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Measuring Pattern Recognition from Decision Tree and Geometric Data Analysis of Industrial CR Images  

Hwang, Jung-Won (Dept. of Electronics Computer Eng., Hanyang University)
Hwang, Jae-Ho (Dept. of Electronic Eng., Hanbat University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.45, no.5, 2008 , pp. 56-62 More about this Journal
Abstract
This paper proposes the use of decision tree classification for the measuring pattern recognition from industrial Computed Radiography(CR) images used in nondestructive evaluation(NDE) of steel-tubes. It appears that NDE problems are naturally desired to have machine learning techniques identify patterns and their classification. The attributes of decision tree are taken from NDE test procedure. Geometric features, such as radiative angle, gradient and distance, are estimated from the analysis of input image data. These factors are used to make it easy and accurate to classify an input object to one of the pre-specified classes on decision tree. This algerian is to simplify the characterization of NDE results and to facilitate the determination of features. The experimental results verify the usefulness of proposed algorithm.
Keywords
Decision tree; Pattern Recognition; Image Analysis; NDE;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 A. Senior, "A combination fingerprint classifier," IEEE Trans. Pattern Anal. and Machine Intell., Vol. 23, no. 10, pp. 1165-1174, Oct. 2001   DOI   ScienceOn
2 J. H. Hwang and J. W. Hwang, "Image analysis for specific region segmentation of steel-tube radiographic Images," in Proc. of ITC-CSCC 2007, pp. 365-366, Busan, Korea, July 2007
3 황중원, 황재호, "산업용방사선영상의 비선형모델링에 의한 영상복구", 전자공학회논문지 제45권 SP편, 제4호, 71-77쪽, 2008년 7월   과학기술학회마을
4 J. R, Quinlan, "Simplifying decision trees," Int. J. of Human-Computer Studies, Vol. 22, no. 2, pp. 497-510, Aug. 1999
5 H. Y. Kim, "Binary halftone image resolution increasing by decision tree learning," IEEE Trans. Image Processing, Vol. 13, no. 8, pp. 1136-1146, Aug. 2004   DOI   ScienceOn
6 C. E. Priebe, D. J. Marchette and D. M. Healy, "Integrated sensing and processing decision trees," IEEE Trans. Pattern Anal. and Machine Intell., Vol. 26, no. 6, pp. 699-708, June 2004   DOI   ScienceOn
7 P.S Michalski et al(ed), Machine Learning: An Artificial Intelligence Approach Vol. II, Los Altos, Morgan Kaufmann, 1986
8 M. M. Amirfathi, S. Morris, P. O'Rorke, W. E. Bond, and D. C. St. Clair, "Pattern recognition for nondestructive evaluation," in Proc. of Aerospace Applications Conference, pp. 601-611, Feb. 1991
9 R. Kohavi and J. R, Quinlan, Data mining tasks and methods: Classification: decision-tree discovery, Oxford University Press, 2002