Automatic Feature Extraction and Indexing for Content-Based Visual Query

: Content-based indexing and query has been considered as a powerful technique for accessing large visual information systems (databases and video servers). By extracting and indexing the visual contents of the images such as texture, color, and shape, users may search desired images by specifying the image contents directly. However, a practical and economical solution cannot afford extensive user involvement. This paper proposes an approach in which image processing technology is explored to the limit of its capability for automatic extraction and indexing of image features. We relax the criterion of image content recognition that concrete 3D objects can be successfully segmented from 2D images. Instead, we aim to index the prominent image regions with distinctive features only. By combining multiple modalities of useful signal features, we hope to characterize the prominent image objects efficiently and effectively. In order to further explore the maximum synergy between feature ex..