The Multiple Determination of Illusory Contours: 1. A Review

Perception ◽  
1983 ◽  
Vol 12 (3) ◽  
pp. 281-291 ◽  
Author(s):  
Diane F Halpern ◽  
Billie Salzman
Keyword(s):  
Illusory Contour ◽  
Brightness Contrast ◽  
Simultaneous Contrast ◽  
Illusory Contours ◽  
Contour Perception ◽  
Partial Activation ◽  
Multiple Determination

Four theories of illusory-contour perception are reviewed—brightness contrast (simultaneous contrast, assimilation, and dissimilation), depth/completion, partial activation of neural feature analyzers, and the diffuse—sharp dichotomy. It is concluded that the processes and mechanisms involved in illusory-contour perception most likely depend upon the stimulus elements used in the illusory-contour display.

The Multiple Determination of Illusory Contours: 2. An Empirical Investigation

Perception ◽  
1983 ◽  
Vol 12 (3) ◽  
pp. 293-303 ◽  
Author(s):  
Diane F Halpern ◽  
Billie Salzman ◽  
Wayne Harrison ◽  
Keith Widaman
Keyword(s):  
Illusory Contour ◽  
Factor Model ◽  
Illusory Contours ◽  
Contour Perception ◽  
Confirmatory Factor ◽  
Linear Effects ◽  
Explained Variance ◽  
Taxonomic Approach ◽  
Contour Strength

Judgments of contour strength or saliency for twenty-four illusory-contour configurations were subjected to a confirmatory factor analysis. A four-factor model that posited the involvement of simultaneous contrast, linear effects (assimilation and dissimilation), depth/completion cues, and feature analyzers accounted for a substantial proportion of the variance in judgments of illusory-contour strength. The hierarchical addition of a fifth factor, diffuse illusory contours, significantly improved the overall fit of the model, but added little to the proportion of explained variance. The taxonomic approach adopted provides support for a multiprocess model of illusory-contour perception.

The Determinants of Illusory-Contour Perception

Perception ◽  
1981 ◽  
Vol 10 (2) ◽  
pp. 199-213 ◽  
Author(s):  
Diane F Halpern
Keyword(s):  
Illusory Contour ◽  
Experimental Results ◽  
Brightness Contrast ◽  
Apparent Depth ◽  
Primary Role ◽  
Illusory Contours ◽  
Contour Perception

The term ‘illusory contours' refers to contours perceived where none physically exist. Three hypotheses that have been successful in their ability to account for this phenomenon invoke: (i) apparent depth; (ii) brightness contrast; and (iii) use of figural cues. An experiment has been designed to determine the extent to which each hypothesis accounts for the overall variation in subjects' responses to illusory contours when all three hypotheses are considered simultaneously. Experimental results suggest that different processes may assume a primary role in the perception of illusory contours depending upon the type of inducing area and the configuration. The results highlight the multifaceted nature of the processes involved, and indicate that no single theory can explain the perception of illusory contours.

The Generic-Viewpoint Assumption and Illusory Contours

Perception ◽  
10.1068/p3016 ◽  
2000 ◽  
Vol 29 (3) ◽  
pp. 303-312
Author(s):  
Marc K Albert ◽  
Donald D Hoffman
Keyword(s):  
Machine Vision ◽  
Infinite Number ◽  
Illusory Contour ◽  
Human Vision ◽  
Visual Images ◽  
Illusory Contours ◽  
Contour Perception ◽  
The World

Visual images are ambiguous. Any image, or collection of images, is consistent with an infinite number of possible scenes in the world. Yet we are generally unaware of this ambiguity. During ordinary perception we are generally aware of only one, or perhaps a few of these possibilities. Human vision evidently exploits certain constraints—assumptions about the world and images formed of it—in order to generate its perceptions. One constraint that has been widely studied by researchers in human and machine vision is the generic-viewpoint assumption. We show that this assumption can help to explain the widely discussed fact that outlines of blobs are ineffective inducers of illusory contours. We also present a number of novel effects and report an experiment suggesting that the generic-viewpoint assumption strongly influences illusory-contour perception.

scholarly journals Influence of Parallel and Orthogonal Real Lines on Illusory Contour Perception

2010 ◽  
Vol 103 (1) ◽  
pp. 55-64 ◽  
Author(s):  
Barbara Dillenburger ◽  
Anna W. Roe
Keyword(s):  
Real Line ◽  
Illusory Contour ◽  
Contextual Effects ◽  
Line Orientation ◽  
The Other ◽  
Imaging Data ◽  
Illusory Contours ◽  
Contour Perception ◽  
Parallel Lines

Real lines and illusory contours (ICs) have been reported to either interfere with or facilitate the perception of the other, depending on real line orientation and contrast. Here we investigate contextual effects of real lines on illusory contour perception. Curvature discrimination thresholds of Kanizsa-contours were measured for superimposed real lines of different sub- and suprathreshold contrasts. We find that parallel lines interfere with curvature discrimination at suprathreshold, whereas orthogonal lines interfere at subthreshold contrasts. We did not find stable facilitating effects of lines in any orientation or contrast. These results are discussed in relation to existing physiological and imaging data.

