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This work was supported by the National Aeronautics and Space Administration under EPSCOR grant NCC5-171.
 

Summary: This work was supported by the National Aeronautics and Space
Administration under EPSCOR grant NCC5-171.
Abstract
Two image segmentation methods are presented
and compared in terms of rate-distortion within
an object-based coding scheme. The LOMO
segmentation exploits the relationship between
mathematical morphology and local
monotonicity in producing a multiscale
segmentation. The process is a morphological
analogy to the Laplacian of Gaussian. The level
set approach uses area morphology to generate
segmented regions having a specified minimum
area. Segments are optimally chosen from the
connected components of the image level sets. A
simple object-based coding scheme using the
discrete cosine transform is used to avoid the
artifacts produced by conventional block-based
coding at segment boundaries. Results of each
segmentation method are given and compared

  

Source: Acton, Scott - Department of Electrical and Computer Engineering, University of Virginia

 

Collections: Computer Technologies and Information Sciences