Fractal Dimensions in Perceptual Color Space: A Comparison Study Using Jackson Pollock's Art

The fractal dimensions of color-specific paint patterns in various Jackson Pollock paintings are calculated using a filtering process which models perceptual response to color differences (\Lab color space). The advantage of the \Lab space filtering method over traditional RGB spaces is that the former is a perceptually-uniform (metric) space, leading to a more consistent definition of ``perceptually different'' colors. It is determined that the RGB filtering method underestimates the perceived fractal dimension of lighter colored patterns but not of darker ones, if the same selection criteria is applied to each. Implications of the findings to Fechner's 'Principle of the Aesthetic Middle' and Berlyne's work on perception of complexity are discussed.Comment: 21 pp LaTeX; two postscript figure

On Multifractal Structure in Non-Representational Art

Multifractal analysis techniques are applied to patterns in several abstract expressionist artworks, paintined by various artists. The analysis is carried out on two distinct types of structures: the physical patterns formed by a specific color (``blobs''), as well as patterns formed by the luminance gradient between adjacent colors (``edges''). It is found that the analysis method applied to ``blobs'' cannot distinguish between artists of the same movement, yielding a multifractal spectrum of dimensions between about 1.5-1.8. The method can distinguish between different types of images, however, as demonstrated by studying a radically different type of art. The data suggests that the ``edge'' method can distinguish between artists in the same movement, and is proposed to represent a toy model of visual discrimination. A ``fractal reconstruction'' analysis technique is also applied to the images, in order to determine whether or not a specific signature can be extracted which might serve as a type of fingerprint for the movement. However, these results are vague and no direct conclusions may be drawn.Comment: 53 pp LaTeX, 10 figures (ps/eps

Aesthetic complexity: practice and perception in art & design

My research investigates the aesthetics of visual complexity in the practice and perception of visual art and design. The aim is to understand visual complexity in terms of the relationship between the objective properties of images and subjective properties of perception. I take a computational and empirical approach to this subject, incorporating methods from information theory, computer graphics, complexity theory and experimental psychology. For testing, I create cellular automata programs to generate stimulus images, and borrow other types of visual material from students and professional artists, designers and craftspeople. Visual complexity is measured in two ways: Firstly, an objective measure of complexity is based on the compression of digital image files, which provides an information-based scale of order to randomness. Secondly, psychophysical techniques are employed to measure the subjective complexity of the images and other aesthetic judgements. Research in complex systems theory and experimental aesthetics suggests that we can expect an inverted ‘U’ correlation between the two measures of complexity

Objective dysphonia quantification in vocal fold paralysis: comparing nonlinear with classical measures

Clinical acoustic voice recording analysis is usually performed using classical perturbation measures including jitter, shimmer and noise-to-harmonic ratios. However, restrictive mathematical limitations of these measures prevent analysis for severely dysphonic voices. Previous studies of alternative nonlinear random measures addressed wide varieties of vocal pathologies. Here, we analyze a single vocal pathology cohort, testing the performance of these alternative measures alongside classical measures.

We present voice analysis pre- and post-operatively in unilateral vocal fold paralysis (UVFP) patients and healthy controls, patients undergoing standard medialisation thyroplasty surgery, using jitter, shimmer and noise-to-harmonic ratio (NHR), and nonlinear recurrence period density entropy (RPDE), detrended fluctuation analysis (DFA) and correlation dimension. Systematizing the preparative editing of the recordings, we found that the novel measures were more stable and hence reliable, than the classical measures, on healthy controls.

RPDE and jitter are sensitive to improvements pre- to post-operation. Shimmer, NHR and DFA showed no significant change (p > 0.05). All measures detect statistically significant and clinically important differences between controls and patients, both treated and untreated (p < 0.001, AUC > 0.7). Pre- to post-operation, GRBAS ratings show statistically significant and clinically important improvement in overall dysphonia grade (G) (AUC = 0.946, p < 0.001).

Re-calculating AUCs from other study data, we compare these results in terms of clinical importance. We conclude that, when preparative editing is systematized, nonlinear random measures may be useful UVFP treatment effectiveness monitoring tools, and there may be applications for other forms of dysphonia.
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Fractals in the Nervous System: conceptual Implications for Theoretical Neuroscience

This essay is presented with two principal objectives in mind: first, to document the prevalence of fractals at all levels of the nervous system, giving credence to the notion of their functional relevance; and second, to draw attention to the as yet still unresolved issues of the detailed relationships among power law scaling, self-similarity, and self-organized criticality. As regards criticality, I will document that it has become a pivotal reference point in Neurodynamics. Furthermore, I will emphasize the not yet fully appreciated significance of allometric control processes. For dynamic fractals, I will assemble reasons for attributing to them the capacity to adapt task execution to contextual changes across a range of scales. The final Section consists of general reflections on the implications of the reviewed data, and identifies what appear to be issues of fundamental importance for future research in the rapidly evolving topic of this review

