Abstract:

Recently, there are two possible ways to achieve efficiency of choosing an effective dimension algorithm and using an appropriate relevance feedback technique in image retrieval. Locality Preserving Projections （LPP）is an effective linear dimensionality reduction algorithm, and it preserves the image structure. In order to improve the efficiency of the retrieval accuracy, the article incorporates the users’ feedbacks. Using the algorithm of LPP, we map the data points to a subspace. In this subspace, a weighted graph G can be constructed by a candidate data set  to consist of k nearest neighbors of the query data points, and query data set. We then compute the geodesic distances between all pairs of vertices of the graph G , and sort them, obtain feedback results. The experimental results show that the algorithm can effectively improve retrieval accuracy, and an optimal retrieval results can be obtained.

Key words: image retrieval；dimension reduction；locality preserving projection；relevance feedback