Separation of Figure from Ground as an Adaptive Image Processing

We define the separation of figure from ground as a visual-attribute-dependent and task-dependent representation of sensory information in higher-level visual processes. A computer model for adaptive segmentation of 2-D visual objects (Dudkin et al, 1995 Proceedings of SPIE 122) was developed in these studies. The description and separation of figure from ground are implemented by spatial frequency filters and feature detectors performing as self-organising mechanisms. The simulation of control processes caused by attention (top - down), and lateral, frequency-selective, and cross-orientation inhibition (bottom - up) determines the adaptive image processing.

The first stage is the estimation of input image produced by the analysis of the spatial brightness distribution by algorithms calculating the vector of primary descriptive attributes. These results provide the synthesis of control processes based on several algorithms, each of which transforms descriptive attributes into separate control parameters. The creation of two primary descriptions: ‘sustained’ (contours) and ‘transient’ (fragments with homogeneous intensity), and the selection of feature-detection operators are governed by the complete set of control parameters. The primary descriptions allow formation of the intermediate image description in which similar elements are grouped by identical brightness, colour, spatial position, curvature, and texture according to Gestalt concepts. To divide the image into basic areas and to extract fragments which belong to a putative figure, all these descriptions are combined into the final integrated image representation. The model has been tested on various images.