A novel interactive image retrieval method based on LSH and SVM

Content-based image retrieval (CBIR) has attracted people´s attention for many years, while the semantic gap and curse of dimensionality are still two open questions of CBIR. In this paper, we propose a new interactive image retrieval method based on locality-sensitive hashing (LSH) and support vector machine (SVM): LSH is adopted to overcome the curse of dimensionality and a SVM-based relevance feedback (RF) scheme is introduced to shorten the semantic gap. The experimental results show the effectiveness of the proposed method.