DocumentCode
1420149
Title
Morphological decomposition of 2-D binary shapes into convex polygons: a heuristic algorithm
Author
Xu, Jianning
Author_Institution
Dept. of Comput. Sci., Rowan Univ., Glassboro, NJ, USA
Volume
10
Issue
1
fYear
2001
fDate
1/1/2001 12:00:00 AM
Firstpage
61
Lastpage
71
Abstract
In many morphological shape decomposition algorithms, either a shape can only be decomposed into shape components of extremely simple forms or a time consuming search process is employed to determine a decomposition. In this paper, we present a morphological shape decomposition algorithm that decomposes a two-dimensional (2-D) binary shape into a collection of convex polygonal components. A single convex polygonal approximation for a given image is first identified. This first component is determined incrementally by selecting a sequence of basic shape primitives. These shape primitives are chosen based on shape information extracted from the given shape at different scale levels. Additional shape components are identified recursively from the difference image between the given image and the first component. Simple operations are used to repair certain concavities caused by the set difference operation. The resulting hierarchical structure provides descriptions for the given shape at different detail levels. The experiments show that the decomposition results produced by the algorithm seem to be in good agreement with the natural structures of the given shapes. The computational cost of the algorithm is significantly lower than that of an earlier search-based convex decomposition algorithm. Compared to nonconvex decomposition algorithms, our algorithm allows accurate approximations for the given shapes at low coding costs
Keywords
approximation theory; computational complexity; image processing; mathematical morphology; 2-D binary shapes; approximations; basic shape primitives; computational cost; concavities; convex polygonal approximation; convex polygons; detail level; heuristic algorithm; morphological decomposition; morphological shape decomposition algorithms; natural structures; set difference operation; shape components; shape information; Computational efficiency; Costs; Data mining; Heuristic algorithms; Image analysis; Image coding; Morphological operations; Morphology; Structural shapes; Two dimensional displays;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/83.892443
Filename
892443
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