Third-derivative filters predict edge locations in spatial vision

Stuart A. Wallis; Mark A. Georgeson

Third-derivative filters predict edge locations in spatial vision

Stuart A. Wallis, Mark A. Georgeson

Optometry

Research output: Unpublished contribution to conference › Poster › peer-review

Abstract

Edge detection is crucial in visual processing. Previous computational and psychophysical models have often used peaks in the gradient or zero-crossings in the 2nd derivative to signal edges. We tested these approaches using a stimulus that has no such features. Its luminance profile was a triangle wave, blurred by a rectangular function. Subjects marked the position and polarity of perceived edges. For all blur widths tested, observers marked edges at or near 3rd derivative maxima, even though these were not 1st derivative maxima or 2nd derivative zero-crossings, at any scale. These results are predicted by a new nonlinear model based on 3rd derivative filtering. As a critical test, we added a ramp of variable slope to the blurred triangle-wave luminance profile. The ramp has no effect on the (linear) 2nd or higher derivatives, but the nonlinear model predicts a shift from seeing two edges to seeing one edge as the ramp gradient increases. Results of two experiments confirmed such a shift, thus supporting the new model. [Supported by the Engineering and Physical Sciences Research Council].

Original language	English
Publication status	Published - 2007
Event	13th European Conference on Visual Perception - Arezzo (IT), Italy Duration: 27 Aug 2007 → 31 Aug 2007

Conference

Conference	13th European Conference on Visual Perception
Country/Territory	Italy
City	Arezzo (IT)
Period	27/08/07 → 31/08/07

Bibliographical note

Abstract published in Applied Vision Association Annual 2007 Meeting "Active and Passive Vision", Perception, 36 (Suppl. S), pp. 1401-1402. ISSN 0001-4966. If you have discovered material in AURA which is unlawful e.g. breaches copyright, (either yours or that of a third party) or any other law, including but not limited to those relating to patent, trademark, confidentiality, data protection, obscenity, defamation, libel, then please read our Takedown Policy and contact the service immediately.

Keywords

edge detection
visual processing
2nd derivative
signal edges
luminance profile
perceived edges
blur widths
3rd derivative maxima
1st derivative maxima
2nd derivative zero-crossings

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ECVP_2007_poster6.pdf
Abstract published in Applied Vision Association Annual 2007 Meeting "Active and Passive Vision", Perception, 36 (Suppl. S), pp. 1401-1402. ISSN 0001-4966. If you have discovered material in AURA which is unlawful e.g. breaches copyright, (either yours or that of a third party) or any other law, including but not limited to those relating to patent, trademark, confidentiality, data protection, obscenity, defamation, libel, then please read our Takedown Policy and contact the service immediately.

Cite this

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title = "Third-derivative filters predict edge locations in spatial vision",

abstract = "Edge detection is crucial in visual processing. Previous computational and psychophysical models have often used peaks in the gradient or zero-crossings in the 2nd derivative to signal edges. We tested these approaches using a stimulus that has no such features. Its luminance profile was a triangle wave, blurred by a rectangular function. Subjects marked the position and polarity of perceived edges. For all blur widths tested, observers marked edges at or near 3rd derivative maxima, even though these were not 1st derivative maxima or 2nd derivative zero-crossings, at any scale. These results are predicted by a new nonlinear model based on 3rd derivative filtering. As a critical test, we added a ramp of variable slope to the blurred triangle-wave luminance profile. The ramp has no effect on the (linear) 2nd or higher derivatives, but the nonlinear model predicts a shift from seeing two edges to seeing one edge as the ramp gradient increases. Results of two experiments confirmed such a shift, thus supporting the new model. [Supported by the Engineering and Physical Sciences Research Council].",

keywords = "edge detection, visual processing, 2nd derivative, signal edges, luminance profile, perceived edges, blur widths, 3rd derivative maxima, 1st derivative maxima, 2nd derivative zero-crossings",

author = "Wallis, {Stuart A.} and Georgeson, {Mark A.}",

note = "Abstract published in Applied Vision Association Annual 2007 Meeting {"}Active and Passive Vision{"}, Perception, 36 (Suppl. S), pp. 1401-1402. ISSN 0001-4966. If you have discovered material in AURA which is unlawful e.g. breaches copyright, (either yours or that of a third party) or any other law, including but not limited to those relating to patent, trademark, confidentiality, data protection, obscenity, defamation, libel, then please read our Takedown Policy and contact the service immediately.; 13th European Conference on Visual Perception ; Conference date: 27-08-2007 Through 31-08-2007",

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TY - CONF

T1 - Third-derivative filters predict edge locations in spatial vision

AU - Wallis, Stuart A.

AU - Georgeson, Mark A.

N1 - Abstract published in Applied Vision Association Annual 2007 Meeting "Active and Passive Vision", Perception, 36 (Suppl. S), pp. 1401-1402. ISSN 0001-4966. If you have discovered material in AURA which is unlawful e.g. breaches copyright, (either yours or that of a third party) or any other law, including but not limited to those relating to patent, trademark, confidentiality, data protection, obscenity, defamation, libel, then please read our Takedown Policy and contact the service immediately.

PY - 2007

Y1 - 2007

N2 - Edge detection is crucial in visual processing. Previous computational and psychophysical models have often used peaks in the gradient or zero-crossings in the 2nd derivative to signal edges. We tested these approaches using a stimulus that has no such features. Its luminance profile was a triangle wave, blurred by a rectangular function. Subjects marked the position and polarity of perceived edges. For all blur widths tested, observers marked edges at or near 3rd derivative maxima, even though these were not 1st derivative maxima or 2nd derivative zero-crossings, at any scale. These results are predicted by a new nonlinear model based on 3rd derivative filtering. As a critical test, we added a ramp of variable slope to the blurred triangle-wave luminance profile. The ramp has no effect on the (linear) 2nd or higher derivatives, but the nonlinear model predicts a shift from seeing two edges to seeing one edge as the ramp gradient increases. Results of two experiments confirmed such a shift, thus supporting the new model. [Supported by the Engineering and Physical Sciences Research Council].

AB - Edge detection is crucial in visual processing. Previous computational and psychophysical models have often used peaks in the gradient or zero-crossings in the 2nd derivative to signal edges. We tested these approaches using a stimulus that has no such features. Its luminance profile was a triangle wave, blurred by a rectangular function. Subjects marked the position and polarity of perceived edges. For all blur widths tested, observers marked edges at or near 3rd derivative maxima, even though these were not 1st derivative maxima or 2nd derivative zero-crossings, at any scale. These results are predicted by a new nonlinear model based on 3rd derivative filtering. As a critical test, we added a ramp of variable slope to the blurred triangle-wave luminance profile. The ramp has no effect on the (linear) 2nd or higher derivatives, but the nonlinear model predicts a shift from seeing two edges to seeing one edge as the ramp gradient increases. Results of two experiments confirmed such a shift, thus supporting the new model. [Supported by the Engineering and Physical Sciences Research Council].

KW - edge detection

KW - visual processing

KW - 2nd derivative

KW - signal edges

KW - luminance profile

KW - perceived edges

KW - blur widths

KW - 3rd derivative maxima

KW - 1st derivative maxima

KW - 2nd derivative zero-crossings

M3 - Poster

T2 - 13th European Conference on Visual Perception

Y2 - 27 August 2007 through 31 August 2007

ER -

Third-derivative filters predict edge locations in spatial vision

Abstract

Conference

Bibliographical note

Keywords

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Cite this