Affect from mere perception: Illusory contour perception feels good.

Emotion ◽  
2017 ◽  
Vol 17 (5) ◽  
pp. 856-866 ◽  
Author(s):  
Thorsten M. Erle ◽  
Rolf Reber ◽  
Sascha Topolinski
Keyword(s):  
Illusory Contour ◽  
Contour Perception

Insect perception of illusory contours

1992 ◽  
Vol 337 (1279) ◽  
pp. 59-64 ◽  
Keyword(s):  
Human Visual System ◽  
Illusory Contour ◽  
Optic Lobe ◽  
Insect Vision ◽  
Local Contrast ◽  
Fault Line ◽  
Illusory Contours ◽  
Striped Pattern ◽  
Processing Power ◽  
As If

The human visual system sees an illusory contour where there is a fault line across a regular striped pattern. We demonstrate that bees respond as if they see the same illusory contour. There is also a type of neuron in the lobula of the dragonfly optic lobe which responds directionally to motion of the illusory contour as if to an edge or line. Apparently insects have a mechanism that sees illusory contours and therefore assists in the demarcation of edges and objects at places where local contrast falls to zero at an edge, or where one textured object partially obscures another. These results suggest that insect vision, although spatially crude and low in processing power, sees separate objects by similar mechanisms to our own.

APPROXIMATING THE POTASSIUM FERTILIZATION REQUIREMENT OF COTTON ON SOME REPRESENTATIVE SEMIARID TROPICAL SAVANNAH SOILS OF NIGERIA

1981 ◽  
Vol 61 (3) ◽  
pp. 507-516
Author(s):  
GANYIR LOMBIN
Keyword(s):  
Cotton Yield ◽  
Seed Cotton ◽  
Potassium Fertilizer ◽  
Quadratic Polynomials ◽  
Independent Variables ◽  
Regression Procedure ◽  
Fertilizer Requirement ◽  
Relevant Variables ◽  
Multiple Determination

Potassium fertilizer requirement of rain-fed cotton was evaluated in a 3-yr field study conducted at three locations using four rates (0, 25, 50 and 75 kg∙ha−1)of K. Significant response was not obtained above 25 kg∙ha−1 applied K. Quadratic polynomials, using leaf K, exch. K, exch. (Ca + Mg)/K and applied K as independent variables, were fitted to the seed-cotton yield. As a single parameter, leaf K emerged the best predictor of yield with a coefficient of multiple determination (R2) of 86% and a corresponding regression equation of: Y (yield) = 3099.2 + 6031.6%K − 1643.3 (%K)2, followed by fertilizer K with a coefficient of multiple determination of 81% and a yield equation of: Y = 1302.3 + 53.96 app. K − 0.54 (app. K)2. Soil exch. K and (Ca + Mg)/K ratio were slightly less efficient in predicting yield giving R2 values of 0.62 and 0.76, respectively, when both the linear and quadratic terms were entered into their respective yield equations. When all the 12 possible entries (linear, and second-order terms and their square root transformations) were fed into the computer and regressed over cotton yield using a step-wise regression procedure, only two variables, leaf %K and (Ca + Mg)/K, significantly fitted the yield equation giving a predictive value of 87%. But the improvement in the precision of yield predictability as measured by the R2 value was only marginal and would not justify recommending the equation considering the extra laboratory work that will be needed to obtain the relevant variables. Critical values of 1.84% in index leaf, 0.19 meq/100 g exch. K and 50 kg∙ha−1 applied K were approximated for a maximum predicted yield range of 2440–2700 kg∙ha−1.

Neuronal correlates of real and illusory contour perception: functional anatomy with PET

1999 ◽  
Vol 11 (11) ◽  
pp. 4024-4036 ◽  
Author(s):  
Jonas Larsson ◽  
Katrin Amunts ◽  
Balázs Gulyás ◽  
Aleksandar Malikovic ◽  
Karl Zilles ◽  
...  
Keyword(s):  
Illusory Contour ◽  
Functional Anatomy ◽  
Contour Perception

scholarly journals From local to global processing: The development of illusory contour perception

2015 ◽  
Vol 131 ◽  
pp. 38-55 ◽  
Author(s):  
Kritika Nayar ◽  
John Franchak ◽  
Karen Adolph ◽  
Lynne Kiorpes
Keyword(s):  
Illusory Contour ◽  
Global Processing ◽  
Contour Perception
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