Paper Info
Title
A method of shape description by a distribution function
Abstract
Some coding methods aimed at data compression for image communication and storage code the image by regions. This paper proposes a method for describing shapes of silhouette figures efficiently with a small amount of data in these coding methods. This method is one which represents the inside regions of a figure by a set of primitive structuring elements, and the primitive structuring elements are used whose contours are defined by a density distribution function. An algorithm, which automatically obtains a collection of primitive structuring elements approximating the contour of an objective region based on the thinned skeleton of the region has been designed. Moreover, based upon the multiple resolution representation of the region obtained by smoothing the contour with the Gaussian filter, the elements in the central part to the elements in the dilated parts are represented hierarchically by a tree structure. Simulations of the descriptive method were done to object regions in a natural image. Since each element has a property of mutually fusing compared to methods which decompose shapes with fixed-shaped elements, this method can approximate the shape of the region well with less data. Moreover, by tree representation of elements, reproduction of the region at various degrees of approximation and resolution becomes possible.
Year
DOI
Venue
1994
10.1002/scj.4690250406
SYSTEMS AND COMPUTERS IN JAPAN
Keywords
Field
DocType
SHAPE DESCRIPTION,SHAPE DECOMPOSITION,DENSITY DISTRIBUTION FUNCTION,SMOOTHING CONTOUR LINES,TREE REPRESENTATION
Gaussian filter,Computer vision,Computer science,Silhouette,Image processing,Smoothing,Tree structure,Artificial intelligence,Structuring,Data compression,Shape analysis (digital geometry)
Journal
Volume
Issue
ISSN
25
4
0882-1666
Citations 
PageRank 
References 
0
0.34
2
Authors
3
Name
Order
Citations
PageRank
Tadahiko Kimoto1158.40
Motohiro Asai200.34
Yasuhiko Yasuda311317.55