Learning-Based Approach for Semantic Image Retrieval by Using a Dynamic Semantic Network

Nowadays, image retrieval systems, emphasize the combining of high level semantics and low level visual features in the image indexing process and of course the performance of such systems for image retrieval is increased with perfect semantic network. In this research, a dynamic high level semantic network in synonym sets of keywords is used and a dynamic approach is presented for updating the semantic network and semantic contents of the images in an interactive way. The proposed approach, certainly, executes a novel kind of long term learning-based on user's opinion in the several interactions with system, and relates the behavior of system to the behavior of users in the recognition process of semantic similarity between the images. The evaluating results of system's performance show improving the accuracy of semantic network and semantic contents related to the images after applying the long term learning process.