Flexible image decomposition for multimedia indexing and retrieval

摘要

Content-based image and, more generally, multimedia retrieval calls for a semantic understanding of the content of an image. However, the discrepancy between any automated segmentation technique and a operator-based segmentation is now established. There is therefore a strong need for a technique that exploits the best of analytical segmentation techniques while remaining flexible enough to allow for a useful decomposition of the image. In this paper, we describe an interactive image segmentation framework and applications where this framework is essential. Our technique is general enough to allow a generic segmentation technique to be embedded and optimally exploited. The principle is to efficiently obtain a fine-to-coarse image decomposition and represent this structure using an XML description scheme. When browsing through this pyramid, the user will retrieve and mark semantically useful structures within the document. The result may then be used in different contexts such as image indexing and annotation, object-based multimedia query formulation, object tracking in video, etc. We first study the conditions for a base segmentation technique to fit within our framework. Then, we show that our framework provides a solution to typical problems encountered in the context of multimedia information indexing and retrieval. We detail an example Java-based implementation which may be used as a stand-alone tool or as a module within other applications.