TY  - CPAPER
A1  - Alekseychuk, Oleksandr
A1  - Zscherpel, Uwe
T1  - Recent developments for longitudinal crack detection using a Continuous Density Hidden Markov Model (CDHMM)
T2  - DIR 2007 - International Symposium on Digital Industrial Radiology and Computed Tomography (Proceedings)
N2  - Recent developments for automatic detection of crack indications in welding
seams are presented addressing the task from a probabilistic point of view.
This work improves the algorithm developed several years ago. The distinctive
feature of these algorithms is a translation of the task of detection into an
optimisation task in such a way, that the the maximum of a scoring function in
the space of all possible positions, lengths and shapes can be found exactly and
computationally effective. The progress of the new algorithm presented here
consists in the replacement of the discrete (binary) model of crack indications
(i.e. defect present vs. defect absent) previously used with a continuous grey
value model and the development of a new scoring function. The restriction
of the noise model to additive Gaussian allowed the utilisation of conjugate
priors for the posterior probability estimation in a computationally effective
way too. Results of experimental evaluation of the developed algorithm are
presented.
T2  - DIR 2007 - International Symposium on Digital industrial Radiology and Computed Tomography
CY  - Lyon, France
DA  - 2007-06-25
KW  - Industrial radiographic testing
KW  - Crack detection
KW  - Curve detection
KW  - Detection in noisy images
KW  - Bayesian network
KW  - HMM
KW  - CDHMM
KW  - Dynamic programming
KW  - Kalman filter
PY  - 2007
UR  - http://www.ndt.net/article/dir2007/papers/p1.pdf
IS  - (Poster P1)
SP  - 1
EP  - 16
CY  - Lyon, France
AN  - OPUS4-16065
LA  - eng
AD  - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany
ER  -