Parts of planar shapes

An algorithm for partitioning the shape of a planar pattern into near-convex parts is described, which utilizes ancillary processes such as dominant point detection and label propagation. The shape features taken into account are negative minima of curvature on the contour and spines, i.e. suitable...

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Bibliographic Details
Published inPattern recognition Vol. 29; no. 10; pp. 1703 - 1711
Main Authors Abe, Keiichi, Arcelli, Carlo, Hisajama, Takeshi, Ibaraki, Toshio
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 01.10.1996
Elsevier Science
Subjects
Algorithmics. Computability. Computer arithmetics
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Dominant point
Exact sciences and technology
Label propagation
Pattern recognition. Digital image processing. Computational geometry
Shape decomposition
Skeleton
Theoretical computing
Zone of influence
Skeleton
Dominant point
Label propagation
Zone of influence
Shape decomposition
Pattern recognition
Pattern extraction
Decomposition method
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Summary:An algorithm for partitioning the shape of a planar pattern into near-convex parts is described, which utilizes ancillary processes such as dominant point detection and label propagation. The shape features taken into account are negative minima of curvature on the contour and spines, i.e. suitable skeleton subsets. Each spine has its own view of the pattern and exerts an influence over the neighboring pixels as far as no conflicts with other spines arise. The parts of the decomposition are found as the zones of influence of the spines. To favor a more compact description, the algorithm also includes a phase devoted to the extraction of loop components in correspondence with the holes of the pattern.
ISSN:0031-3203
1873-5142
DOI:10.1016/0031-3203(96)00021-0