Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Computer Analysis of Images and Patterns - 8th International Conference, CAIP 1999, Proceedings |
| Herausgeber/-innen | Franc Solina, Aleš Leonardis |
| Seiten | 275-284 |
| Seitenumfang | 10 |
| Publikationsstatus | Veröffentlicht - 1999 |
| Veranstaltung | 8th International Conference on Computer Analysis of Images and Patterns, CAIP 1999 - Ljubljana, Slowenien Dauer: 1 Sept. 1999 → 3 Sept. 1999 |
Publikationsreihe
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Band | 1689 |
| ISSN (Print) | 0302-9743 |
| ISSN (elektronisch) | 1611-3349 |
Abstract
In nondestructive testing for quality control of industrial objects the standard X-ray analysis produces a 2D projection of the 3D objects. Defects can be detected but cannot be localized in 3D position, size and shape. Tomographic testing equipment turns frequently out to be too costly and time consuming for many applications. Here a new approach for 3D reconstruction is suggested using standard X-ray equipment without costly positioning equipment. The new approach requires only a small number of X-ray views from different directions in order to reduce the image acquisition time. The geometric and photometric imaging properties of the system are ca- librated using different calibration patterns. The parameters of a CAHV camera model are obtained for each view permitting the exact registration of the acquired images. The efficiency of the 3D reconstruction algorithm has been increased by limiting the reconstruction to regions of interest around the defects. This requires an automated segmentation. The 3D reconstruction of the defects is performed with an iterative procedure. Regularization of the reconstruction problem is achieved on the basis of the maximum entropy principle. The reliability and robustness of the method has been tested on simulated and real data.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
- Allgemeine Computerwissenschaft
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Computer Analysis of Images and Patterns - 8th International Conference, CAIP 1999, Proceedings. Hrsg. / Franc Solina; Aleš Leonardis. 1999. S. 275-284 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 1689).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - 3D reconstruction of volume defects from few X-ray images
AU - Lehr, C.
AU - Liedtke, C. E.
N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 1999.
PY - 1999
Y1 - 1999
N2 - In nondestructive testing for quality control of industrial objects the standard X-ray analysis produces a 2D projection of the 3D objects. Defects can be detected but cannot be localized in 3D position, size and shape. Tomographic testing equipment turns frequently out to be too costly and time consuming for many applications. Here a new approach for 3D reconstruction is suggested using standard X-ray equipment without costly positioning equipment. The new approach requires only a small number of X-ray views from different directions in order to reduce the image acquisition time. The geometric and photometric imaging properties of the system are ca- librated using different calibration patterns. The parameters of a CAHV camera model are obtained for each view permitting the exact registration of the acquired images. The efficiency of the 3D reconstruction algorithm has been increased by limiting the reconstruction to regions of interest around the defects. This requires an automated segmentation. The 3D reconstruction of the defects is performed with an iterative procedure. Regularization of the reconstruction problem is achieved on the basis of the maximum entropy principle. The reliability and robustness of the method has been tested on simulated and real data.
AB - In nondestructive testing for quality control of industrial objects the standard X-ray analysis produces a 2D projection of the 3D objects. Defects can be detected but cannot be localized in 3D position, size and shape. Tomographic testing equipment turns frequently out to be too costly and time consuming for many applications. Here a new approach for 3D reconstruction is suggested using standard X-ray equipment without costly positioning equipment. The new approach requires only a small number of X-ray views from different directions in order to reduce the image acquisition time. The geometric and photometric imaging properties of the system are ca- librated using different calibration patterns. The parameters of a CAHV camera model are obtained for each view permitting the exact registration of the acquired images. The efficiency of the 3D reconstruction algorithm has been increased by limiting the reconstruction to regions of interest around the defects. This requires an automated segmentation. The 3D reconstruction of the defects is performed with an iterative procedure. Regularization of the reconstruction problem is achieved on the basis of the maximum entropy principle. The reliability and robustness of the method has been tested on simulated and real data.
KW - Calibration
KW - Tomography
KW - X-ray
UR - http://www.scopus.com/inward/record.url?scp=38849136810&partnerID=8YFLogxK
U2 - 10.1007/3-540-48375-6_34
DO - 10.1007/3-540-48375-6_34
M3 - Conference contribution
AN - SCOPUS:38849136810
SN - 3540663665
SN - 9783540663669
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 275
EP - 284
BT - Computer Analysis of Images and Patterns - 8th International Conference, CAIP 1999, Proceedings
A2 - Solina, Franc
A2 - Leonardis, Aleš
T2 - 8th International Conference on Computer Analysis of Images and Patterns, CAIP 1999
Y2 - 1 September 1999 through 3 September 1999
ER -