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Adaptive industrial CT outlier detection and accommodation using innovation orthogonal
Zuo Kai, Sun Tongjing, Li Zhenhua, Tao Liang*
School of Control Science and Engineering, Shandong University, Jinan 250061, China

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Abstract�� The problem of defect recognition in industrial CT(computerized tomography) projection image was discussed based on the innovation orthogonality principle. Projection image was modeling in a 2-D state space structure. By analyzing the innovation orthogonality of Kalman filtering algorithm, a dynamic evaluation function and the corresponding threshold on the determination of image region and grey scale were defined respectively. A new adaptive defect recognition method was obtained. Based on 2-D Kalman filter, the proposed method was implemented for defecting image recognition adaptively which can improve the efficiency and accuracy for CT image recognition. An experiment was given to illustrate the effectiveness of the proposed method.
Keywords�� industrial   computerized tomography   Kalman filtering   innovation   orthogonal   image recognition     
Received 2010-03-12;
Fund:

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About author: �� ��(1972-),��,ɽ��̩����,��ʿ��,zuokai@tom.com.
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��, ��ͬ��, ����, ����.������Ϣ�����Ĺ�ҵCTͼ������Ӧȱ��ʶ��[J]  �������պ����ѧѧ��, 2010,V36(9): 1103-1107
Zuo Kai, Sun Tongjing, Li Zhenhua, Tao Liang.Adaptive industrial CT outlier detection and accommodation using innovation orthogonal[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2010,V36(9): 1103-1107
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