DocumentCode :
990034
Title :
A new convexity measure for polygons
Author :
Zunic, Jovisa ; Rosin, Paul L.
Volume :
26
Issue :
7
fYear :
2004
fDate :
7/1/2004 12:00:00 AM
Firstpage :
923
Lastpage :
934
Abstract :
Convexity estimators are commonly used in the analysis of shape. In this paper, we define and evaluate a new convexity measure for planar regions bounded by polygons. The new convexity measure can be understood as a "boundary-based" measure and in accordance with this it is more sensitive to measured boundary defects than the so called "area-based" convexity measures. When compared with the convexity measure defined as the ratio between the Euclidean perimeter of the convex hull of the measured shape and the Euclidean perimeter of the measured shape then the new convexity measure also shows some advantages-particularly for shapes with holes. The new convexity measure has the following desirable properties: 1) the estimated convexity is always a number from (0, 1], 2) the estimated convexity is I if and only if the measured shape is convex, 3) there are shapes whose estimated convexity is arbitrarily close to 0, 4) the new convexity measure is invariant under similarity transformations, and 5) there is a simple and fast procedure for computing the new convexity measure.
Keywords :
computational geometry; set theory; shape measurement; Euclidean perimeter; area based convexity measure; boundary based convexity measure; boundary defects; computational geometry; convex hull; convexity estimators; planar regions; polygons; set theory; shape analysis; Area measurement; Biology computing; Indexing; Noise robustness; Powders; Shape measurement; Shape; convexity; measurement.; polygons; Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2004.19
Filename :
1300562
Link To Document :
بازگشت