Face Recognition by Cortical Multi-scale Line and Edge Representations. In: Campilho A, Kamel M, editors. Image Analysis and Recognition. Berlin: Springer Berlin Heidelberg; 2006. pp. 329-40. [DOI: 10.1007/11867661_30]

Multi-scale lines and edges in V1 and beyond: brightness, object categorization and recognition, and consciousness

In this paper we present an improved model for line and edge detection in cortical area V1. This model is based on responses of simple and complex cells, and it is multi-scale with no free parameters. We illustrate the use of the multi-scale line/edge representation in different processes: visual reconstruction or brightness perception, automatic scale selection and object segregation. A two-level object categorization scenario is tested in which pre-categorization is based on coarse scales only and final categorization on coarse plus fine scales. We also present a multi-scale object and face recognition model. Processing schemes are discussed in the framework of a complete cortical architecture. The fact that brightness perception and object recognition may be based on the same symbolic image representation is an indication that the entire (visual) cortex is involved in consciousness.

A model of contour extraction including multiple scales, flexible inhibition and attention

A mathematical model of contextual integration and contour extraction in the primary visual cortex developed in a recent work [Ursino, M., & La Cara, G. E. (2004). A model of contextual interactions and contour detection in primary visual cortex. Neural Networks, 17, 719-735] has been significantly improved to include two fundamental additional aspects, i.e., multi-scale decomposition and attention. The model incorporates two independent paths for visual processing corresponding to two different scales. Attention from higher hierarchical levels works by modifying different properties of the network: by selecting the portion of the image to be scrutinized and the appropriate scale, by modulating the threshold of a gating mechanism, and by modifying the width and/or strength of lateral inhibition. Through computer simulations of real complex and noisy black-and-white images, we demonstrate that appropriate selection of the above factors allows accurate analysis of image contours at different levels, from global perception of the overall objects without details, down to a fine examination of minute particulars (such as the lips in a face or the fingers of a hand). Attentive reconfiguration of lateral inhibition plays a key role in the analysis of images at different detail levels.