Abstract
In the field of computer vision, computer scientists extract knowledge from an image by manipulating it through image transforms. In the mathematical language of image algebra an image transformation often corresponds to an image-template product. When performing this operation on a computer, savings in time and memory as well as a better fit to the specific computer architecture can often be achieved by using the technique of template decomposition. In this paper we use global optimization techniques to solve a general problem of morphological template decomposition.
This research was partially supported by US Air Force Contract F08635-89-C-0134.
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© 1996 Kluwer Academic Publishers
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Sussner, P., Pardalos, P.M., Ritter, G.X. (1996). Global Optimization Problems in Computer Vision. In: Floudas, C.A., Pardalos, P.M. (eds) State of the Art in Global Optimization. Nonconvex Optimization and Its Applications, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-3437-8_28
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DOI: https://doi.org/10.1007/978-1-4613-3437-8_28
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