Texture similarity queries and relevance feedback for image retrieval

The measurement of perceptual similarities between textures is a difficult problem in applications such as image classification and image retrieval in large databases. Among the various texture analysis methods or models developed over the years, those based on a multi-scale multi-orientation paradigm seem to give more reliable results with respect to human visual judgement. This work introduces new texture features extracted from an oriented multi-scale pyramid structure called a "steerable pyramid". These texture features are then used in the search through an image database to find the most "similar" textures to a selected one. We have also introduced a relevance feedback to improve the retrieval quality.