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Decision-level fusion of spatially scattered multi-modal data for nondestructive inspection of surface defects
- This article focuses on the fusion of flaw indications from multi-sensor nondestructive materials testing. Because each testing method makes use of a different physical principle, a multi-method approach has the potential of effectively differentiating actual defect indications from the many false alarms, thus enhancing detection reliability. In this study, we propose a new technique for aggregating scattered two- or three-dimensional sensory data. Using a density-based approach, the proposed method explicitly addresses localization uncertainties such as registration errors. This feature marks one of the major of advantages of this approach over pixel-based image fusion techniques. We provide guidelines on how to set all the key parameters and demonstrate the technique's robustness. Finally, we apply our fusion approach to experimental data and demonstrate its capability to locate small defects by substantially reducing false alarms under conditions where no single-sensor method isThis article focuses on the fusion of flaw indications from multi-sensor nondestructive materials testing. Because each testing method makes use of a different physical principle, a multi-method approach has the potential of effectively differentiating actual defect indications from the many false alarms, thus enhancing detection reliability. In this study, we propose a new technique for aggregating scattered two- or three-dimensional sensory data. Using a density-based approach, the proposed method explicitly addresses localization uncertainties such as registration errors. This feature marks one of the major of advantages of this approach over pixel-based image fusion techniques. We provide guidelines on how to set all the key parameters and demonstrate the technique's robustness. Finally, we apply our fusion approach to experimental data and demonstrate its capability to locate small defects by substantially reducing false alarms under conditions where no single-sensor method is adequate.…
Autor*innen: | René Heideklang, P. Shokouhi |
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Dokumenttyp: | Zeitschriftenartikel |
Veröffentlichungsform: | Verlagsliteratur |
Sprache: | Englisch |
Titel des übergeordneten Werkes (Englisch): | Sensors |
Jahr der Erstveröffentlichung: | 2016 |
Veröffentlichende Institution: | Bundesanstalt für Materialforschung und -prüfung (BAM) |
Verlag: | MDPI |
Verlagsort: | Basel, Switzerland |
Jahrgang/Band: | 16 |
Erste Seite: | Article Number: 105 |
DDC-Klassifikation: | Naturwissenschaften und Mathematik / Chemie / Analytische Chemie |
Freie Schlagwörter: | Defect detection; Density estimation; Multi-sensor data fusion; Nondestructive testing; Registration errors; Scattered data |
DOI: | 10.3390/s16010105 |
URN: | urn:nbn:de:kobv:b43-352977 |
ISSN: | 1424-8220 |
Verfügbarkeit des Dokuments: | Datei für die Öffentlichkeit verfügbar ("Open Access") |
Bibliotheksstandort: | Sonderstandort: Publica-Schrank |
Lizenz (Deutsch): | Creative Commons - Namensnennung |
Datum der Freischaltung: | 20.02.2016 |
Referierte Publikation: | Ja |
Datum der Eintragung als referierte Publikation: | 26.01.2016 |