Paper
9 February 2006 Automatic mura detection system for liquid crystal display panels
Li-Te Fang, Hsin-Chia Chen, I-Chieh Yin, Sheng-Jyh Wang, Chao-Hua Wen, Cheng-Hang Kuo
Author Affiliations +
Proceedings Volume 6070, Machine Vision Applications in Industrial Inspection XIV; 60700G (2006) https://doi.org/10.1117/12.650686
Event: Electronic Imaging 2006, 2006, San Jose, California, United States
Abstract
In this paper, we propose an automatic inspection system, which can automatically detect four types of muras on an LCD panel: cluster mura, v-band mura, rubbing mura, and light leakage mura. To detect cluster muras, the Laplacian of Gaussian (LOG) filter is used. A multi-resolution approach is proposed to detect cluster muras of different scales. To speed up the processing speed, this multi-resolution approach is actually implemented in the frequency domain. To detect v-band muras, we check the variation tendency of the projected 1-D intensity profile. Then, v-band muras are detected by identifying these portions of the 1-D profile where a large deviation occurs. To detect rubbing muras, we designed a frequency mask to detect distinct components in the frequency domain. To detect light leak muras, we apply image mirroring over the boundary parts and adopt the same LOG filter that has been used in detecting cluster muras. All four types of mura detection are integrated together in an efficient way and simulation results demonstrate that this system is indeed very helpful in detecting mura defects.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Li-Te Fang, Hsin-Chia Chen, I-Chieh Yin, Sheng-Jyh Wang, Chao-Hua Wen, and Cheng-Hang Kuo "Automatic mura detection system for liquid crystal display panels", Proc. SPIE 6070, Machine Vision Applications in Industrial Inspection XIV, 60700G (9 February 2006); https://doi.org/10.1117/12.650686
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Cited by 5 scholarly publications.
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KEYWORDS
Inspection

Electronic filtering

LCDs

V band

Convolution

Fourier transforms

Detection and tracking algorithms

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