Preattentive grouping and attentive selection for early visual computation

The segmentation of objects in a real world scene is a prerequisite for any higher level recognition or interpretation process. Biological visual systems exploit efficient mechanisms for object extraction which seem to be mostly data driven. We propose a network for perceptual grouping inspired from neurophysiological and psychophysical findings, incorporating a phase diffusion process which labels the whole image into its constituent objects and the background, followed by a selective attention stage which sequentially extracts objects in the scene. The image is processed by four successive stages, copying the design of visual cortical mechanisms. Direction specific edge responses are used as starting points for a competitive and cooperative phase process. The resulting phase image is processed by an attention mechanism, extracting homogeneous regions using both spatial and phase information, followed by the generation of a saccadic signal