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Published on: August 30, 2013
Detecting low shape-frequencies in smooth and jagged contours
Nicolaas Prins1, Frederick A A Kingdom, Anthony Hayes
1Department of Psychology, University of Mississippi, Oxford, MS 38677, USA. nprins@olemiss.edu
Visual contour processing uses two filter stages. Our study shows that detecting deviations from linearity relies on various spatial scales and primarily uses local filter positions, not orientations, especially for low-frequency contours.
Area of Science:
- Visual perception
- Computational neuroscience
- Image processing
Background:
- Visual contour coding is often modeled with two stages: local luminance filtering and spatial integration.
- The role of spatial scales and feature extraction (orientation vs. position) in early visual processing remains an active research area.
Purpose of the Study:
- To investigate the spatial scales of luminance filters involved in detecting contour deviations from linearity.
- To determine whether local orientation or position information from first-stage filters is used in the second stage for co-linearity failure detection.
Main Methods:
- Experiments focused on detecting co-linearity failure in smooth and jagged contours across varying spatial and shape frequencies.
- Analysis of detection thresholds in relation to the spatial scales and feature properties (orientation, position) of early luminance filters.
Main Results:
- Detection thresholds for co-linearity failure were largely independent of the spatial scale of luminance information.
- Detection of co-linearity failure in low shape-frequency contours predominantly utilized the local positions, rather than orientations, of first-stage luminance filters.
Conclusions:
- Early luminance filters tuned to a range of spatial scales can effectively mediate the detection of co-linearity failure.
- Contour co-linearity failure detection at low frequencies relies on local filter positions. Contour orientation may be signaled by second-order filters acting on these positions.
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