The role of crowding in contextual influences on contour integration

Dakin and Baruch (2009) investigated how context influences contour integration, specifically reporting that near-perpendicular surrounding-elements reduced the exposure-duration observers required to localize and determine the shape of contours (compared to performance with randomly oriented surrounds) while near-parallel surrounds increased this time. Here, we ask if this effect might be a manifestation of visual crowding (the disruptive influence of "visual clutter" on object recognition). We first report that the effect generalizes to simple contour-localization (without explicit shape-discrimination) and influences tolerance to orientation jitter in the same way it affects threshold exposure-duration. We next directly examined the role of crowding by quantifying observers' local uncertainty (about the orientation of the elements that comprised our contours), showing that this largely accounts for the effects of context on global contour integration. These findings support the idea that context influences contour integration at a predominantly local stage of processing and that the local effects of crowding eventually influence downstream stages in the cortical processing of visual form

The role of crowding in contextual influences on contour integration

Dakin and Baruch (2009) investigated how context influences contour integration, specifically reporting that nearperpendicular surrounding-elements reduced the exposure-duration observers required to localize and determine the shape of contours (compared to performance with randomly oriented surrounds) while near-parallel surrounds increased this time. Here, we ask if this effect might be a manifestation of visual crowding (the disruptive influence of ''visual clutter'' on object recognition). We first report that the effect generalizes to simple contour-localization (without explicit shape-discrimination) and influences tolerance to orientation jitter in the same way it affects threshold exposure-duration. We next directly examined the role of crowding by quantifying observers' local uncertainty (about the orientation of the elements that comprised our contours), showing that this largely accounts for the effects of context on global contour integration. These findings support the idea that context influences contour integration at a predominantly local stage of processing and that the local effects of crowding eventually influence downstream stages in the cortical processing of visual form

Reduced crowding and poor contour detection in schizophrenia are consistent with weak surround inhibition

Detection of visual contours (strings of small oriented elements) is markedly poor in schizophrenia. This has previously been attributed to an inability to group local information across space into a global percept. Here, we show that this failure actually originates from a combination of poor encoding of local orientation and abnormal processing of visual context

A class of quasi-sparse companion pencils

In this paper, we introduce a general class of quasi-sparse potential companion pencils for arbitrary square matrix polynomials over an arbitrary field, which extends the class introduced in [B. Eastman, I.-J. Kim, B. L. Shader, K.N. Vander Meulen, Companion matrix patterns. Linear Algebra Appl. 436 (2014) 255-272] for monic scalar polynomials. We provide a canonical form, up to permutation, for companion pencils in this class. We also relate these companion pencils with other relevant families of companion linearizations known so far. Finally, we determine the number of different sparse companion pencils in the class, up to permutation.This work has been partially supported by theMinisterio de Economía y Competitividad of Spain through grants MTM2015-68805-REDT and MTM2015-65798-P

Maximizing the detection of thermal imprints in civil engineering composites via numerical and thermographic results pre-processed by a groundbreaking mathematical approach

New composite materials are always subjected to non-destructive evaluation (NDE) prior to being placed on the market. This is to fully understand the reactions (i.e., development of defects) at the interface between two subsequent layers. Active infrared thermography (aIRT) can help in this regard, especially if anticipated by a simulation of the heat transfer from the exterior (lamp) to the interior (multilayer). Comsol Multiphysics® was used in this work as a tool by developing an innovative approach, which is designed – on the one hand – to minimize the computational cost and – on the other hand – to optimize the radiation to be delivered. The innovation produced by our work also concerns the pre-processing step of the thermal images; in fact, the 2D Fast Iterative Filtering (FIF2) is here introduced, discussing its benefits in comparison to previously developed techniques. Pre-processed data were further analyzed during the post-processing step demonstrating the reliability of FIF2 in enhancing thermal imprints, which leads to an improved detection of subsurface features. In particular, enhanced thermal imprints highlight the shape of the grid of glass fibres present beneath an external coating of hemp fibres (and, in general, added to the whole specimen along the x-y vectors). This grid of glass fibres was recently introduced as an insulation material for buildings. A brief review of the use of the pre-processing step in aIRT allows the reader to better understand the decisive step forward provided by FIF2 combined with a clever numerical simulation in the applied thermal engineering field. Qualitative and quantitative IRT results are shown and discussed thoroughly. Finally, a validation among numerical and experimental (thermographic) data is provided thanks to the Parker (laser flash) method