Contour detection is a salient operation in many computer vision applications as it extracts
features that are important for distinguishing objects in scenes. It is believed to be a primary …

To effectively perform visual tasks like detecting contours, the visual system normally needs
to integrate multiple visual features. Sufficient physiological studies have revealed that for a …

The goal of this work is to present a computational model for contour detection, based on the
surround suppression mechanisms of the primary visual cortex, in which the strength of …

This paper addresses contour detection by simulating the human visual system and its
application to visual object classification. Unlike previously designed bioinspired contour …

Contour is a critical feature for image description and object recognition in many computer
vision tasks. However, detection of object contour remains a challenging problem because …

We propose a biologically motivated method, called nonclassical receptive field (non-CRF)
inhibition (more generally, surround inhibition or suppression), to improve contour detection …

A contour detection model, inspired by the behavior of the primary visual cortex, is
presented. The response of a central stimulus in the receptive field is affected by the …

We propose a biologically motivated computational step, called non-classical receptive field
(non-CRF) inhibition, to improve the performance of contour detectors. Non-CRF inhibition is …

We propose a biologically motivated computational step, called nonclassical receptive field
(non-CRF) inhibition, to improve the performance of contour detectors. We introduce a …

We propose a computational step, called surround suppression, to improve detection of
object contours and region boundaries in natural scenes. This step is inspired by the …