FOCUS: A system for searching for multi-colored objects in a diverse image database

摘要

We describe a new multi-phase, color-based image retrieval system (FOCUS) which is capable of identifying multi-colored query objects in an image in the presence of significant, interfering backgrounds. The query object may occur in arbitrary sizes, orientations, and locations in the database images. Scale and rotation invariant color features have been developed to describe an image, such that the matching process is fast even in the case of complex images. The first phase of processing matches the query object color with the color content of an image computed as the peaks in the color histogram of the image. The second phase matches the spatial relationships between color regions in the image with the query using a spatial proximity graph (SPG) structure designed for the purpose. Processing at coarse granularity is preferred over pixel-level processing to produce simpler graphs, which significantly reduces computation time during matching. The speed of the system and the small storage overhead make it suitable for use in large databases with online user interfaces. Test results with multi-colored query objects from man-made and natural domains show that FOCUS is quite effective in handling interfering backgrounds and large variations in scale. The experimental results on a database of diverse images highlights the capabilities of the system.