DocumentCode
1742311
Title
Exploring the performance of genetic algorithms as polygonal approximators
Author
Traver, V. Javier ; Recatala, Gabriel ; Inesta, Jose Manuel
Author_Institution
Dept. de Inf., Univ. Jaume I, Castellon, Spain
Volume
3
fYear
2000
fDate
2000
Firstpage
766
Abstract
The construction of polygonal approximations for digital curves is a well-known technique to obtain a compact representation of them. Over the last years, a number of methods have been proposed to optimize this process, based on different criteria. In this paper, polygonal approximation is viewed as an optimization problem, and the use of a genetic algorithm is proposed as a method to find a solution that best meets a given set of requirements. This paper analyses the capability and the performance of the genetic algorithm to select the vertices of the polygons, and some advantages and drawbacks are discussed
Keywords
approximation theory; edge detection; genetic algorithms; image representation; digital contours; digital curves; genetic algorithms; optimization; polygonal approximation; polygons; Algorithm design and analysis; Encoding; Genetic algorithms; Iterative algorithms; Merging; Optimization methods; Performance analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location
Barcelona
ISSN
1051-4651
Print_ISBN
0-7695-0750-6
Type
conf
DOI
10.1109/ICPR.2000.903657
Filename
903657
Link To Document