| abstract |
Apparatus and an accompanying method for generating a semantically based, linguistically searchable, numeric descriptor of a pre-defined group of input images and which is particularly useful in a system for automatically classifying individual images, on a numerical basis, in, e.g., an image database, and, through a query-by-example paradigm, retrieving a desired image(s) therefrom. Specifically, a signature is computed for each image in a set using multi-level iterative convolution filtering, with pixel values supplied as input to each filtering level being separately convolved with each one of a set of predefined Gaussian kernels. Average and variance vectors, as collective numeric descriptors of all the images in the set, are separately computed across corresponding elements in all the image signatures for the set. A linguistic term, semantically descriptive of all the images in the set, is associated with the numeric descriptors of this set and, with this set, is stored in a database. For image retrieval, the descriptor for any set is accessed by a textual search through the database using the appropriate linguistic term. The descriptor is then compared against accessed signatures for other images in the database in order to retrieve a image, among those stored in the database, that is the most similar to those in the set associated with the descriptor. |