Title : 
Image retrieval based on multi-feature similarity score fusion using genetic algorithm
         
        
            Author : 
Chen, Mianshu ; Fu, Ping ; Sun, Yuan ; Zhang, Hui
         
        
            Author_Institution : 
Sch. of Commun. Eng., Jilin Univ., Changchun, China
         
        
        
        
        
        
        
            Abstract : 
This paper proposes an image retrieval method based on multi-feature similarity score fusion using genetic algorithm. Single feature describes image content only from one point of view, which has a certain one-sided. Fusing multi-feature similarity score is expected to improve the system´s retrieval performance. In this paper, the retrieval results from color feature and texture feature are analyzed, and the method of fusing multi-feature similarity score is described. For the purpose of assigning the fusion weights of multi-feature similarity scores reasonably, the genetic algorithm is applied. For comparison, other three methods are implemented. They are image retrieval based on color feature, texture feature and fusion of color-texture feature similarity score with equal weights. The experimental results show that the proposed method is superior to other methods.
         
        
            Keywords : 
genetic algorithms; image colour analysis; image fusion; image retrieval; image texture; color feature; genetic algorithm; image retrieval; multifeature similarity score fusion; texture feature; Computer science education; Content based retrieval; Feature extraction; Genetic algorithms; Genetic engineering; Image retrieval; Information retrieval; Shape; Spatial resolution; Sun; fusion; genetic algorithm; image retrieval;
         
        
        
        
            Conference_Titel : 
Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on
         
        
            Conference_Location : 
Singapore
         
        
            Print_ISBN : 
978-1-4244-5585-0
         
        
            Electronic_ISBN : 
978-1-4244-5586-7
         
        
        
            DOI : 
10.1109/ICCAE.2010.5451373