A real-time visual processing theory is used to analyze real and illusory contour formation, contour and brightness interactions, neon color spreading, complementary color induction, and filling-in of discounted illuminants and scotomas. The theory also physically interprets and generalizes Land's retinex theory. These phenomena are traced to adaptive processes that overcome limitations of visual uptake to synthesize informative visual representations of the external world. Two parallel contour sensitive processes interact to generate the theory's brightness, color, and form estimates. A boundary contour process is sensitive to orientation and amount of contrast but not to direction of contrast in scenic edges. It synthesizes boundaries sensitive to the global configuration of scenic elements. A feature contour process is insensitive to orientation but sensitive to both amount of contrast and to direction of contrast in scenic edges. It triggers a diffusive filling-in of featural quality within perceptual domains whose boundaries are determined by completed boundary contours. The boundary contour process is hypothesized to include cortical interactions initiated by hypercolumns in Area 17 of the visual cortex. The feature contour process is hypothesized to include cortical interactions initiated by the cytochrome oxydase staining blobs in Area 17. Relevant data from striate and prestriate visual cortex, including data that support two predictions, are reviewed. Implications for other perceptual theories and axioms of geometry are discussed.

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A real-time visual processing theory is used to analyze and explain a wide variety of perceptual grouping and segmentation phenomena, including the grouping of textured images, randomly defined images, and images built up from periodic scenic elements. The theory explains how "local" feature processing and "emergent" features work together to segment a scene, how segmentations may arise across image regions that do not contain any luminance differences, how segmentations may override local image properties in favor of global statistical factors, and why segmentations that powerfully influence object recognition may be barely visible or totally invisible. Network interactions within a Boundary Contour (BC) System, a Feature Contour (FC) System, and an Object Recognition (OR) System are used to explain these phenomena. The BC System is defined by a hierarchy of orientationally tuned interactions, which can be divided into two successive subsystems called the OC filter and the CC loop. The OC filter contains two successive stages of oriented receptive fields which are sensitive to different properties of image contrasts. The OC filter generates inputs to the CC loop, which contains successive stages of spatially short-range competitive interactions and spatially long-range cooperative interactions. Feedback between the competitive and cooperative stages synthesizes a global context-sensitive segmentation from among the many possible groupings of local featural elements. The properties of the BC System provide a unified explanation of several ostensibly different Gestalt rules. The BC System also suggests explanations and predictions concerning the architecture of the striate and prestriate visual cortices. The BC System embodies new ideas concerning the foundations of geometry, on-line statistical decision theory, and the resolution of uncertainty in quantum measurement systems. Computer simulations establish the formal competence of the BC System as a perceptual grouping system. The properties of the BC System are compared with probabilistic and artificial intelligence models of segmentation. The total network suggests a new approach to the design of computer vision systems, and promises to provide a universal set of rules for perceptual grouping of scenic edges, textures, and smoothly shaded regions.

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Acknowledgements: 'T'he authors wish to thank Robin Locke for her valuable assistance in the preparation of the manusc:ript. AbstractVisual search data are given a unified quantitative explanation by a rnodel of how spatial maps in the parietal cortex and object recognition categories in the infcrotempora.l cortex deploy attentiona.l re;,ources as they reciprocally interact with visual representations in the prcstriate cortex. Tire rrrodcl visual representations arc organi~ed into rnultiple boundary and surface representations. Vi;,ual ;,carch in the rrrodel is initiated by organi~ing rnultiple items that lie within a given boundary or surface representation into a candidate search grouping. These items arc cornpared with object recognition categori()S to test for matches or rnismatches. Misnntches can trigger deeper searches and recursive selection of new groupings until a target object io identified. Thi;, search model is algorithmically specified to quantitatively simulate search data using a single set of parameters, as well as to qualitatively explain a still larger data base, including data of Aks and Enns (1992), Bravo and Blake (1990), Chella.zzi, Miller, Duncan, and Desirnonc (199:3), Egcth, Vir~i, and Garbart (1984), Cohen and Ivry (1991), Enno and Renoink (1990), He and Nakayarna (1992), Hurnphreys, Quinlan, and Riddoch ( 1 989), Mordkoff, Yantis, and Egcth (1990), Nakayama and Silverman (191-iGl, T'reioman and Geladc (1980), 'l'reisma,n and Sato (1990), Wolfe, Cave, and Fran~el (1989 , and Wolfe ancl Friedman-Hill (1992). The model hereby provides an alternative to recent variationfi on tbe Featmc Integration and Guided Search rnoclelo, and grounds the analysis of visual search in nemal rnoclels of preattentive vioion, attentive object learning and categori~ation, and attentive spatial localization and orientation.

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Three experiments examine the perceptual salience of shading information for the visual specification of three-dimensional form. The observers in these experiments were required to estimate the surface curvature and direction of illumination depicted in computer-synthesized images of cylindrical surfaces, both with and without texture. The results indicate that the shininess of a surface enhances the perception of curvature, but has no effect on perceived direction of illumination; and that shading is generally less effective than texture for depicting surfaces in three dimensions. These and other findings are used to evaluate the psychological validity of several mathematical analyses of shading information that have recently been proposed in the literature.