Robust automated multiple view inspection

Pizarro, L; Mery, D; Delpiano, R.; Carrasco M.

Abstract

Recently, Automated Multiple View Inspection (AMVI) has been developed for automated defect detection of manufactured objects, and the framework was successfully implemented for calibrated image sequences. However, it is not easy to be implemented in industrial environments because the calibration is a difficult and an unstable process. To overcome these disadvantages, the robust AMVI strategy, which assumes that an unknown affine transformation exists between each pair of uncalibrated images, is proposed. This transformation is estimated using two complementary robust procedures: a global approximation of the affine mapping is computed by creating candidate correspondences via B-splines and selecting those which better satisfy the epipolar constraint for uncalibrated images. Then, we use this approximation as initial estimate of a robust intensity-based matching approach, which is applied locally on each potential defect. The result is that false alarms are discarded, and the defects of an industrial object are actually tracked along the uncalibrated image sequence. The method is successful as shown in our experiments on aluminum die castings. © 2007 Springer-Verlag London Limited.

Más información

Título según WOS: Robust automated multiple view inspection
Título según SCOPUS: Robust automated multiple view inspection
Título de la Revista: Pattern Analysis and Applications
Volumen: 11
Número: 1
Editorial: Springer
Fecha de publicación: 2008
Página de inicio: 21
Página final: 32
Idioma: English
URL: http://link.springer.com/10.1007/s10044-007-0075-9
DOI:

10.1007/s10044-007-0075-9

Notas: ISI, SCOPUS