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Proceedings Paper

Quantification of line mura defect levels based on multiple characterizing features
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Paper Abstract

Recently, with an increasing FPD market, automatic detection of the mura in the manufacturing process has become a critical issue for manufactures interested in increasing their TFT-LCD quality. But segmentation based detection algorithms deviate from human visual perception model. To supplement the detection error produced by deviation, the mura is re-inspected through a visual inspection during manufacturing process. If we could objectively quantify each mura's defect degree, then based on some threshold of defect degree, we could reduce the number of re-inspection. We call this degree line muras defect level. Our approach is an attempt to quantify the ideal defect level of line mura, that for each individual could vary because of subjectivity, based on multiple features crucial in the detection of line mura. In the process, we approximated what we call JND surface that passes through the middle of feature points with mean mura visibility of 0.5. Then Index function, which measures distance from JND surface, is employed to measure the objective defect level of each candidate mura.

Paper Details

Date Published: 18 January 2006
PDF: 8 pages
Proc. SPIE 6066, Vision Geometry XIV, 606603 (18 January 2006); doi: 10.1117/12.642828
Show Author Affiliations
No K. Park, Seoul National Univ. (South Korea)
Kyu N. Choi, Seoul National Univ. (South Korea)
Suk I. Yoo, Seoul National Univ. (South Korea)

Published in SPIE Proceedings Vol. 6066:
Vision Geometry XIV
Longin Jan Latecki; David M. Mount; Angela Y. Wu, Editor(s)

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