DocumentCode
3061999
Title
Association of adaptative smoothing and Markovian models for detection of valley bottoms on strongly noisy images [nondestructive testing]
Author
Azencott, R. ; Chalmond, B. ; Coldefy, F.
Author_Institution
Univ. de Paris-Sud, Orsay, France
fYear
1992
fDate
30 Aug-3 Sep 1992
Firstpage
327
Lastpage
330
Abstract
The paper is related to a nondestructive control industrial task: the detection of defects in γ radiographic images. The images are very noisy and have a strong luminosity gradient. The authors adopt a Bayes-Markov model in order to estimate the noise, the gradient and the defects. The proposed model is general and can be used in other situations for detecting valley bottoms in noisy images
Keywords
Bayes methods; Markov processes; decision theory; flaw detection; image processing; radiography; Bayes-Markov model; adaptative smoothing; defects detection; flaw detection; image processing; noise estimation; nondestructive control industrial task; strongly noisy images; valley bottoms; Degradation; Humans; Image reconstruction; Industrial control; Power generation; Radio control; Radiography; Signal to noise ratio; Smoothing methods; Surface reconstruction;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings., 11th IAPR International Conference on
Conference_Location
The Hague
Print_ISBN
0-8186-2920-7
Type
conf
DOI
10.1109/ICPR.1992.201991
Filename
201991
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