Content Based Image Retrieval of User’s Interest Using Feature Fusion and Optimization Using Genetic Algorithm: A Survey

(CBIR) systems is becoming wide as more and more applications are building up over it. In order to imitate the way human being treat the image management, the conventional way of text based retrieval systems are being replaced by the visual content based systems. The image content has several dominant characteristics like color, texture,shape and it is interesting to see the classification of images on content-basis can be achieved with these features. These different descriptor for the images can form a combined feature vector. However, in order to have optimum performance and to reduce the feature dimensionality for making system real-time, genetic algorithm (GA) based feature selection may be used. 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. For the purpose of assigning the fusion weights of multi-feature similarity scores reasonably, the genetic algorithm is applied. Keywords- Content based image retrieval (CBIR), Genetic Algorithm, image retrieval,fusio