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一种新颖的微机电系统微结构显微图像三维自动拼接方法 被引量:1

Novel Method for Automatic Three-dimensional Stitching of Microscopic Images of MEMS Microstructure
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摘要 提出一种基于白光垂直扫描显微镜(White-light vertical scanning interference microscopy,WVSIM)的微机电系统(Micro electro mechanical systems,MEMS)微结构三维自动拼接方法,来获得包含完整MEMS信息的大视场、高分辨率的MEMS微结构显微图像,以满足MEMS微结构功能特征分析、评定的需要。通过分析白光垂直扫描显微成像原理,将MEMS微结构显微图像的三维拼接分解为x-y向拼接与z向高度校正。将二维图像配准的尺度不变特征变换特征匹配算法应用到MEMS微结构显微图像的三维拼接中,实现MEMS微结构显微图像的智能、鲁棒三维自动拼接。试验表明,该方法不需要超高精度的硬件,解决了任意形状MEMS微结构显微图像的高精度三维自动拼接问题。横向拼接精度可达0.8μm,纵向拼接精度小于1 nm。 A novel method for automatic three-dimonsional(3D) stitching of microscopic images of micro electro mechanical systems (MEMS) microstructure is proposed. After the microscopic images of MEMS microstructure are captured by white-light vertical scanning interference microscopy(WVSIM), the microscopic image of MEMS microstructure which contains complete information of MEMS microstructure with large field and high resolution is obtained by the proposed method, it could meet the demand of the analysis and evaluation of functional characteristics of MEMS microstructure. By analyzing the principle of WVSIM, the process of 3D stitching microscopic images of MEMS microstructure is decomposed to x-y stitching and height correction. Scale invariant feature transform(SIFT), which is frequently used for 2D image registration, is applied to 3D stitching of microscopic images of MEMS microstructure, so that it is smart and robust. The strict alignment is unnecessary and the problem of the automatic stitching of microscopic images of MEMS microstructure with arbitrary shape with high precision is solved by the method. The experiment result shows that the lateral accuracy could be reached 0.8 ~tn and the vertical accuracy is smaller than lnm.
出处 《机械工程学报》 EI CAS CSCD 北大核心 2013年第18期85-91,共7页 Journal of Mechanical Engineering
基金 国家自然科学基金资助项目(51075169)
关键词 微机电系统微结构 三维自动拼接 白光垂直扫描显微镜 尺度不变特征变换 Micro electro mechanical systems(MEMS) microstructure Automatic three-dimonsional(3D) stitching White-light vertical scanning interference microscopy(WVSIM) Scale invariant feature transform(SIFT)
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