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Identification and measurement of fibers in scanning electron microscopy images using a high-order correlation process

dc.contributor.authorAzimi-Sadjadi, Mahmood R., author
dc.contributor.authorYáñez-Suárez, Oscar, author
dc.contributor.authorIEEE, publisher
dc.date.accessioned2007-01-03T04:43:36Z
dc.date.available2007-01-03T04:43:36Z
dc.date.issued1999
dc.description.abstractThis work describes the development of a dedicated system capable of identifying, measuring and counting various types of fibers and other objects in digitized scanning electron micrograph (SEM) imagery. The system uses a recursive high order correlation (HOC) process to extract the corner pixels of the fibers. The objects are defined by grouping connected corners, so that morphometric analysis can be performed. The method developed performs satisfactorily when the density of fibers per image ranges from low to medium. Simulation results for several cases are presented, along with a discussion on the capabilities and limitations of the current version of the system.
dc.description.sponsorshipThis work was supported by Schuller, Inc., Denver, CO.
dc.format.mediumborn digital
dc.format.mediumarticles
dc.identifier.bibliographicCitationYáñez-Suárez, Oscar and Mahmood R. Azimi-Sadjadi, Identification and Measurement of Fibers in Scanning Electron Microscopy Images Using a High-Order Correlation Process, IEEE Transactions on Instrumentation and Measurement 48, no. 1 (February 1999): 55-61.
dc.identifier.urihttp://hdl.handle.net/10217/852
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©1999 IEEE.
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectmeasurement technology
dc.subjectimage analysis
dc.subjectfiberglass identification
dc.titleIdentification and measurement of fibers in scanning electron microscopy images using a high-order correlation process
dc.typeText

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