Visual perception of texture regularity: conjoint measurements and a wavelet response-distribution model

Texture regularity, such as the repeating pattern in a carpet, brickwork or tree bark, is a ubiquitous feature of the visual world. The perception of regularity has generally been studied using multi-element textures in which the degree of regularity has been manipulated by adding random jitter to the elements’ positions. Here we used three-factor Maximum Likelihood Conjoint Measurement (MLCM) to investigate the encoding of regularity information under more complex conditions in which element spacing and size, in addition to positional jitter, were manipulated. Human observers were presented with large numbers of pairs of multi-element stimuli with varying levels of the three factors, and indicated on each trial which stimulus appeared more regular. All three factors contributed to regularity perception. Jitter, as expected, strongly affected regularity perception. This effect of jitter on regularity perception is strongest at small element spacing and large texture element size, suggesting that the visual system utilizes the edge-to-edge distance between elements as the basis for regularity judgments. We then examined how the responses of a bank of Gabor wavelet spatial filters might account for our results. Our analysis indicates that SF-peakedness, a previously favored proposal, is insufficient for regularity encoding since it varied more with element spacing and size than with jitter. Instead, our results support the idea that the visual system may extract texture regularity information from the moments of the SF-distribution across orientation. In our best-performing model, the variance of SF-distribution skew across orientations can explain 70% of the variance of estimated texture regularity from our data, suggesting that it could provide a candidate readout for perceived regularity.Author SummaryWe investigated human perception of texture regularity, in which subjects made comparative judgements of regularity in pairs of texture stimuli with differing levels of three parameters of texture construction - spacing and size of texture elements, and their positional jitter. We analyzed the data using a novel approach involving three-factor Maximum Likelihood Conjoint Measurement (MLCM). We utilized a novel analysis-of-variance approach in MLCM to evaluate the effect size and significance of the three factors as well as their interactions. We found that all three factors contributed to perceived regularity, with significant main effects and interactions between factors, in a manner suggesting edge-to-edge distances between elements might contribute importantly to regularity judgments. Using a bank of Gabor wavelet spatial filters to model the response of the human visual system to our textures, we compared four types of ways that the distribution of wavelet responses could account for our measured data on perceived regularity. Our results suggest that the orientation as well as spatial frequency information from the wavelet filters also contributes importantly - in particular, the skew of the variance of the SF-distribution across orientation provides a candidate basis for perceived texture regularity.

Adjoint optimization of surface textures in mixed lubrication regime

In this work we assess the applicability of the adjoint optimization technique for determining optimal surface topographies of two surfaces in relative motion in presence of a thin lubricant films that can cavitate. Among the existing numerical tools for topology optimization in engineering problems, the adjoint method represents a promising and versatile technique, which can also be applied to the field of full film tribology. In particular, the design of surfaces with complex textures can thoroughly benefit from this method, as it allows dealing with a large number of degrees of freedom at low computational cost. We show that this optimization method can be successfully applied to cavitating lubricant flows such as in pin-on-disc tribometers, giving the possibility to extend the results also to other typical applications such as journal and slider bearings. It is shown that the adjoint method can optimize the whole gap height distribution point by point in a more efficient way than traditional optimization approaches and parametric studies. In particular, thanks to the sensitivity analysis the adjoint method is able to find the placement and depth profile of each texture element.

An Efficient Acoustic Scattering Model Based on Target Surface Statistical Descriptors for Synthetic Aperture Sonar Systems

Acoustic scattering as the perturbation of an incident acoustic field from an arbitrary object is a critical part of the target-recognition process in synthetic aperture sonar (SAS) systems. The complexity of scattering models strongly depends on the size and structure of the scattered surface. In accurate scattering models including numerical models, the computational cost significantly increases with the object complexity. In this paper, an efficient model is proposed to calculate the acoustic scattering from underwater objects with less computational cost and time compared with numerical models, especially in 3D space. The proposed model, called texture element method (TEM), uses statistical and structural information of the target surface texture by employing non-uniform elements described with local binary pattern (LBP) descriptors by solving the Helmholtz integral equation. The proposed model is compared with two other well-known models, one numerical and other analytical, and the results show excellent agreement between them while the proposed model requires fewer elements. This demonstrates the ability of the proposed model to work with arbitrary targets in different SAS systems with better computational time and cost, enabling the proposed model to be applied in real environment.

Influence Of Laser Beam Intensity On Geometry Parameters Of A Single Surface Texture Element

Laser surface texturing is used more and more often in modern machines for the implementation of variety of purposes such as for example intensification of lubrication, intensification of heat exchange, stimulation of microfluidics, increasing the chemical activity of the surface. Owing to the development of technologies using a concentrated energy flux, including laser microprocessing, it has become feasible. The present paper concentrates on the selection of parameters of laser microprocessing with picosecond pulses so as to obtain the highest efficiency and accuracy of the execution of a single texture element.

Orientation Disparity: A Cue for 3D Orientation?

Orientation disparity, the difference in orientation that results when a texture element on a slanted surface is projected to the two eyes, has been proposed as a binocular cue for 3D orientation. Since orientation disparity is confounded with position disparity, neither behavioral nor neurophysiological experiments have successfully isolated its contribution to slant estimates or established whether the visual system uses it. Using a modified disparity energy model, we simulated a population of binocular visual cortical neurons tuned to orientation disparity and measured the amount of Fisher information contained in the activity patterns. We evaluated the potential contribution of orientation disparity to 3D orientation estimation and delimited the stimulus conditions under which it is a reliable cue. Our results suggest that orientation disparity is an efficient source of information about 3D orientation and that it is plausible that the visual system could have mechanisms that are sensitive to it. Although orientation disparity is neither necessary nor sufficient for estimating slant, it appears that it could be useful when combined with estimates from position disparity gradients and monocular perspective cues.