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Principal component analysis based i...

Zhou, Yi.

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Principal component analysis based image fusion routine with application to stamping split detection.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Principal component analysis based image fusion routine with application to stamping split detection./
Author:	Zhou, Yi.
Description:	165 p.
Notes:	Source: Dissertation Abstracts International, Volume: 71-10, Section: B, page: 6255.
Contained By:	Dissertation Abstracts International71-10B.
Subject:	Automotive engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3419314
ISBN:	9781124191171

Principal component analysis based image fusion routine with application to stamping split detection.
Zhou, Yi.

Principal component analysis based image fusion routine with application to stamping split detection. - 165 p.

Source: Dissertation Abstracts International, Volume: 71-10, Section: B, page: 6255.

Thesis (Ph.D.)--Clemson University, 2010.

This dissertation presents a novel thermal and visible image fusion system with application in online automotive stamping split detection. The thermal vision system scans temperature maps of highly reflective steel panels to locate abnormal temperature readings indicative of high local wrinkling pressure that causes metal splitting. The visible vision system offsets the blurring effect of thermal vision system caused by heat diffusion across the surface through conduction and heat loss to the surroundings through convection. The fusion of thermal and visible images combines two separate physical channels and provides more informative result image than either of the original ones.

ISBN: 9781124191171Subjects--Topical Terms:

2181195
Automotive engineering.

Principal component analysis based image fusion routine with application to stamping split detection.
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020 $a 9781124191171
035 $a (MiAaPQ)AAI3419314
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040 $a MiAaPQ $c MiAaPQ
100 1 $a Zhou, Yi. $3 1928781
245 1 0 $a Principal component analysis based image fusion routine with application to stamping split detection.
300 $a 165 p.
500 $a Source: Dissertation Abstracts International, Volume: 71-10, Section: B, page: 6255.
500 $a Adviser: Mohammed A. Omar.
502 $a Thesis (Ph.D.)--Clemson University, 2010.
520 $a This dissertation presents a novel thermal and visible image fusion system with application in online automotive stamping split detection. The thermal vision system scans temperature maps of highly reflective steel panels to locate abnormal temperature readings indicative of high local wrinkling pressure that causes metal splitting. The visible vision system offsets the blurring effect of thermal vision system caused by heat diffusion across the surface through conduction and heat loss to the surroundings through convection. The fusion of thermal and visible images combines two separate physical channels and provides more informative result image than either of the original ones.
520 $a Principal Component Analysis (PCA) is employed to transform original image to its eigenspace. By retaining the principal components with influencing eigenvalues, PCA keeps the key features in the original image and reduces noise level. Then pixel level image fusion algorithms are developed to fuse original images from the thermal and visible channels, enhance the result image from low level and reduce undesirable noises. Finally, an automatic split detection algorithm is designed and implemented to perform online objective automotive stamping split detection.
520 $a The integrated PCA based image fusion system for stamping split detection is developed and tested on an automotive press line. It is also assessed by online thermal and visible acquisitions and illustrates performance and success. Different splits with variant shape, size and amount are detected under actual operating conditions.
590 $a School code: 0050.
650 4 $a Automotive engineering. $3 2181195
650 4 $a Mechanical engineering. $3 649730
650 4 $a Electrical engineering. $3 649834
690 $a 0540
690 $a 0548
690 $a 0544
710 2 $a Clemson University. $b Mechanical Engineering. $3 1023734
773 0 $t Dissertation Abstracts International $g 71-10B.
790 $a 0050
791 $a Ph.D.
792 $a 2010
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3419314