Comparative Study of Neural Networks for Image Retrieval

In this paper, we describe two new approaches to content-based image retrieval (CBIR) based on preference information provided by the user interacting with an image search system. First, we present the existing methods of image retrieval with relevance feedback, which serve then as a reference for the new approaches. The first extension of the distance function-based CBIR approach makes it possible to apply this approach to complex objects .Next we discuss the second approach for image retrieval. That new algorithm is based on an approximation of user preferences by a neural network. Finally we discuss the advantages and disadvantages and further improvements and future scope in this particular area.