Special Section on Quality Control by Artificial Vision

Content based segmentation of patterned wafers

[+] Author Affiliations
Pierrick Bourgeat

Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, Tennessee 37831-6011

University of Burgundy, Le2i Laboratory, 12 rue de la fonderie, 71200 Le Creusot, France

Fabrice Meriaudeau

University of Burgundy, Le2i Laboratory, 12 rue de la fonderie, 71200?Le Creusot, France

Kenneth W. Tobin

Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, Tennessee 37831-6011

Patrick Gorria

University of Burgundy, Le2i Laboratory, 12 rue de la fonderie, 71200 Le Creusot, France

J. Electron. Imaging. 13(3), 428-435 (Jul 01, 2004). doi:10.1117/1.1762518
History: Received Aug. 6, 2003; Accepted Feb. 27, 2004; Online July 29, 2004
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We extend our previous work on the image segmentation of electronic structures on patterned wafers to improve the defect detection process on optical inspection tools. Die-to-die wafer inspection is based on the comparison of the same area on two neighboring dies. The dissimilarities between the images are a result of defects in this area of one of the dies. The noise level can vary from one structure to the other, within the same image. Therefore, segmentation is required to create a mask and apply an optimal threshold in each region. Contrast variation on the texture can affect the response of the parameters used for the segmentation. We show a method to anticipate these variations with a limited number of training samples, and modify the classifier accordingly to improve the segmentation results. © 2004 SPIE and IS&T.

© 2004 SPIE and IS&T

Citation

Pierrick Bourgeat ; Fabrice Meriaudeau ; Kenneth W. Tobin and Patrick Gorria
"Content based segmentation of patterned wafers", J. Electron. Imaging. 13(3), 428-435 (Jul 01, 2004). ; http://dx.doi.org/10.1117/1.1762518


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