There is a huge increase in the multimedia data, such as images and videos on the internet. This is because of the sudden large increase in the use of computers and digital devices all around the world in various fields. The needs of retrieval systems that deal with huge data repositories of multimedia databases have increased with time The goal of the proposed system is to increase both the accuracy of the retrieved images and the speed of image retrieval. And Decrease the difference between low-level features and the human precipitation of image features “semantic gap”. These objectives will be achieved by the combination between fuzzy relevance feedback techniques. Also, in order to satisfy these goals, low level feature extraction algorithms, deriving high-level semantic features, similarity, measurement, and query by keyword are utilized in the system. The evaluation of the retrieved results of this system showed that the system is working in an effective way for an online processing system.