A neuromorphic architecture for cortical multi-layer integration of early visual tasks

The characteristics and performances of a hierarchical neural architecture, inspired by models of mammalian visual cortex, are considered. The visual pathway from sensory space to the intermediate (cortical) representation is structured in three layers, with intra and inter-layer connections through feedforward and recurrent pathways. These interconnections provide a complex perceptual organization that integrates the specific functional tasks performed by each layer. This improves the capabilities of the architecture in feature extraction and segregation, further providing clues on the information content of the intermediate representation (primal sketch). Applications to preattentive vision tasks (edge and contour extractions, texture analysis and boundary completion, and defect detection) are presented with satisfactory results.