A neural model of contour integration in the primary visual cortex
Neural Computation
Fast synchronization of perceptual grouping in laminar visual cortical circuits
Neural Networks - 2004 Special issue Vision and brain
A model of contextual interactions and contour detection in primary visual cortex
Neural Networks - 2004 Special issue Vision and brain
A Cortical Mechanism for Triggering Top-Down Facilitation in Visual Object Recognition
Journal of Cognitive Neuroscience
A model of surround suppression through cortical feedback
Neural Networks
Homeostatic synaptic scaling in self-organizing maps
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
A neural network implementation of a saliency map model
Neural Networks
Face recognition by cortical multi-scale line and edge representations
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
A computational model for boundary detection
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
Contour detection based on nonclassical receptive field inhibition
IEEE Transactions on Image Processing
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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.