Indexing flowers by color names using domain knowledge-driven segmentation

We describe a solution to the problem of indexing images of flowers for searching a flower patents database by color. We use a natural language color classification derived from the ISCC-NBS color system and the X Window color names to effectively use the domain knowledge available, provide perceptually correct retrieval and allow natural language queries. We have developed an automatic iterative segmentation algorithm with knowledge-driven feedback to isolate a flower region from the background. The color of the flower is defined by the color names present in the flower region and their relative proportions. The database can be queried by example and by color names. We demonstrate the effectiveness of the strategy on a test database.