Spindle-deviation minimization method for classification in NDE system

Z. D. Jiang; F. Tong; B. L. Luk; K. P. Liu

doi:10.1109/CISP.2008.31

Spindle-deviation minimization method for classification in NDE system

Z. D. Jiang, F. Tong, B. L. Luk, K. P. Liu

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

Various feature extraction methods are developed in non-destructive evaluation (NDE). Among many linear methods been proposed, the Fisher linear discriminant is a very useful technique. But as the mean square error (MSE) increased, a classifier based on Fisher criterion will reduce the efficiency. In this paper, we expand the criterion and develop a spindle-deviation minimization (SDM) method to solve the classification problem. A comparison on global solution based on Fisher criterion with our method will be given, and it shows our method has good performance. Also, the results on our impact acoustic NDE system will verify the method efficient further. © 2008 IEEE.

Original language	English
Title of host publication	Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008
Pages	528-530
Volume	5
DOIs	https://doi.org/10.1109/CISP.2008.31
Publication status	Published - 2008
Event	1st International Congress on Image and Signal Processing, CISP 2008 - Sanya, Hainan, China Duration: 27 May 2008 → 30 May 2008

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Volume	5

Conference

Conference	1st International Congress on Image and Signal Processing, CISP 2008
Place	China
City	Sanya, Hainan
Period	27/05/08 → 30/05/08

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@inproceedings{3dabbdda55904300b089a9522ba2ecdb,

title = "Spindle-deviation minimization method for classification in NDE system",

abstract = "Various feature extraction methods are developed in non-destructive evaluation (NDE). Among many linear methods been proposed, the Fisher linear discriminant is a very useful technique. But as the mean square error (MSE) increased, a classifier based on Fisher criterion will reduce the efficiency. In this paper, we expand the criterion and develop a spindle-deviation minimization (SDM) method to solve the classification problem. A comparison on global solution based on Fisher criterion with our method will be given, and it shows our method has good performance. Also, the results on our impact acoustic NDE system will verify the method efficient further. {\textcopyright} 2008 IEEE.",

author = "Jiang, {Z. D.} and F. Tong and Luk, {B. L.} and Liu, {K. P.}",

year = "2008",

doi = "10.1109/CISP.2008.31",

language = "English",

isbn = "9780769531199",

volume = "5",

pages = "528--530",

booktitle = "Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008",

note = "1st International Congress on Image and Signal Processing, CISP 2008 ; Conference date: 27-05-2008 Through 30-05-2008",

}

Jiang, ZD, Tong, F, Luk, BL & Liu, KP 2008, Spindle-deviation minimization method for classification in NDE system. in Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008. vol. 5, 4566884, pp. 528-530, 1st International Congress on Image and Signal Processing, CISP 2008, Sanya, Hainan, China, 27/05/08. https://doi.org/10.1109/CISP.2008.31

Spindle-deviation minimization method for classification in NDE system. / Jiang, Z. D.; Tong, F.; Luk, B. L. et al.
Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008. Vol. 5 2008. p. 528-530 4566884.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Spindle-deviation minimization method for classification in NDE system

AU - Jiang, Z. D.

AU - Tong, F.

AU - Luk, B. L.

AU - Liu, K. P.

PY - 2008

Y1 - 2008

N2 - Various feature extraction methods are developed in non-destructive evaluation (NDE). Among many linear methods been proposed, the Fisher linear discriminant is a very useful technique. But as the mean square error (MSE) increased, a classifier based on Fisher criterion will reduce the efficiency. In this paper, we expand the criterion and develop a spindle-deviation minimization (SDM) method to solve the classification problem. A comparison on global solution based on Fisher criterion with our method will be given, and it shows our method has good performance. Also, the results on our impact acoustic NDE system will verify the method efficient further. © 2008 IEEE.

AB - Various feature extraction methods are developed in non-destructive evaluation (NDE). Among many linear methods been proposed, the Fisher linear discriminant is a very useful technique. But as the mean square error (MSE) increased, a classifier based on Fisher criterion will reduce the efficiency. In this paper, we expand the criterion and develop a spindle-deviation minimization (SDM) method to solve the classification problem. A comparison on global solution based on Fisher criterion with our method will be given, and it shows our method has good performance. Also, the results on our impact acoustic NDE system will verify the method efficient further. © 2008 IEEE.

UR - http://www.scopus.com/inward/record.url?scp=51849138283&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-51849138283&origin=recordpage

U2 - 10.1109/CISP.2008.31

DO - 10.1109/CISP.2008.31

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9780769531199

VL - 5

SP - 528

EP - 530

BT - Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008

T2 - 1st International Congress on Image and Signal Processing, CISP 2008

Y2 - 27 May 2008 through 30 May 2008

ER -

Spindle-deviation minimization method for classification in NDE system

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