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Proceedings Paper

Nonlinear adaptive edge-detection techniques for wafer inspection and alignment
Author(s): Scott C. Douglas; Teresa H.-Y. Meng; Roger Fabian W. Pease
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Paper Abstract

In this paper we present a class of nonlinear adaptive filtering schemes to detect edges to the nearest pixel in digital images. These one- or two-dimensional filters are adapted by training to a subset of image data to produce peaked output at user-specified edge locations within the image. A nonlinear adaptive algorithm has been developed and has shown improved performance over standard cross correlation schemes in binary classification situations. The resulting filters are then applied non-adaptively to the entire image set, and signal peaks within the image are detected to produce a binary edge map. A short theoretical development of the algorithm is given, and results for images representative of harsh alignment conditions are presented.

Paper Details

Date Published: 1 June 1990
PDF: 9 pages
Proc. SPIE 1261, Integrated Circuit Metrology, Inspection, and Process Control IV, (1 June 1990); doi: 10.1117/12.20041
Show Author Affiliations
Scott C. Douglas, Stanford Univ. (United States)
Teresa H.-Y. Meng, Stanford Univ. (United States)
Roger Fabian W. Pease, Stanford Univ. (United States)

Published in SPIE Proceedings Vol. 1261:
Integrated Circuit Metrology, Inspection, and Process Control IV
William H. Arnold, Editor(s)

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