BibTeX:

@article{IJIRSTV2I1070,
     title={Image Retrieval using Genetic Algorithm Based on Multi-Feature Similarity Score Fusion},
     author={Deepika P. Shrivastava and Krunal Panchal},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={2},
     number={1},
     pages={278--281},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV2I1070.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

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 multifeature 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.

image retrieval; fusion; genetic algorithm