DATA MODELING IN SCIENTIFIC IMAGES USING SIMULATED ANNEALING
Date
1993-02-01
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
One 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.
Description
Keywords
Computer Science