NDLI: An automated method based on Second Order Moment for defect extraction in photomask images

Content Provider	IEEE Xplore Digital Library
Author	Jihee Choi Sheng Yan Hong Jeong
Copyright Year	2009
Description	Author affiliation: Department of EEE, Pohang University of Science and Technology, 790-784, South Korea (Jihee Choi; Sheng Yan; Hong Jeong)
Abstract	In this paper, we present a new and automated technique to extract defects in photomask images. To correctly extract defects, we propose a robust automated method based on Second Order Moment (SOM) between reference and test images and a statistical model based on difference image are used. The statistical model is distribution of the normalized Absolute Difference Value (ADV) between reference and test image that divided by a maximum value of ADV. In our algorithm, the photomask images: transmitted reference, test image pair and reflected images pair are compared and used to get acceptable results. The SOM shows a wide range of selectable threshold values and the statistics model reduces interference element. Together, these methods improve defect extraction. Our proposed algorithm guaranteed accurate extraction of defects.
Starting Page	1015
Ending Page	1018
File Size	2338421
Page Count	4
File Format	PDF
ISBN	9788955191387
ISSN	17389445
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-02-15
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Electronics and Telecommunications Research Institute
Subject Keyword	Glass Data mining Pixel Optical noise Automatic testing Manufacturing processes Image converters Wiener filter Robustness Statistics Defect Extraction Photomask Inspection Second Order Moment
Content Type	Text
Resource Type	Article

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