Corner Enhancement Research Articles

Study on the deformation mode and energy absorption characteristics of a corner-enhanced biomimetic spider web hierarchical structure

To improve the energy absorption properties of honeycomb structures based on the underlying mechanism of uniform stress dispersion and to effectively increase the strength of a spiderweb, a corner-enhanced spiderweb hierarchical honeycomb structure was proposed herein. This study involved a quasistatic compression test and simulation of a corner-enhanced spiderweb hierarchical structure complemented by 3D printing. The deformation pattern of the common spiderweb honeycomb (CSH) was //-shaped. However, the deformation pattern of the honeycomb after corner enhancement tended to be monolithic, forming an X shape. The deformation characteristics of both the CSH and the first-order local cellular elements were analyzed. The corner-enhanced honeycomb cellular elements dispersed the load onto the inner wall to achieve a common load-bearing effect. Further numerical simulation analysis was carried out in conjunction with the experiments, and local destruction analysis was performed for single-cell elements. Corner enhancement could increase the plastic hinge energy absorption of the structure, with a first-order corner-enhanced spiderweb honeycomb (CESH-F) exhibiting a 46.3 % improvement in specific energy absorption compared to that of a conventional CSH. The layers were reinforced to compress the load uniformly, and a third-order corner-enhanced spiderweb honeycomb (CESH-T) had a 25.7 % improvement in specific energy absorption compared to that of the CESH-F. In addition, optimization was performed for corner-enhanced spiderweb honeycomb (CESH) according to different helix radii. The effect of the radial line thickness on honeycomb-specific energy absorption was explored, and the radial line thickness was positively proportional to honeycomb-specific energy absorption. These findings offered valuable insights into the design of lightweight and high-energy-absorbing biomimetic structures.

Object recognition and localization enhancement in visual prostheses: a real-time mixed reality simulation

Blindness is a main threat that affects the daily life activities of any human. Visual prostheses have been introduced to provide artificial vision to the blind with the aim of allowing them to restore confidence and independence. In this article, we propose an approach that involves four image enhancement techniques to facilitate object recognition and localization for visual prostheses users. These techniques are clip art representation of the objects, edge sharpening, corner enhancement and electrode dropout handling. The proposed techniques are tested in a real-time mixed reality simulation environment that mimics vision perceived by visual prostheses users. Twelve experiments were conducted to measure the performance of the participants in object recognition and localization. The experiments involved single objects, multiple objects and navigation. To evaluate the performance of the participants in objects recognition, we measure their recognition time, recognition accuracy and confidence level. For object localization, two metrics were used to measure the performance of the participants which are the grasping attempt time and the grasping accuracy. The results demonstrate that using all enhancement techniques simultaneously gives higher accuracy, higher confidence level and less time for recognizing and grasping objects in comparison to not applying the enhancement techniques or applying pair-wise combinations of them. Visual prostheses could benefit from the proposed approach to provide users with an enhanced perception.

Efficient corner detection based on corner enhancement filters

Multi-scale analysis based corner detection algorithms yield impressive performance, however, they are not efficient and not suitable for real-time computer vision tasks. The classical corner detection algorithms including FAST and Harris are computationally efficient, but their detection accuracy and repeatability are insufficient. This paper describes a novel fast corner detector with a simple architecture and high parallel computing characteristics. In order to simplify the corner detection architecture and improve its parallel computing performance, a new type of filter is proposed that can enhance corners and suppress edges and noise simultaneously. Then a novel efficient corner detector is proposed, which can be adapted to achieve real-time detection in hardware. Experimental results show that, with a very low computational cost and simple architecture, the proposed detector can achieve or even exceed the detection accuracy of multi-scale analysis based detectors. Its repeatability is similar to multi-scale analysis based detectors and clearly higher than other types of corner detectors. Therefore, it is potentially useful as an efficient corner detector for computer vision applications especially for portable real-time tasks.

