Paper Info
Title
Genetic Algorithm for Silhouette Matching
Abstract
Genetic algorithms (GAs) have been applied to matching problem. However, traditional GAs do not perform well in matching problem because there can be many locally similar parts. This paper presents a new genetic algorithm for silhouette matching. New concepts of partially matched gene-strings in the initial population, the extending operator and the order adjustment algorithm are proposed. Each gene-string in the initial population only has three matched points while other points are unmatched. During the evolution, each gene-string will have more matched points due to the applications of the crossover and extending operators. The extending operator determines a potential match for an unmatched point near a matched point by searching the local space. After the application of the crossover and extending operators, the adjustment algorithm enforces each gene-string to be an ordered list by removing some matched points, if necessary. Our experiments show that the new matching algorithm based on GA performs better than traditional GA-based algorithms
Year
DOI
Venue
2006
10.1109/ICARCV.2006.345256
Singapore
Keywords
Field
DocType
feature extraction,genetic algorithms,image matching,image retrieval,genetic algorithm,image retrieval,partially matched gene-strings,shape retrieval,shape similarity,silhouette matching,Genetic algorithm,Image retrieval,Shape retrieval,Shape similarity,Silhouette matching
Population,Crossover,Pattern recognition,Silhouette,Computer science,Image retrieval,Feature extraction,Operator (computer programming),Artificial intelligence,Genetic algorithm,Blossom algorithm
Conference
ISSN
ISBN
Citations 
2474-2953
1-4214-042-1
0
PageRank 
References 
Authors
0.34
18
4
Name
Order
Citations
PageRank
Yanchun Liang149563.74
P. N. Suganthan210876412.72
Xiang-lin Qi3152.85
Wang, Y.J.421621.29