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Edges and bars: where do people see features in 1-D images?
Gillian S. Hesse
, Mark A. Georgeson
Optometry
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Contribution to journal
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Article
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peer-review
35
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Citations (Scopus)
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Keyphrases
Amplitude Spectrum
50%
Burr
50%
By Design
50%
Computer Vision-based
50%
Contrast Energy
50%
Cursor
50%
Detailed Model
50%
Early Vision
100%
Energy Peak
50%
Feature Detection
50%
First-order Features
50%
Fourier Components
50%
Gaussian Derivative
50%
Human Vision
100%
Local Contrast
50%
Local Energy
50%
Local Phase
50%
Luminance Distribution
50%
Luminance Gradient
50%
Perceived Position
50%
Phase Alignment
50%
Phase Offset
50%
Spatial Alignment
50%
Spatial Derivatives
50%
Spatial Distribution
50%
Spatial Frequency
50%
Square Wave
50%
Engineering
Amplitude Spectrum
50%
Burrs
50%
Computervision
50%
Detailed Model
50%
Early Vision
100%
Features Detection
50%
Fourier Component
50%
Gaussians
50%
Human Vision
100%
Local Contrast
50%
Peak Energy
50%
Peak Luminance
50%
Spatial Distribution
50%
Spatial Frequency
50%
Earth and Planetary Sciences
Computer Vision
100%
Spatial Distribution
100%
Square Wave
100%
Agricultural and Biological Sciences
Computer Vision
100%