Perception of stationary plaids: The role of spatial filters in edge analysis

@article{Georgeson1997PerceptionOS,
  title={Perception of stationary plaids: The role of spatial filters in edge analysis},
  author={Mark A. Georgeson and Tim S. Meese},
  journal={Vision Research},
  year={1997},
  volume={37},
  pages={3255-3271}
}
Adaptive Filtering in Spatial Vision: Evidence from Feature Marking in Plaids
TLDR
It is suggested that combination and segmentation of spatial filters in the patchwise Fourier domain underpins the perceptual segmentation observed in the experiments.
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A plaid pattern is mediated by a combination of orientation-selective mechanisms, which can be explained by a multiple-mechanism divisive inhibition model, which contains several orientation- selective mechanisms.
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The time course of feature integration in plaid patterns revealed by meta- and paracontrast masking.
TLDR
The present study reveals the time course of this process by applying meta- and paracontrast masking to both simple oriented and plaid gratings, and discusses in how far these results could also be explained by the dynamics of cross-orientation suppression and how they might relate to the process of feature integration in plaids.
Low spatial frequencies are suppressively masked across spatial scale, orientation, field position, and eye of origin.
TLDR
The results confirm that above detection threshold, cross-channel masking involves contrast suppression and not (purely) mask-induced noise, and conclude that cross-Channel masking can be a powerful phenomenon, particularly at low test spatial frequencies and when mask and test are presented to different eyes.
Feedback and Surround Modulated Boundary Detection
TLDR
A biologically-inspired edge detection model in which orientation selective neurons are represented through the first derivative of a Gaussian function resembling double-opponent cells in the primary visual cortex (V1), which shows a big improvement compared to the current non-learning and biologically- inspired state-of-the-art algorithms while being competitive to the learning-based methods.
Contour integration and scale combination processes in visual edge detection.
TLDR
This work determined spatial-frequency tuning for the detection of contours composed of broadband edge elements, alternating with narrow-band Gabor elements, to determine how these two types of combination fit together.
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Perceived spatial structure was found to depend on plaid orientation: compound structures were perceived more often when the plaid components were balanced around the cardinal axes of the retina, and it was suggested that the principles governing the combination of oriented-filter outputs might be learnt during the development of the visual system by using a Hebb-type rule.
Human vision combines oriented filters to compute edges
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TLDR
The outlines of a model for edge finding in human vision are proposed, where two-component plaid components are processed through cortical, orientationselective filters that are subject to attenuation by forward masking and adaptation, and zero crossings in the combined output are used to determine edge locations.
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