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Proceedings Paper

Pattern recognition for MEMS images of surface topography using wavelets
Author(s): Kai Hu; Xiangqian Jiang
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Paper Abstract

Micro-Electro-Mechanical Systems (MEMS) have been growing in interest in recent years. Due to the small size of the MEMS, the traditional method of metrology measurement seriously affects the parameter of the object being measured, and high accuracy metrology cannot be acquired. MEMS microstructure images of surface are most composed of a number of steps, grooves and slots. Pattern analysis and recognition of these microstructures with linear feature is one of the key problems in metrology and testing technology of Micro-Electro-Mechanical-System (MEMS). Effective detections of these components play an important role in simplifying feature model in pattern recognition and pattern match. Traditional Linear feature detectors based on pixel processing each by each may fail to detect out lines in image with low SNR. A fast discrete beamlet transform and a novel method of linear feature detection are proposed, which can detect lines with any orientation, location and length. Experiment results prove the efficiency of the method proposed even in image with very low SNR.

Paper Details

Date Published: 14 November 2007
PDF: 5 pages
Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67905B (14 November 2007); doi: 10.1117/12.751026
Show Author Affiliations
Kai Hu, Huazhong Univ. of Science and Technology (China)
Xiangqian Jiang, Huazhong Univ. of Science and Technology (China)
Univ. of Huddersfield (United Kingdom)


Published in SPIE Proceedings Vol. 6790:
MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications

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