Title
Shape Preservation in Morphological Filtering and Segmentation
Abstract
This paper discusses the behavior of some image filtering and segmentation approaches, focusing on techniques that belongs to mathematical morphology. In particular, this works studies some morphological operators and filters that consider connectivity in a special way and that, therefore, satisfactorily preserve the significant shapes and contours of an input image. Such morphological connected filters compare favorably to other filtering techniques that attempt to preserve shapes, such as, for example, anisotropic filtering or morphological non-connected filtering. Some locality and adjacency relationships are satisfied by openings and closings by reconstruction, the ``building'' pieces of the filter by reconstruction class. In addition, the composition properties of some filters by reconstruction make them suitable for multi-scale image representation. The extension of the connect filtering philosophy to the image segmentation problem achieves segmentation methods that avoid the so called resolution problem that affects some techniques. Some examples are shown that illustrate the ideas described in the paper.
Year
DOI
Venue
1999
10.1109/SIBGRA.1999.805732
SIBGRAPI
Keywords
Field
DocType
segmentation method,segmentation approach,shape preservation,morphological filtering,adjacency relationship,input image,composition property,reconstruction class,image segmentation problem,morphological operator,resolution problem,multi-scale image representation,image segmentation,image resolution,layout,mathematical morphology,anisotropic filtering,morphology,image reconstruction,filtering,satisfiability
Computer vision,Morphological skeleton,Scale-space segmentation,Image texture,Filter (signal processing),Anisotropic filtering,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Morphological gradient,Mathematics
Conference
ISBN
Citations 
PageRank 
0-7695-0481-7
6
0.68
References 
Authors
0
2
Name
Order
Citations
PageRank
José Crespo112624.90
Victor Maojo233353.22