Research and Application of Image Retrieval Improved Algorithm Based on BOF

Abstract

The feature description of image and the index mechanism of the feature are the keys to realize the content-based image retrieval, aiming at the problem of massive image data and “dimension curse”, this paper proposes the BOF-based image retrieval improved algorithm, and combines with VLAD and soft assignment it generates the soft assignment local aggregation descriptor (SA-VLAD) which has a better ability to resist the dimension reduction and a higher recognition rate. When the index mechanism IVFADC is at query time, to ensure the recall ratio and precision rate of the result, the candidates inverted index chain are increased, which leads to the problems of distance calculation and the query time’s increasing. For this point, in the index phase, the scattered distribution is carried out aiming at the database vector, which reduces the burden of distance calculation, and improves the quality of the query results at the same time. The experimental results show that the algorithm in this paper obtains a good effect in the content-based massive image database retrieval.