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Proceedings Paper

Alignment mark detection using signed-contrast gradient edge maps
Author(s): John Raymond Jordan
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Paper Abstract

Fast, accurate alignment plays an important role in microelectronics manufacturing. As a result, the automation of alignment mark detection via image processing algorithms has been widely investigated. Algorithms for automatic alignment mark detection traditionally fall into one of two classes -- correlation-based or contour-based. Despite considerable success in these investigations, current algorithms are often time-consuming and sensitive to changes in illumination and rotation. In this paper, a novel algorithm for detecting alignment marks in grey-level images is presented. The fundamental advantage of this algorithm is the use of signed-contrast gradient edge maps, which represent intensity edges in terms of locally normalized intensity gradients. Appropriate use of these signed-contrast gradient edge maps yields alignment mark detection which is faster and more robust than traditional methods such as normalized cross-correlation. The efficacy of this algorithm is demonstrated by applying it to the automatic detection and location of alignment marks for semiconductor wafer alignment and directly comparing its performance against that of normalized cross-correlation in terms of accuracy, invariance to changes in mark rotation, and algorithm speed.

Paper Details

Date Published: 1 August 1992
PDF: 12 pages
Proc. SPIE 1661, Machine Vision Applications in Character Recognition and Industrial Inspection, (1 August 1992); doi: 10.1117/12.130304
Show Author Affiliations
John Raymond Jordan, Insystems (United States)


Published in SPIE Proceedings Vol. 1661:
Machine Vision Applications in Character Recognition and Industrial Inspection
Donald P. D'Amato; Wolf-Ekkehard Blanz; Byron E. Dom; Sargur N. Srihari, Editor(s)

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