Automatic TFT-LCD mura defect inspection using discrete cosine transform-based background filtering and 'just noticeable difference' quantification strategies
Automatic TFT-LCD mura defect inspection using discrete cosine transform-based background filtering and 'just noticeable difference' quantification strategies
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DOI：
10.1088/0957-0233/19/1/015507
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发表时间：
2008-01-01
影响因子：
2.4
通讯作者：
Kuo, Chia-Cheng
中科院分区：
文献类型：
--
作者：
Chen, Liang-Chia;Kuo, Chia-Cheng
提出了一种基于离散余弦变换（DCT）原理和背景图像滤波策略的薄膜晶体管液晶显示器（TFT-LCD）Mura缺陷自动检测方法。平板显示器（FPD）面板上的有效且准确的表面缺陷检测在实现FPD制造的高良率方面从未如此重要。由于不均匀的亮度背景以及缺陷区域和背景之间的亮度水平略有不同，检测LCD面板中的斑点-不均匀缺陷可能是困难的。为了克服这一问题，提出了一种基于DCT的背景重建算法，将缺陷与背景图像分离。使用JND定义可以合理地量化不均匀缺陷的显著水平。对含有自然mura缺陷的工业LCD面板进行了评估，开发的方法的实际性能。实验测试结果表明，该算法具有上级性能，能够有效、准确地检测出Mura缺陷。
An innovative mura defect detection methodology for a thin-film transistor liquid crystal display (TFT-LCD) is developed for automatic inspection of mura defects using the discrete cosine transform (DCT) principle and background image filtering strategy. Efficient and accurate surface defect detection on flat panel display (FPD) panels has never been so important in achieving a high yield rate of FPD manufacturing. Detecting blob-mura defects in an LCD panel can be difficult due to non-uniform brightness background and slightly different brightness levels between the defect region and the background. To overcome this problem, a DCT-based background reconstruction algorithm was developed to establish the background image separated from the defects. The significant level of mura defects can be rationally quantified using the just noticeable difference (JND) definition. Actual performance of the developed method was evaluated on industrial LCD panels containing natural mura defects. Results of experimental tests verified that the proposed algorithm has a superior capability for detecting mura defects efficiently and accurately.