Multifeature similarity score image retrieval S.Muralikaruppaiyan M.E., Communication systems

Abstract—This project deals with efficient retrieval of images from large databases based on the multi-feature similarity score fusion using genetic algorithm. With the increasing popularity of the use of large volume image data base in various applications, it becomes imperative to build an efficient retrieval to browse through the entire data base. Unlike previous approaches which concentrate on extracting a single concise feature, our technique combines features that represent both the color and texture in images. 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