Merging MPEG-7 descriptors for image content analysis

A segmentation algorithm for image content analysis is presented. We assume that the textures in a video scene can be labeled subjectively relevant or irrelevant. Relevant textures are defined as containing subjectively meaningful details, while irrelevant textures can be seen as image content with less important subjective details. We apply this idea to video coding using a texture analyzer and a texture synthesizer. The texture analyzer (encoder side) identifies the texture regions with unimportant subjective details and generates side information for the texture synthesizer (decoder side), which in turn inserts synthetic textures at the specified locations. The focus of this paper is the texture analyzer, which uses multiple MPEG-7 descriptors simultaneously for similarity estimation. The texture analyzer is based on a split and merge segmentation approach. Its current implementation yields an identification rate of up to 96% and an average gain of up to 10% compared to single descriptor usage.