Deconstructing landscape pattern : applications of remote sensing to physiognomic landscape mapping

Funding Information: This research was supported by European Social Fund?s Dora Plus Programme (Grant No. 4-12/89). Authors are grateful to Ms Joanna Storie (Estonian University of Life Sciences) for English editing and proofreading, applied to the text. Publisher Copyright: © 2019, Springer Nature B.V.In 1939, Carl Troll pointed out that “air photo interpretation is to a large extent landscape ecology”. From that time forward, remote sensing has been applied across different disciplines to comprehend the holistic and dynamic spatial layout of the visual Earth environment. However, its applicability in the domain of landscape character assessment, landscape design and planning is still questionable. The purpose of this paper was to synthesise some historical and current applications of remote sensing for the decomposition of the continual visual landscape from a bird’s eye perspective and to explore the potential for bridging geographic processes with visual perception and an appreciation of the landscape pattern. From the point of view of landscape ecology, the organisation of the landscape pattern [namely, the size, shape (form), number, density and diversity, the complexity of landscape elements, and colours and textures of the land cover] is crucial for the cognition of both the visual landscape experience and the geographic processes. There are numerous pieces of evidence from the literature that remote sensing data are widely implemented in the modelling of physiognomic landscape. The synthesis of the literature concludes with perspective directions of remote sensing applications, such as mapping the status of the ecosystem (landscape) services provision, the delineation of the boundaries of the protected areas based on the quality of the visual environment, and the assessment of the sustainability of the land use practices, regarding their impact on landscape aesthetics extent.Peer reviewe

Primary motor cortex stimulation facilitates visual guidance.

The choices for analyzing cognitive load performance data are often problematic as they are task-dependent and do not generalize well. This makes research into task independent variables necessary. Complexity is one such measure that one can retrieve from normal cognitive load measurements. Using time series analysis techniques provides an efficient, less altered route to measurements that can account for multiple task dependent measures without being attached to the specific task. In this experiment, we present stimuli to participants based on occluded hand location to determine object recognition effectiveness. Maintaining a 65%- 75%-correct identification rate using a staircase procedure allowed for object recognition time and accuracy profile creation. Over the 18-inch hand movement, we observed a bi-modal distribution in reaction times with a "far hand effect" decreasing times at around 18-15 inches from the stimulus, increasing to a peak at 15-12 inches, and decreasing again as a participant moves his/her hand closer to the stimulus. Nonlinear time series analysis was performed on the data; more specifically I used wavelet transform modulus maxima to analyze a continuous wavelet transform created from the time series based off the effect hand location has on object perception

A user preference modelling method for the assessment of visual complexity in building façade

This work aims to provide a method to assess the perceptual impact of visual complexity of building facades. The research identifies three variables that incorporate the effect of visual complexity. These variables are the number of design elements and the variation in their position and colour. It introduces the concepts of vertices and corners as atomic indicators on which the physical measurement of the three variables is built. The study designs an experiment, which involves measuring visual complexity and its variables in images of building facades using image-processing techniques, collecting participant's' characteristics and reactions towards the images through an online questionnaire and statistically analysing the relationships between these measures and the reactions and characteristics of participants. The research offers a quantitative lens on the effect of visual complexity as a comprehensive phenomenon on preferences. The study demonstrates that the three variables can be systematically measured, and shows that participants have common visual reactions toward the aspects of visual complexity in images of building facades. This uniformity is confirmed by a regression model, which provides an adequate fit of the three variables as independent variables and preference as a dependent variable. It offers an objective method to assess visual complexity in images of building facades according to common optimal values of the three variables as guidelines to evaluate the design of building facades. These optimal values correspond to the average of the highest rates of the preferences of residents. Planning authorities and design firms can use this method as an objective way to evaluate design alternatives based on the preferences of residents

Aesthetic image statistics vary with artistic genre

Research to date has not found strong evidence for a universal link between any single low-level image statistic, such as fractal dimension or Fourier spectral slope, and aesthetic ratings of images in general. This study assessed whether different image statistics are important for artistic images containing different subjects and used partial least squares regression (PLSR) to identify the statistics that correlated most reliably with ratings. Fourier spectral slope, fractal dimension and Shannon entropy were estimated separately for paintings containing landscapes, people, still life, portraits, nudes, animals, buildings and abstracts. Separate analyses were performed on the luminance and colour information in the images. PLSR fits showed shared variance of up to 75% between image statistics and aesthetic ratings. The most important statistics and image planes varied across genres. Variation in statistics may reflect characteristic properties of the different neural sub-systems that process different types of image