Off-line metrology on SEM images using gray scale morphology

dc.contributor.author	Ζώης, Ηλίας Ν.	el
dc.contributor.author	Ράπτης, Ιωάννης	el
dc.contributor.author	Αναστασόπουλος, Βασίλειος	el
dc.date.accessioned	2015-01-09T17:55:39Z
dc.date.available	2015-01-09T17:55:39Z
dc.date.issued	2015-01-09
dc.identifier.uri	http://hdl.handle.net/11400/3644
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://www.springer.com/	en
dc.subject	Lithography
dc.subject	Morphology
dc.subject	Λιθογραφία
dc.subject	Μορφολογία
dc.title	Off-line metrology on SEM images using gray scale morphology	en
heal.type	journalArticle
heal.classification	Electrical engineering
heal.classification	Electronics
heal.classification	Ηλεκτρολογική μηχανική
heal.classification	Ηλεκτρονική
heal.classificationURI	http://skos.um.es/unescothes/C01311
heal.classificationURI	http://zbw.eu/stw/descriptor/10455-2
heal.classificationURI	N/A-Ηλεκτρολογική μηχανική
heal.classificationURI	N/A-Ηλεκτρονική
heal.identifier.secondary	DOI 10.1007/s00604-006-0564-3
heal.language	en
heal.access	free
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Ηλεκτρονικών Μηχανικών Τ.Ε.	el
heal.publicationDate	2006
heal.bibliographicCitation	Zois, E., Raptis, I. and Anastassopoulos, V. (September 2006). Off-line metrology on SEM images using gray scale morphology. Microchimica Acta. 155(1-2). pp. 323-326. Springer-Verlag. Available from: http://link.springer.com/ [28/04/2006]	en
heal.abstract	Discrimination and metrology results of microlithographic patterns from top-down SEM images are explored bymeans ofmorphological image analysis. The method relies on the use of various morphological filters on a top down SEM image. The resulted images are segmented in order to derive a quality factor which discriminates the candidate images as under- or fullydeveloped. Furthermore, the fully developed images are processed in order to extract useful measurements. The proposed image analysis methodology achieves for first time, to the authors’ knowledge, successful off-line discrimination between under-developed and fully-developed cases. For the latter case, the measuring method relies upon the evaluation of the connected regions in the SEM image after segmentation. This is expressed by the Useful Threshold Range (UTR), which corresponds to that specific value of connected regions obtained for the wider range of the threshold. The method is experimentally demonstrated by employing 72 test images from high resolution patterns. The evaluated critical pattern parameters are found in good agreement to those derived from on-line procedures.	en
heal.publisher	Springer-Verlag	en
heal.journalName	Microchimica Acta	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true