DATA MODELING IN SCIENTIFIC IMAGES USING SIMULATED ANNEALING

dc.contributor.authorParker, J.R.eng
dc.contributor.authorGroisman, G.eng
dc.date.accessioned2008-05-08T18:40:58Z
dc.date.available2008-05-08T18:40:58Z
dc.date.computerscience1999-05-27eng
dc.date.issued1993-02-01eng
dc.description.abstractOne way to measure objects in some classes of scientific image is to model the objects by functions and then make the measurements on the functions. This works especially well for images that contain information in the form of relationships between grey level pixels. Here, the use of a Moffat function as a data model is explored, as is the use of simulated annealing to fit many instances of this function to the data in the image. Two examples are presented: stellar photometry, a natural application for the Moffat function, and reading DNA sequencing gels.eng
dc.description.notesWe are currently acquiring citations for the work deposited into this collection. We recognize the distribution rights of this item may have been assigned to another entity, other than the author(s) of the work.If you can provide the citation for this work or you think you own the distribution rights to this work please contact the Institutional Repository Administrator at digitize@ucalgary.caeng
dc.identifier.department1993-503-8eng
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/30935
dc.identifier.urihttp://hdl.handle.net/1880/46423
dc.language.isoEngeng
dc.publisher.corporateUniversity of Calgaryeng
dc.publisher.facultyScienceeng
dc.subjectComputer Scienceeng
dc.titleDATA MODELING IN SCIENTIFIC IMAGES USING SIMULATED ANNEALINGeng
dc.typeunknown
thesis.degree.disciplineComputer Scienceeng
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