Content-based image indexing and retrieval in ImageRoadMap

ImageRoadMap is a new content-based image retrieval system for retrieval of images by visual information. The system provides full capabilities for indexing and retrieval of images, their visual features and many other diverse data types. We introduce combination of effective indexing methods based on a novel spatial color distribution model. By utilizing Self-Organizing Feature Map (SOFM) and other indexing methods, spatial color distribution, dominant color set, number of objects and other visual features may be computed. It also provides capabilities for similarity measurement and similarity based indexing. ImageRoadMap includes a powerful multi-faceted querying mechanism, which allows queries to be formulated and presented in several different ways. Depending on the characteristics and the nature of the query, the user may choose: Query by Example, Query by Spatial Color Distribution, Query by Color Contents, Query by Sketch, Query by Concept, or a combination of any of the above. The current interface support iterative multi-modal query formulation in which the user presents whatever relevant information that is available through appropriate windows.