Proceedings ArticleDOI
Morphological shape representation
Ioannis Pitas,Anastasios N. Venetsanopoulos +1 more
- pp 2381-2384
TLDR
A new approach for shape representation is described which provides a general scheme for object description and unifies some of the existing representation techniques, based on the use of simple geometric objects which are intuitively used by humans in their perception of shapes and on mathematical morphology.Abstract:
A new approach for shape representation is described which provides a general scheme for object description and unifies some of the existing representation techniques (e.g. CSG, skeletons, shape decomposition). It is based on the use of simple geometric objects which are intuitively used by humans in their perception of shapes and on mathematical morphology. Furthermore, its unifying framework can be used both in computer graphics and computer vision, thus providing a tool to close the existing gap between object modeling and object recognition in certain applications, e.g. in robotic vision. >read more
Citations
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Book ChapterDOI
Morphological Segmentation for Textures and Particles
Luc Vincent,Edward R. Dougherty +1 more
TL;DR: The present chapter concerns image segmentation via the methods of morphological image processing with a focus on watershed segmentation, which has the advantages of being very general, usually accurate and fast, and applicable to both binary and grayscale images.
Journal ArticleDOI
Scene Learning for Cloud Detection on Remote-Sensing Images
Zhenyu An,Zhenwei Shi +1 more
TL;DR: A novel automatic supervised approach based on the “scene-learning” scheme, which aims at training and applying a cloud detector on the whole image scenes, and proves that more features lead to better performance of scene learning under certain circumstance.
Proceedings Article
Shape Representation: Comparison between the Morphological Skeleton and Morphological Shape Decomposition.
TL;DR: The morphological skeleton and morphological shape decomposition (MSD) are two popular approaches for shape representation as discussed by the authors, where each method represents an object as an algebraic combination of a number of components, where each component is given by a locus of points dilated by a specified structuring-element homothetic.
Journal ArticleDOI
Morphological decomposition of 2-D binary shapes into conditionally maximal convex polygons
TL;DR: A morphological shape segmentation algorithm that decomposes a 2-D (two-dimensional) binary shape into a collection of restricted convex polygons that can be used to construct structural shape description and for other shape analysis purposes.
Journal ArticleDOI
Morphological decomposition of 2-D binary shapes into convex polygons: a heuristic algorithm
TL;DR: A morphological shape decomposition algorithm that decomposes a two-dimensional (2-D) binary shape into a collection of convex polygonal components that allows accurate approximations for the given shapes at low coding costs.
References
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BookDOI
Nonlinear Digital Filters
TL;DR: This chapter discusses digital filters based on order statistics, Morphological image and signal processing, and Adaptive nonlinear filters.
Journal ArticleDOI
Representations for Rigid Solids: Theory, Methods, and Systems
TL;DR: A coherent view, based on sound theoretical principles, of what is presently known about the representation of solids is provided by providing a simple mathematical framework for characterizing certain important aspects of representations, for example, their semantic (geometric) integrity.
Journal ArticleDOI
Morphological skeleton representation and coding of binary images
Petros Maragos,R. Schafer +1 more
TL;DR: The morphological skeleton is shown to unify many previous approaches to skeletonization, and some of its theoretical properties are investigated.
Book
A review of algorithms for shape analysis
TL;DR: In this article, the authors reviewed and classified algorithms for shape analysis under two criteria: whether they examine the boundary only or the whole area, and whether they describe the original picture in terms of scalar measurements or through structural descriptions.
Journal ArticleDOI
A review of algorithms for shape analysis
TL;DR: Algorithms for shape analysis are reviewed and classified under two criteria: whether they examine the boundary only or the whole area, and whether they describe the original picture in terms of scalar measurements or through structural descriptions.
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