Dynamic target tracking based on corner enhancement with Markov decision process

The tracking–learning–detection (TLD) algorithm applied in the home environment can effectively improve the tracking robustness. However, it has the problems of single target tracking and poor selection of feature points. This study proposed a dynamic target tracking method based on corner enhancement with Markov decision process (MDP) model. The MDP target tracking method is adopted to change a multi-target tracking problem into a strategy problem based on MDP model, in which one MDP model represents the life cycle of a target, and multiple targets are represented by multiple MDP models. In the tracking process, the strong corners generated by the Shi-Tomasi corner method are used to replace the feature points generated by the traditional TLD algorithm at intermediate intervals, which makes the target feature points more stable during the tracking process. The similarity function learning for data association is equivalent to the learning of the MDP strategy, in which the reinforcement learning method is used and has double advantages of both online and offline learning. The tracking experiments with different data sets are performed, and the results show that dynamic target tracking algorithm based on the corner enhancement with MDP has both good tracking performance and good anti-interference capability.

A benchmark analytical approach for evaluating ultimate compressive strength of hollow corrugated stub columns

This paper deals with developing advanced, yet design-oriented expressions for ultimate strength of the newly developed hollow corrugated stub columns with or without ultra-high strength corner tubes under uniaxial compressive loading. This is achieved by individually analysing comprising self-strengthened corrugated plates using the effective width concept whilst the effect of corner enhancement is taken into calculation. For stiffened panels such as corrugated plates, the ultimate limit state design is equated to the lowest value among all collapse provisions. However, the finite element analyses show that Euler buckling state may govern the ultimate load capacity of corrugated plates used in the proposed columns. This is verified by comparing the results obtained from the proposed analytical formulations with those demonstrated by the finite element modelling and experiments. The results are also compared with the guidelines for design of corrugated panels available in the literature. Finally, several cases with different corrugation geometrical parameters are defined and the capacity of corresponding columns is evaluated and compared to each other.

The visual system prioritizes locations near corners of surfaces (not just locations near a corner)

When a new visual object appears, attention is directed toward it. However, some locations along the outline of the new object may receive more resources, perhaps as a consequence of their relative importance in describing its shape. Evidence suggests that corners receive enhanced processing, relative to the straight edges of an outline (corner enhancement effect). Using a technique similar to that in an original study in which observers had to respond to a probe presented near a contour (Cole et al. in Journal of Experimental Psychology: Human Perception and Performance 27:1356-1368, 2001), we confirmed this effect. When figure-ground relations were manipulated using shaded surfaces (Exps. 1 and 2) and stereograms (Exps. 3 and 4), two novel aspects of the phenomenon emerged: We found no difference between corners perceived as being convex or concave, and we found that the enhancement was stronger when the probe was perceived as being a feature of the surface that the corner belonged to. Therefore, the enhancement is not based on spatial aspects of the regions in the image, but critically depends on figure-ground stratification, supporting the link between the prioritization of corners and the representation of surface layout.

Experimental and theoretical study on the behavior of cold-formed stainless steel stub columns

This paper presents an experimental investigation on the behavior of cold-formed stainless steel stub columns under axial compression. Nineteen hollow section specimens of seven section types were tested. Geometric imperfections, material properties and full-range load-displacement curves were obtained. The test strengths were compared with the four design strengths, which are respectively calculated by using the American specification, the European specification, the design method proposed by Rasmussen in 2004, and the design method proposed by Gardner in 2008. The American specification, the European specification, and the design method proposed by Rasmussen are generally conservative. While the design method proposed by Gardner is relatively accurate. Based on the comparisons, modifications to Winter equation were derived to involve both the factors of the corner enhancement of the cold-formed members and the nonlinear property of stainless steel. The modified Winter equation can predict the strengths with low scatter.

The Role of Figure-Ground in the Corner Enhancement Effect

The appearance of a new object in the visual field captures visual attention. Moreover, detection is faster for a probe presented in a region adjacent to the corner of a stimulus, compared to a probe adjacent to the straight edge. This corner enhancement effect is believed to show that probes near corners receive enhanced processing (Cole et al 2007, Attention, Perception and Psychophysics69, 400–412). We tested the corner effect for convex and concave corners for surfaces arranged in depth. We used coloured regions with cast shadows to specify foreground and background and a square stimulus that could be perceived as either an object or a hole (a figure-ground reversal). The probe was a small red line that could appear near a corner or a straight edge 100 msec after the stimulus onset. We asked the participants to discriminate the orientation of the probe (horizontal or vertical). The corner effect was found for both convex (Experiment 1) and concave (Experiment 2) vertices but only when the probe was ne...

