Algorithms of Vocabulary Tree Hierarchical Semantic Model Image Retrieval

Creating a semantic mapping method is important in solving semantic map.This paper proposes a vocabulary tree hierarchical semantic model image retrieval method.First extracting the characteristics of the image, such as the color information, SIFT feature, and then generating the visual vocabulary to describe the image of visual information.Using Bayesian theory map the visual vocabulary to the semantic subject information, then constructing a hierarchical semantic model.So based on this model we realize a semantic content-based image retrieval algorithms.Through the user's relevance feedback, not only can be added to the positive feedback image, but also can be able to amend the high-level semantic mapping. Results perform stability, and with the increase in the number of feedback retrieval results can improve significantly.