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Fractals in Art and Nature: Why do we like them?

机译:艺术与自然的分形:为什么我们喜欢它们?

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Fractals have experienced considerable success in quantifying the visual complexity exhibited by many natural patterns, and continue to capture the imagination of scientists and artists alike. Fractal patterns have also been noted for their aesthetic appeal, a suggestion further reinforced by the discovery that the poured patterns of the American painter Jackson Pollock are also fractal, together with the findings that many forms of art resemble natural scenes in showing scale-invariant, fractal-like properties. While some have suggested that fractal-like patterns are inherently pleasing because they resemble natural patterns and scenes, the relation between the visual characteristics of fractals and their aesthetic appeal remains unclear. Motivated by our previous findings that humans display a consistent preference for a certain range of fractal dimension across fractal images of various types we turn to scale-specific processing of visual information to understand this relationship. Whereas our previous preference studies focused on fractal images consisting of black shapes on white backgrounds, here we extend our investigations to include grayscale images in which the intensity variations exhibit scale invariance. This scale-invariance is generated using a 1/f frequency distribution and can be tuned by varying the slope of the rotationally averaged Fourier amplitude spectrum. Thresholding the intensity of these images generates black and white fractals with equivalent scaling properties to the original grayscale images, allowing a direct comparison of preferences for grayscale and black and white fractals. We found no significant differences in preferences between the two groups of fractals. For both set of images, the visual preference peaked for images with the amplitude spectrum slopes from 1.25 to 1.5, thus confirming and extending the previously observed relationship between fractal characteristics of images and visual preference.
机译:分形在量化许多自然图案所表现出的视觉复杂性方面取得了相当大的成功,并且继续吸引着科学家和艺术家的想象力。分形图案也因其美学吸引力而闻名,这一发现因发现美国画家杰克逊·波洛克(Jackson Pollock)的倒模也是分形而被发现,以及发现许多形式的艺术品在表现尺度不变时都类似于自然场景的发现进一步加强了这一建议。分形性质。尽管有些人认为分形图案很自然,因为它们类似于自然图案和场景,但分形的视觉特征与其美学吸引力之间的关系仍然不清楚。基于我们先前的发现,人们对各种类型的分形图像在一定范围内的分形维数表现出一致的偏好,因此我们转向视觉信息的特定比例处理来理解这种关系。尽管我们以前的偏好研究主要关注由白色背景上的黑色形状组成的分形图像,但在这里,我们将研究范围扩展到包括灰度图像,其中强度变化表现出尺度不变性。使用1 / f频率分布可以生成此比例不变性,并且可以通过更改旋转平均傅里叶振幅谱的斜率来对其进行调整。对这些图像的强度进行阈值处理会生成具有与原始灰度图像相同的缩放属性的黑白分形,从而可以直接比较灰度分形和黑白分形的首选项。我们发现两组分形之间的偏好没有显着差异。对于这两组图像,对于振幅频谱斜率从1.25到1.5的图像,视觉偏好达到峰值,从而确认并扩展了先前观察到的图像分形特性与视觉偏好之间的关系。

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