Fuzzy object patterns for visual indexing and segmentation
In this paper, we propose a fuzzy object pattern (FOP) for the representation of image content. The FOP is derived from view-based object recognition against a pre-defined vocabulary of visual object classes. Tessellation of FOPs over an image is further aggregated spatially to summarize the image content. This description scheme has been deployed in image indexing and retrieval on home photographs with very promising results. Furthermore, the FOP spans a new fuzzy pattern space in which incremental clustering is carried out to aggregate adjacent FOPs into larger regions. As a consequence, dominant regions can be segmented from an image.