基于视觉词袋法的TFT-LCD缺陷分类

2012 IEEE 6th International Conference on Information and Automation for Sustainability Pub Date : 2012-09-01 DOI:10.1109/ICIAFS.2012.6419899

Wei Huang, Hongtao Lu

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引用次数: 0

摘要

提出了一种基于视觉词袋法的薄膜晶体管液晶显示器缺陷分类算法。引入颜色特征和SIFT特征来描述缺陷区域。视觉词汇是根据每个特征分开学习的。将这两个特征分别编码到视觉词包中，并用多个卡方核支持向量机进行组合。实验中比较了不同参数下分类器的性能。最后得到了一个足够好的分类器，可以识别5类缺陷。

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Defect classification of TFT-LCD with bag of visual words approach

A defect classification algorithm with bag of visual words approach for thin film transistor liquid crystal display (TFT-LCD) manufacturing is proposed in this paper. Color and SIFT features are introduced to describe defect region. Visual words vocabularies are learnt separated for each features. The two features are separately coded in bag of visual words and combined by multiple chi-square kernel SVM. Classifier performances with different parameters are compared in experiments. Finally a good enough classifier for identifying 5 classes of defect is achieved.

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来源期刊

2012 IEEE 6th International Conference on Information and Automation for Sustainability

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