A new approach to indexing a specialized database by utilizing the color and spatial domain knowledge available for the database is described. This approach is illustrated by using it to provide a solution to the problem of indexing images of flowers for searching a flower patents database by color. The flower region is isolated from the background by using an automatic iterative segmentation algorithm with domain knowledge-driven feedback. 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. The system provides a perceptually correct retrieval with natural language queries by using a natural language color classification derived from the ISCC-NBS color system and the X Window color names. The effectiveness of the strategy on a test database is demonstrated. replication is much more effective at decreasing the query response time than collection partitioning for a loaded system, even with {em fewer} resources, and it requires only modest query locality. Our results also show that partial collection replication performs better than collection selection when there exists enough query locality, and it performs worse when the collection access is fairly uniform after collection selection. Finally our results show that replica and collection selection can be combined to provide quick response time for a terabyte of text. Changes of system configurations do not significantly change the relative improvements due to partial collection replication and collection selection, although they affect the absolute response time.