Semantics-Sensitive Integrated Matching

We present here SIMPLIcity (Semantics-sensitive Integrated Matching for Picture Libraries), an image database retrieval system, which uses high-level semantics classification and integrated region matching (IRM) based upon image segmentation. The SIMPLIcity system represents an image by a set of regions, roughly corresponding to objects, which are characterized by color, texture, shape, and location. Based on segmented regions, the system classifies images into semantically meaningful categories. These high-level categories, such as textured-nontextured, indoor-outdoor, objectionable-benign, graph-photograph, enhance retrieval by narrowing down the searching range in a database and permitting semantically-adaptive searching methods. A measure for the overall similarity between images is defined by a region-matching scheme that integrates properties of all the regions in the images. Armed with this global similarity measure, the system provides users a simple querying interface. The integrated region matching (IRM) similarity measure is insensitive to inaccurate segmentation.