Using Pattern Recognition for Self-Localization in Semiconductor Manufacturing Systems
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Using Pattern Recognition for Self-Localization in Semiconductor Manufacturing Systems.
In DAGM-Symposium, 520-527, 2004
Online Version
A pdf version is available for download.
Abstract
In this paper we present a new method for self-localization on wafers using geometric hashing. The proposed technique is robust to image changes induced by process variations, as opposed to the traditional, correlation based methods. Moreover, it eliminates the need in training on reference patterns. Two enhancements are introduced to the basic geometric hashing scheme improving its performance and reliability: using quad tree for efficient data access and optimal rehashing for Bayesian voting. The approach proved to be highly reliable when tested on real wafer images.
Co-authors
Bibtex Entry
@inproceedings{LifshitsGRR04i,
title = {Using Pattern Recognition for Self-Localization in Semiconductor Manufacturing Systems.},
author = {Michael Lifshits and Roman Goldenberg and Ehud Rivlin and Michael Rudzsky},
year = {2004},
booktitle = {DAGM-Symposium},
pages = {520-527},
abstract = {In this paper we present a new method for self-localization on wafers using geometric hashing. The proposed technique is robust to image changes induced by process variations, as opposed to the traditional, correlation based methods. Moreover, it eliminates the need in training on reference patterns. Two enhancements are introduced to the basic geometric hashing scheme improving its performance and reliability: using quad tree for efficient data access and optimal rehashing for Bayesian voting. The approach proved to be highly reliable when tested on real wafer images.}
}