Efficient content-based image retrieval using automatic feature selection

We describe a self-organizing framework for content-based retrieval of images from large image databases at the object recognition level. The system uses the theories of optimal projection for optimal feature selection and a hierarchical image database for rapid retrieval rates. We demonstrate the query technique on a large database of widely varying real-world objects in natural settings, and show the applicability of the approach even for large variability within a particular object class.