Authors: Žunić, Anastazia 
Title: Shape diameter for object analysis
Journal: Information Processing Letters
Volume: 136
First page: 76
Last page: 79
Issue Date: 2018
Rank: M23
ISSN: 0020-0190
DOI: 10.1016/j.ipl.2018.03.012
Shape diameter, defined as the longest distance between two shape points, is a natural and dissent shape characteristics. In this paper we show how the shape diameter can be utilized to define two quantities, herein named the elongation measures. Both measures have a discriminative capacity and, as such, can be used to distinguish among the objects presented on digital images. The first elongation measure is based on comparison of the shape diameter and shape area. The second one is based on the relationship between the shape diameter and shape perimeter. The basic desirable properties of the new measures are given. A number of simple examples are given in order to illustrate the behavior of the new measures.
Keywords: Computational geometry | Image processing | Pattern recognition | Shape analysis
Publisher: Elsevier

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