Content Based Indexing of Image and Video Databases by Global and Shape Features

Indexing and retrieval methods based on the image content are required to effectively use information from the larger and larger repositories of digital images and videos currently available. Both global (colour, texture, motion, etc. . . ) and local (object shape, etc. . . ) features are needed to perform a reliable content based retrieval. In this paper we present a method for automatic extraction of global image features, like colour and motion parameters, and their use for data restriction in video datatabase querying. Further retrieval is therefore accomplished, in a restricted set of images, by shape feature (skeleton, local simmetry, moments, correlation, etc.) local search. The proposed indexing methodology has been developed and tested inside JACOB, a prototypal system for contentbased video database querying. 1. Introduction Effective querying in image and video databases should be directly grounded on the image content. In domain independent cases, describing semantics o..