The paper proposes an adaptive retrieval approach based on the concept of relevance-feedback, which establishes a link between high-level concepts and low-level features, using the user's feedback not only to assign proper weights to the features, but also to dynamically select them within a large collection of parameters. The target is to identify a set of relevant features according to a user query while at the same time maintaining a small sized feature vector to attain better matching and lower complexity. To this end, the image description is modified during each retrieval by removing the least significant features and better specifying the most significant ones. The feature adaptation is based on a hierarchical approach. The weights are then adjusted based on previously retrieved relevant and irrelevant images without further user-feedback. The algorithm is not fixed to a given feature set. It can be used with different hierarchical feature sets, provided that the hierarchical structure is defined a priori. Results achieved on different image databases and two completely different feature sets show that the proposed algorithm outperforms previously proposed methods. Further, it is experimentally demonstrated that it approaches the results obtained by state-of-the-art feature-selection techniques having complete knowledge of the data set.

One of the main problems in content-based image retrieval is the query initialization and so-called "page-zero problem". The early solutions range from the use of similar images to definition of a user sketch (using color, texture, or shape information). The latter implies user's choice of a starting point, which can be achieved in different ways. In this paper a new approach to this problem is proposed based on relevance feedback. The objective is to provide a very simple interface, where at each iteration the user should make a binary decision based on two presented images. Experimental results show that the proposed approach performs very well compared to existing methods, while providing a very simple and intuitive interaction