title: Automated defect detection and evaluation in X-ray CT images
creator: Eisele, Heiko
subject: ddc-530
subject: 530 Physics
description: X-ray computed tomography gains increasing popularity for industrial quality inspection tasks. It is a challenge however to use it in a fully automated assembly line, which requires robust algorithms for volumetric image analysis on noisy data. This work provides methods for the automatic detection of defects and their geometric description. The approach will be based on spatial statistical analysis of the voxel structure to determine the presence of a defect. Once detected, defect voxels will be clustered to determine shape and size of the associated material faults. The effectiveness of the method will be shown on pores and cracks in steel parts.
date: 2002
type: Dissertation
type: info:eu-repo/semantics/doctoralThesis
type: NonPeerReviewed
format: application/pdf
identifier: https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/3106/1/diss.pdf
identifier: DOI:10.11588/heidok.00003106
identifier: urn:nbn:de:bsz:16-opus-31066
identifier:   Eisele, Heiko  (2002) Automated defect detection and evaluation in X-ray CT images.  [Dissertation]     
relation: https://archiv.ub.uni-heidelberg.de/volltextserver/3106/
rights: info:eu-repo/semantics/openAccess
rights: http://archiv.ub.uni-heidelberg.de/volltextserver/help/license_urhg.html
language: eng