Content Based Image Retrieval of User’s Interest Using Interactive Genetic Algorithm: a Review

-In present time, digital image libraries and other multimedia databases have been suddenly expanded. Therefore Semantic gap that between the visual features and human semantics has become very important area of research known as content based image retrieval (CBIR). If there is a need of retrieving an image from a large image database effectively and precisely, the development of content-based image retrieval (CBIR) system has become an important research issue. The need for improving the retrieval accuracy of image retrieval systems and narrowing down the semantic gap is high in view of the fast growing need of image retrieval. In this paper we review, a user-oriented technique for CBIR method based on low level visual features and interactive genetic algorithm (IGA). Before applying the visuality features we have divided the images into k x k blocks and a block wise comparison has been done. Color attributes like the mean value, the standard deviation, and the image bitmap of a color image are used as the features for retrieval. In addition, the entropy based on the gray level co-occurrence matrix considered as the texture features and the Canny edge detection technique for image can be considered as edge features. Finally, some future research directions and problems of image retrieval are presented.