A Qualitative, Multi-scale Grammar For Image Description and Analysis

A qualitative image description grammar with automatic image fitting and object modelling algorithms is presented. The grammar is based on assigning a square sub-region of an image one of a finite number of qualitative labels, based on the occurrence of object boundaries within this region and how these intersect the region boundary. In the general case there is an infinite number of such labels, however the use of a multi-scale approach allows a finite (small) number of labels at each scale. This makes the problem tractable within a constraint satisfaction type framework. Constraints are put on neighboring labels based on the premise that all object boundaries are continuous, having no ending within an image. A minimum description length (MDL) approach is suggested for description hypothesis selection (based on colour histograms) and methods for (constraint based) hypothesis generation/adaption and (Hidden Markov Model based) a-priori shape modelling are presented.