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 …

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 …

The broad region outside the classical receptive field (CRF) of a neuron in the primary visual
cortex (V1), namely non-CRF (nCRF), exerts robust modulatory effects on the responses to …

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

The responses of neurons in the primary visual cortex (V1) to stimulus inside the receptive
field (RF) can be markedly modulated by stimuli outside the classical receptive field. The …

Physiological studies have revealed that the center–surround mechanism widely exists in
the primary stages of the human visual system, such as the retina, lateral geniculate nucleus …

This work develops a biologically inspired neural network for contour detection in natural
images by combining the nonclassical receptive field modulation mechanism with a deep …

Contour integration is an important intermediate stage of object recognition, in which line
segments belonging to an object boundary are perceptually linked and segmented from …

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 …