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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/51624


    Title: DEFECT CLASSIFICATION FOR LCD COLOR FILTERS USING NEURAL-NETWORK DECISION TREE CLASSIFIER
    Authors: Tseng,DC;Chung,IL;Tsai,PL;Chou,CM
    Contributors: 資訊工程學系
    Keywords: INDEPENDENT COMPONENT ANALYSIS;RECOGNITION;SURFACES;MACHINE
    Date: 2011
    Issue Date: 2012-03-27 18:57:45 (UTC+8)
    Publisher: 國立中央大學
    Abstract: A real-time automatic defect classification scheme is proposed to understand the situation of color-filter production procedure by analyzing the defect types. The proposed system consists of three stages: defect extraction, feature description, and defect-type classification. A reflex-lighted image and the same-area back-lighted image are both used for the defect classification. Four features extracted from the reflex-lighted images describe the shape of the defects and other four features extracted from the back-lighted images describe the appearance of the defects on the color-filter cells. A neural-network decision tree classifier is then designed for classifying the defect types. The neural network has the ability to analyze the complicated non-linear relationship between input signals and the desired outputs. A back propagation algorithm is used as the training method for the proposed classifier. The experimental results show that the proposed scheme can efficiently classify the defect types and the proposed neural-network classifier is superior to other classifiers.
    Relation: INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL
    Appears in Collections:[資訊工程學系] 期刊論文

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