Home // ICAS 2018, The Fourteenth International Conference on Autonomic and Autonomous Systems // View article
Authors:
Du-Ming Tsai
Yan-Hsin Tseng
S. K. Morris Fan
Keywords: defect detection; automated visual inspection; TFT-LCD; fourier transform
Abstract:
Flat-panel displays have become increasingly important in recent years for use in handheld devices and video monitors. In this paper, we have considered the problem of detecting micro defects including pinholes, particles and scratches in patterned Thin Film Transistor-Liquid Crystal Display (TFT-LCD) surfaces. The proposed method is based on a global image reconstruction scheme using the Fourier transform. A typical TFT-LCD panel consists of orthogonal gate lines and data lines with TFTs in each intersection of the lines, which result in a structural texture with repetitive patterns. By eliminating the frequency components associated with the structural pattern of data lines, gate lines and TFTs, and back-transforming the Fourier domain image, the reconstructed image can effectively remove the background pattern and distinctly preserve anomalies. A simple adaptive thresholding is then used to segment the defective regions from the uniform background in the filtered image. Experimental results have shown that the proposed method can successively detect and locate various ill-defined defects in a TFT-LCD panel without designing and measuring the quantitative features of individual defect types.
Pages: 13 to 18
Copyright: Copyright (c) IARIA, 2018
Publication date: May 20, 2018
Published in: conference
ISSN: 2308-3913
ISBN: 978-1-61208-634-7
Location: Nice, France
Dates: from May 20, 2018 to May 24, 2018