关键词[WOS] | CLASSIFIER ; RECOGNITION ; SIMULATION ; ROUGHNESS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000348968600002 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/8066]  |
| 专题 | 精密感知与控制研究中心_精密感知与控制 |
| 作者单位 | Chinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yin, Yingjie,Xu, De,Zhang, Zhengtao,et al. Surface Defect Detection on Optical Devices Based on Microscopic Dark-Field Scattering Imaging[J]. STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING,2015,61(1):24-32. |
| APA | Yin, Yingjie.,Xu, De.,Zhang, Zhengtao.,Bai, Mingran.,Zhang, Feng.,...&Wang, Xingang.(2015).Surface Defect Detection on Optical Devices Based on Microscopic Dark-Field Scattering Imaging.STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING,61(1),24-32. |
| MLA | Yin, Yingjie,et al."Surface Defect Detection on Optical Devices Based on Microscopic Dark-Field Scattering Imaging".STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING 61.1(2015):24-32. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。