Involuntary capture of visual-spatial attention occurs for intersections, both real and “imagined”

In three spatial precuing experiments, we demonstrate attentional capture by an intersection that occurs (1) between two lines that are not part of an enclosed object, and (2) between a line in the cuing array that is not physically present during target search and the invisible circumference of a perceptual circle formed by the elements in the target array. This capture effect conceptually replicates Cole, Gellatly, and Blurton's (2001) corner enhancement effect, in which responses are faster for targets presented near an object's corners rather than along its straight edges. However, it extends that effect by showing that it occurs even when the intersection is not part of an enclosed object and is not physically present during target search. More important, our capture effect occurred even though the target's position was not designated by a perceptually distinctive feature and was not predicted by the intersection's position. Thus, it seems that a line intersection--whether it be real or imaginary-automatically captures visual-spatial attention, contrary to Folk, Remington, and Johnston's (1992) and Gibson and Kelsey's (1998) views that such an involuntary capture of spatial attention is contingent on attentional control settings.

Object and spatial representations in the corner enhancement effect

Cole, Gellatly, and Blurton have shown that targets presented adjacent to geometric corners are detected more efficiently than targets presented adjacent to straight edges. In six experiments, we examined how this corner enhancement effect is modulated by corner-of-object representations (i.e., corners that define an object's shape) and local base-level corners that occur as a result of, for instance, overlapping the straight edges of two objects. The results show that the corner phenomenon is greater for corners of object representations than for corners that do not define an object's shape. We also examined whether the corner effect persists within the contour boundaries of an object, as well as on the outside. The results showed that a spatial gradient of attention accompanies the corner effect outside the contour boundaries of an object but that processing within an object is uniform, with no corner effect occurring. We discuss these findings in relation to space-based and object-based theories of attention.

Simulation of viscoelastic flows of polymer solutions in abrupt contractions using an arbitrary Lagrangian Eulerian (ALE) based finite element method

We present a method for simulation of viscoelastic flows using an Arbitrary Lagrangian Eulerian (ALE) technique based finite element formulation. The ALE technique provides advantages of both Lagrangian and Eulerian frameworks by allowing the computational mesh to move in an arbitrary manner, independent of the material motion. In the present method, a fractional step ALE technique is employed in which the Lagrangian phase of material motion and convection arising out of mesh motion are decoupled. In the first step the relevant flow and constitutive equations are solved in Lagrangian framework. The simpler representation of polymer constitutive equations in a Lagrangian framework avoids the difficulties associated with convective terms thereby resulting in a robust numerical formulation. In the second step the mesh is moved in ALE mode and the associated convection of the stress is performed using a Godunov type scheme. This ALE technique is easy to implement and can accurately simulate the complex viscoelastic behaviour of transient polymer flow through complex geometries. In the present study, steady flows through abrupt contractions of planar and axisymmetric geometries are studied by performing transient flow simulations until steady state is achieved. The proposed method is validated with previously published numerical and experimental studies for polymer solutions obeying the Oldroyd B and Phan Thien Tanner (PTT) models. The simulated corner and lip vortex enhancement mechanism and flow behavior are in good agreement with experimentally obtained flow visualization photographs. The strength of the proposed method lies in its ability to simulate free surface flows such as swell.

CORNER ENHANCEMENT IN CURVATURE SCALE SPACE

Corner detection is very important for pattern recognition, computer vision and other works. However, successfully extracting corners from a planar curve is difficult because we do not know how to select the appropriate scale for the extraction. In this paper, the problem of corner enhancement via the curve scale space is addressed. The main idea of the approach is to deform the original curve (or construct the curve scale space) and the corners on the deformed curve become distinguished from other structures which eases the process of corner detection. Started from the general geometric heat flow (GGHF), we study under what conditions the GGHF satisfies the scale space causality criteria. This is very important because many different evolution approaches, which have regular scale space properties and other specific properties, can then be found from these conditions. The criteria of corner enhancement are also proposed. Having all these constraints, a new curve evolution scheme which can enhance strong corners suppress noise and satisfies the scale space criteria is presented.

Nonlinear image filtering with edge and corner enhancement

The authors describe a model of nonlinear image filtering for noise reduction and edge enhancement using anisotropic diffusion. The method is designed to enhance not only edges, but corners and T junctions as well. The method roughly corresponds to a nonlinear diffusion process with backward heat flow across the strong edges. Such a process is ill posed, making the results depend strongly on how the algorithm differs from the diffusion process. Two ways of modifying the equations using simulations on a variable grid are studied.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>