DocumentCode
782353
Title
Measuring photolithographic overlay accuracy and critical dimensions by correlating binarized Laplacian of Gaussian convolutions
Author
Nishihara, H. Keith ; Crossley, P.A.
Author_Institution
Schlumberger Palo Alto Res., CA, USA
Volume
10
Issue
1
fYear
1988
fDate
1/1/1988 12:00:00 AM
Firstpage
17
Lastpage
30
Abstract
A technique is described for measuring overlay accuracy and critical dimensions in IC manufacture and similar fields, based on a theory originally developed for matching binocular stereo images. The method uses targets composed of small elements that can be at the minimum feature size of the photolithographic process. Alignment is measured using clusters of those elements rather than the small elements individually. This makes the method insensitive to many of the imaging effects that have plagued other approaches, such as interference fringes and edge topology differences between process steps. The method is tolerant of high noise levels, which allows operation on process layers that produce low-contrast images or high-noise backgrounds as is the case when aligning resist over metal. Adding an appropriate bar grating to the alignment target causes element size changes to induce a proportional shift in alignment, allowing critical dimensions to be measured by the alignment technique
Keywords
Laplace transforms; computer vision; computerised pattern recognition; integrated circuit technology; photolithography; IC manufacture; bar grating; binarized Laplacian of Gaussian convolutions; computer vision; convolution correlation; critical dimensions; edge topology differences; feature matching; interference fringes; low-contrast images; noise tolerance; pattern recognition; photolithographic overlay accuracy; picture element clusters; positioning accuracy measurement; resist alignment; Fabrication; Geometry; Integrated circuit measurements; Interference; Laplace equations; Lithography; Noise level; Printers; Resists; Topology;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.3864
Filename
3864
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