Auto-expanded multi query examples technology in content-based image retrieval

摘要

In order to narrow the semantic gap existing in content-based image retrieval (CBIR), a novel retrieval technology called auto-extended multi query examples (AMQE) is proposed. It expands the single one query image used in traditional image retrieval into multi query examples so as to include more image features related with semantics. Retrieving images for each of the multi query examples and integrating the retrieval results, more relevant images can be obtained. The property of the recall-precision curve of a general retrieval algorithm and the K-means clustering method are used to realize the expansion according to the distance of image features of the initially retrieved images. The experimental results demonstrate that the AMQE technology can greatly improve the recall and precision of the original algorithms.