Line Edge Detection and Characterization in SEM Images Using Wavelets

被引：14

作者：

Sun, Wei ^{[1
]}

Romagnoli, Jose A. ^{[2
]}

Tringe, Joseph W. ^{[3
]}

Letant, Sonia E. ^{[3
]}

Stroeve, Pieter ^{[4
]}

Palazoglu, Ahmet ^{[4
]}

机构：

[1] Beijing Univ Chem Technol, Beijing, Peoples R China

[2] Louisiana State Univ, Cain Dept Chem Engn, Baton Rouge, LA 70803 USA

[3] Lawrence Livermore Natl Lab, Chem Mat Earth & Life Sci Directorate, Livermore, CA 94551 USA

[4] Univ Calif Davis, Dept Chem Engn & Mat Sci, Davis, CA 95616 USA

来源：

IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING | 2009年 / 22卷 / 01期

关键词：

Line edge roughness (LER); scanning electron microscopy (SEM); wavelets; NEURAL-NETWORK; ROUGHNESS; QUANTIFICATION; PHOTORESISTS; INSPECTION; PROFILE; ETCH;

D O I：

10.1109/TSM.2008.2011174

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Edge characterization has become increasingly important in nanotechnology due to the growing demand for precise nanoscale structure fabrication and assembly. Edge detection is often performed by thresholding the spatial information of a top-down image obtained by scanning electron microscopy or other surface characterization techniques. Results are highly dependent on an arbitrary threshold value, which makes it difficult to reveal the nature of the real surface and to compare results among images. In this paper, we present an alternative edge boundary detection technique based on the wavelet framework. Our results indicate that the method facilitates nanoscale edge detection and characterization by providing a systematic threshold determination step.

引用

页码：180 / 187

页数：8

共 16 条

[1] Using wavelets to analyze AFM images of thin films: Surface micelles and supported lipid bilayers [J].