Infrared thermography is a nondestructive evaluation method with an increasing span of applications. In this paper the pixel-level image fusion of infrared light and visible light image for infrared thermography and its application in nondestructive testing (NDT) of pressure vessel are studied. First in the image fusion, different mode image registration has been done based on feature corners. The corners and curves relative to each corner are extracted using the curvature scale space method. A new shape context descriptor for each corner is computed as the criterion to match the corners. Marks can then be added to pick up the corners, especially if there are no distinct matching feature corners between the different mode images. Two fusion methods, contrast modulation and transparent fusion, are introduced to fuse the visual and infrared light images. The experimental results show that the methods are good for pixel-level image fusion. Finally the method is applied to inspection of pressure vessel. The research indicates that image fusion for infrared thermography can facilitate defect location and interpretation of inspection results.

Issue Section:
Nde
Keywords:
infrared thermography, image fusion, registration, curvature scale space, shape context descriptor, image fusion, image registration, infrared imaging, mechanical engineering computing, nondestructive testing, pressure vessels
Topics:
Corners (Structural elements), Image registration, Inspection, Nondestructive evaluation, Pressure vessels, Shapes, Thermography, Transparency, Infrared radiation
1.
Ibarra-Castanedo
,
C.
,
Galmiche
,
F.
,
Darabi
,
A.
,
Pilla
,
M.
,
Klein
,
M.
,
Ziadi
,
A.
,
Vallerand
,
S.
,
Pelletier
,
J. -F.
, and
Maldague
,
X. P.
, 2003, “
Thermographic Nondestructive Evaluation: Overview of Recent Progress
,” Thermosense XXV,
Proceedings of the Society of Photo-Optical Instrumentation Engineers
,
K. E.
Cramer
 and
X. P.
Maldague
, eds., pp.
450
–
459
.
2.
Gros
,
X. E.
,
Strachan
,
P.
,
Lowden
,
D. W.
, and
Edwards
,
I.
, 1994, “
NDT Data Fusion
,”
Proceedings of the Sixth European Conference on NDT
, Nice, France.
3.
Avdelidis
,
N. P.
,
Delegou
,
E. T.
,
Almond
,
D. P.
, and
Moropoulou
,
A.
, 2004, “
Surface Roughness Evaluation of Marble by 3D Laser Profilometry and Pulsed Thermography
,”
NDT & E Int.
,
37
(
7
), pp.
571
–
575
. 0963-8695
Crossref
Search ADS
 
4.
Gros
,
X. E.
, 1997, “
A Review of NDT Data Fusion Processes and Applications
,”
Insight
,
39
(
9
), pp.
652
–
657
. 1060-135X
5.
Dessendre
,
M.
,
Thevenot
,
F.
,
Liot
,
A.
,
Tretout
,
H.
, and
Exmelin
,
A.
, 1997, “
NDT and CAD Data Fusion for Diagnosis Assistance and Diffusion Bonding Improvement
,”
1997 COFREND Congress on Nondestructive Testing
, Nantes, France.
6.
Gros
,
X. E.
,
Bousigue
,
J.
, and
Takahashi
,
K.
, 1999, “
NDT Data Fusion at Pixel Level
,”
NDT & E Int.
,
32
(
5
), pp.
283
–
292
. 0963-8695
Crossref
Search ADS
 
7.
He
,
X. C.
, and
Yung
,
N. H. C.
, 2004, “
Curvature Scale Space Corner Detector With Adaptive Threshold and Dynamic Region of Support
,”
17th International Conference on Pattern Recognition (ICPR’04)
, pp.
791
–
794
.
8.
Belongie
,
S.
,
Malik
,
J.
, and
Puzicha
,
J.
, 2002, “
Shape Matching and Object Recognition Using Shape Contexts
,”
IEEE Trans. Pattern Anal. Mach. Intell.
0162-8828,
24
(
4
), pp.
509
–
522
.
Crossref
Search ADS
 
9.
Rockinger
,
O.
, and
Fechner
,
T.
, 1998, “
Pixel-Level Image Fusion: The Case of Image Sequences
,”
Proceedings of the Society of Photo-Optical Instrumentation Engineers: Signal Processing, Sensor Fusion, and Target Recognition VII
,
I.
Kadar
, ed., Orlando, FL, pp.
378
–
388
.
10.
Toet
,
A.
,
van Ruyven
,
L. J.
, and
Valeton
,
J. M.
, 1989, “
Merging Thermal and Visual Images by a Contrast Pyramid
,”
Opt. Eng. (Bellingham)
0091-3286,
28
(
7
), pp.
789
–
792
.
11.
Tian
,
G. Y.
,
Gledhill
,
D.
, and
Taylor
,
D.
, 2003, “
Comprehensive Interest Points Based Imaging Mosaic
,”
Pattern Recogn. Lett.
,
24
(
9–10
), pp.
1171
–
1179
. 0167-8655
12.
Temkin
,
B.
,
Vaidyanath
,
S.
, and
Acosta
,
E.
, 2005, “
A High Accuracy, Landmark-Based, Sub-Pixel Level Image Registration Method
,”
International Congress Series. CARS 2005: Computer Assisted Radiology and Surgery
, Vol.
1281
, pp.
254
–
259
.
13.
Petrovic
,
V. S.
, 2003, “
Multilevel Image Fusion
,”
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications
,
Proceedings of the Society of Photo-Optical Instrumentation Engineers
,
B. V.
Dasarathy
, ed., Bellingham, WA, pp.
87
–
96
.
14.
Wang
,
Z.
,
Ziou
,
D.
,
Armenakis
,
C.
,
Li
,
D.
, and
Qingquan
,
L.
, 2005, “
A Comparative Analysis of Image Fusion Methods
,”
IEEE Trans. Geosci. Remote Sens.
0196-2892,
43
(
6
), pp.
1391
–
1402
.
Crossref
Search ADS
 
15.
Shiming
,
X.
, 2002,
Visual C++ Digital Image and Graphics Processing
,
Electronic Industry
,
Beijing
.
Copyright © 2009
 by American Society of Mechanical Engineers
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